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    University of Kansas Medical Center Reports Findings in Alzheimer Disease (Machi ne learning based on event-related oscillations of working memory differentiates between preclinical Alzheimer’s disease and normal aging)

    89-90页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Neurodegenerative Dise ases and Conditions - Alzheimer Disease is thesubject of a report. According to news reporting out of Kansas City, Kansas, by NewsRx editors, researchstated, “To apply machine learning approaches on EEG event-related oscillations (ERO) to discriminatepreclinical Alzheimer’s disease (AD) from age- and sex-matched con trols. Twenty-two cognitively normalpreclinical AD participants with elevated a myloid and 21 cognitively normal controls without elevatedamyloid completed n-b ack working memory tasks (n = 0, 1, 2).”

    University of Kansas Medical Center Reports Findings in Alzheimer Disease (Machi ne learning based on event-related oscillations of working memory differentiates between preclinical Alzheimer’s disease and normal aging)

    89-90页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Neurodegenerative Dise ases and Conditions - Alzheimer Disease is thesubject of a report. According to news reporting out of Kansas City, Kansas, by NewsRx editors, researchstated, “To apply machine learning approaches on EEG event-related oscillations (ERO) to discriminatepreclinical Alzheimer’s disease (AD) from age- and sex-matched con trols. Twenty-two cognitively normalpreclinical AD participants with elevated a myloid and 21 cognitively normal controls without elevatedamyloid completed n-b ack working memory tasks (n = 0, 1, 2).”

    Study Findings on Machine Learning Published by a Researcher at Huaqiao Universi ty (Research on the Classification and Recognition of Lacquer Painting Art Style s Based on Machine Learning Algorithms)

    90-91页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Research findings on artificial intelligence are discussed in a new report. According to news reportingoriginating from Quanzhou , People’s Republic of China, by NewsRx correspondents, research stated, “Alacq uer painting is a transparent coating that, if dry, creates a firm, long-lasting finish. The design isintended to be chip-resistant, waterproof, and breathable .”

    Study Findings on Machine Learning Published by a Researcher at Huaqiao Universi ty (Research on the Classification and Recognition of Lacquer Painting Art Style s Based on Machine Learning Algorithms)

    90-91页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Research findings on artificial intelligence are discussed in a new report. According to news reportingoriginating from Quanzhou , People’s Republic of China, by NewsRx correspondents, research stated, “Alacq uer painting is a transparent coating that, if dry, creates a firm, long-lasting finish. The design isintended to be chip-resistant, waterproof, and breathable .”

    Researcher from Nanjing University Discusses Findings in Artificial Intelligence (How Can Generative Artificial Intelligence Techniques Facilitate Intelligent R esearch into Ancient Books?)

    91-92页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Research findings on artificial intell igence are discussed in a new report. Accordingto news originating from Nanjing , People’s Republic of China, by NewsRx editors, the research stated,“Generativ e AI changes the paradigm of natural language processing research, sets off a ne w trend ofresearch in computational humanities and computational social science s, and provides unique perspectiveson digital intelligence-enabled ancient book revitalization and intelligent applications.”

    Researcher from Nanjing University Discusses Findings in Artificial Intelligence (How Can Generative Artificial Intelligence Techniques Facilitate Intelligent R esearch into Ancient Books?)

    91-92页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Research findings on artificial intell igence are discussed in a new report. Accordingto news originating from Nanjing , People’s Republic of China, by NewsRx editors, the research stated,“Generativ e AI changes the paradigm of natural language processing research, sets off a ne w trend ofresearch in computational humanities and computational social science s, and provides unique perspectiveson digital intelligence-enabled ancient book revitalization and intelligent applications.”

    Research on Artificial Intelligence Published by Researchers at Department of El ectrical Engineering (An Explicit Investigation in Demand Side Management Based on Artificial Intelligence Techniques)

    92-93页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Researchers detail new data in artific ial intelligence. According to news reportingoriginating from Jharkhand, India, by NewsRx correspondents, research stated, “The several artificiallyintelligen t techniques used in demand-side management (DSM) are exhaustively reviewed in t his article.”The news editors obtained a quote from the research from Department of Electrica l Engineering: “Theobjective of the demand-side management is to connect and di sconnect the available generating unitswith the variable loads with the objecti ve of meeting peak load and base load demand. The meeting ofload demand with th e adjustment in available generating units is accompanied by demand-side management. It is observed that ANN is utilized for short-term load and pricing forecas ting, and other natureencouragedoptimization techniques like swarm intelligenc e, game theory, deep learning methods, etc.may be used as speculation methods b ecause these optimization techniques are less precise. Demand-sidemanagement in volves highly complicated losses in all existing methodologies that have been co ntrolledand reduced by artificial intelligence and machine learning. Smart pric ing for customers results fromincreasing the economic efficiency of consumption by promoting energy load demand during off-peak hoursand discouraging energy l oad demand during peak hours. Less fuel consumption also helps to reducecarbon emissions from these power generation projects, which helps power suppliers save on additional fuelcosts due to severe and unpredictable margin variations in p ower generation.”

    Research on Artificial Intelligence Published by Researchers at Department of El ectrical Engineering (An Explicit Investigation in Demand Side Management Based on Artificial Intelligence Techniques)

    92-93页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Researchers detail new data in artific ial intelligence. According to news reportingoriginating from Jharkhand, India, by NewsRx correspondents, research stated, “The several artificiallyintelligen t techniques used in demand-side management (DSM) are exhaustively reviewed in t his article.”The news editors obtained a quote from the research from Department of Electrica l Engineering: “Theobjective of the demand-side management is to connect and di sconnect the available generating unitswith the variable loads with the objecti ve of meeting peak load and base load demand. The meeting ofload demand with th e adjustment in available generating units is accompanied by demand-side management. It is observed that ANN is utilized for short-term load and pricing forecas ting, and other natureencouragedoptimization techniques like swarm intelligenc e, game theory, deep learning methods, etc.may be used as speculation methods b ecause these optimization techniques are less precise. Demand-sidemanagement in volves highly complicated losses in all existing methodologies that have been co ntrolledand reduced by artificial intelligence and machine learning. Smart pric ing for customers results fromincreasing the economic efficiency of consumption by promoting energy load demand during off-peak hoursand discouraging energy l oad demand during peak hours. Less fuel consumption also helps to reducecarbon emissions from these power generation projects, which helps power suppliers save on additional fuelcosts due to severe and unpredictable margin variations in p ower generation.”

    Findings from Binghamton University Broaden Understanding of Machine Learning (P redicting Unpaid Care Work In India Using Random Forest: an Analysis of Socioeco nomic and Demographic Factors)

    93-94页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Ma chine Learning. According to news reportingout of Binghamton, New York, by News Rx editors, the research stated, “Given the complexity of unpaidcare work in th e Indian context, this study employs advanced machine learning techniques to unv eilhidden patterns within the 2019 time-use survey dataset. The study pursues a dual objective: (1) assessingthe superior predictive capability of machine lea rning over traditional statistical methods in estimatingunpaid care work time, and (2) unveiling the sociodemographic determinants of extended unpaid care workdurations.”

    Findings from Binghamton University Broaden Understanding of Machine Learning (P redicting Unpaid Care Work In India Using Random Forest: an Analysis of Socioeco nomic and Demographic Factors)

    93-94页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Ma chine Learning. According to news reportingout of Binghamton, New York, by News Rx editors, the research stated, “Given the complexity of unpaidcare work in th e Indian context, this study employs advanced machine learning techniques to unv eilhidden patterns within the 2019 time-use survey dataset. The study pursues a dual objective: (1) assessingthe superior predictive capability of machine lea rning over traditional statistical methods in estimatingunpaid care work time, and (2) unveiling the sociodemographic determinants of extended unpaid care workdurations.”