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Detecting Suicide Risk From Wristworn Activity Tracker Data Using Machine Learning Approaches, Pallavi Atluri
Detecting Suicide Risk From Wristworn Activity Tracker Data Using Machine Learning Approaches, Pallavi Atluri
Electrical Engineering Theses
Suicide is a prevalent cause of death worldwide and depression is a primary concern of many suicidal acts. It is possible that an individual during depression never has any suicidal thoughts at all. On the other hand, some individuals in stable condition with no apparent symptoms of depression feel urges to commit suicide (suicidal ideation). Many such individuals never let anyone know what they are feeling or planning. Suicidal ideation considered an important precursor to suicidal acts.
Detecting the suicide risk in individuals with mood disorders is a major challenge. The current clinical practice to assess suicide risk in these …
Piezoelectric Transformer And Hall-Effect Based Sensing And Disturbance Monitoring Methodology For High-Voltage Power Supply Lines, Sneha Arun Lele
Piezoelectric Transformer And Hall-Effect Based Sensing And Disturbance Monitoring Methodology For High-Voltage Power Supply Lines, Sneha Arun Lele
Electronic Thesis and Dissertation Repository
Advancements in relaying algorithms have led to an accurate and robust protection system widely used in power distribution. However, in low power sections of relaying systems, standard voltage and current measurement techniques are still used. These techniques have disadvantages like higher cost, size, electromagnetic interference, resistive losses and measurement errors and hence provide a number of opportunities for improvement and integration. We present a novel microsystem methodology to sense low-power voltage and current signals and detect disturbances in high-voltage power distribution lines. The system employs dual sensor architecture that consists of a piezoelectric transformer in combination with Hall-effect sensor, used …