Volume 13 | Issue 6 |

 Abstract

Adware, often dismissed as a low-priority threat in mobile security, has evolved into a sophisticated attack vector capable of compromising user privacy, draining resources, and facilitating data exfiltration. This paper presents a novel, behavior-based approach to detecting adware attacks on mobile phones, addressing the growing challenge of aggressive ad libraries, click fraud, and covert data transmission. Our methodology integrates both static and dynamic feature extraction, focusing on permission overuse, sensitive API call patterns, and behavioral anomalies such as excessive CPU usage, battery drain, and ad network interactions. We employ a Random Forest classifier optimized for mobile deployment, achieving a detection accuracy of 96.12% and an AUC-ROC score of 0.9914. Explainability techniques, including SHAP analysis, provide transparent insights into model decisions, highlighting key features like READ PHONE STATE and RECEIVE BOOT COMPLETED as primary indicators. The proposed system, with its lightweight architecture (1.7 MB) and low false positive rate (1.42%), offers practical applications for enterprise mobile device management, app store review automation, and end-user security tools. Future directions include incorporating network traffic analysis and adaptive learning to counter advanced adware evasion techniques.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mobile adware detection, Android malware, behavior-based analysis, machine learning, Random Forest, mobile security, mobile device management (MDM).

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's digital world, social media plays a big role in shaping how people think and shop especially among young users. This study looks at how Instagram and Facebook affect online buying behaviour among the youth of Shillong, Meghalaya. Shillong is a unique city where modern life and traditional culture come together. As internet use grows in North-East India, social media is becoming more than just a place to chat - it's now a powerful tool that encourages people to shop online. The study uses both surveys and interviews to gather data from young people aged 18 to 30, including students and working professionals. The results show that well-designed posts, recommendations from friends, and promotions by influencers strongly influence buying decisions. Instagram has a greater impact than Facebook because of its focus on images and interactive features. Another key finding is that many young people trust local influencers and their friends more than big advertisements. Their buying choices also differ based on gender, comfort with technology, and the type of products - like clothes, cosmetics, or gadgets. The study also finds that eye-catching posts, limited-time deals, and seeing others like or comment on a product create a strong desire to buy. This effect becomes stronger because social media shows users content they are most likely to respond to. This research adds a local, youth-focused view to the study of online shopping. It suggests that brands should adjust their digital marketing to fit the needs and culture of young people in smaller cities like Shillong.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Social Media Marketing, Online Shopping Behaviour, Youth Consumers, Instagram and Facebook Influence, Digital Trends in North-East India.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Soil serves as a fundamental component of terrestrial ecosystems and a primary medium for agricultural production. It acts as a reservoir of water and nutrients, making its physical and chemical properties vital to crop growth and yield. Among these, soil texture and structure are paramount in determining how water is retained and distributed within the soil matrix. Soil texture refers to the relative proportions of sand, silt, and clay particles, while soil structure pertains to the arrangement of these particles into aggregates or peds. These physical attributes influence porosity, permeability, aeration, root development, microbial activity, and ultimately, crop performance. This review paper critically evaluates how soil texture and structure interact to influence water retention and crop productivity. Drawing upon various scientific studies, it explores the fundamental principles governing soil-water interactions, the classification and significance of different soil types, and how management practices and organic amendments can enhance soil water dynamics. Furthermore, this paper examines the role of emerging technologies like remote sensing, artificial intelligence (AI), and geographic information systems (GIS) in improving water use efficiency in agriculture. The paper also highlights the importance of tailored soil management for specific crops like wheat, rice, and maize, based on their water requirements and root behavior. The review considers the implications of climate change, particularly shifts in rainfall patterns, increased evapotranspiration, and prolonged droughts, on soil-water relationships. Finally, it identifies gaps in current research and suggests future directions for developing sustainable soil and water management strategies that support long-term agricultural productivity. Integrating multidisciplinary approaches and ensuring knowledge dissemination among farmers and policymakers will be key to maintaining soil health and ensuring food security under evolving environmental conditions.

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Soil is the foundation of life on land, serving as the critical interface between the atmosphere, biosphere, hydrosphere, and lithosphere. For agricultural productivity, soil provides the essential medium in which plants anchor their roots and from which they absorb water and nutrients. The physical characteristics of soil determine its capability to sustain plant growth and maintain ecological balance. Among the many attributes, soil texture and soil structure are pivotal in influencing soil-wa

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: Newspapers publish reports on various topics. Mostly hard news gets the space at the first page of the newspapers. A reporter maintains objectivity in reporting incidents by following right representation of the incident without exaggerating the fact and figure, using right words to depict the situation, using relevant words to make the headline and lead sentence and narrating the incident by incorporating quotations from witnesses, government officials, affected people, celebrities, etc. Though it is the duty of the sub-editor to finalise the report along with the making of a suitable headline; reporters nowadays have to work hard to make the news print-worthy. This research paper aimed to identify the various methods that newspapers use when reporting incidents of terror attacks and attract readers' attention.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pahalgam, terrorist, attack, Kashmir, headline, lead.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The safe and uninterrupted administration of intravenous (IV) fluids and medications is critical in modern healthcare. Smart infusion pumps have emerged as a technological solution to monitor and automate this process, yet their reliability and ability to predict infusion longevity and detect failures remain pressing challenges. This review paper evaluates current research focused on analyzing smart pump event logs and the integration of machine learning algorithms to enhance the prediction and prevention of infusion-related failures. Drawing from over 15 recent and relevant studies, we compare supervised, unsupervised, and deep learning approaches across metrics such as failure detection accuracy, infusion longevity prediction, and early warning timeframes. Our analysis indicates that techniques like LSTM-Kalman filtering and unsupervised anomaly detection have outperformed traditional threshold-based alerts by up to 35% in predictive accuracy. Despite technological advancements, issues such as alarm fatigue, interoperability, and cybersecurity risks remain under-addressed. This paper concludes by identifying critical gaps and offering directions for future research to ensure safer, more intelligent IV infusion systems. The safe, continuous administration of intravenous (IV) fluids and medications is foundational to patient care in hospitals, intensive care units, and emergency settings. Any disruption in infusion delivery--due to pump failure, occlusions, or device misconfiguration--can result in adverse patient outcomes. To address these concerns, smart infusion pumps have become widely adopted for their programmable safety features, event logging capabilities, and ability to provide real-time feedback. However, their predictive reliability remains a significant challenge. This review synthesizes current research focused on leveraging machine learning (ML) and artificial intelligence (AI) techniques to analyze smart pump data logs for early detection and prevention of infusion failures.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Smart infusion pumps, LSTM - Kalman Networks, Predictive maintenance, Alarm fatigue, Anamoly detection.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents the development of an overcurrent protection circuit for electric vehicle (EV) charging stations. The main objective is to ensure safe and efficient charging while preventing battery damage due to excessive current. The system utilizes an ESP32 microcontroller interfaced with an ACS712 current sensor to enable real-time current monitoring. When an overcurrent condition is detected, the ESP32 instantly disconnects the power using a 5V relay. A 16x2 LCD is used to notify users of current values and fault states. Experimental validation under simulated overcurrent confirms that the system responds effectively, contributing to improved battery safety and operational reliability.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Electric Vehicle (EV), Overcurrent Protection, ESP32 Microcontroller, ACS712 Current Sensor, Smart Charging, Relay Cutoff, Real-Time Monitoring, Embedded System, Battery Safety, Power Electronics

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

AI and automation are transforming the way Human Resource departments operate. From recruitment to performance management, AI tools are being used to streamline processes, save time, and reduce human error. But while the benefits are real, there are also concerns -- bias in AI algorithms, job displacement, loss of the "human touch," and privacy risks. "While AI and automation offer powerful tools to optimize HR processes, their true impact depends on how responsibly and ethically they are implemented -- making them both a friend and potential foe." The rapid advancement of Artificial Intelligence (AI) and automation technologies is reshaping the landscape of Human Resource Management (HRM), raising critical questions about their role as either enablers or disruptors. This study explores the dualistic nature of AI and automation in HRM by examining their potential to enhance efficiency, decision-making, and employee engagement, while also highlighting the ethical, social, and organizational challenges they introduce. From AI-powered recruitment and performance analytics to automated employee support systems, the paper investigates how these technologies can serve as powerful allies in optimizing HR functions. However, it also critically evaluates the risks of bias, job displacement, and loss of human touch in employee relations. By drawing on recent research, case studies, and expert insights, the paper provides a balanced perspective on whether AI and automation are friends or foes to HRM, ultimately offering recommendations for strategic integration that prioritizes both innovation and human values.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence (AI), Performance Analytics, Employee Engagement, Ethical Challenges, HR Technologies, Loss of Human Touch

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Prashikshanadheen Shikshakon Dwara Shikshan ko Ek Peshe ke Roop Mein Apnane ki Pravritti: Sanyog Se ya Chayan Se .?

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Prashikshanadheen Shikshakon Dwara Shikshan ko Ek Peshe ke Roop Mein Apnane ki Pravritti: Sanyog Se ya Chayan Se .?

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Explores the critical aspects of ensuring cloud data integrity and security through enhanced cryptographic techniques. Emphasizing the need for robust protection in cloud environments, the study delves into improved cryptographic methods as a pivotal means to safeguard sensitive information. The paper highlights advancements in encryption technologies, addressing emerging threats and bolstering data integrity within the dynamic landscape of cloud computing.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Cloud computing, security, cryptography, encryption, decryption

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Wireless mesh network is a multi-leap communication. All packets produce from source to goal node in leap by leap forwarding manner. To assure the genuineness of each node is much substantive and communication must be protected. WMN can be defined as an influential, self-concerned, self-construct, propagates wireless multi-leap network. WMN comprises of mesh routers (MRs), mesh clients (MCs) and gateways. When WMN is indexed the nodes will form a network automatically and lead off listening to broadcasting notification. Security has turn the leading pertain to provide protected communication between different mesh nodes. The objective is to study the mechanism Multilayer model for preventing WMNs, possibility of Denial of Service attack in WMNs networks and a high efficiency DoS attack detection algorithm.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

DoS (Denial of Service), Authorization, Security Mechanisms, IP Filter, WMNs etc.

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Creative Commons Attribution 4.0 and The Open Definition