Volume 13 | Issue 1 |

 Abstract

Schizophrenia is a mental condition that is affecting approx. 1.0 percent of the worldwide population, with devastating consequences for affected individuals and their families. Homoeopathy could be an effective alternative mode of treatment and can minimize the consequences of it.This study is done to have a brief review of the condition of Schizophrenia and to evaluate the role of Homoeopathy as an alternative mode of treatment in patients suffering from this condition.The research is performed as an retrospective study by searching Pubmed, IJRH, ISOR-JDMS, WHO, and Medscape databases. Reference books related to medicine and homoeopathy were also reviewed. The search used the keywords like Schizophrenia, Homoeopathy, psychiatry, hallucinations, paranoia, ICD-10, DSM-5, etc.This study is conducted at Peripheral Health Centres, Karode centre for Mentally ill women, EMMAUS Rehabilitation centres at Ummancode, Mekkamandapam and also at the OPD for Psychiatry in Sarada Krishna Homoeopathic Medical College, Kulasekharam.Schizophrenia alters the thinking, feeling and behavior of affected person and is presented in form of delusion, hallucination with social withdrawal. Homoeopathy can be an alternative mode of treatment to not only help in improving this condition but also treat the same. There are not much studies that has been conducted to evaluate the role of Homoeopathy in schizophrenia. Out of few, one study has suggested improvement in the symptoms of paranoid schizophrenia using Brief Psychiatric Rating Scale (BPRS) score system.Schizophrenia is a psychiatric condition not only affecting routine of daily of life but also the Quality of life. Homoeopathy is a non-toxic, gentle, permanent treatment which is based on totality of symptoms (TOS) and individualization. In the process of construction of TOS and individualization, more importance is given to mental symptoms. As again pschizophrenia is a psychiatric condition which affects the mental process of patient, Homoeopathy can be used as an effective method of treatment but to establish the efficacy of it, more studies including randomized controlled trials are suggestede analytical framework contains.The purpose of this study was to determine the relationship of stress levels with the menstrual cycle in adolescents. These deserve careful evaluation as uncorrected menstrual problems may adversely affect the daily routine and quality of life. A cross-sectional study was conducted among 100 students in different colleges in India, by administering a questionnaire consisting of premenstrual symptoms and psychosocial stress Assessment scale. Psychosocial stress was assessed using Perceived Stress Scale (PSS10). This study found a strong link between stress levels and menstrual cycle abnormalities in adult female students who experienced premenstrual symptoms such anxiety, mood swings, irritability, headaches, and dysmenorrhea. This suggests that measures to lessen stress can enhance the menstrual health of adult females, lowering future health risks and enhancing quality of life.

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 Keywords

Schizophrenia, Homoeopathy, BPRS scale, individualization

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 Abstract

This study examines the potential cost savings associated with the use of artificial intelligence (AI) in insurance claims processing. AI can automate processes and tasks that would otherwise require manual intervention, thereby enabling insurers to reduce operational costs. By applying AI algorithms to insurance and customer data, insurers can identify appropriate products, detect potentially fraudulent claims, reduce operational costs, and improve decision-making accuracy. Additionally, AI can automate customer/policyholder interactions, enabling faster and more accurate responses. Furthermore, AI can power predictive analytics, using data to forecast changes in customer demand and identify key trends in the marketplace. This can allow insurers to better manage their internal costs and optimize pricing structures to remain competitive. Finally, AI-powered systems can enable improved compliance with applicable regulations, thereby increasing efficiency whilst reducing the costs associated with non-compliance.

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 Keywords

Artificial Intelligence, Insurance Claims Processing, Machine Learning, Cost Reduction, Fraud Detection, Predictive Analytics.

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 Abstract

Intelligent service robots are being increasingly deployed in commercial and institutional settings to improve customer satisfaction and reduce operational costs. In this paper we present the design and development of a low-cost AI based HelpDesk Robot that provides independent client support through multimodal interaction. For customer identification, the system is equipped with a PIR motion sensor, an OLED display for visual feedback, and an ESP32 microcontroller for system control. It also includes an AI Thinker VC-02 voice module for offline speech recognition and speech synthesis and an ESP32-CAM module for real time face recognition. The PIR sensor activates the system when a client approaches, the ESP32-CAM identifies the visitor using facial recognition and the speech module allows natural language interaction to answer commonly asked queries by using a locally stored knowledge base. The robot ensures that communication is accessible and user-friendly by providing synchronised text and voice responses. The proposed architecture reduces the manual intervention thereby providing continuous availability of the services and improving user interaction, thus ensuring low deployment and maintenance costs. The experimental implementation demonstrates reliable client detection, accurate face recognition, responsive voice interaction, and effective real-time system performance. The proposed system, thanks to its modular and scalable design, can be deployed in hospitals, schools, retail centers, corporate offices, banks, and other public service settings where intelligent automated help is required.

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 Keywords

AI-Based Help Desk Robot, ESP32-CAM, Face Recognition, Voice Recognition, Human-Robot Interaction, Embedded Systems, Customer Service Automation, ESP32, OLED Display, PIR Sensor.

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Unmanned Aerial Vehicles (UAV) have become an important technology in modern surveillance, environmental monitoring, disaster management, agriculture and security applications. Recent advances in embedded systems, wireless communication and autonomous flight control have enabled drones to perform complex tasks with increased accuracy and reliability. The M3 Max Autonomous Drone is an intelligent UAV for stable flight, real-time monitoring and autonomous navigation. In this paper, we present the architecture, surveillance integration and performance analysis of the M3 Max drone. The proposed system consists of Flight Controller, Brushless DC (BLDC) motors, Electronic Speed Controllers (ESCs), Optical Flow Positioning System, 360o Obstacle Avoidance System (OAS), Inertial Measurement Unit (IMU) and high definition First Person View (FPV) camera for effective aerial surveillance and collision free operation. The study is focused on the interaction of hardware components, embedded control algorithms and wireless communication modules that achieve accurate positioning, stable hovering, obstacle detection and real-time video transmission. Performance evaluation shows that the combination of optical flow positioning and intelligent obstacle avoidance can significantly improve the flight stability, navigation accuracy and operational safety in indoor and outdoor environments. The proposed architecture offers a reliable and efficient framework for autonomous surveillance and builds a foundation for future enhancements using Artificial Intelligence, Computer Vision and IoT based drone technologies for next generation smart aerial applications.

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 Keywords

Autonomous Drone, M3 Max, UAV, Flight Controller, Optical Flow Positioning, Obstacle Avoidance, FPV Camera, Real-Time Surveillance.

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 Abstract

THE LAW RELATING TO ARTIFICIAL INTELLIGENCE (A I) :- A BIRD VIEW

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THE LAW RELATING TO ARTIFICIAL INTELLIGENCE (A I) :- A BIRD VIEW

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Digital image watermarking is still an important method for copyright protection, ownership proof, and image authentication. Among many approaches, frequency-domain watermarking has remained popular because it usually gives better balance between image quality and robustness than simple spatial-domain methods [1][2]. This paper presents a systematic review of classical frequency-domain watermarking with focus on DCT, DWT, DFT, and SVD-based hybrid methods. It also studies how these traditional methods perform when images are changed by modern manipulation tools such as AI-based enhancement, inpainting, semantic editing, and watermark removal systems [3][4]. The review combines literature analysis with an experimental synthesis based on published benchmark results. The main observation is that classical methods still perform well against common attacks like compression, filtering, resizing, and noise, but their strength becomes limited when image content is strongly regenerated or semantically modified by modern tools [1][3].

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 Keywords

digital image watermarking, frequency-domain watermarking, DCT, DWT, DFT, SVD, robustness, image manipulation, review

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Corporate Social Responsibility (CSR) has emerged as a strategic framework through which organizations integrate social, environmental, and ethical considerations into their business operations. While traditional views considered CSR as a cost-oriented activity, contemporary perspectives highlight its potential to enhance organizational performance. This conceptual study examines the relationship between CSR and business performance by critically synthesizing existing theoretical and empirical literature. The analysis explores key dimensions such as financial performance, corporate reputation, customer behavior, employee engagement, and long-term sustainability. The study identifies that CSR contributes to value creation primarily through improved stakeholder relationships and enhanced corporate legitimacy. However, the extent of its impact varies across industries and depends on the strategic alignment of CSR initiatives with organizational objectives. The paper also discusses key challenges, including measurement issues, resource constraints, and conflicts between profit maximization and social responsibility. The findings suggest that CSR, when implemented as a core strategic function rather than a peripheral activity, can significantly enhance both economic and social outcomes. The study concludes by emphasizing the need for a more integrated and performance-oriented approach to CSR in modern business environments.

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Corporate Social Responsibility; Business Performance; Financial Performance; Corporate Reputation; Stakeholder Theory; Sustainability; Organizational Performance

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Indigenous knowledge is rooted in deep connections of indigenous people to the land, environment, and culture. Indigenous Knowledge Transmission refers to the process through which the knowledge of indigenous people of a community is passed from generation to generation. The Tiwa tribe, an indigenous group mainly residing in Nagaon, Morigaon, Karbi-Anglong and Kamrup districts of Assam and in the Khasi-Jayantiya hills of Meghalaya. Generally, it is seen that, in a society of Assam, the managers or bearers of indigenous knowledge systems which is related to the development, care and well-being of women and children are senior women, or grandmothers. Tiwa women plays a central role in almost all social aspects of Tiwa community by holdings several portfolios and performing assigned duties and responsibilities. Women are important part of various domestic, agricultural, community-based rituals related to fertility, health, seasonal cycles and worship to the ancestors in Tiwa community. This paper aims to analyze the significant role of Tiwa women in indigenous knowledge transmission to future generation through rituals, festivals etc. This research follows a qualitative methodological framework and relies exclusively on secondary sources.

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 Keywords

Indigenous Knowledge, Knowledge Transmission, Tiwa community, Tiwa women

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Creative Commons Attribution 4.0 and The Open Definition

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Generating physically plausible, environment-responsive character animations in real time sits at one of the harder intersections of deep learning and computer graphics. Current methods force a trade-off: fast solutions cut physical accuracy, while physically accurate pipelines depend on offline computation that cannot adapt when runtime conditions change unexpectedly. This paper presents NeuroMotionNet, a unified framework that combines a multi-head Transformer motion encoder with a Proximal Policy Optimization (PPO) reinforcement learning agent to produce adaptive, temporally coherent character animations at interactive rates.

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 Keywords

Character animation; Transformer; Reinforcement learning; Real-time rendering; Skeletal retargeting; Physics-aware motion; Temporal consistency; 3D intelligent environments; Deep motion synthesis; PPO policy optimization

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 Abstract

Weeds are unwanted plants that grow along with the agricultural crops and compete for nutrients, water, sunlight, and space. They reduce crop yield and quality, impose high economic cost to the farmers and may also promote infestation of variety of insects and diseases in the crops. Weeds also interfere with the harvesting process and become part of harvested produce.

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 Keywords

Rabi crops, weeds, weedicides, integrated weed management, Rabi Crops, infestatio

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Creative Commons Attribution 4.0 and The Open Definition