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Imaginative Techniques in Psychopathology: A Narrative Review.

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  1. Meaning of Imaginative Techniques in Psychopathology Imaginative techniques in psychopathology refer to therapeutic and diagnostic methods that utilize mental imagery, creative visualization, storytelling, and symbolic representation to understand and treat psychological disorders. These techniques engage a person’s imagination to access deep emotional, cognitive, and unconscious processes that may not be easily reached through conventional verbal communication. They are widely used in clinical psychology, psychotherapy, and psychiatry, particularly in approaches such as: Cognitive Behavioral Therapy (CBT) Psychodynamic therapy Trauma-focused therapies Art and expressive therapies 2. Introduction Psychopathology deals with the study of mental disorders, their causes, symptoms, and treatments. Traditional methods often rely on verbal dialogue, behavioral observation, and pharmacological interventions . However, many psychological experiences—especially traum...
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Post-quantum authentication for IoMT ensures secure, future-proof medical data against quantum threats.

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  Meaning Post- quantum authentication in the Internet of Medical Things (IoMT) refers to security methods designed to verify identities and protect communication between medical devices using cryptographic techniques that remain secure even against quantum computers. Traditional systems rely on encryption methods like RSA encryption and Elliptic Curve Cryptography , which could be broken by quantum algorithms such as Shor’s Algorithm . Post-quantum authentication uses quantum-resistant techniques like lattice-based, hash-based, or code-based cryptography to ensure long-term security.  Introduction The Internet of Medical Things (IoMT) is a rapidly growing network of interconnected medical devices such as wearable monitors, implantable sensors, and hospital systems. These devices continuously collect and transmit sensitive patient data. As healthcare becomes more digitized, ensuring data security is critical. However, the emergence of quantum computing poses a serious t...
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Speech Generation for Indigenous Language Education.

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  Speech Generation for Indigenous Language Education 1. Meaning Speech generation for indigenous language education refers to the use of advanced technologies—especially artificial intelligence (AI) and natural language processing (NLP)—to automatically produce spoken content in indigenous or minority languages. These systems convert written text into natural-sounding speech, enabling learners to hear accurate pronunciation, intonation, and conversational patterns in languages that may have limited educational resources. 2. Introduction Indigenous languages represent cultural identity, history, and traditional knowledge. However, many of these languages are endangered due to globalization, urbanization, and dominance of major languages. Speech generation technologies offer a transformative solution by revitalizing these languages through accessible, scalable, and interactive learning tools. With the advancement of AI-driven Text-to-Speech (TTS) systems, it is now possible to ...
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Age matters: Analyzing age-related discussions in app reviews

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  1. Meaning of Age-Related Discussions in App Reviews Age-related discussions in app reviews refer to comments made by users that reflect how different age groups (young users, adults, and elderly users) perceive, use, and evaluate mobile applications. These discussions may include feedback about usability, accessibility, design complexity, readability, privacy concerns, content appropriateness, and technological familiarity. In many cases, younger users may comment about features, speed, gaming elements, and social integration, whereas older users often discuss ease of navigation, font size, clarity of instructions, and reliability. Therefore, analyzing age-related discussions helps researchers and developers understand how age influences user experience, satisfaction, and adoption of mobile applications . Age is a crucial demographic factor in technology acceptance studies. It shapes cognitive abilities, digital literacy levels, preferences, and expectations. By studying ag...
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CSLLM: Code-Specific Large Language Models — A Survey

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  1. Meaning of Code-Specific Large Language Models (CSLLMs) Code-Specific Large Language Models (CSLLMs) are specialized artificial intelligence models designed to understand, generate, analyze, and optimize computer programming code . Unlike general-purpose Large Language Models (LLMs) that process natural language, CSLLMs are trained extensively on source code datasets , programming documentation, repositories, and developer discussions. These models learn patterns, syntax rules, and programming logic from millions of lines of code across multiple programming languages such as Python, Java, C++, JavaScript, and others . CSLLMs are capable of performing tasks such as: Automatic code generation Code completion Bug detection Code translation between programming languages Documentation generation Code optimization Software testing assistance Modern software development increasingly integrates CSLLMs into development environments to improve developer prod...
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