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Best mobile phones under ₹40,000 in India (April 2024): OnePlus 12R, Vivo V30 and more

Best mobile phones under ₹40,000 in India (April 2024): OnePlus 12R, Vivo V30 and more
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Awesome-navy , Qualcomm-snapdragon , Optical-image-stabilization , Electronic-image-stabilization , Interval-shooting , Pro-mode , Movie-mode , Nothing-phone , Motion-photo , Super-res-zoom , Document-mode

Four Indian Americans among 188 Guggenheim Fellows

Four Indian Americans among 188 Guggenheim Fellows
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Varanasi , Uttar-pradesh , India , United-states , Massachusetts , Michigan , New-york , Berkeley , California , Nirman , West-bengal , Cambridge

Quantum Encryption: Pioneering Cybersecurity Advancements

Quantum encryption leverages quantum mechanics' principles and offers unbreakable security for sensitive data transmission.

China , Artur-ekert , Vatsal-vasani , Ashutosh-dhar-dwivedi , Poptika-shutterstock , Gilles-brassard , Susha-cheriyedath , Charles-bennett , Kumar-prateek , Stephen-wiesner , Ruhul-amin , Los-alamos-national-laboratory

Machine Learning Helps Improve Quality Assurance for Wind Turbines

Machine Learning Helps Improve Quality Assurance for Wind Turbines
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David-flynn , Daniel-mitchell , Olga-fink , Head-of-research-division-for-autonomous-systems , Terms-of-service , Operations-systems-laboratory , James-watt-school-of-engineering , University-of-glasgow , School-of-architecture , Elsevier-mechanical-systems , Signal-processing , Intelligent-maintenance

Tracking and tracing water consumption for informed water sensitive intervention through machine learning approach

To develop a water conscious strategy, it is critical to track and trace water from its source to the end users, understand water conservation behaviors, and identify the factors that influence water consumption. However, in developing nations, little research has been done to provide a quantitative picture of how water is consumed and transformed in urban households, as well as the water sensitive interventions needed to improve access to clean water. Hence, the main objective of the study was to determine the most significant residential water consumption variables and to predict residential water consumption in a way that can generate water consumption information for water sensitive intervention decision making using the case study of Adama city in Ethiopia. A combination of top down and bottom up data collection techniques were employed as the data collection instrument. Machine learning was integrated with spatial and socioeconomic analytic techniques to estimate daily household water consumption and identify the factors that significantly influence household water consumption. The results show that there is only “one source option” for the city’s clean water supply and that different water harvesting methods are not likely to be developed. The average daily water consumption per person is 69 liters which falls below the national standard of 80 liters allocated per person per day. The result reveals that the water distribution network covers only 45% of the city master plan. About 38% of the water demand is unmet and 30% of households only receive water once every three days or fewer. This shows that the city is experiencing physical and economic water scarcity. The results demonstrated that family size, housing quality, income, number of rooms, legal status of the parcel, supply reliability, climate, and topographical features are the most important factors in predicting residential water consumption. This study further demonstrates how well supervised machine learning models, such as the Random Forest Regression algorithm, can predict the household’s daily water consumption. The findings also showed that there is a need for significant improvements in water saving habits of the households. Another conclusion that can be drawn is that as long as the city’s business as usual water consumption practice doesn’t change, the water supply problem will worsen over time.

Wallonia , Waals-gewest , Belgium , Malawi , New-york , United-states , Alharsha , Libya-general- , Libya , South-africa , Ethiopia , Qatar

AMD Rocks with New Versal Gen 2 AI Edge SoC FPGAs

AMD Rocks with New Versal Gen 2 AI Edge SoC FPGAs
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Intel-programmable-solutions-group , Intel , Xilinx , Altera , Advanced-boolean-expression-language , Common-universal , Programmable-logic , Automated-map , Manuel-uhm , Holistic-high-tech-marketing-executive , Stephane-gauthier

Signal Conditioning Market Size Worth $1.6 Billion By 2030: IndustryARC

Signal Conditioning Market Size Worth $1.6 Billion By 2030: IndustryARC
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Canada , Japan , Italy , Australia , Ukraine , Netherlands , France , China , Yokogawa , Gumma , Germany , United-kingdom

Computer Scientists: AI Models Can Be Less Power Hungry

Computer Scientists: AI Models Can Be Less Power Hungry
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Copenhagen , Køavn- , Denmark , Sweden , Danish , Raghavendra-selvan , Christian-igel , Pedram-bakhtiarifard , Google , University-of-copenhagen-department-computer-science , Department-of-computer-science , University-of-copenhagen-point

AI Models Can Be Less Energy-Intensive, Researchers Prove

AI Models Can Be Less Energy-Intensive, Researchers Prove
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Denmark , Sweden , Copenhagen , Køavn- , Danish , Raghavendra-selvan , Christian-igel , Pedram-bakhtiarifard , University-of-copenhagen-department-computer-science , International-conference-on-acoustics , University-of-copenhagen-point , Department-of-computer-science

'Recipe book' could make AI less power hungry

New research digs into how to create climate-friendly artificial intelligence systems that work well but require less energy.

Sweden , Copenhagen , Køavn- , Denmark , Danish , Pedram-bakhtiarifard , Raghavendra-selvan , Google , University-of-copenhagen-point , International-conference-on-acoustics , International-conference , Signal-processing