Jha Abhijit Kumar (30 results)

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Paperback. Condition: new. Paperback. In today's life, stress has become a big issue because of excessive working load, study pressure, and unhealthy lifestyle habits. It also impacts the physical health. Typical stress monitoring systems are largely reactive, meaning that they only detect stress once it has occurred, and thus cannot provide timely intervention. In this study, a proactive stress management model based on the wearable physiological signals and intelligent decision-making is proposed, with the aim of predicting or controlling the physiological changes caused by stress by using physiological signals as the input to the system. The proposed system combines three models: Bidirectional Long Short-Term Memory (Bi-LSTM) forecasting, Deep Reinforcement Learning (DRL), and SHAP explainability, to create a predictive and adaptive health support system. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. In today's life, stress has become a big issue because of excessive working load, study pressure, and unhealthy lifestyle habits. It also impacts the physical health. Typical stress monitoring systems are largely reactive, meaning that they only detect stress once it has occurred, and thus cannot provide timely intervention. In this study, a proactive stress management model based on the wearable physiological signals and intelligent decision-making is proposed, with the aim of predicting or controlling the physiological changes caused by stress by using physiological signals as the input to the system. The proposed system combines three models: Bidirectional Long Short-Term Memory (Bi-LSTM) forecasting, Deep Reinforcement Learning (DRL), and SHAP explainability, to create a predictive and adaptive health support system. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condition: Neu. Proactive Stress Management Using LSTM Forecasting, Deep Reinforcement | Abhijit Kumar Jha (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630078862 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. …

Paperback. Condition: new. Paperback. Nella vita di oggi, lo stress e diventato un problema rilevante a causa dell'eccessivo carico di lavoro, della pressione degli studi e di abitudini di vita poco salutari. Esso influisce anche sulla salute fisica. I sistemi tipici di monitoraggio dello stress sono in gran parte reattivi, nel senso che rilevano lo stress solo una volta che si e manifestato e, di conseguenza, non sono in grado di fornire un intervento tempestivo. In questo studio viene proposto un modello proattivo di gestione dello stress basato sui segnali fisiologici rilevati da dispositivi indossabili e su un processo decisionale intelligente, con l'obiettivo di prevedere o controllare i cambiamenti fisiologici causati dallo stress utilizzando tali segnali come input del sistema. Il sistema proposto combina tre modelli: la previsione con Long Short-Term Memory bidirezionale (Bi-LSTM), l'apprendimento profondo per rinforzo (DRL) e la spiegabilita SHAP, per creare un sistema di supporto alla salute predittivo e adattivo. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. Na vida atual, o stress tornou-se um grande problema devido a carga de trabalho excessiva, a pressao dos estudos e a habitos de vida pouco saudaveis. Alem disso, tem impacto na saude fisica. Os sistemas tipicos de monitorizacao do stress sao, em grande parte, reativos, o que significa que apenas detetam o stress depois de este ter ocorrido, nao podendo, por isso, proporcionar uma intervencao atempada. Neste estudo, propoe-se um modelo proativo de gestao do stress baseado em sinais fisiologicos recolhidos por dispositivos vestiveis e na tomada de decisoes inteligente, com o objetivo de prever ou controlar as alteracoes fisiologicas causadas pelo stress, utilizando esses sinais como entrada para o sistema. O sistema proposto combina tres modelos: previsao com Memoria de Curto e Longo Prazo Bidirecional (Bi-LSTM), Aprendizagem Profunda por Reforco (DRL) e explicabilidade SHAP, para criar um sistema de apoio a saude preditivo e adaptativo. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Paperback. Condition: new. Paperback. W dzisiejszym zyciu stres stal sie powaznym problemem z powodu nadmiernego obciazenia praca, presji zwiazanej z nauka oraz niezdrowych nawykow zyciowych. Wplywa on rowniez na zdrowie fizyczne. Typowe systemy monitorowania stresu maja w duzej mierze charakter reaktywny, co oznacza, ze wykrywaja stres dopiero po jego wystapieniu, a zatem nie sa w stanie zapewnic interwencji w odpowiednim czasie. W niniejszym badaniu zaproponowano proaktywny model zarzadzania stresem oparty na sygnalach fizjologicznych rejestrowanych przez urzadzenia noszone na ciele oraz inteligentnym podejmowaniu decyzji, ktorego celem jest przewidywanie lub kontrolowanie zmian fizjologicznych wywolanych stresem poprzez wykorzystanie sygnalow fizjologicznych jako danych wejsciowych do systemu. Proponowany system laczy trzy modele: prognozowanie z wykorzystaniem dwukierunkowej sieci Long Short-Term Memory (Bi-LSTM), glebokie uczenie sie przez wzmocnienie (DRL) oraz wyjasnialnosc SHAP, tworzac predykcyjny i adaptacyjny system wsparcia zdrowia. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. Im heutigen Alltag ist Stress aufgrund uebermaessiger Arbeitsbelastung, Leistungsdruck im Studium und ungesunder Lebensgewohnheiten zu einem grossen Problem geworden. Er wirkt sich zudem auf die koerperliche Gesundheit aus. Typische Stressueberwachungssysteme sind groesstenteils reaktiv, das heisst, sie erkennen Stress erst, wenn er bereits aufgetreten ist, und koennen daher keine rechtzeitigen Massnahmen ergreifen. In dieser Studie wird ein proaktives Stressmanagementmodell vorgeschlagen, das auf tragbaren physiologischen Signalen und intelligenter Entscheidungsfindung basiert. Ziel ist es, die durch Stress verursachten physiologischen Veraenderungen vorherzusagen oder zu steuern, indem physiologische Signale als Eingabe fuer das System verwendet werden. Das vorgeschlagene System kombiniert drei Modelle: die Prognose mittels bidirektionalem Long Short-Term Memory (Bi-LSTM), Deep Reinforcement Learning (DRL) und SHAP-Erklaerbarkeit, um ein praediktives und adaptives Gesundheitsunterstuetzungssystem zu schaffen. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. Nella vita di oggi, lo stress e diventato un problema rilevante a causa dell'eccessivo carico di lavoro, della pressione degli studi e di abitudini di vita poco salutari. Esso influisce anche sulla salute fisica. I sistemi tipici di monitoraggio dello stress sono in gran parte reattivi, nel senso che rilevano lo stress solo una volta che si e manifestato e, di conseguenza, non sono in grado di fornire un intervento tempestivo. In questo studio viene proposto un modello proattivo di gestione dello stress basato sui segnali fisiologici rilevati da dispositivi indossabili e su un processo decisionale intelligente, con l'obiettivo di prevedere o controllare i cambiamenti fisiologici causati dallo stress utilizzando tali segnali come input del sistema. Il sistema proposto combina tre modelli: la previsione con Long Short-Term Memory bidirezionale (Bi-LSTM), l'apprendimento profondo per rinforzo (DRL) e la spiegabilita SHAP, per creare un sistema di supporto alla salute predittivo e adattivo. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condition: new. Paperback. Na vida atual, o stress tornou-se um grande problema devido a carga de trabalho excessiva, a pressao dos estudos e a habitos de vida pouco saudaveis. Alem disso, tem impacto na saude fisica. Os sistemas tipicos de monitorizacao do stress sao, em grande parte, reativos, o que significa que apenas detetam o stress depois de este ter ocorrido, nao podendo, por isso, proporcionar uma intervencao atempada. Neste estudo, propoe-se um modelo proativo de gestao do stress baseado em sinais fisiologicos recolhidos por dispositivos vestiveis e na tomada de decisoes inteligente, com o objetivo de prever ou controlar as alteracoes fisiologicas causadas pelo stress, utilizando esses sinais como entrada para o sistema. O sistema proposto combina tres modelos: previsao com Memoria de Curto e Longo Prazo Bidirecional (Bi-LSTM), Aprendizagem Profunda por Reforco (DRL) e explicabilidade SHAP, para criar um sistema de apoio a saude preditivo e adaptativo. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Taschenbuch. Condition: Neu. Gestão proativa do stress através de previsões com LSTM e reforço profundo | Abhijit Kumar Jha (u. a.) | Taschenbuch | Portugiesisch | 2026 | Edições Nosso Conhecimento | EAN 9786630119879 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. …

Taschenbuch. Condition: Neu. Gestione proattiva dello stress tramite previsioni LSTM e apprendimento profondo con rinforzo | Abhijit Kumar Jha (u. a.) | Taschenbuch | Italienisch | 2026 | Edizioni Sapienza | EAN 9786630114751 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.…

Paperback. Condition: new. Paperback. W dzisiejszym zyciu stres stal sie powaznym problemem z powodu nadmiernego obciazenia praca, presji zwiazanej z nauka oraz niezdrowych nawykow zyciowych. Wplywa on rowniez na zdrowie fizyczne. Typowe systemy monitorowania stresu maja w duzej mierze charakter reaktywny, co oznacza, ze wykrywaja stres dopiero po jego wystapieniu, a zatem nie sa w stanie zapewnic interwencji w odpowiednim czasie. W niniejszym badaniu zaproponowano proaktywny model zarzadzania stresem oparty na sygnalach fizjologicznych rejestrowanych przez urzadzenia noszone na ciele oraz inteligentnym podejmowaniu decyzji, ktorego celem jest przewidywanie lub kontrolowanie zmian fizjologicznych wywolanych stresem poprzez wykorzystanie sygnalow fizjologicznych jako danych wejsciowych do systemu. Proponowany system laczy trzy modele: prognozowanie z wykorzystaniem dwukierunkowej sieci Long Short-Term Memory (Bi-LSTM), glebokie uczenie sie przez wzmocnienie (DRL) oraz wyjasnialnosc SHAP, tworzac predykcyjny i adaptacyjny system wsparcia zdrowia. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condition: new. Paperback. Im heutigen Alltag ist Stress aufgrund uebermaessiger Arbeitsbelastung, Leistungsdruck im Studium und ungesunder Lebensgewohnheiten zu einem grossen Problem geworden. Er wirkt sich zudem auf die koerperliche Gesundheit aus. Typische Stressueberwachungssysteme sind groesstenteils reaktiv, das heisst, sie erkennen Stress erst, wenn er bereits aufgetreten ist, und koennen daher keine rechtzeitigen Massnahmen ergreifen. In dieser Studie wird ein proaktives Stressmanagementmodell vorgeschlagen, das auf tragbaren physiologischen Signalen und intelligenter Entscheidungsfindung basiert. Ziel ist es, die durch Stress verursachten physiologischen Veraenderungen vorherzusagen oder zu steuern, indem physiologische Signale als Eingabe fuer das System verwendet werden. Das vorgeschlagene System kombiniert drei Modelle: die Prognose mittels bidirektionalem Long Short-Term Memory (Bi-LSTM), Deep Reinforcement Learning (DRL) und SHAP-Erklaerbarkeit, um ein praediktives und adaptives Gesundheitsunterstuetzungssystem zu schaffen. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condition: Neu. Proaktywne zarz¿dzanie stresem z wykorzystaniem prognozowania opartego na sieci LSTM oraz g¿¿bokiego uczenia wzmacniaj¿cego | Abhijit Kumar Jha (u. a.) | Taschenbuch | Polnisch | 2026 | Wydawnictwo Nasza Wiedza | EAN 9786630117318 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. …

Taschenbuch. Condition: Neu. Proaktives Stressmanagement mithilfe von LSTM-Prognosen und Deep Reinforcement | Abhijit Kumar Jha (u. a.) | Taschenbuch | 132 S. | Deutsch | 2026 | Verlag Unser Wissen | EAN 9786630107074 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. …