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460 articles for “sensing”
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Innovations in Mineral Science and Engineering for Sustainable Resource Development
Abstract: The growing global demand for mineral resources, coupled with increasing environmental and social concerns, has intensified the need for sustainable approaches in mineral science and engineering. Traditional mining and mineral processing practices, while essential for industrial development, are often associated with high energy consumption, resource depletion, and environmental degradation. In response, recent innovations in mineral science and engineering have focused on improving resource efficiency, minimizing environmental impact, and ensuring long-term …
Published in International Journal of Minerals · Vol. 3, Issue 1, 2026 · pp. 31–36 Read article
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Collaborative Robotics and Smart Automation: Enhancing Human–Robot Synergy in Industry 5.0
Abstract: Industry 5.0 marks a paradigm shift from efficiency-centric automation to a human-centred, sustainable, and collaborative production environment . In this context, collaborative robots, commonly referred to as cobots, play a central role by enabling direct and safe interaction between humans and machines within shared workspaces. These systems are designed to support human operators by undertaking repetitive, precision-intensive, and physically demanding tasks, thereby allowing humans to focus on supervisory control, problem-solving, …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 22–29 Read article
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Time Multiplexed Binary Offset Carrier (TMBOC) Transmitter with Polarimetric Interferometric Synthetic Aperture Radar (Pol-InSAR)
Abstract: This paper provides insights into Time Multiplexed Binary Offset Carrier (TMBOC), a modulation technique employed in satellite navigation systems, specifically designed for GPS L1C. TMBOC improves signal correlation properties by time-multiplexing Binary Offset Carrier (BOC) (1, 1) and (6, 1). The text discusses various TMBOC models, including spectral representations and power distributions. Performance analysis reveals the potential of TMBOC signals in achieving superior tracking accuracy and interference resistance compared to …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 34–49 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Intelligent Electromagnetic Synthesis: An AI-Driven IoT Framework for Adaptive Antenna Design in Missile Navigation
Abstract: The rapid evolution of hypersonic and long-range tactical missile systems necessitates antenna architecture capable of maintaining robust communication links under extreme thermal, mechanical, and signal-jamming environments. Traditional antenna design methodologies often relying on iterative simulation cycles and static optimization are increasingly insufficient for the real-time requirements of modern aerospace navigation. This paper proposes an AI-driven, IoT- integrated framework that facilitates autonomous antenna design and performance optimization. By deploying a distributed …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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IoT-Based Battery Health Monitoring for Electric Vehicles Using Machine Learning
Abstract: With increasing utilization of the Electric Vehicles (EV)s in global scale, battery health management becomes a critical factor which has great impact on vehicle performance, safety and longevity. Battery materials, such as NMC LFP lithium-ion batteries and lithium-ion batteries, degrade over time from charging behaviour, heat stress, discharging voltage profiles and environmental limits. Conventional BMS only offer threshold based health diagnostics and cannot perform accurate degradation prediction. This work presents …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Development and implementation of Solar-Thermoelectric Hybrid Energy Harvester
Abstract: In today’s consumer-oriented and technology-driven market, researchers are increasingly emphasizing the need to harvest energy from ambient and renewable sources to support sustainable power generation and to minimize dependence on conventional energy resources such as batteries and fossil-fuel-based electricity. The rising deployment of portable electronics, wireless sensor networks, and Internet of Things (IoT) devices has created an urgent demand for compact, low-power, long-life, and maintenance-free energy solutions. In many real-world …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article
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Thermal Steganography: A New Way to Steal Data from Air-Gapped Computers Using Heat and Fan Noise
Abstract: Nowadays, high-security computers are "air-gapped," meaning they are not connected to the internet to prevent hacking. Cybercriminals are increasingly using direct, physical methods to access and take data instead of relying on internet-based attacks. This paper introduces a new cybersecurity threat called Thermal-Secret. Most existing heat-based attacks are very slow and fail if the room temperature changes. To solve this, we developed a Slope-Based method. Instead of looking at how …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Design of an Integrated Health Monitoring System on an IoT-Based Framework
Abstract: With the advent of industrialization, health ailments have become a major cause of concern owing to an inactive and fast lifestyle, polluted environments, and detrimental eating habits. However, IoT has become a boon for the health sector and humanity on account of its countless benefits, rendering improved quality of service and patient-centric care. An Integrated Health Monitoring System (IHMS) is presented in this paper. This new IoT-based framework integrates wearable …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 1–7 Read article
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Energy-Aware Task Offloading in 6G-Enabled Mobile Edge Computing Environments
Abstract: The emergence of sixth-generation (6G) wireless communication networks is expected to revolutionize future mobile systems by enabling ultra-low latency communication, extremely high data rates, massive connectivity, and intelligent network management. In parallel, mobile edge computing (MEC) has gained significant attention as a promising paradigm that brings computational resources closer to end users, thereby alleviating network congestion and reducing end-to-end service delays. Despite these advantages, the rapid growth of computation-intensive and …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 1, 2026 · pp. 14–19 Read article
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The Dark Side of Technology: Addressing the Rise of Cybercrime and Data Breaches
Abstract: In the digital age, technological advancements have brought about remarkable improvements in communication, business, and daily life. However, these innovations have also given rise to a darker side of the tech world: an increase in cybercrime and data breaches. This article examines the growing threats posed by malicious actors, including hackers, cybercriminal syndicates, and state-sponsored entities, who exploit vulnerabilities in digital systems. It explores the wide-reaching impacts of cybercrime, from …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 06–15 Read article
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Television Media and Children: A Sociological Insight on Rural Society in Punjab
Abstract: The present paper deals with to understand the media forms of television and digital media as an influential agent of socialisation in contemporary society, especially among the children. The increasing accessibility of television and digital media, especially in the rural society of Punjab, have greatly impacted the patterns of childhood socialisation, cultural norms, religious practices, attitudes, and routine behaviour. During the study it is found that television continues to occupy …
Published in International Journal of Children · Vol. 3, Issue 2, 2026 · pp. 21–34 Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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An Analytical Study of the Effectiveness of the Child Development Scheme in Anganwadi Centers of Rudraprayag District
Abstract: From the perspective of human development, childhood is regarded as a highly sensitive and multidimensional phase that plays a pivotal role in shaping the trajectory of human life. During childhood, children undergo rapid growth across their mental, social, psychological, and physical domains. Currently, the mental, physical, and social well-being—as well as the overall health—of children remains a grave challenge for the entire world. An increase in nutritional and health-related problems …
Published in International Journal of Children · Vol. 3, Issue 2, 2026 · pp. 35–47 Read article
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Listening to Colonial Disruption: Sound, Silence, and Cultural Memory in the Works of Chinua Achebe
Abstract: This article examines the significance of sound and silence in the fiction of Chinua Achebe,arguing that auditory experience functions as a crucial medium through which cultural memory,identity, and resistance are represented. Although Achebe’s novels have been extensively studied in relation to colonialism, nationalism, and language politics, comparatively little attention has been paid to their acoustic dimensions. Drawing on postcolonial theory, oral tradition studies, and cultural memory studies, this paper investigates …
Published in Emerging Trends in Languages · Vol. 3, Issue 2, 2026 Read article
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Emerging Trends in Photobiology: Exploring the Photophysics and Photobiology of the Eye
Abstract: The eye consists of three main segments: the cornea, lens, and retina. The primary function of the anterior ocular tissue, the cornea and lens, is to transmit and focus light onto the retina without distortion. They also filter UV light (under 400 nm), preventing it from reaching the retina. While light reaching the retina is mostly used for vision, it can also have various effects on the eye's constituents, both …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 1, 2025 · pp. 31–37 Read article
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Host Invasion to Immune Evasion: Emerging Concepts in Pathogen Virulence Strategies
Abstract: The interaction between hosts and pathogens represents a continuous evolutionary struggle, shaping both microbial virulence and host immunity. Pathogens employ diverse strategies to evade immune surveillance, ranging from antigenic variation and molecular mimicry to hijacking of host immune checkpoints. Simultaneously, hosts refine innate and adaptive immune mechanisms to counteract infection and limit damage. This reciprocal adaptation, known as host–pathogen coevolution, influences pathogen persistence, transmission, and fitness, while also sculpting immune …
Published in International Journal of Pathogens · Vol. 3, Issue 1, 2026 Read article
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The Role of Artificial Intelligence in Enhancing Athlete Performance and Training Strategies
Abstract: Artificial Intelligence (AI) is transforming modern sports by improving athlete performance, training methods, and decision-making processes. The integration of AI technologies such as machine learning, data analytics, wearable sensors, and computer vision has enabled coaches and sports scientists to analyze large amounts of performance data with greater accuracy and efficiency. Athletes' physiological indicators, movement patterns, injury risks, and recuperation processes are all monitored by these technology. Training regimens can therefore …
Published in Recent Trends in Sports · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article