The Cohort Effect Approach to a Friction in Students-Life Beyond Religious and Mental Health for Anxiety Disorder at IAIN Langsa

The article scrutinized a friction stem in students, a false or a real of hope, struggle, and retentive in life when anxiety attacking the consciousness and bridging religious tradition and mental health status. Beyond reality to fantasy, within the inner perceptive, students construct artificial facts in the brain to stimulate action as a course of reactions. The artificial are related to a hope, an expectation, inviting a positive outcome to be believed as an alternative fact to subdue anxiety of fears, which come to overshadow students’ mental status. For inner students’ mental status, there is friction which pressing one to another for their artificial feeling either became the greatest power or worst nightmare affected to daily life and exposure both internally and externally reactions. A cohort effect approaches were applied to observe a longitudinal study for students’ behaviors in contemplating anxiety disorder affect that relied on religious and mental health for an individual sample. Student’s behaviors respect a particular characteristic as the aging process. The approaches aimed at physical features; body shape, decision making, level of aggressiveness, fears, and matting patterns. Thus, students’ frictions are traceable to foresee students’ mental health disorders as an umbrella from a diverse field in clinical psychology

Cognition as Embodied Morphological Computation

Cognitive science is considered to be the study of mind (consciousness and thought) and intelligence in humans. Under such definition variety of unsolved/unsolvable problems appear. This article argues for a broad understanding of cognition based on empirical results from i.a. natural sciences, self-organization, artificial intelligence and artificial life, network science and neuroscience, that apart from the high level mental activities in humans, includes sub-symbolic and sub-conscious processes, such as emotions, recognizes cognition in other living beings as well as extended and distributed/social cognition. The new idea of cognition as complex multiscale phenomenon evolved in living organisms based on bodily structures that process information, linking cognitivists and EEEE (embodied, embedded, enactive, extended) cognition approaches with the idea of morphological computation (info-computational self-organisation) in cognizing agents, emerging in evolution through interactions of a (living/cognizing) agent with the environment

Developmental changes in perceived moral standing of robots

We live in an age where robots are increasingly present in the social and moral world. Here, we explore how children and adults think about the mental lives and moral standing of robots. In Experiment 1 (N = 116), we found that children granted humans and robots with more mental life and vulnerability to harm than an anthropomorphized control (i.e., a toy bear). In Experiment 2 (N = 157), we found that, relative to children, adults ascribed less mental life and vulnerability to harm to robots. In Experiment 3 (N = 152), we modified our experiment to be within-subjects and measured beliefs concerning moral standing. Though younger children again appeared willing to assign mental capacities — particularly those related to experience (e.g., being capable of experiencing hunger) — to robots, older children and adults did so to a lesser degree. This diminished attribution of mental life tracked with diminished ratings of robot moral standing. This informs ongoing debates concerning emerging attitudes about artificial life

Analysis of the Development of Artificial Intelligence in the Field of Biomedical Applications

With the concept of artificial intelligence, its long evolution and development, and gradually and super computing technology, big data analysis technology, network technology, sensing technology, brain science and other new technologies, new theories combined application, which effectively promote the development of social development of economic and industrial development. Currently, artificial intelligence has been widely used in a number of industries, especially in the current biomedical field, in a series of exploration, research, practice has been achieved under the cross-border integration, human-machine collaboration, autonomous manipulation, deep learning and other modes, biomedical industry and people's physical and mental health have a direct relationship. In the current situation of improving living standards, people are more and more concerned about their physical and mental health, living environment, life expectancy, etc., which requires the application of artificial intelligence science in the field of biomedicine and the analysis of the specific application development

An Exposition of Moral Issues in the Use of Sensor Technology on Psychiatric Patients

The advance of scientific approaches to life has recorded a plethora of successes as well as failures. Man being at the center of its experiment is tossed toe and fro by the result of its inquiry. Predictions are that in the nearest time, humanity might be living absolutely under the directives of Technology based on Artificial intelligence. At present, Technology based on Artificial Intelligence is quickly finding its way into various areas of life including health and social services. This spread and or interplay connotes the relinquishing of health responsibilities from man to sensor technology as well as dependency on the data and result of this technology. This effort questions this unethical dependency as well as raises moral issues associated with the use of Technology base on artificial intelligence on psychiatric patient. It dabbles into medical values such as; autonomy of the patient cum consent, Kantian universal principle and its implication to implementing the universal usage of technology in mental health care services, and so on. The work of Patricia A. Arean (2016) titled Mobile Technology for Mental Health Assessment gave an in-depth analysis of the available approaches, doting advantages of sensor technology on psychiatric patient. The paper applied the analytic, descriptive and prescriptive method of philosophy to achieve its objective. To this end, it is in the view of this work imperative for the mental-medical community to consider reflectively these issues and the philosophic recommendations provided herein

Baymax- Your Mental Health Care Companion - An Artificial Intelligence based Chat bot for Mental Health Care

Artificial intelligence (AI) technologies and techniques have useful purposes in every domain of mental health care including clinical decision-making, treatments, assessment, self-care, mental health care management and more. Recent technological innovations are highlighted to demonstrate capabilities and opportunities. This application involves an AI based Expert System which can significantly contribute to improving mental health of an individual to lead a better life without any stress or melancholy. The expert system provides expert advice and therapy to overcome negative thoughts. This app can also help to reduce the number of suicides caused due to extreme depression. It is about virtual human conversation with the system to support user’s interaction within a mental health care context. It provides private online healthcare guidance and support where the app can serve the role of a clinician or a psychotherapist.It uses Smartphone technology particularly relevant for applications in Mental health. Recent advances in artificial intelligence are providing an unprecedented ability of online mental health care research and clinical organizations to collect and analyse data that is broader in scope. This application provides a system capable of calculating the depression level using Fuzzy Logic Controller. It sends an alert message to user’s acquaintance thereby preventing the user from causing harm to himself. It tries to imbibe happy thoughts and optimism into the user. Thus, this system can have a meaningful impact on people’s lives by improving their mental health

AI-Enabled Smartphone-Based Intervention Mental Health Application for University Students

The novel COVID-19 outbreak has resulted in lockdowns and university campus closure which affected the mental health of university students negatively. This was reflected in mental disorders, with emotional, physical fitness, exercise, and studying are the most affected aspects during the pandemic. The design and development of a smartphone application is the objective of this paper. The app\u27s goal is to assist university students in improving their mental health and overall quality of life by answering a structured questionnaire at first then the app uses artificial intelligence for sentiment analysis of a user’s social interaction. Then the app connects the user with random peers who share similar mental sentiments to chat with and if there is no peer available, a chatbot is used. In case of significant loneliness, the app connects the user with caregivers, community volunteers, and health professionals

Does Artificial Intelligence Use Private Language?

Wittgenstein’s Private Language Argument holds that language requires rule-following, rule following requires the possibility of error, error is precluded in pure introspection, and inner mental life is known only by pure introspection, thus language cannot exist entirely within inner mental life. Fodor defends his Language of Thought program against the Private Language Argument with a dilemma: either privacy is so narrow that internal mental life can be known outside of introspection, or so broad that computer language serves as a counter-example. I suggest that the developing field of artificial intelligence (deep learning neural networks) tends to vitiate Fodor’s defense and hence vindicate the Private Language Argument. The first horn of Fodor’s dilemma requires language to encompass genuinely internal mental life, i.e. non-projected intentional states, which are not exhibited in classical machine learning but only by deep learning neural networks (artificial intelligence). Such networks act as black boxes, however, whose state cannot be understood by tracking the changes in their supervenience bases without shared context, and that shared context introduces the possibility of error. The language of artificial intelligence is not private

The persistent vegetative state: legal and ethical issues

Recent advances in technology and medical expertise have enabled doctors to prolong the lives of many severely injured patients who only a few years ago would have died from their injuries. The prolongation of life by such measures has raised many legal, ethical and social issues. When in 1992 the House of Lords determined in Airdale NHS Trust V Bland that life-supporting measures, including artificial nutrition and hydration (ANH) might lawfully be withdrawn from Anthony Bland, a patient in a persistent vegetative state (PVS), attention was focused on these issues particularly as they apply to the patient in PVS. Since the PVS patient is neither competent to refuse treatment, nor is he dying or suffering, the reasons normally advanced for withdrawing life-supporting measures do not apply. In Bland, their Lordships relied on the best interests test laid down in Re F (mental patient: sterilisation) [1989] 2 All ER 545, and, with the exception of Lord Mustill, on the Bolam test (Bolam v Friern Barnet Hospital Management Committee) [1957] 1 WLR 582. This thesis examines the decision mBland and addresses some of the issues raised. The appropriateness of the best interests test as applied to the patient in PVS is explored and compared with the approach of substituted judgement employed in some other common law jurisdictions. The relevance of the Bolam test to decisions regarding the withdrawal of life-supporting measures is considered. The legal requirements for the withdrawal of ANH are discussed, together with the ethical debate and the moral dilemmas posed by its withdrawal. Finally, the question as to whether the decision in Bland is good law is addressed, and it will be argued that whilst it may be morally acceptable to withdraw ANH from some patients, as regards a patient in PVS, the moral imperative is that we should not

EEG-based Deep Emotional Diagnosis: A Comparative Study

Emotion is an important part of people's daily life, particularly relevant to the mental health of people. Emotional diagnosis is closely related to the nervous system, which can well reflect people's mental conditions in response to the surrounding environment or the development of various neurodegenerative diseases. Emotion recognition can help the medical diagnosis of mental health. In recent years, emotion recognition based on EEG has attracted the attention of many researchers accompanying with the continuous development of artificial intelligence and brain computer interface technology. In this paper, we carried out a comparison on the performance of three deep learning techniques on EEG classification, including DNN, CNN and CNN-LSTM. DEAP data set was used in our experiments. EEG signals were transformed from time domain to frequency domain first, and then features are extracted to classify emotions. From our research, it shows these deep learning techniques can achieve good accuracy on emotional diagnosis