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Excel - Time Series Forecasting - Part 1 of 3
 
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Part 2: http://www.youtube.com/watch?v=5C012eMSeIU&feature=youtu.be Part 3: http://www.youtube.com/watch?v=kcfiu-f88JQ&feature=youtu.be This is Part 1 of a 3 part "Time Series Forecasting in Excel" video lecture. Be sure to watch Parts 2 and 3 upon completing Part 1. The links for 2 and 3 are in the video as well as above.
Views: 758976 Jalayer Academy
Clustering of Electricity Consumption Behavior Dynamics toward Big Data Applications
 
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Clustering of Electricity Consumption Behavior Dynamics toward Big Data Applications To get this project in Online or through training sessions Contact: Chennai Office: JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai – 83. Landmark: Next to Kotak Mahendra Bank / Bharath Scans. Landline: (044) - 43012642 / Mobile: (0)9952649690 Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry – 9. Landline: (0413) - 4300535 / (0)9952649690 Email: [email protected], Website: http://www.jpinfotech.org, Blog: http://www.jpinfotech.blogspot.com In a competitive retail market, large volumes of smart meter data provide opportunities for load serving entities (LSEs) to enhance their knowledge of customers' electricity consumption behaviors via load profiling. Instead of focusing on the shape of the load curves, this paper proposes a novel approach for clustering of electricity consumption behavior dynamics, where “dynamics” refer to transitions and relations between consumption behaviors, or rather consumption levels, in adjacent periods. First, for each individual customer, symbolic aggregate approximation (SAX) is performed to reduce the scale of the data set, and time-based Markov model is applied to model the dynamic of electricity consumption, transforming the large data set of load curves to several state transition matrixes. Second, a clustering technique by Fast Search and Find of Density Peaks (CFSFDP) is primarily carried out to obtain the typical dynamics of consumption behavior, with the difference between any two consumption patterns measured by the Kullback–Liebler (K-L) distance, and to classify the customers into several clusters. To tackle the challenges of big data, the CFSFDP technique is integrated into a divide-and-conquer approach toward big data applications. A numerical case verifies the effectiveness of the proposed models and approaches.
Views: 270 jpinfotechprojects
Time Series Analysis via Matrix Estimation
 
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Devavrat Shah, Massachusetts Institute of Technology https://simons.berkeley.edu/talks/devavrat-shah-3-29-18 Societal Networks
Views: 712 Simons Institute
Mario Bergés: Using Analytics to Understand Energy Consumption in Buildings
 
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Energy bills show usage as a total number, leaving consumers, building managers and others to wonder which activities or appliances are using the most electricity. Civil and Environmental Engineering Professor Mario Bergés is using sensing and analytics to understand energy consumption in buildings and disaggregate the total usage into its parts.
Sentilla Energy Manager profiles Server Power Consumption
 
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A demonstration of the Sentilla Energy Manager analyzing the power consumption of a typical server. With a small wireless device monitoring electricity use directly where it is used, Sentilla shows the energy consumption of every thing that consumes energy via the web. This video illustrates the real time impact of startup, compute load, disk usage, and fan operations on power consumption. With instantaneous energy information, Sentilla infers what the server is doing based on its energy consumption. Each server's energy data sets a baseline for energy use, identifies energy waste, and helps put in place a plan for energy reduction.
Views: 665 polastre
28c3: Smart Hacking for Privacy
 
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Download high quality version: http://bit.ly/sexyIG Description: http://events.ccc.de/congress/2011/Fahrplan/events/4754.en.html Dario Carluccio, Stephan Brinkhaus: Smart Hacking For Privacy Advanced metering devices (aka smart meters) are nowadays being installed throughout electric networks in Germany, in other parts of Europe and in the United States. Due to a recent amendment especially in Germany they become more and more popular and are obligatory for new and refurbished buildings. Unfortunately, smart meters are able to become surveillance devices that monitor the behavior of the customers leading to unprecedented invasions of consumer privacy. High-resolution energy consumption data is transmitted to the utility company in principle allowing intrusive identification and monitoring of equipment within consumers' homes (e. g., TV set, refrigerator, toaster, and oven) as was already shown in different reports. This talk is about the Discovergy / EasyMeter smart meter used for electricity metering in private homes in Germany. During our analysis we found several security bugs that range from problems with the certificate management of the website to missing security features for the metering data in transit. For example (un)fortunately the metering data is unsigned and unencrypted, although otherwise stated explicitly on the manufacturer's homepage. It has to be pointed out that all tests were performed on a sealed, fully functionally device. In our presentation we will mainly focus on two aspects which we revealed during our analysis: first the privacy issues resulting in even allowing to identify the TV program out of the metering data and second the "problem" that one can easily alter data transmitted even for a third party and thereby potentially fake the amount of consumed power being billed. In the first part of the talk we show that the analysis of the household's electricity usage profile can reveal what channel the TV set in the household is displaying. We will also give some test-based assessments whether it is possible to scan for copyright-protected material in the data collected by the smart meter. In the second part we focus on the data being transmitted by the smart meter via the Internet. We show to what extent the consumption data can be altered and transmitted to the server and visualize this by transmitting some kind of picture data to Discovergy's consumption data server in a way that the picture content will become visible in the electricity profile. Moreover, we show what happens if the faked power consumption data reflects unrealistic extreme high or negative power consumptions and how that might influence the database and service robustness.
Views: 48429 28c3
The human insights missing from big data | Tricia Wang
 
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Why do so many companies make bad decisions, even with access to unprecedented amounts of data? With stories from Nokia to Netflix to the oracles of ancient Greece, Tricia Wang demystifies big data and identifies its pitfalls, suggesting that we focus instead on "thick data" -- precious, unquantifiable insights from actual people -- to make the right business decisions and thrive in the unknown. Check out more TED talks: http://www.ted.com The TED Talks channel features the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and more. Follow TED on Twitter: http://www.twitter.com/TEDTalks Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: https://www.youtube.com/TED
Views: 90596 TED
#1 Estimating with Excel for the Small Contractor
 
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In the video I will teach you how to use Excel to build a worksheet for estimating projects for the small contractor. The end result is a very basic, but usable estimating template. I hope to make additional videos to expand on this template and build a complete system of estimating, proposals letters, tracking your hours and materials and invoicing the job. All your information about the job is in one worksheet. I am not selling a product and I am a contractor just like you. I just wanted to teach other contractors how to use Excel in estimating. If I get some interest in the video then I will continue to make more of them. If no one is interested then I'll just stop at one video.
Views: 503822 rcargin1
Data Mining and Prediction Modelling in the Dairy Industry Using Time Series and Sliding Windows
 
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"WHY - As a major livestock producer, the European Union is directly affected by the global need for more sustainable food production. Climate change will undoubtedly impact on farm animal production but the health and welfare of livestock is also of increasing public concern. Due to rapid development of precision livestock farming technologies and availability of high-throughput from milk sensors, large-scale massive data has become available on research farms. The preferred matrix to measure the biomarkers is milk, as it is more accessible than blood and allows low-cost, automated repeat sampling using ‘in-line’ sampling and analytical technologies. WHAT - Certain biomarkers in milk such as N-glycan structures (BM-1), metabolites (BM-2) or mid-infra-red spectra (BM-3) can serve as biomarkers to predict production efficiency and disease. Data mining and machine learning can unlock insights around such biomarkers. As more of the aforementioned types of datasets become available over the near future, scalable data mining and prediction pipelines applied to animals science are needed. TAKEAWAYS -In this session you will learn: The methodology for ranking multiple biomarkers according to their predictive power; Data processing and statistical modelling performed using Spark v2.1.1 with scala API; Infrastructure, configuration, and implementation of the data pipeline using sliding windows with Apache Spark’s MLlib Visualization of of datasets via ElasticSearch-Kibana. Talk by Miel Hostens Session hashtag: #EUds14"
Views: 398 Databricks
APC 7920 PDU #1 overview, usage scenarios and teardown
 
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We make a general overview on an APC 7920 PDU by looking at the the main functionality of this power distribution unit (PDU). The PDU can be both managed over the web or over a command line interface CLI. For the management either the 10/100 Mbit ethernet or the RJ12 serial port can be used. The power is fed in through a C13 port (maximum 12Amps current) and it is than switched to eight C14 power outlet plugs, which share the power (maximum 10A per C14 output plug, or 12A combined). In the first portion of the video we go over the way how the PDU operates and present some scenarios of how it can be employed in a production environment or in a home lab for automation or for saving power. This APC PDU can be both monitored and managed through SNMP, which offer enhanced functionality for monitoring and scripting, which makes such a unit very versatile. Jump to 12:20 if you are only interested in the teardown. In the teardown we have a look on the general construction, than focus on the power switching elements and inner logic inside the PDU, and also analyze the path of the power through the unit. This PDU has two separate switch mode power supplies providing +24V DC for the relays and a low voltage one as well for the digital electronics. These are based on the TOP244YN integrated circuit. The main CPU is an AT56753-1U, which is a custom part made by Atmel for APC, so there is not much data available on it. The overall build quality is really high, and the components are good quality, which is expected from a manufacturer like APC.
Views: 5904 Donkey Learning IT
Electricity Rates and Bill Savings for Residential and Commercial Projects in SAM 2017.1.17
 
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This webinar is a walk-through of the inputs and results associated with electricity bill calculations for SAM's residential, commercial, and third party financial models. It covers weather and load data, electricity rate inputs, electricity bill savings, impact of bill savings on project cash flow.
Clustering of Electricity Consumption Behavior Dynamics toward Big Data Applications
 
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Clustering of Electricity Consumption Behavior Dynamics toward Big Data Applications To get this project in ONLINE or through TRAINING Sessions, Contact: JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83.Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai,Thattanchavady, Puducherry -9.Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690, Email: [email protected], web: http://www.jpinfotech.org, Blog: http://www.jpinfotech.blogspot.com In a competitive retail market, large volumes of smart meter data provide opportunities for load serving entities (LSEs) to enhance their knowledge of customers' electricity consumption behaviors via load profiling. Instead of focusing on the shape of the load curves, this paper proposes a novel approach for clustering of electricity consumption behavior dynamics, where “dynamics” refer to transitions and relations between consumption behaviors, or rather consumption levels, in adjacent periods. First, for each individual customer, symbolic aggregate approximation (SAX) is performed to reduce the scale of the data set, and time-based Markov model is applied to model the dynamic of electricity consumption, transforming the large data set of load curves to several state transition matrixes. Second, a clustering technique by Fast Search and Find of Density Peaks (CFSFDP) is primarily carried out to obtain the typical dynamics of consumption behavior, with the difference between any two consumption patterns measured by the Kullback–Liebler (K-L) distance, and to classify the customers into several clusters. To tackle the challenges of big data, the CFSFDP technique is integrated into a divide-and-conquer approach toward big data applications. A numerical case verifies the effectiveness of the proposed models and approaches.
Views: 180 JPINFOTECH PROJECTS
Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data
 
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Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data David Hallac (Stanford University) Sagar Vare (Stanford University) Stephen Boyd (Stanford University) Jure Leskovec (Stanford University) Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through an expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve both the E and M-steps in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios. More on http://www.kdd.org/kdd2017/
Views: 4273 KDD2017 video
Goldcorp leads with data-driven decision making and Power BI
 
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Headquartered in Vancouver, British Columbia, Goldcorp is focused on responsible mining practices throughout the Americas. The mining industry is very dynamic and Goldcorp needed a platform to manage data from their highly technical mining operations and inform real-time, data-driven decisions. With Microsoft Power BI, Goldcorp is driving performance, limiting variability and building the foundation for the future of technology-enabled mines.
The Surprising Places We Waste Energy
 
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Viewers like you help make PBS (Thank you 😃) . Support your local PBS Member Station here: https://to.pbs.org/PBSDSDonate Check out our whole series on ENERGY! http://bit.ly/1BnH5zu Subscribe: http://bit.ly/iotbs_sub Twitter: @okaytobesmart ↓ More info and sources below ↓ We use a LOT of energy, but we waste a lot too. Where that waste happens might surprise, you though. We don't just waste energy when we leave the lights on or the thermostat cranked down too low. It happens at the dinner table and the water faucet as too! LEARN MORE: Special thanks to Sheril Kirshenbaum and the Webber Energy Group at the University of Texas at Austin for their help with this series. http://www.webberenergygroup.com/ Check out their awesome online course "Energy 101" to learn about energy and energy policy from A to Z! http://www.energy101.com/ And to find out what people think about energy, check out the UT Energy Poll: http://www.utenergypoll.com/ Have an idea for an episode or an amazing science question you want answered? Leave a comment or check us out at the links below! Follow on Twitter: http://twitter.com/okaytobesmart http://twitter.com/jtotheizzoe Follow on Tumblr: http://www.itsokaytobesmart.com Follow on Instagram: http://instagram.com/jtotheizzoe ----------------- It's Okay To Be Smart is written and hosted by Joe Hanson, Ph.DFollow me on Twitter: @jtotheizzoe Email me: itsokaytobesmart AT gmail DOT com Facebook: http://www.facebook.com/itsokaytobesmart Google+ https://plus.google.com/+itsokaytobesmart For more awesome science, check out: http://www.itsokaytobesmart.com Produced by PBS Digital Studios: http://www.youtube.com/user/pbsdigitalstudios Joe Hanson - Creator/Host/Writer Joe Nicolosi - Director Amanda Fox - Producer, Spotzen IncKate Eads - Associate Producer Andrew Matthews - Editing/Motion Graphics/Animation Katie Graham - Director of Photography John Knudsen - Gaffer Theme music: "Ouroboros" by Kevin MacLeod Other music via APM Stock images from Shutterstock, stock footage from Videoblocks ----------------- Last week's video: Does the Moon Orbit the Earth? https://www.youtube.com/watch?v=3cJ3AemeUFM More videos: Why Does February Have 28 Days? https://www.youtube.com/watch?v=AgKaHTh-_Gs Why Vaccines Work https://www.youtube.com/watch?v=3aNhzLUL2ys Why Are Some People Left-Handed? https://www.youtube.com/watch?v=NPvMUpcxPSA Where Does the Smell of Rain Come From? https://www.youtube.com/watch?v=lGcE5x8s0B8
Views: 420924 It's Okay To Be Smart
Implementing a Neoteric Clustering approach in Wireless Sensor Networks using Spectral Clustering an
 
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In recent years, one of the most popular modern clustering algorithms in various fields like Network Science applications, Data mining, Pattern Recognition, etc., are spectral clustering algorithms. Another area of research interest found much attractive recently are Wireless Sensor Networks(WSNs), consisting of low power, low-cost, and energy-constrained sensors employed to monitor and report a physical phenomenon to the sink node where the end-user can access the data. Some of the important challenges in WSNs are increasing network longevity and decreasing consumption of sensor energy. To handle these clustering algorithms can be utilized and use spectral graph theory in order to subdivide the network such that each cluster includes the highest inter-correlated sensors. In this presentation, we widely analyze the need and efficacy of use of Spectral Clustering algorithms from a network Graph partitioning point of view. To do this, some vital aspects of spectral clustering was studied; Also analysis and actual implementation of meaningful partition of simple data sets was employed. This was followed by deriving and subsequent implementations of two typical spectral clustering algorithms, namely, ratio-cuts and normalized-cuts thus providing sufficient insight by proposing experiments on large web-graphs and thereafter discussing/analyzing the results. Finally, using a neoteric approach called K-Way Spectral Clustering Algorithm in Wireless Sensor Network (KSCA-WSN) we can try to address its aforementioned challenges. Experimental results and subsequent simulations and observations attest to the fact that this implementation produces performance of better quality, they give a good approximation of the min-cut graph partitioning problem in terms of reducing the cut size and KSCA-WSNs help in effectively distributing the overall consumption of sensor energy as well as ensuring larger network lifetimes, taking into account quantitative as well as visual evaluations.
Views: 167 Sankalp Mohanty
Energy consumption Bitcoin vs Banking System
 
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The highest estimates for Bitcoins annual terawatt hours consumption is 28.67. This means, more than 3 times more efficient than a very conservative calculation of the cost of the global banking system. Example considers 30,000 banks globally. Carlos Domingo: The Bitcoin vs Visa Electricity Consumption Fallacy https://hackernoon.com/the-bitcoin-vs-visa-electricity-consumption-fallacy-8cf194987a50 Jonathan Koomey gets quoted in the Washington Post, and other estimates https://www.washingtonpost.com/news/energy-environment/wp/2017/12/19/why-the-bitcoin-craze-is-using-up-so-much-energy Highest estimates by Digiconomist https://digiconomist.net/bitcoin-energy-consumption Data center energy consumption study from 2014, estimated 10% https://ftalphaville.ft.com/2014/09/09/1960891/the-dark-side-of-data-centres What's the carbon footprint of your credit card? https://www.creditcards.com/credit-card-news/carbon-footprint-credit-card-1276.php Music & Sound effects by Academy Trailer Tools Vol. 1 and EpicStockMedia.com Images and video footage via http://pixabay.com
Views: 784 Climate State
Bitcoin Q&A: Proof-of-work changes
 
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What do you think about a Bitcoin proof-of-work algorithm change to combat mining centralisation like Monero did? Is ASIC-resistance futile? Is a hard fork still a valid option in case of an emergency? These questions were part of the monthly live Patreon Q&A session on March 31st and the (rescheduled) April session on May 5th. If you want early-access to talks and a chance to participate in the monthly live Q&As with Andreas, become a patron: https://www.patreon.com/aantonop RELATED: The value of proof-of-work - https://youtu.be/ZDGliHwstM8 The mining process - https://youtu.be/L4Xtau0YMJw Miners, pools, and consensus - https://youtu.be/JHz7LM4ncLw Bitmain and the ASICBoost allegations - https://youtu.be/t6jJDD2Aj8k Energy consumption - https://youtu.be/2T0OUIW89II What is Consensus? Rules Without Rulers - https://youtu.be/2tqo7PX5Pyc Forkology: A Study of Forks For Newbies - https://youtu.be/rpeceXY1QBM What is a fork? - https://youtu.be/QwEDtdkV3Q4 Altcoins and specialisation - https://youtu.be/b_Yhr8h6xnA Cryptographic primitives - https://youtu.be/RIckQ6RBt5E Nonces, mining, and quantum computing - https://youtu.be/d4xXJh677J0 Migrating to post-quantum cryptography - https://youtu.be/dkXKpMku5QY Andreas M. Antonopoulos is a technologist and serial entrepreneur who has become one of the most well-known and respected figures in bitcoin. Follow on Twitter: @aantonop https://twitter.com/aantonop Website: https://antonopoulos.com/ He is the author of two books: “Mastering Bitcoin,” published by O’Reilly Media and considered the best technical guide to bitcoin; “The Internet of Money,” a book about why bitcoin matters. THE INTERNET OF MONEY, v1: https://www.amazon.co.uk/Internet-Money-collection-Andreas-Antonopoulos/dp/1537000454/ref=asap_bc?ie=UTF8 [NEW] THE INTERNET OF MONEY, v2: https://www.amazon.com/Internet-Money-Andreas-M-Antonopoulos/dp/194791006X/ref=asap_bc?ie=UTF8 MASTERING BITCOIN: https://www.amazon.co.uk/Mastering-Bitcoin-Unlocking-Digital-Cryptocurrencies/dp/1449374042 [NEW] MASTERING BITCOIN, 2nd Edition: https://www.amazon.com/Mastering-Bitcoin-Programming-Open-Blockchain/dp/1491954388 Subscribe to the channel to learn more about Bitcoin & open blockchains! Music: "Unbounded" by Orfan (https://www.facebook.com/Orfan/) Outro Graphics: Phneep (http://www.phneep.com/) Outro Art: Rock Barcellos (http://www.rockincomics.com.br/)
Views: 12136 aantonop
Mining Human Activity Patterns from Smart Home Big Data for Healthcare Applications
 
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Mining Human Activity Patterns from Smart Home Big Data for Healthcare Applications To get this project in ONLINE or through TRAINING Sessions, Contact: JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83.Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #37, Kamaraj Salai,Thattanchavady, Puducherry -9.Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690, Email: [email protected], web: http://www.jpinfotech.org Nowadays, there is an ever-increasing migration of people to urban areas. Health care services is one of the most challenging aspects that is greatly affected by the vast influx of people to city centers. Consequently, cities around the world are investing heavily in digital transformation in an effort to provide healthier ecosystem for people. In such transformation, millions of homes are being equipped with smart devices (e.g. smart meters, sensors etc.) which generate massive volumes of fine-grained and indexical data that can be analyzed to support smart city services. In this paper, we propose a model that utilizes smart home big data as a means of learning and discovering human activity patterns for health care applications. We propose the use of frequent pattern mining, cluster analysis and prediction to measure and analyze energy usage changes sparked by occupants’ behavior. Since people’s habits are mostly identified by everyday routines, discovering these routines allows us to recognize anomalous activities that may indicate people’s difficulties in taking care for themselves, such as not preparing food or not using shower/bath. Our work addresses the need to analyze temporal energy consumption patterns at the appliance level, which is directly related to human activities. For the evaluation of the proposed mechanism, this research uses the UK Domestic Appliance Level Electricity dataset (UK-Dale) - time series data of power consumption collected from 2012 to 2015 with time resolution of six seconds for five houses with 109 appliances from Southern England. The data from smart meters are recursively mined in the quantum/data slice of 24 hours, and the results are maintained across successive mining exercises. The results of identifying human activity patterns from appliance usage are presented in details in this paper along with accuracy of short and long term predictions.
Views: 546 JPINFOTECH PROJECTS
How to Perform K-Means Clustering in R Statistical Computing
 
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In this video I go over how to perform k-means clustering using r statistical computing. Clustering analysis is performed and the results are interpreted. http://www.influxity.com
Views: 185931 Influxity
Bugra Akyildiz - Outlier Detection in Time Series Signals
 
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PyData SV 2014 Many real-world datasets have missing observations, noise and outliers; usually due to logistical problems, component failures and erroneous procedures during the data collection process. Although it is easy to avoid missing points and noise to some level, it is not easy to detect wrong measurements and outliers in the dataset. These outliers may present a larger problem in time-series signals since every data point has a temporal dependency to the data point before and after. Therefore, it is crucially important to be able to detect and possibly correct these outliers. In this talk, I will introduce three different methods to be able to detect outliers in time-series signals; Fast Fourier Transform(FFT), Median Filtering and Bayesian approach. http://bugra.github.io/work/notes/2014-03-31/outlier-detection-in-time-series-signals-fft-median-filtering/
Views: 3306 PyData
Duke as an Energy Laboratory: Disaggregating Energy Data, with Kyle Bradbury
 
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From Session 1: Energy Modeling, Computation and Analytics at the Duke University Energy Research Collaboration Workshop on May 7, 2013. Kyle Bradbury is a Postdoctoral Energy Fellow with the Duke University Energy Initiative.
Views: 876 DukeUEnergy
opinion aspect relations in cognizing customer feelings via reviews- IEEE PROJECTS 2018
 
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opinion aspect relations in cognizing customer feelings via reviews- IEEE PROJECTS 2018 Download projects @ www.micansinfotech.com WWW.SOFTWAREPROJECTSCODE.COM https://www.facebook.com/MICANSPROJECTS Call: +91 90036 28940 ; +91 94435 11725 IEEE PROJECTS, IEEE PROJECTS IN CHENNAI,IEEE PROJECTS IN PONDICHERRY.IEEE PROJECTS 2018,IEEE PAPERS,IEEE PROJECT CODE,FINAL YEAR PROJECTS,ENGINEERING PROJECTS,PHP PROJECTS,PYTHON PROJECTS,NS2 PROJECTS,JAVA PROJECTS,DOT NET PROJECTS,IEEE PROJECTS TAMBARAM,HADOOP PROJECTS,BIG DATA PROJECTS,Signal processing,circuits system for video technology,cybernetics system,information forensic and security,remote sensing,fuzzy and intelligent system,parallel and distributed system,biomedical and health informatics,medical image processing,CLOUD COMPUTING, NETWORK AND SERVICE MANAGEMENT,SOFTWARE ENGINEERING,DATA MINING,NETWORKING ,SECURE COMPUTING,CYBERSECURITY,MOBILE COMPUTING, NETWORK SECURITY,INTELLIGENT TRANSPORTATION SYSTEMS,NEURAL NETWORK,INFORMATION AND SECURITY SYSTEM,INFORMATION FORENSICS AND SECURITY,NETWORK,SOCIAL NETWORK,BIG DATA,CONSUMER ELECTRONICS,INDUSTRIAL ELECTRONICS,PARALLEL AND DISTRIBUTED SYSTEMS,COMPUTER-BASED MEDICAL SYSTEMS (CBMS),PATTERN ANALYSIS AND MACHINE INTELLIGENCE,SOFTWARE ENGINEERING,COMPUTER GRAPHICS, INFORMATION AND COMMUNICATION SYSTEM,SERVICES COMPUTING,INTERNET OF THINGS JOURNAL,MULTIMEDIA,WIRELESS COMMUNICATIONS,IMAGE PROCESSING,IEEE SYSTEMS JOURNAL,CYBER-PHYSICAL-SOCIAL COMPUTING AND NETWORKING,DIGITAL FORENSIC,DEPENDABLE AND SECURE COMPUTING,AI - MACHINE LEARNING (ML),AI - DEEP LEARNING ,AI - NATURAL LANGUAGE PROCESSING ( NLP ),AI - VISION (IMAGE PROCESSING),mca project CLOUD COMPUTING 1. Cloud-Based Fine-Grained Health Information Access Control Framework for Lightweight IoT Devices with Dynamic Auditing and Attribute Revocation (April-June 1 2018 ) 2. Secured outsourcing towards cloud computing environment based on DNA cryptography ( 23 April 2018) 3. Data Security in Cloud Computing Using AES Under HEROKU Cloud (07 June 2018) 4. Privacy-Preserving Indexing and Query Processing for Secure Dynamic Cloud Storage 5. Improving Privacy-Preserving and Security for Decentralized Key-Policy Attributed-Based Encryption 6. A Practical Public Key Encryption Scheme Based on Learning Parity with Noise 7. An Approach to Balance Maintenance Costs and Electricity Consumption in Cloud Data Centers 8. Integrated Authentication and Key Agreement Framework for Vehicular Cloud Computing 9. A Power-of-Two Choices Based Algorithm for Fog Computing 10. virtFlow: Guest Independent Execution Flow Analysis Across Virtualized Environments 11. Adaptive Resource Management for Analyzing Video Streams from Globally Distributed Network Cameras 12. Enhancing Performance and Energy Efficiency for Hybrid Workloads in Virtualized Cloud Environment 13. Minimal Cost Server Configuration for Meeting Time-Varying Resource Demands in Cloud Centers 14. VMGuard: A VMI-based Security Architecture for Intrusion Detection in Cloud Environment 15. Aggregation-Based Colocation Datacenter Energy Management in Wholesale Markets 16. Provably secure and lightweight identity-based authenticated data sharing protocol for cyber-physical cloud environment 17. Energy Efficient Scheduling of Servers with Multi-Sleep Modes for Cloud Data Center 18. A tight estimate of job completion time in vehicular clouds 19. HealthDep: An Efficient and Secure Deduplication Scheme for Cloud-Assisted eHealth Systems 20. An Efficient and Fair Multi-Resource Allocation Mechanism for HeterogeneousServers 21. Dynamic VM Scaling: Provisioning and Pricing through an Online Auction 22. Price-based Resource Allocation for Edge Computing: A Market Equilibrium Approach 23. A Key-Policy Attribute-Based Temporary Keyword Search scheme for Secure Cloud Storage 24. Efficient Retrieval Over Documents Encrypted by Attributes in Cloud Computing 25. A Planning Approach for Reassigning Virtual Machines in IaaS Clouds 26. A Robust Formulation for Efficient Application Offloading to Clouds 27. Efficient Traceable Authorization Search System for Secure Cloud Storage 28. An Efficient and Secured Framework for Mobile Cloud Computing 29. Adaptive Resource Allocation and Provisioning in Multi-Service Cloud Environments 30. Cloud Centric Authentication for Wearable Healthcare Monitoring System 31. Towards Shared Ownership in the Cloud 32. Security Analysis of Smartphone and Cloud Computing Authentication Frameworksand Protocols 33. Integrated Authentication and Key Agreement Framework for Vehicular CloudComputing 34. CLASS: Cloud Log Assuring Soundness and Secrecy Scheme for Cloud Forensics 35. An Approach to Balance Maintenance Costs and Electricity Consumption in Cloud Data Centers
Views: 4 Micans Infotech
The Weeknd - D.D.
 
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http://theweeknd.co/BeautyBehindTheMadness THE MADNESS FALL TOUR 2015: http://republicrec.co/BBTMtickets
Views: 4729341 The Weeknd
#99 Measuring Power, hacked Sonoff POW, MQTT, Adafruit.io and Home Automation
 
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The Sonoff POW is a very interesting device for Home Automation. It costs only 10$ and can measure power, transmit it to your server, and switch 110/220 volt devices. I hack it and implement my own code. I also test the measurement results and give hints, how to improve them. I also include a library for the HLW8012 Power Meter Chip for the ESP8266. Itead Recall: https://www.itead.cc/blog/sonoff-th16-and-pow-recall-notice Links: Code and Sonoff POW library: https://github.com/SensorsIot/Sonoff-POW WiFi Manager (forked): https://github.com/kentaylor/WiFiManager Remote Debug: https://github.com/JoaoLopesF/RemoteDebug Solve Equations: https://www.youtube.com/watch?v=AvSXCQi75i0 https://www.facebook.com/profile.php?id=100013947273409 https://twitter.com/spiessa
Views: 33426 Andreas Spiess
An Empirical Performance Evaluation of Relational Keyword Search Systems
 
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Title: An Empirical Performance Evaluation of Relational Keyword Search Systems Domain: Data Mining Abstract: In the past decade, extending the keyword search paradigm to relational data has been an active area of research within the database and information retrieval (IR) community. A large number of approaches have been proposed and implemented, but despite numerous publications, there remains a severe lack of standardization for system evaluations. This lack of standardization has resulted in contradictory results from different evaluations, and the numerous discrepancies muddle what advantages are proffered by different approaches. In this paper, we present a thorough empirical performance evaluation of relational keyword search systems. Our results indicate that many existing search techniques do not provide acceptable performance for realistic retrieval tasks. In particular, memory consumption precludes many search techniques from scaling beyond small datasets with tens of thousands of vertices. We also explore the relationship between execution time and factors varied in previous evaluations; our analysis indicates that these factors have relatively little impact on performance. In summary, our work confirms previous claims regarding the unacceptable performance of these systems and underscores the need for standardization—as exemplified by the IR community—when evaluating these retrieval systems. Key Features: 1. The success of keyword search stems from what it does not require—namely, a specialized query language or knowledge of the underlying structure of the data. Internet users increasingly demand keyword search interfaces for accessing information, and it is natural to extend this paradigm to relational data. This extension has been an active area of research throughout the past decade. However, we are not aware of any research projects that have transitioned from proof-of-concept implementations to deployed systems. 2. We conduct an independent, empirical performance evaluation of 7 relational keyword search techniques, which doubles the number of comparisons as previous work. 3. Our results do not substantiate previous claims regarding the scalability and performance of relational keyword search techniques. Existing search techniques perform poorly for datasets exceeding tens of thousands of vertices. 4. We show that the parameters varied in existing evaluations are at best loosely related to performance, which is likely due to experiments not using representative datasets or query workloads. 5. Our work is the first to combine performance and search effectiveness in the evaluation of such a large number of systems. Considering these two issues in conjunction provides better understanding of these two critical tradeoffs among competing system designs. For more details contact: E-Mail: [email protected] Buy Whole Project Kit for Rs 5000%. Project Kit: • 1 Review PPT • 2nd Review PPT • Full Coding with described algorithm • Video File • Full Document Note: *For bull purchase of projects and for outsourcing in various domains such as Java, .Net, .PHP, NS2, Matlab, Android, Embedded, Bio-Medical, Electrical, Robotic etc. contact us. *Contact for Real Time Projects, Web Development and Web Hosting services. *Comment and share on this video and win exciting developed projects for free of cost. Search Terms: 1. 2017 ieee projects 2. latest ieee projects in java 3. latest ieee projects in data mining 4. 2017 – 2018 data mining projects 5. 2017 – 2018 best project center in Chennai 6. best guided ieee project center in Chennai 7. 2017 – 2018 ieee titles 8. 2017 – 2018 base paper 9. 2017 – 2018 java projects in Chennai, Coimbatore, Bangalore, and Mysore 10. time table generation projects 11. instruction detection projects in data mining, network security 12. 2017 – 2018 data mining weka projects 13. 2017 – 2018 b.e projects 14. 2017 – 2018 m.e projects 15. 2017 – 2018 final year projects 16. affordable final year projects 17. latest final year projects 18. best project center in Chennai, Coimbatore, Bangalore, and Mysore 19. 2017 Best ieee project titles 20. best projects in java domain 21. free ieee project in Chennai, Coimbatore, Bangalore, and Mysore 22. 2017 – 2018 ieee base paper free download 23. 2017 – 2018 ieee titles free download 24. best ieee projects in affordable cost 25. ieee projects free download 26. 2017 data mining projects 27. 2017 ieee projects on data mining 28. 2017 final year data mining projects 29. 2017 data mining projects for b.e 30. 2017 data mining projects for m.e 31. 2017 latest data mining projects 32. latest data mining projects 33. latest data mining projects in java 34. data mining projects in weka tool 35. data mining in intrusion detection system 36. intrusion detection system using data mining 37. intrusion detection system using data mining ppt 38. intrusion detection system using data mining technique
Views: 1638 InnovationAdsOfIndia
Hadoop Tutorial: Import Excel Files into Datameer
 
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http://www.datameer.com Learn how to import Excel spreadsheets, including those with existing formulas, into Datameer for Big Data analysis.
Views: 774 Datameer
Online Clustering of Multivariate Time Series
 
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Supplementary materials for SDM 2016 submission
Views: 815 OEC
NIPS 2015 Workshop (Fox) 15505 Time Series Workshop
 
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Data, in the form of time-dependent sequential observations emerge in many key real-world problems ranging from biological data, to financial markets, to weather forecasting and audio/video processing. However, despite the ubiquity of such data, the vast majority of learning algorithms have been primarily developed for the setting in which sample points are drawn i.i.d. from some possibly unknown fixed distribution. While there exist algorithms designed to handle non-i.i.d. data, these typically assume specific parametric form of data-generating distribution. Such assumptions may undermine the possibly complex nature of modern data which can possess long-range dependency patterns that we now have the computing power to discern. On the other extreme, some online learning algorithms consider a non-stochastic framework without any distributional assumptions. However, such methods may fail to fully address the stochastic aspect of real-world time-series data. lt br gt lt br gt The goal of this workshop is to bring together theoretical and applied researchers interested in the analysis of time series, and the development of new algorithms to process sequential data. This includes algorithms for time series prediction, classification, clustering, anomaly and change point detection, correlation discovery, dimensionality reduction as well as a general theory for learning and comparing stochastic processes. We invite researchers from the related areas of batch and online learning, reinforcement learning, data analysis and statistics, econometrics, and many others to contribute to this workshop.
Views: 341 NIPS
Excel Power BI Intro for Developers
 
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Excel Power BI offers analytics without programming. As a developer you can utilize it to deliver reports and data to end users. Find out how in this 2-hour video tutorial delivered by Dr. Nitin Paranjape, Office MVP and Microsoft Regional Director. Key highlights: - Pivot Table (2:00) - Why use Excel tables (4:56) - Pivot Table - deep dive (15:22) - Slicer (30:00) - Working with Multiple Pivot Table - Data Connection and Global Filter(32:10) - Cleaning up cross-tab data (35:34) - Power Query (41:00) - Certified Query - Sharepoint Data Steward (49:10) - Power Pivot (51:00) - Context-sensitive functions in Power BI (1:02:52) - Browser view options: reduce bandwith and increase performance (1:08:06) - The importance of naming sheets, tables, Pivot table (1:13:10) - Sharepoint versioning explained: Major version and Minor versions (1:15:32) - Conceptual difference between end-user BI and enterprise BI (1:17:19) - New Method of data analysis using Power View (1:19:30) - Scrollbars and slicers right in Power View (1:22:00) - Integrate images into reports and dashboards (1:26:35) - Visualize reports and dashboards in geographical distribution (1:29:22) - Power BI functionality on mobile and tablet devices - Ipad, Android devices (1:36:00) - Power Map (1:40:45) - Plotting data on 3D globe with geographical visualization (1:41:00) Dr. Nitin Paranjape (Office MVP)
Views: 38930 Efficiency 365
Condition Based Monitoring for Industrial Systems
 
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An aggregate producer wanted a Condition Based Monitoring (CBM) system that could monitor the motors in real time, apply data analytics to detect changes in motor behavior before they developed into major problems, and alert maintenance staff via email or text, anywhere they happened to be. B+B SmartWorx partnered with Comprehensive Communications to provide a complete solution. B+B provided the hardware and the data connectivity; Comprehensive Communications provided the platform based dashboard. Read more - http://bb-smartworx.com/condition-based-monitoring/
30 Or 40 Won’t Do, India Needs At Least 300 Nuclear Reactors Over The Next 50 Years
 
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There has been much debate over the expansion of nuclear energy in India, the arguments covering a gamut of angles from safety and environmental concerns to liability, security and affordability. However, whether India should go down the nuclear path is a moot question. The issue is not if India needs nuclear energy but how quickly it can expand its capacity. To understand this, a few data points about its present situation need to be kept in mind. As of January 2018, India generated 331 GW of electricity. Of this, some 66 per cent comes from thermal energy, 13.6 per cent from hydroelectric power, 18 per cent from renewable energy, and a mere two per cent from nuclear energy. Industry consumes 40 per cent of the total capacity, agriculture takes 18 per cent, domestic consumption is 24 per cent, and the rest goes to railways, commercial use, and other odds and ends. India’s per capita consumption of power is approximately 1,122 kWh and over 240 million people in India still have no access to electricity. By way of comparison, the United States (US) consumes over 12,000 kWh per capita, China utilises 4,310 kWh per person, and the countries in western Europe such as France, Germany and Britain approximately 6,500 kWh. The connection between energy consumption and economic growth cannot be overemphasised. The present definition of rural electrification employed by the government of India is that a village is considered electrified if 10 per cent of the households have at least one electric point. Even functional electrification – televisions, refrigerators, computers, mobile phones, air conditioning, fans – to all without considering any increase in industrial and other demands would require a mammoth increase in generating capacity no matter how conservatively electricity is used. The demand for electricity will only increase as India’s economy and population grow, with greater manufacturing capability and a more prosperous citizenry desirous of the many comforts of life. Several studies have predicted that India’s electricity needs will rise some eight times by the middle of this century. Environmental and all other considerations aside, this purely physical bottleneck is one of the greatest arguments for the aggressive expansion of nuclear power in India. The difference in the energy release of chemical and nuclear processes is several orders of magnitude higher for the latter. The fission of one atom of uranium releases as much energy as the combustion of 33 million atoms of carbon. This means that uranium is far more energy-dense than carbon, making transportation far easier. The rapid expansion of nuclear power and a gradual shift from coal will free enormous capacity in Indian transportation infrastructure, saving billions in unnecessary expansion costs for roads, rail networks and ports. This is from merely the logistical benefits of shifting from coal to nuclear – other equally compelling factors have not been considered in this article for reasons of brevity and focus. Can this not be achieved via other means, such as solar or wind power? The short answer is no. It is one thing to reduce the burden on the grid by installing solar panels on residential buildings but domestic electricity consumption represents only 22 per cent of the total. Scaling up renewable energy to meet the demands of the next century is a challenge of an entirely different magnitude. Again limiting ourselves to analysing logistical difficulties alone, mining the rare earths for the solar panelling and energy storage required is well beyond global manufacturing capabilities. If India is to have ample energy for its economic growth and that story includes high speed rail, electric cars, and other substitutions of electrical power for fossil fuels, it cannot afford not to get bullish on nuclear power. At present, some 40 reactor projects are ongoing or have been stalled due to legal complications but Delhi should not be thinking about 30 or 40 reactors – it should be considering 300 or 400. Even with such a massive investment over the next 50 years, Disclaimer- This channel is for defence related news worldwide . We try to give you true news related to each and every aspects of defence . It is either country, defence weapon, air Force, army ,navy, military or anything we will try to fully explain . The content specially news we upload are taken from various news channels and media houses . we never claim it is 100 % on our behalf but we try to deliver you exact without rumours . our news is specially related to india . As India is a growing country specially in defence under narendra modi BJP government . Channel Link: https://www.youtube.com/DefenceTube Facebook Link: https://www.facebook.com/defencetube Twitter Link : https://twitter.com/DefenceTube Check my all playlist : https://www.youtube.com/defencetube/playlist
Views: 505 Defence Tube
Intro to Azure ML: What is Azure Machine Learning?
 
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What's better than machine learning? Machine learning where coding is optional! Drag and drop machine learning with a visual interface! We’re going to introduce you to a new tool to add to your data science toolkit, Azure Machine Learning Studio. Azure Machine Learning is a cloud based data science platform on the Azure cloud ecosystem. Azure Machine Learning Studio also supports coding in Python, SQL, and R. In Part 1 we will cover: - What is Azure Machine Learning Studio - Being in the cloud - Subscriptions you need - Pricing of Azure Introduction to Data Mining: https://www.youtube.comhttps://www.youtube.com/playlist?list... -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 3600+ employees from over 742 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: https://hubs.ly/H0f8mQq0 See what our past attendees are saying here: https://hubs.ly/H0f8m_C0 -- Like Us: https://www.facebook.com/datascienced... Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data... Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_scienc... Vimeo: https://vimeo.com/datasciencedojo
Views: 28051 Data Science Dojo
Blackhat 2012 EUROPE - Dissecting Smart Meters
 
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This video is part of the Infosec Video Collection at SecurityTube.net: http://www.securitytube.net Blackhat 2012 EUROPE - Dissecting Smart Meters The Smart Grid brings greater benefits for electric utilities and customer alike, however these benefits come at a cost from a security perspective. This presentation will explore the architecture of most Smart Meters, the protocols they use, a breakdown of their embedded components, and the functionality their headend servers contain. We'll explain the methodologies we've developed to perform penetration testing these AMI systems, enumerate the types of vulnerabilities we commonly find, and discuss the solutions we recommend to Smart Meter vendors. We will even demonstrate at least one of the attacks we commonly perform in our penetration tests. This will be done without the FUD and over-hyped framing that we usually find in the media and other Smart Grid presentations. https://media.blackhat.com/bh-eu-12/Searle/bh-eu-12-Searle-Smart_Meters-WP.pdf https://media.blackhat.com/bh-eu-12/Searle/bh-eu-12-Searle-Smart_Meters-Slides.pdf
Views: 883 SecurityTubeCons
Improving privacy preserving and security for decentralized key policy attributed based encryption
 
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Improving privacy preserving and security for decentralized key policy attributed basaed encryption- IEEE PROJECTS 2018 Download projects @ www.micansinfotech.com WWW.SOFTWAREPROJECTSCODE.COM https://www.facebook.com/MICANSPROJECTS Call: +91 90036 28940 ; +91 94435 11725 IEEE PROJECTS, IEEE PROJECTS IN CHENNAI,IEEE PROJECTS IN PONDICHERRY.IEEE PROJECTS 2018,IEEE PAPERS,IEEE PROJECT CODE,FINAL YEAR PROJECTS,ENGINEERING PROJECTS,PHP PROJECTS,PYTHON PROJECTS,NS2 PROJECTS,JAVA PROJECTS,DOT NET PROJECTS,IEEE PROJECTS TAMBARAM,HADOOP PROJECTS,BIG DATA PROJECTS,Signal processing,circuits system for video technology,cybernetics system,information forensic and security,remote sensing,fuzzy and intelligent system,parallel and distributed system,biomedical and health informatics,medical image processing,CLOUD COMPUTING, NETWORK AND SERVICE MANAGEMENT,SOFTWARE ENGINEERING,DATA MINING,NETWORKING ,SECURE COMPUTING,CYBERSECURITY,MOBILE COMPUTING, NETWORK SECURITY,INTELLIGENT TRANSPORTATION SYSTEMS,NEURAL NETWORK,INFORMATION AND SECURITY SYSTEM,INFORMATION FORENSICS AND SECURITY,NETWORK,SOCIAL NETWORK,BIG DATA,CONSUMER ELECTRONICS,INDUSTRIAL ELECTRONICS,PARALLEL AND DISTRIBUTED SYSTEMS,COMPUTER-BASED MEDICAL SYSTEMS (CBMS),PATTERN ANALYSIS AND MACHINE INTELLIGENCE,SOFTWARE ENGINEERING,COMPUTER GRAPHICS, INFORMATION AND COMMUNICATION SYSTEM,SERVICES COMPUTING,INTERNET OF THINGS JOURNAL,MULTIMEDIA,WIRELESS COMMUNICATIONS,IMAGE PROCESSING,IEEE SYSTEMS JOURNAL,CYBER-PHYSICAL-SOCIAL COMPUTING AND NETWORKING,DIGITAL FORENSIC,DEPENDABLE AND SECURE COMPUTING,AI - MACHINE LEARNING (ML),AI - DEEP LEARNING ,AI - NATURAL LANGUAGE PROCESSING ( NLP ),AI - VISION (IMAGE PROCESSING),mca project CLOUD COMPUTING 1. Cloud-Based Fine-Grained Health Information Access Control Framework for Lightweight IoT Devices with Dynamic Auditing and Attribute Revocation (April-June 1 2018 ) 2. Secured outsourcing towards cloud computing environment based on DNA cryptography ( 23 April 2018) 3. Data Security in Cloud Computing Using AES Under HEROKU Cloud (07 June 2018) 4. Privacy-Preserving Indexing and Query Processing for Secure Dynamic Cloud Storage 5. Improving Privacy-Preserving and Security for Decentralized Key-Policy Attributed-Based Encryption 6. A Practical Public Key Encryption Scheme Based on Learning Parity with Noise 7. An Approach to Balance Maintenance Costs and Electricity Consumption in Cloud Data Centers 8. Integrated Authentication and Key Agreement Framework for Vehicular Cloud Computing 9. A Power-of-Two Choices Based Algorithm for Fog Computing 10. virtFlow: Guest Independent Execution Flow Analysis Across Virtualized Environments 11. Adaptive Resource Management for Analyzing Video Streams from Globally Distributed Network Cameras 12. Enhancing Performance and Energy Efficiency for Hybrid Workloads in Virtualized Cloud Environment 13. Minimal Cost Server Configuration for Meeting Time-Varying Resource Demands in Cloud Centers 14. VMGuard: A VMI-based Security Architecture for Intrusion Detection in Cloud Environment 15. Aggregation-Based Colocation Datacenter Energy Management in Wholesale Markets 16. Provably secure and lightweight identity-based authenticated data sharing protocol for cyber-physical cloud environment 17. Energy Efficient Scheduling of Servers with Multi-Sleep Modes for Cloud Data Center 18. A tight estimate of job completion time in vehicular clouds 19. HealthDep: An Efficient and Secure Deduplication Scheme for Cloud-Assisted eHealth Systems 20. An Efficient and Fair Multi-Resource Allocation Mechanism for HeterogeneousServers 21. Dynamic VM Scaling: Provisioning and Pricing through an Online Auction 22. Price-based Resource Allocation for Edge Computing: A Market Equilibrium Approach 23. A Key-Policy Attribute-Based Temporary Keyword Search scheme for Secure Cloud Storage 24. Efficient Retrieval Over Documents Encrypted by Attributes in Cloud Computing 25. A Planning Approach for Reassigning Virtual Machines in IaaS Clouds 26. A Robust Formulation for Efficient Application Offloading to Clouds 27. Efficient Traceable Authorization Search System for Secure Cloud Storage 28. An Efficient and Secured Framework for Mobile Cloud Computing 29. Adaptive Resource Allocation and Provisioning in Multi-Service Cloud Environments 30. Cloud Centric Authentication for Wearable Healthcare Monitoring System 31. Towards Shared Ownership in the Cloud 32. Security Analysis of Smartphone and Cloud Computing Authentication Frameworksand Protocols 33. Integrated Authentication and Key Agreement Framework for Vehicular CloudComputing 34. CLASS: Cloud Log Assuring Soundness and Secrecy Scheme for Cloud Forensics 35. An Approach to Balance Maintenance Costs and Electricity Consumption in Cloud Data Centers
Views: 4 Micans Infotech
Crowdsourcing Predictors of Behavioral Outcomes 2013-2014 IEEE
 
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To get this project in ONLINE or through TRAINING Sessions, Contact: JP INFOTECH, 45, KAMARAJ SALAI, THATTANCHAVADY, PUDUCHERRY-9 Landmark: Opposite to Thattanchavady Industrial Estate, Next to VVP Nagar Arch. Mobile: (0) 9952649690 , Email: [email protected], web: www.jpinfotech.org Blog: www.jpinfotech.blogspot.com Crowdsourcing Predictors of Behavioral Outcomes 2013-2014 IEEE Generating models from large data sets—and determining which subsets of data to mine—is becoming increasingly automated. However, choosing what data to collect in the first place requires human intuition or experience, usually supplied by a domain expert. This paper describes a new approach to machine science which demonstrates for the first time that nondomain experts can collectively formulate features and provide values for those features such that they are predictive of some behavioral outcome of interest. This was accomplished by building a Web platform in which human groups interact to both respond to questions likely to help predict a behavioral outcome and pose new questions to their peers. This results in a dynamically growing online survey, but the result of this cooperative behavior also leads to models that can predict the user's outcomes based on their responses to the user-generated survey questions. Here, we describe two Web-based experiments that instantiate this approach: The first site led to models that can predict users' monthly electric energy consumption, and the other led to models that can predict users' body mass index. As exponential increases in content are often observed in successful online collaborative communities, the proposed methodology may, in the future, lead to similar exponential rises in discovery and insight into the causal factors of behavioral outcomes.
Views: 590 jpinfotechprojects
Earn money while sleeping-- Bitcoin mining  cloud mining -
 
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Earn money while sleeping-- Bitcoin mining cloud mining - link ::: http://emining.club/?rinvite=ag7193930 How Does Cloud Mining Bitcoin Work? If you want to invest in bitcoin mining without the hassle of managing your own hardware, there is an alternative. You can use the cloud to earn your coins. Put very simply, cloud mining means using (generally) shared processing power run from remote data centres. One only needs a home computer for communications, optional local bitcoin wallets and so on. However, there are certain risks associated with cloud mining that investors need to understand prior to purchase. Pros Here’s why you might want to consider cloud mining: A quiet, cooler home – no constantly humming fansNo added electricity costsNo equipment to sell when mining ceases to be profitableNo ventilation problems with hot equipmentReduced chance of being let down by mining equipment suppliers. Cons Here’s why you might notwant to consider cloud mining: Risk of fraudOpaque mining operationsLess fun (if you’re a geek who likes system building!)Lower profits – the operators have to cover their costs after allContractual warnings that mining operations may cease depending on the price of bitcoinLack of control and flexibility. Types of cloud mining In general, there are three forms of remote mining available at the moment: Hosted mining Lease a mining machine that is hosted by the provider.Virtual hosted mining Create a (general purpose) virtual private server and install your own mining software.Leased hashing power Lease an amount of hashing power, without having a dedicated physical or virtual computer. (This is, by far, the most popular method of cloud mining.) How to determine profitability We have previously covered ways to calculate mining profitability. However, the web services offered are designed to work with your hardware parameters, not cloud-mining parameters. Even so, you can still use these calculators by thinking clearly about the costs involved. Profitability calculators (for example, The Genesis Block) often ask for your electricity costs, and sometimes the initial investment in hardware. Effectively, you are being asked for your ongoing costs and your one-off investments. Therefore, since the provider, not you, is paying the electricity bills, you can enter the monthly mining bill in place of the electricity cost. The conversion process isn’t completely straightforward, though. In the case of hardware miners, you can work out the monthly running cost by multiplying your electricity charge (ie: $ per KWh) by the power consumption of the unit and by a conversion factor of 0.744 (the ratio of seconds per month to joules of energy per KWh). But, for cloud mining calculations, you need to do the opposite, because the provider gives you an (effective) monthly running cost. Hence, you need to calculate an equivalent cost per kilowatt hour to feed into the mining calculator. This is done by dividing (not multiplying) the monthly running cost by the 0.744 conversion factor mentioned above. Risk vs reward When engaging in any type of cryptocurrency mining there are risks, but profitability is possible if you make the right choices. In this article, we’ve given you some pointers on how to decide which way to go. In your test calculations, you will likely see that somecloud mining services will be profitable for a few months, but, as the difficulty level of bitcoin increases, you would probably start to make a loss in four to six months and beyond. A possible remedy to this situation is to reinvest what you have made into maintaining a competitive hashing rate, but this is highly speculative. As mentioned above, the risk of fraud and mismanagement is all too common in the cloud mining space. Investors should only invest in cloud mining if they are comfortable with these risks – as the saying goes, never invest more than you are willing to lose. Investigate social media channels, speak with former customers and ask pointed questions of operators prior to investing. Ultimately, you should practice the same kind of due diligence that you would for any investment. Disclaimer: This article should not be viewed as an endorsement of any of the services mentioned. Please do your own research before considering investing any funds via these services. Australian mine, server room, accounting and reward and risk images via Shutterstock
Views: 95 Alert Of The Day
"Lessons Learned from the International Workshop on Release Engineering," Bram Adams
 
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The release engineering process brings high quality code changes from a developer's workspace to the end user, encompassing (amongst others) the integration of code changes, continuous building/testing of such changes (CI), setup of deployment environments, deployment and release. Recent practices of continuous delivery, which bring changes to the end user in the order of days or hours rather than years, have convinced many companies to invest in their release engineering pipeline and teams. However, what exactly should these companies invest in? Which continuous delivery strategies work, and which ones did not (and why)? Do only large companies benefit? These and other questions were targeted by the past three editions of the International Workshop on Release Engineering (RELENG) and the 1st IEEE Software Special Issue on Release Engineering. This webinar will revisit the major insights and discussion points of RELENG, aiming to provide a starting point for companies to decide on their future release engineering strategy. Bram Adams, Polytechnique Montréal Bram Adams is an assistant professor at Polytechnique Montréal (Canada), where he heads the MCIS lab on Maintenance, Construction and Intelligence of Software. He obtained his PhD at the GH-SEL lab at Ghent University (Belgium), and was an adjunct assistant professor in the Software Analysis and Intelligence Lab at Queen's University (Canada). His research interests include all aspects of software release engineering, mining software repositories and software maintenance. His work has been published at premier software engineering venues such as EMSE, TSE, ICSE, FSE, ASE, MSR and ICSME. Stephany Bellomo, Software Engineering Institute, Carnegie Mellon University Stephany Bellomo is a member of the technical staff at the Software Engineering Institute, Carnegie Mellon University. She has an MS in Software Engineering from George Mason University. Bellomo focuses her time on empirical research for improving software delivery and working with DoD/government practitioners on software-related challenges. Recent publications include papers on practices to enable rapid deployment. Bellomo served on the program committee as the Tutorial Chair for the 2013 Software Engineering Institute (SEI) Architecture Technology User Network (SATURN) Conference and has served as a technical reviewer yearly for the SATURN conference since 2010. She also served as a technical reviewer for the SEI Software Product Lines conference 2013. Foutse Khomh, Ecole Polytechnique de Montréal Foutse Khomh is an assistant professor at the Ecole Polytechnique de Montréal (Canada). He received a Ph.D in Software Engineering from the University of Montreal in 2010, under the supervision of Yann-Gaël Guéhéneuc. His main research interest is in the field of empirical software engineering, with an emphasis on developing techniques and tools to improve software quality. He has studied many aspects of the release engineering process of large software companies such as RIM and Mozilla, and has published several papers in international conferences and journals, including ICSM, MSR, WCRE, ICWS, JSS, JSP, and EMSE. He is the recipient of a best paper award from the European Research Consortium for Informatics and Mathematics. Foutse has served on the program committees of several international conferences including ICSM, WCRE, MSR, ICPC, and has reviewed for top international journals such as SQJ, EMSE, and TSE. Shane McIntosh, McGill University Shane McIntosh is an Assistant Professor in the Department of Electrical and Computer Engineering at McGill University. He received his Bachelor's degree from the University of Guelph and his MSc and PhD degrees from Queen's University, where he held an NSERC Vanier Scholarship. In his research, Shane uses empirical software engineering techniques to study software build systems, release engineering, and software quality. His research has been published at several top-tier software engineering venues, such as the International Conference on Software Engineering (ICSE), the International Symposium on the Foundations of Software Engineering (FSE), and the Springer Journal of Empirical Software Engineering (EMSE).
What is Dynamic Time Warping
 
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This is a brief introduction to Dynamic Time Warping. We try to give you a basic understanding of the general concept.
Views: 13572 EpicFactFind
Google NYC Tech Talk: Google Ideas
 
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Google Tech Talk June 30, 2015 (click "show more" for more information) Presented by Yasmin Green, Salome Vakhtangadze, and Baris Yuksel ABSTRACT As long as people have expressed ideas, others have tried to silence them. Today one out of every three people lives in a society that is severely censored. Online barriers can include everything from filters that block content to targeted attacks designed to take down websites. For many people, these obstacles are more than an inconvenience—they represent full-scale repression. Engineers from Google Ideas will present the way technology is being used to enable free expression online, and protect every voice in the digital debate. Google Presenters: Yasmin Green Yasmin Green is the Head of Strategy and Operations for Google Ideas. She also oversees the team’s work on counter-radicalization and fragile states. At Google, Yasmin has assumed roles as Head of Sales Strategy and Operations for Southern Europe, Middle East, and Africa and Sub-Saharan Africa Operations Manager, and prior to joining Google, she consulted for Booz Allen Hamilton across Europe, the Middle East and Africa. Yasmin has extensive experience leading and project managing in some of the world’s toughest environments. She has spent time in Iran, Syria and Nigeria, where she has worked cross-functionally in sectors ranging from oil and gas to the Internet. She recently led a multi-partner coalition to launch Against Violent Extremism, the world's first online network of former violent extremists and survivors of terrorism. Yasmin is a Senior Advisor on Innovation to Oxford Analytica and Co-Chair of the European Commission's’ Working Group on Online Radicalization. Salome Vakhtangadze Salome is a Software Engineer. She joined Google Ideas after having worked on Google's Search Infrastructure team for 3 years. She currently works on uProxy, and is passionate about human rights. Baris Yuksel Baris Yuksel is a tech lead and software engineering manager. He is currently leading projects at Google Ideas, a think/do tank that explores how technology can enable people to confront threats in the face of conflict, instability and repression. Google Ideas was founded on the principle that the next five billion to come online will face far greater human challenges than the first two billion. Baris has been focusing on designing and developing next generation features and technologies, trying to create magic moments not for few but for all. In the past, Baris worked on Google Search with Craig Nevill-Manning, founder of Google New York. Together they worked on features bridging the gap between Search and Google Now. Baris has been a volunteer with ScriptEd teaching high school students with an experimental curriculum, which he has been developing under the guidance of ScriptEd. He is hopeful that it will contribute to the major teaching effort. Baris graduated from MIT with a BS in Electrical Engineering and Computer Science, minoring in Economics.
Views: 4635 GoogleTechTalks
Accelerated Crash Course (ACC) 2014
 
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The above video is a condensation of the 4.5-hour long full Crash Course video series. The data and analysis underlying the material represent over a decade of intensive research and study. Over that decade, its forecasts have proved increasingly validated by events like the collapse of the housing bubble in 2007, the 2008 credit crisis and the anemic 'recovery' since, oil prices persistently over $100 per barrel, the five-fold rise in gold prices, and many other symptoms of an unsustainable world economy reaching its failure point. Sadly, the risks warned of in this video are very real, and they are arriving now. Once you've finished watching the video, please share it with those whom you think would most benefit from it. The more people we wake up to its message, the more hands we'll have supporting us today in planning for tomorrow. With thanks, Chris Martenson PhD & Adam Taggart V.1.1
Views: 109319 ChrisMartensondotcom
Outward Bound: Colonizing Jupiter
 
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Jupiter and its moon are a rarely considered prospect for colonization, but potentially the ripest opportunity for it in the solar system. In this episode of the Outward Bound series we will examine the options for colonizing each of Jupiter's primary moons and even discuss ways to colonize the giant planet itself. Visit our Website: http://www.isaacarthur.net Join the Facebook Group: https://www.facebook.com/groups/1583992725237264/ Support the Channel on Patreon: https://www.patreon.com/IsaacArthur Visit the sub-reddit: https://www.reddit.com/r/IsaacArthur/ Listen or Download the audio of this episode from Soundcloud: https://soundcloud.com/isaac-arthur-148927746/colonizing-jupiter Cover Art by Jakub Grygier: https://www.artstation.com/artist/jakub_grygier Graphics Team: Edward Nardella Jarred Eagley Justin Dixon Jeremy Jozwik Katie Byrne Kris Holland Misho Yordanov Murat Mamkegh Pierre Demet Sergio Botero Stefan Blandin Script Editing: Andy Popescu Connor Hogan Edward Nardella Eustratius Graham Gregory Leal Jefferson Eagley Keith Blockus Luca de Rosa Mark Warburton Michael Gusevsky Mitch Armstrong MolbOrg Naomi Kern Philip Baldock Sigmund Kopperud Tiffany Penner Music: Markus Junnikkala, "Hail the Victorious Dead" Koalips, "Kvazar" Lombus, "Hydrogen Sonata" Aerium, "Waters of Atlantis" Chris Zabriskie, "CGI Snake" Kai Engel, "Snowfall (Intro)"
Views: 240606 Isaac Arthur
UCR Time Series Classification Archive
 
02:06
For More Medical and Healthcare related Services Visit : http://www.medverdict.com For More Medical and Healthcare related Services Visit : http://www.medverdict.com UCR Time Series Classification Archive http://www.phwiki.com/
Views: 144 Medverdict
PRACTICE: Outside In | Inside Out
 
03:33:37
This symposium considers discourse on contemporary issues of design practice in two parts: the external pressures of economic, environmental, and political systems, and internal forces of tools, techniques, and strategies for design. Addressing the multifaceted nature of the profession, we will explore themes for the design of practice, such as work and labor, tools and technology, and ethics and agency. The symposium highlights potential avenues for the growth and constitution of practice, as well as the issues currently at stake within the profession. The following discussions confront pressing questions regarding the shifting responsibilities of design practice, and the future of practice itself. This symposium is generously sponsored by the Carl M. Sapers Ethics in Practice Fund, and co-hosted by the GSD Practice Platform and the Department of Architecture. Panelists: Aaron Cayer, Neena Verma, Jesse Keenan, Alison Brooks, Eduard Sancho Pou, Sawako Kaijima, Randy Deutsch, Robert Pietrusko Moderators: Mark Lee, Grace La
Views: 1585 Harvard GSD
Thorium.
 
06:27:00
http://ThoriumRemix.com/ Thorium is an abundant material which can be transformed into massive quantities of energy. To do so efficiently requires a very different nuclear reactor than the kind we use today- Not one that uses solid fuel rods, but a reactor in which the fuel is kept in a liquid state. Not one that uses pressurized water as a coolant, but a reactor that uses chemically stable molten salts. Such a reactor is called a "Molten Salt Reactor". Many different configurations are possible. Some of these configurations can harness Thorium very efficiently. This video explores the attributes of Molten Salt Reactors. Why are they compelling? And why do many people (including myself) see them as the only economical way of fully harnessing ALL our nuclear fuels... including Thorium. This video has been under development since 2012. I hope it conveys to you why I personally find Molten Salt Reactors so compelling, as do the many volunteers and supporters who helped create it. Much of the footage was shot by volunteers. All music was created by: http://kilowattsmusic.com To support this project, please visit: https://patreon.com/thorium Entities pursuing Molten Salt Reactors are... Flibe Energy - http://flibe-energy.com/ Terrestrial Energy - http://terrestrialenergy.com/ Moltex Energy - http://www.moltexenergy.com/ ThorCon Power - http://thorconpower.com/ Transatomic - http://www.transatomicpower.com/ Seaborg - http://seaborg.co/ Copenhagen Atomics - http://www.copenhagenatomics.com/ TerraPower - http://terrapower.com/ Bhabha Atomic Research Centre - http://www.barc.gov.in/ Chinese Academy of Sciences - http://english.cas.cn/ Regular Thorium conferences are organized by: http://thoriumenergyalliance.com/ http://thoriumenergyworld.com/ Table of Contents 0:00:00 Space 0:17:29 Constraints 0:28:22 Coolants 0:40:15 MSRE 0:48:54 Earth 0:59:46 Thorium 1:22:03 LFTR 1:36:13 Revolution 1:44:58 Forward 1:58:11 ROEI 2:05:41 Beginning 2:08:36 History 2:38:59 Dowtherm 2:47:57 Salt 2:51:44 Pebbles 3:06:07 India 3:18:44 Caldicott 3:35:55 Fission 3:56:22 Spectrum 4:04:25 Chemistry 4:12:51 Turbine 4:22:27 Waste 4:40:15 Decommission 4:54:39 Candlelight 5:13:06 Facts 5:26:08 Future 5:55:39 Pitches 5:56:17 Terrestrial 6:08:33 ThorCon 6:11:45 Flibe 6:20:51 End 6:25:53 Credits Some of this footage is remixed from non-MSR related sources, to help explain the importance of energy for both space exploration and everyday life here on Earth. Most prominently... Pandora's Promise - https://youtu.be/bDw3ET3zqxk Dr. Neil DeGrasse Tyson - https://youtu.be/Pun76NZMjCk Dr. Robert Zubrin - https://youtu.be/EKQSijn9FBs Mars Underground - https://youtu.be/tcTZvNLL0-w Andy Weir & Adam Savage - https://youtu.be/5SemyzKgaUU Periodic Table Videos - https://youtube.com/channel/UCtESv1e7ntJaLJYKIO1FoYw
Views: 130493 gordonmcdowell
From Bitcoin To Hashgraph (Documentary) Hidden Secrets Of Money Episode 8
 
01:14:26
Bonus Features: http://www.hiddensecretsofmoney.com Today, mankind stands at a crossroads, and the path that humanity chooses may have a greater impact on our freedom and prosperity than any event in history. In 2008 a new technology was introduced that is so important that its destiny, and the destiny of mankind are inextricably linked. It is so powerful that if captured and controlled, it could enslave all of humanity. But if allowed to remain free and flourish - it could foster unimaginable levels of peace and prosperity. It has the power to replace all financial systems globally, to supplant ninety percent of Wall St, and to provide some functions of government. It has no agenda. It's always fair and impartial. It can not be manipulated, subverted, corrupted or cheated. And - it inverts the power structure and places control of one's destiny in the hands of the individual. In the future, when we look back at the 2.6 million-year timeline of human development and the major turning points that led to modern civilization - the creation of farming, the domestication of animals, the invention of the wheel, the harnessing of electricity and the splitting of the atom - the sixty year development of computers, the internet and this new technology will be looked upon as a single event...a turning point that will change the course of human history. It's called Full Consensus Distibuted Ledger Technology, and so far its major use has been for cryptocurrencies such as Bitcoin....but its potential goes far, far beyond that. The Crypto Revolution: From Bitcoin to Hashgraph is our latest episode of Hidden Secrets of Money. It’s about the evolution of cryptocurrencies and full consensus distributed ledger technology, and how they will change our world. I believe that this video is by far the easiest way for the average person to gain an understanding of what cryptocurrencies are and how they work, but more importantly, the immense power of full consensus distributed ledger technology and the impact it will have on our daily lives. I have an absolute passion for monetary history and economics, and I love teaching them. Cryptocurrencies are our future, and there is no escaping it… this is the way everything will be done from now on. But, we now stand at a crucial turning point in history. Full consensus ledgers such as Blockchain and Hashgraph have the power to enslave us, or free us… it all depends on how we choose to use them. If we choose to support centralized versions issued by governments and the financial sector we will be granting them more control over our daily lives. Politicians and bureaucrats will be able raise taxes instantly, whenever they want, on every dollar you make as you make them, and every dollar you spend as you spend them. If they think the economy needs stimulating they'll be able to enforce huge negative interest rates, effectively punishing you for not spending everything you earn before you earn it. They'll be able to decide where you can go and where you can’t, what you can buy and what you can’t, and what you can do and whatever they decide you can’t do… and if they don't like you, they can just disconnect you from the monetary system. So, will the monetary system become fully distributed and help to free mankind, or will it be centralized and enslave us? The choice is in front of us right now, and our decisions will create our future. I believe that this will be a binary outcome, there is no middle ground, it will either be one future or the other. The question is, will it be the future we want? Or the future they want? I’m a precious metals dealer and one thing I’ve learned is that gold, silver, and now free market decentralized cryptocurrencies, represent freedom. Because of this knowledge I started investing in crypto currencies long ago and also became one of the first precious metals dealers to accept bitcoin as payment for gold and silver. I would really appreciate it if you could share this video with everyone you know. I think it’s very important that as many people as possible find out about the changes to the global monetary system that are happening right now… nothing will affect us more, and everyone’s future depends on it. Thanks, Mike If you enjoyed watching this video, be sure to pick up a free copy of Mike's bestselling book, Guide to Investing in Gold & Silver: https://goldsilver.com/buy-online/investing-in-gold-and-silver/ (Want to contribute closed captions in your language for our videos? Visit this link: http://www.youtube.com/timedtext_cs_panel?tab=2&c=UCThv5tYUVaG4ZPA3p6EXZbQ)
Innovation, Safety and the Future of Mining | Curtin University Lecture
 
01:03:04
The future of mining, where is it going? Join our four prominent alumni as they lead this conversation and share their expertise on innovation, safety, policy and leadership within the industry. Speakers: - Mr Neil Warburton (Master of Ceremonies), Executive Chairman at White Rivers Exploration - Mr Greg Lilleyman, Director of Operations at Fortescue Metals Group - Dr Vanessa Guthrie, Chairman of the Minerals Council of Australia - Mr Steve Durkin, Managing Director at Safescape Chapter Markers: This Alumni Innovator Series: Innovation, Safety and the Future of Mining was held on Wednesday 31 May 2017 at our Bentley Campus. This video has been closed captioned.
Views: 1346 Curtin University
How To Fill Form Grass Mahakosh Government Receipt Challan Step By Step Tutorial
 
06:13
Who To Fill Form Grass Mahakosh Receipt Challan Step By Step Tutorial GRAS-Government Receipt Accounting System Get Challan GRN Number, green environment tax,Other Receipt Vehicle,Passenger tax for stage carriage,Payment of fees and fines,Road Safety Cess,tax on motor vehicle,tax on entry of goods into local areas, Get Challan GRN Number, green environment tax,Other Receipt Vehicle,Passenger tax for stage carriage,Payment of fees and fines,Road Safety Cess,tax on motor vehicle,tax on entry of goods into local areas,Chief Electrical Inspector,Chief Judge, Small Causes Court, Bombay,Chief Metropolitan Magistrate, Bombay,Co-operation .marketing And Textiles Department.(mantralaya),Commissioner Of Labour,Commissioner Of Police, Mumbai,Commissioner, State Excise,Commissionerate Dairy Development,Commissionerate Of Agriculture,Commissionerate Of Animal Husbandary,Commissionerate Of Fisheries,Commissionerate Of Sales Tax,Controller Of Legal Metrology,Director General Of Police,Directorate General Of Information And Public Relations, Directorate Of Accounts And Treasuries ,Directorate Of Anti Corruption Bureau, M. S. Mumbai, Directorate Of Education, Directorate Of Geology And Mining,Directorate Of Health Services,Directorate Of Industrial Safety And Health,Directorate Of Insurance,Directorate Of Medical Education and Reserch,Directorate Of Steam Boilers,Directorate Of Town Planning And Valuation,District And Sessions Court,Finance Department (mantralaya),Food And Drugs Administration,Food, Civil Supplies and consumer Protection Department,High Court,Industrial Courts,Inspector General Of Registration Labour Courts,Maharashtra Institute Of Labour Studies P. L ,Deshpande Maharashtra Kala Academy Principal Judge, Bombay City Civil And Sessions Court Registrar Of Firms Revenue Department,Settlement Commissioner And Director Of Land Records,
Views: 42960 Salam Aayiba log
Know About GDP & IIP | TAMIL | NSE | MCX | TAMIL | NIFTY | CTA
 
13:50
Gross domestic product (GDP) is the monetary value of all the finished goods and services produced within a country's borders in a specific time period. GDP is a broad measurement of a nation’s overall economic activity. Though GDP is usually calculated on an annual basis, it can be calculated on a quarterly basis as well. GDP includes all private and public consumption, government outlays, investments, private inventories, paid-in construction costs and the foreign balance of trade (exports are added, imports are subtracted). GDP is commonly used as an indicator of the economic health of a country, as well as a gauge of a country's standard of living. GDP can be used to compare the productivity of various countries with a high degree of accuracy. A nation’s GDP from any period can be measured as a percentage relative to previous periods. An important statistic that indicates whether an economy is expanding or contracting, GDP can be tracked over long spans of time and used in measuring a nation’s economic growth or decline, as well as in determining if an economy is in recession (generally defined as two consecutive quarters of negative GDP growth). Providing a quantitative figure for GDP helps a government make decisions such as whether to stimulate a stagnant economy by pumping money into it or, conversely, to slow down an economy that's getting over-heated. Businesses can also use GDP as a guide to decide how best to expand or contract their production and other business activities. And investors also watch GDP since it provides a framework for investment decision-making. The "corporate profits" and "inventory" data in the GDP report are a great resource for equity investors, as both categories show total growth during the period; corporate profits data also displays pre-tax profits, operating cash flows and breakdowns for all major sectors of the economy. The Central Statistics Office (CSO), under the Ministry of Statistics and Program Implementation, is responsible for macroeconomic data gathering and statistical record keeping.  The CSO collects and compiles the data required to calculate the GDP and other statistics. The GDP in India is calculated using two different methods, The first method is based on economic activity (at factor cost), and the second is based on expenditure (at market prices). Further calculations are made to arrive at nominal GDP (using current market price) and real GDP (inflation-adjusted). The factor cost figure is calculated by collecting data for the net change in value for each sector during a particular time period. The following eight industry sectors are considered in this cost: Agriculture, forestry, and fishing; Mining and quarrying; Manufacturing; Electricity, gas and water supply; Construction; Trade, hotels, transport and communication; Financing, insurance, real estate and business services; Community, social and personal services. Index of Industrial Production The Index of Industrial Production (IIP) is an index for India which details out the growth of various sectors in an economy such as mineral mining, electricity and manufacturing. The all India IIP is a composite indicator that measures the short-term changes in the volume of production of a basket of industrial products during a given period with respect to that in a chosen base period. It is compiled and published monthly by the central statistical organization (CSO), Ministry of Statistics and Program Implementation six weeks after the reference month ends. For further to register as member : http://app.aliceblueonline.com/OpenAccount.aspx?c=CTA Twitter : https://twitter.com/chennaittradin1 Facebook : https://www.facebook.com/chennaitradingacademy/ LinkedIn : https://www.linkedin.com/in/chennai-trading-academy-cta-b0571b165/

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