Volume 12 | Issue 12

 Abstract

The development of any village, city, or country in the modern era depends significantly on electrical energy. While fossil fuels have been a primary energy source, they contribute heavily to pollution, suffer from efficiency losses, and are limited in availability. Renewable energy sources such as solar, wind, and hydro offer a cleaner, sustainable, and inexhaustible alternative. This study models a Solar Photovoltaic (PV) system and employs the Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) technique to ensure consistent energy output. The system's performance is evaluated under varying solar irradiance and load conditions, demonstrating its ability to provide stable energy for diverse applications. This work underscores the importance of MPPT in optimizing solar energy systems for sustainable energy solutions.

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 Keywords

Solar PV, MPPT, Insolation, Insolation, Perturb and Observation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study presents a groundbreaking approach to enhance the accuracy of the YOLOv8 model in object detection, focusing mainly on addressing the limitations of detecting objects in varied image types, particularly for small objects. The proposed strategy of this work incorporates the Context Attention Block (CAB) to effectively locate and identify small objects in images. Furthermore, the proposed work improves the feature extraction capability without increasing model complexity by increasing the thickness of the Coarse-to-Fine(C2F) block. In addition, Spatial Attention (SA) has been modified to accelerate detection performance. The enhanced YOLOv8 model (Namely YOLOv8-CAB) strongly emphasizes the performance of detecting smaller objects by leveraging the CAB block to exploit multiscale feature maps and iterative feedback, thereby optimizing object detection mechanisms. As a result, the innovative design facilitates superior feature extraction, "especially the weak features," contextual information preservation, and efficient feature fusion. Rigorous testing on the Common Objects in Context (COCO) dataset was performed to demonstrate the efficacy of the proposed technique. It is resulting in a remarkable improvement over standard YOLO models. The YOLOv8-CAB model achieved a mean average precision of 97% of detecting rate, indicating a 1% increase compared to conventional models. This study highlights the capabilities of our improved YOLOv8 method in detecting objects, representing a breakthrough that sets the stage for advancements in real-time object detection techniques.

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 Keywords

Artificial Intelligence, Deep Learning, Computer Vision, Object Detection

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Nicotine Dependency, Tobacco Addiction, Youth, Adolescents, Emerging Adults

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Creative Commons Attribution 4.0 and The Open Definition

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My previous research paper demonstrates the importance of attending to styles, practicality, and the blending of working and living space through a consideration of home office arrangements for interior designers. It solves issues such as the following: how does the project promote sustainability, how does it address privacy issues, and how can space be managed effectively? To enhance professionalism and productivity standards within the framework of the environmental directives of the research, the study focuses on the aspects of zonings ergonomics, and inventions. For a variety of needs, solutions such as smart technologies and flexible furniture. As a result, the study focuses on the importance of embodied, adaptive, and creative home offices for sustained gain and client engagement. In this research paper, I will describe important aspects of the interior design style, finishes, and materials related to the project described in the previous research paper by this author. In the next section, I will explain the rationale for these decisions as well as what impact they have on the character of the design.

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 Keywords

1. Bohemian interior style 2. Bamboo 3. Sustainability 4. Frosted glass

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 Abstract

Menstrual hygiene management waste is a widespread issue not only in India but also in several other countries. In the last few decades, menstrual hygiene management has become a key topic in the country, and many non-biodegradable menstrual products have been introduced, like sanitary pads, tampons, etc. Although the usage of menstrual material is a personal choice of any woman, such non-biodegradable products are harmful to the environment in many ways. The present study discussed the major menstrual hygiene management products utilised by women and how they are disposing of these products in Dehra Gopipur town of District Kangra. The study was based on the descriptive research design. The data was collected from 124 women through an interview schedule. The study found that disposable sanitary pads were the most common (about 76%) menstrual products used by women. It also showed that women were disposing of menstrual materials inappropriately. The study concluded that the government promotes menstrual hygiene by providing biodegradable menstrual material to women, but it does not have a solution for appropriately disposing of them. The study suggested that the government should promote sustainable menstrual materials such as menstrual cups, reusable cotton pads, and menstrual underwear, which will reduce the cost of sanitary products while simultaneously minimising the waste generated from non-biodegradable menstrual materials.

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 Keywords

Menstruation, waste, women, town, Himachal Pradesh

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Creative Commons Attribution 4.0 and The Open Definition

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Malware attacks have become a continuous and evolving threat in the digital age, targeting individuals, enterprises, and governments. The ever-changing nature of the malware renders traditional security solutions ineffective for detecting and mitigating sophisticated attacks. Machine learning (ML) techniques have emerged as powerful tools to counter these challenges, enabling adaptive and intelligent detection systems. In many cases, malware attacks make a clear reflection of a common menace in the digital era, the attackers tend to devise very intricate ways for exploiting the vulnerabilities. Current techniques for detection do not avail good fight against advanced evasion such as polymorphism and zero-day attacks. Machine learning (ML) offers achievable strongholds against such threats, yet a number of challenges and the gaps remain. This paper identifies the gaps and existing methodologies while highlighting potential countermeasures on fresh discoveries from various peer-reviewed journal articles. This article presents a comprehensive survey of malware attacks, their classifications, attack vectors, and impacts. We explain the applicability of ML techniques in fighting malware, while discussing their effectiveness, shortcomings, and future research paths.

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Malware, attacks, types of malwares, machine learning, deep learning, malicious, benign, algorithms, android malware.

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In their deep meditative state, our rishis explored the potential of sound, the power of sound to absorb the mind deeply while repeating harmonious sound frequencies in the form of mantras. In the meditation process, they experienced the power of harmonious frequencies, which could reverse the negative effects of the negative thoughts programmed in our subconscious. Hence, they developed a system called Nada Yoga, mainly to practice focused meditation. The yogis found that musical frequencies are not just a source of entertainment rather, they inherit higher purposes that can be achieved with the help of these frequencies in the state of Dhyana. A good amount of Vedantic literature elucidates the use of sound to attain spiritual bliss and asserts that the entire creation begins with the sound vibration or sphot. For past centuries, in Vedic culture, the sacred sounds, in the form of mantras or Kirtans, are used to pierce the sensual, mental and intellectual levels of existence to purify the body and mind and to attain divine enlightenment to become liberated.

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Musical Frequencies, Vibration, Beejmantra, Nadayoga, Consciousness

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The universal phenomenon of the periodic marketing was distributed by transformation of the economy and rapid growth of urbanisation, and was replaced by permanent shops or markets in developed countries as well as in many parts of the developing world. A rural periodic market is the centre of the village, on which the social, economic and cultural activities of several villages depend. These markets are held periodically on same specific day or days of the week at same fixed locations and thus provide different goods and services to the rural masses. The variation of periodicity is a common feature of a rural periodic market. In Dakshin Dinajpur district, the periodic markets are organised either once, twice or trice in a week. These bi-weekly and tri-weekly markets lead to increase the market meeting day in a week. A Chi-square test is conducted to prove that the bi-weekly and tri-weekly markets lead to increase the market meeting for each day in a week above the expected meetings. The periodic markets are linked in space and time. This space-time relationship is called as spatio-temporal synchronisation. It is one of the important themes to explain the nature of periodic markets. A well-integrated marketing system should follow the most useful path 'Proximity in space implies separation in time' which derived by Fagerlund and Smith. This study is concerned with the periodicity and spatio-temporal character as well as their future prospects.

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Rural Periodic Markets, Periodicity, Spatio-Temporal Synchronisation

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The increasing demand for sustainable design solutions has made natural materials like cork integral to innovative interior design. This paper explores the application of cork flooring and wall panels in skincare experience centers, emphasizing their role in promoting sustainability, enhancing sensory engagement, and achieving aesthetic excellence. The study highlights cork's unique properties, such as thermal and acoustic insulation, durability, and visual versatility, while also addressing challenges and solutions for its broader adoption. The findings demonstrate that integrating cork into skincare spaces aligns with modern eco-conscious values and elevates customer experiences.

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Keywords: Cork flooring, cork wall panels, sustainable interior design, skincare experience centers, sensory engagement, aesthetic design, acoustic insulation, thermal insulation, eco-friendly materials, biophilic design, renewable resources, customer experience, sustainable materials, functional aesthetics, design versatility, moisture resistance, smart interior systems.

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Natural disasters are unavoidable phenomena that significantly impact economies, ecosystems, and human lives. Events such as tsunamis, earthquakes, and forest fires often lead to widespread devastation, including collapsed infrastructure, disease outbreaks, and loss of life. To address this challenge, we propose a multilayered deep convolutional neural network (CNN) model capable of classifying natural disasters and determining their intensity. Our model processes input images, compares them with pre-trained datasets, and identifies the type and severity of the disaster with high accuracy. This approach enables faster decision-making and effective disaster response, offering a significant advancement in disaster management technologies.

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Convolutional neural network

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Cinema often mirrors societal realities, shedding light on struggles that are otherwise ignored or normalized. English Vinglish, directed by Gauri Shinde, is one such film that explores the unspoken emotional challenges faced by homemakers in a patriarchal setup. The story follows Shashi Godbole, a dedicated homemaker, who silently endures the dismissive attitudes of her husband and children. Her journey of self-discovery begins when she decides to learn English, a decision that transforms her sense of self-worth and confidence. At its core, the film critiques the subtle patriarchy embedded in everyday family dynamics and highlights the emotional abuse that women often face in the form of unappreciated labor and microaggressions. This paper analyzes Shashi's journey through a feminist lens, focusing on how English Vinglish portrays the psychological impact of such abuse, the symbolic role of language in her empowerment, and the broader cultural implications of undervaluing homemakers.

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 Keywords

Emotional Abuse, Patriarchy, Feminism, Language Empowerment, Women's Struggles.

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 Abstract

Brain cancer is a complex and devastating disease with multifaceted causes, including genetic predisposition, environmental factors, and exposure to carcinogens. The intricate interplay of these factors contributes to the development and progression of brain tumor, presenting significant challenges for diagnosis and treatment.Convolutional Neural Networks (CNNs) have emerged as a powerful tool in medical image analysis, offering automated and data-driven approaches to disease detection and characterization. In the context of brain cancer, CNNs have been utilized to analyse magnetic resonance imaging (MRI) data, extract relevant features, and classify tumor types with high accuracy. Their ability to learn intricate patterns from complex imaging data has paved the way for improved diagnostic capabilities and personalized treatment strategies.This project is proposed to use the You Only Look Once (YOLO) algorithm as an alternative approach for the analysis and prediction of brain cancer.

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CNN,MRI,Image,Tumor.

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This paper presents the development of a robust and efficient algorithm for optimal ship routing, designed to tackle the complexities of dynamic oceanic conditions, fuel consumption, and strict time constraints. The proposed algorithm integrates multiple real-time variables such as weather patterns, sea currents, and vessel specifications, optimizing the route selection process for maximum efficiency. By considering these dynamic factors, the algorithm ensures improved route accuracy, adaptability, and overall navigation performance. The solution aims to not only enhance safety by minimizing risks associated with unpredictable ocean conditions but also to reduce operational costs and minimize the environmental footprint of maritime transportation. The findings demonstrate that this approach offers a significant advancement in optimizing maritime navigation, contributing to both economic and environmental sustainability in the shipping industry.

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Ship routing, optimal navigation, dynamic ocean conditions, fuel efficiency, maritime safety, route optimization, vessel characteristics, environmental impact, real-time weather data, sea currents, maritime transportation, sustainable shipping.

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 Abstract

The increasing frequency of ATM-related crimes, such as theft and violence, underscores the urgent need for advanced security systems capable of real-time anomaly detection and response. This research introduces an intelligent surveillance solution specifically designed for ATMs, leveraging the YOLOv3 object detection model. The system detects critical anomalies, including unauthorized multiple person entries and the presence of weapons, using live video feeds from ATM cameras. Upon detection, the system immediately issues a voice alert within the ATM to deter potential offenders and sends a real-time notification to law enforcement via Telegram. The integration of deep learning with a reliable communication framework ensures swift action to prevent criminal activities. The system achieves an impressive detection accuracy of 98.5%, with notification latency reduced to under two seconds, making it highly efficient and scalable. This work not only enhances ATM security but also reduces reliance on manual monitoring, paving the way for smarter and safer financial infrastructure.

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ATM securiaty, YOLOv3, anomaly detection, Telegram alerts, real-time surveillance, public safety, crime prevention.

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Effluent Treatment Plants (ETPs) play a pivotal role in managing the environmental footprint of the textile industry, which is one of the largest polluters globally. This research explores the design, operation, and effectiveness of ETPs in treating wastewater generated by textile production processes. The study identifies common challenges, evaluates emerging technologies, and proposes best practices for optimizing ETP performance. The findings highlight the critical need for robust ETP systems, integrated regulatory frameworks, and innovations in wastewater treatment technologies to ensure sustainable textile production.

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Effluent Treatment Plants (ETPs),textile industry, sustainable textile

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Indian government has increasingly emphasized the importance of science, technology, and innovation (STI) in formulating its internal security strategies. Advanced weaponry and scientific innovations developed by the DRDO have been effectively utilized by security forces in counter-insurgency operations to maneuver through challenging terrains. Moreover, technologies such as satellites, drones, and skilled sniffer dogs have been deployed to locate Naxal hideouts and detect improvised explosive devices (IEDs) buried underground. In low-intensity conflict (LIC) areas, significant loss of life, both among security forces and civilians, underscores the critical need for STI in developing innovative solutions to enhance the capabilities of security agencies. This involves investing in research and development, fostering public-private partnerships, and leveraging technological advancements to create a more resilient internal security apparatus. Some regions remain inaccessible due to harsh environments and difficult terrains. Interestingly, science, technology, and innovation have also been adopted by Naxals in LIC areas, enabling them to survive for extended periods. This presents a challenge, as technology alone does not determine dominance in warfare. The indiscriminate use of lethal weapons and improvised explosive devices IEDs by Naxals makes it particularly difficult for security forces to achieve success in counter-insurgency operations. To combat these challenges, counter-insurgency operations have increasingly relied on STI to enhance their effectiveness. Understanding the modus operandi of Naxals in LIC areas, along with the technologies they utilize, is essential. Equally important is recognizing the equipment and tools used by the military, paramilitary forces, and agencies such as the Central Armed Police Forces (CAPF) and state police during these operations. The role of STI is crucial in saving the lives of security forces and disrupting the insurgent activities carried out by Naxals. Addressing this complexity necessitates a comprehensive understanding of the role of science, technology, and innovation in both insurgency and counter-insurgency doctrines. This paper focuses on the latest technologies adopted by Maoists in their warfare against the Indian state, as well as the advanced technologies employed by security forces in counter-insurgency operations, particularly in jungle warfare. It also highlights the efforts made by the Indian state to tackle the challenges posed by Maoist activities.

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 Keywords

Low-Intensity Conflicts, Counter-Insurgency, Science & Technology, Innovations.

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This study examines how the hydraulic conductivity of sand is affected by submersion in saline water. To find out how hydraulic conductivity changes when sand samples are immersed in different amounts of saline solutions, laboratory tests were carried out. The findings show that ionic interactions influencing particle configurations and variations in pore water viscosity cause saline water to modify hydraulic conductivity. The results have ramifications for groundwater research in saline-prone areas and coastal engineering

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Hydraulic conductivity, Permeability, Darcy's Law, Permeameter, Concentration.

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There is a growing consensus around the world that environmental protection and sustainable development are paramount in the fight to save Earth from the destruction that humans have wrought upon it. Sustainable economic growth can be achieved through green banking. When it comes to economic development, banks are indispensable, and they are also perfectly suited to engage in Green Banking initiatives. "Going green" is the current mantra in the banking sector. The term "Green" encompasses many different aspects of environmental, social, and ethical responsibility. The term "Green Banking" refers to a subset of banking activity that prioritizes ecological issues alongside socioeconomic ones. This is done with the goal of protecting the environment and preserving natural resources. Banks may make a difference for the environment by implementing green practices across the company and educating its customers about the importance of doing the same. Banks, governments, NGOs, international financial institutions (IFIs), the Central Bank, consumers, and business communities all have a hand in making green banking a reality. Banks' green initiatives encompass a wide range of activities, such as managing the internal environment, developing and implementing principles, promoting other stakeholders, and conducting environmental disclosure and reporting.

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Key words: Ecology, NGOs, IFIs, IGOs

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Creative Commons Attribution 4.0 and The Open Definition

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This paper explores the application of the Markov Chain model to forecast stock behaviour, focusing on stocks indexed within the NIFTY 50. The NIFTY 50, an Indian stock market index, represents the float-weighted average of the 50 largest companies listed on the National Stock Exchange (NSE). Alongside NSE, the Bombay Stock Exchange (BSE) serves as a prominent trading platform in India. The stock market is an attractive avenue for investment, enticing both domestic and foreign investors. Understanding and predicting stock market trends are crucial for making informed investment decisions. While the Markov Chain model has been widely utilized to predict stock market trends, most applications focus on indices or groups of stocks rather than individual stocks. The overall objective of this study therefore, was to apply Markov Chain to model and forecast trend. The study was conducted through 2 years historical data of Nifty 50 daily closing price. Secondary quantitative data on the daily closing share prices was obtained from Yahoo Finance website over a period covering 12th December 2022 to 12th December 2024 forming a 493 days trading data panel. A Markov chain model was determined based on probability transition matrix and initial state vector. MATLAB software used to determine initial state vector, transition matrix and trend values using moving average. In the long run, irrespective of the current state of share price, the model predicted that the Nifty 50 would increase, decrease and remains constant with a probability of 0.5639, 0.4341 & 0.0020 respectively.

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Markov Chain, Transition Matrix, Initial State Vector, MATLAB

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The researcher utilized qualitative case study to analyze the beneficiary of DILP under the group category in the Province of Tarlac. This research explores the success and challenge faced by the beneficiaries of the Department of Labor and Employment Integrated Livelihood Program or DILP focusing on livelihood projects under 30 groups. Through interviews and analysis, the study structured support, government partnership and interventions, and skill-building initiatives impact cooperative resilience, financial stability, and market adaptability. Case studies reveal that while many groups achieved sustainable livelihoods through innovative market strategies and active community involvement, others struggled with internal coordination, competitive pressure, and resource limitation. The research identifies best practices of the success beneficiaries, such as regular training, adaptive business model and stronger market linkages, to support sustainable growth. Meanwhile The study proposes to the prevailing problems encountered by the beneficiaries such as ongoing skill development, improve monitoring and flexible financial options can enhance the efficacy of DILP initiative and promote long-term community empowerment. Findings of this study contribute valuable insights for public administration and cooperative development, emphasizing strategic support for inclusive growth.

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DILP, Livelihood, DOLE, Groups, Beneficiaries, Success, Failure, Government

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Creative Commons Attribution 4.0 and The Open Definition