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Agrivoltaics: Combining Food And Solar Power On Agricultural Lands, Dharla Soteros, Kendall Becker, Spencer J. Good, Ngoni Mufute, Matt Yost, Logan Mitchell, Scott Hotaling Oct 2026

Agrivoltaics: Combining Food And Solar Power On Agricultural Lands, Dharla Soteros, Kendall Becker, Spencer J. Good, Ngoni Mufute, Matt Yost, Logan Mitchell, Scott Hotaling

All Current Publications

Utah’s ranchers and farmers face pressure to sell land to developers, conserve water, and manage increasing production costs (Li et al., 2019). One way producers can keep growing food while diversifying and increasing revenue is by integrating agriculture and solar electricity generation on the same land, a practice known as agrivoltaics. In this fact sheet, the authors describe agrivoltaic setup options, summarize agrivoltaics' impacts on livestock and crop production, and discuss implementation economics.

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Wilson's Phalarope, A Migratory Bird, Depends On The Declining Great Salt Lake, William Christenson, Kendall Becker, Spencer J. Good, T.J. Clark-Wolf, Scott Hotaling Oct 2026

Wilson's Phalarope, A Migratory Bird, Depends On The Declining Great Salt Lake, William Christenson, Kendall Becker, Spencer J. Good, T.J. Clark-Wolf, Scott Hotaling

All Current Publications

This fact sheet describes how declining water levels and increasing salinity degrade habitat for brine flies and other prey Wilson’s phalaropes rely on. Because human use drives low water levels, changes to water management could reverse the lake’s decline and improve habitat quality for Wilson’s phalaropes and other species that depend on the Great Salt Lake.

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Research On Data Risk And Governance Of Generative Artificial Intelligence Empowering Intelligence Work, Yonghui Guo, Xiaobei Guo, Yuan Feng, Yapeng Li Oct 2026

Research On Data Risk And Governance Of Generative Artificial Intelligence Empowering Intelligence Work, Yonghui Guo, Xiaobei Guo, Yuan Feng, Yapeng Li

Journal of Scientific Information Research

[Purpose/significance] Generative Artificial Intelligence（GAI）generates numerous data risks in the process of empowering intelligence work. Fully understanding, identifying, and governing the data risks are the key to the effective empowerment of intelligence work by GAI. [Method/process] Based on the four stages of intelligence work, this paper subdivides the main data activities in intelligence work empowered by generative artificial intelligence from the perspective of the data workflow. Based on risk management theory, the data risks in data input, data processing, data content generation and data content dissemination, are systematically analyzed and identified. From three perspectives of institution, subject, and technology, a data …

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Twinning Behavior Of Molecule-Adapted Gaussian-Type Orbitals (Gtos) In Cyclo-Hydrocarbons, Tong-Hyok Cha, Gum-Chol Kim, Kwang-Jin Ri, Jin-Nam Kim, Yong-Su Pak Oct 2026

Twinning Behavior Of Molecule-Adapted Gaussian-Type Orbitals (Gtos) In Cyclo-Hydrocarbons, Tong-Hyok Cha, Gum-Chol Kim, Kwang-Jin Ri, Jin-Nam Kim, Yong-Su Pak

Turkish Journal of Chemistry

The saturated cyclo-hydrocarbons CnH2n (n = 3–7) were constructed by the iterative coupling of the structural unit groups (SUGs), specifically the SUG-CH2C2 fragment, which was previously established for molecular basis optimization. For the McLean–Chandler 6-311+G basis set, under the SUG perturbation, the outer (s′, p′) and diffuse (sʺ, pʺ) primitive Gaussian type orbitals for the core-atom C* of SUG-CH2C2 undergo an off-center spatial displacement into a twinning configuration. Specifically, the s-type twins (s′, sʺ) share identical Gaussian exponents and are symmetrically shifted toward the two neighboring carbon atoms, while the p-type twins (p′, pʺ) exhibit a matching configuration. Generally, this …

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Phytochemical Characterization, Cytotoxic Effects, And Potential Oxidative Dna Damage-Modulating Activities Of Arum Italicum Extract, Oznour Mourat Moustafa, Hülya Yağar Oct 2026

Phytochemical Characterization, Cytotoxic Effects, And Potential Oxidative Dna Damage-Modulating Activities Of Arum Italicum Extract, Oznour Mourat Moustafa, Hülya Yağar

Turkish Journal of Chemistry

Arum italicum is traditionally utilized in the Thrace region for the treatment of hepatic and dermatological disorders; however, experimental evidence supporting these ethnopharmacological applications remains limited. As oxidative stress-induced DNA damage is an important contributor to the pathogenesis of liver and skin diseases, the aim in the present study was to investigate the ability of A. italicum leaf and tuber extracts to modulate oxidative DNA damage in vitro using nontumorigenic and cancerous hepatic and cutaneous cell models. Phytochemical profiling, antioxidant capacity, and cytotoxic activity were also assessed to support and contextualize the observed DNA damage-related effects.In vitro investigations were conducted …

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Facile One-Step Activated Glassy Carbon Electrode For Sensitive Tryptophan Sensing In Yogurt, Sevi̇lay Erdoğan Kablan, Ahmet Çeti̇nkaya, Si̇bel Özkan, Emi̇rhan Nemutlu Oct 2026

Facile One-Step Activated Glassy Carbon Electrode For Sensitive Tryptophan Sensing In Yogurt, Sevi̇lay Erdoğan Kablan, Ahmet Çeti̇nkaya, Si̇bel Özkan, Emi̇rhan Nemutlu

Turkish Journal of Chemistry

Activation of glassy carbon electrodes (GCEs) in tailored solution environments introduces oxygenated surface functionalities such as hydroxyl, carboxyl, and quinone groups. These modifications enhance electron‐transfer kinetics and strengthen interactions with target analytes, thereby improving electrochemical sensitivity. In this study, square-wave voltammetry was used, and the most suitable supporting electrolyte for tryptophan (TRP) analysis was a pH 3 Britton–Robinson buffer. The cyclic voltammetry potential range and number of cycles for the Act-GCE were obtained as 0–1.5 V and seven cycles, respectively. The activated electrode exhibited excellent analytical performance, with a linear response for TRP over 0.20–6.28 μM, a detection limit of …

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Thiophene-Carbazole-Based Covalent Organic Polymer Electrodes For Electrochromic And Supercapacitor Applications, Si̇nem Altinişik Oct 2026

Thiophene-Carbazole-Based Covalent Organic Polymer Electrodes For Electrochromic And Supercapacitor Applications, Si̇nem Altinişik

Turkish Journal of Chemistry

In this study, a thiophene-carbazole-based conjugated organic polymer was successfully synthesized on indium tin oxide (ITO)/glass and graphite sheet substrates using in situ oxidative polymerization. In terms of electrochromic properties, the electrodes exhibited significant color change from light yellow-green to dark gray in the potential range of 0 V to 1.2 V, with optical contrast ranging from 84.2% to 47.2% and coloring efficiency of 171.3 cm2/C. The prepared PCBP-Th_ITO/glass electrode also exhibited fast switching times (tb = 0.89 s and tc = 2.05 s) at 650 nm. Furthermore, 90% optical stability was maintained after 1000 cycles. In terms of energy …

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Fabrication Of Cross-Linked Thiophene-Coumarin-Fluorene Donor–Acceptor Pentamer Thin Films For Electrochromic Devices Application, Ari̇fe Aktaş, Mert Akgün, Mücahi̇t Özdemi̇r, Sermet Koyuncu Oct 2026

Fabrication Of Cross-Linked Thiophene-Coumarin-Fluorene Donor–Acceptor Pentamer Thin Films For Electrochromic Devices Application, Ari̇fe Aktaş, Mert Akgün, Mücahi̇t Özdemi̇r, Sermet Koyuncu

Turkish Journal of Chemistry

Functionalized p-conjugated polymers have emerged as promising electrochromic materials due to their well-defined molecular structures, facile synthesis, and ability to form smooth and homogeneous thin films. Furthermore, surface cross-linking enhances the mechanical and environmental stability of these films while improving their durability during electrochemical operation. In this study, a unique band gap-tunable pentamer (FBP) was developed featuring a D-A-D-A-D configuration, which includes thiophene, coumarin, and fluorene. Cross-linked films (FBPX) were obtained using both spray and electrospray methods in the presence of tetrathiol-based crosslinkers and 366 nm light, thanks to the functionalizable allyl groups present in the FBP structure. UV–Vis analysis …

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Synthesis And Catalytic Activity Of Water-Soluble Ruthenium(Ii) P-Cymene Complexes In Tandem Nitroarene Reduction/N-Methylation And Transfer Hydrogenation, Si̇nem Çakir, Serdar Batikan Kavukcu, Hayati̇ Türkmen Oct 2026

Synthesis And Catalytic Activity Of Water-Soluble Ruthenium(Ii) P-Cymene Complexes In Tandem Nitroarene Reduction/N-Methylation And Transfer Hydrogenation, Si̇nem Çakir, Serdar Batikan Kavukcu, Hayati̇ Türkmen

Turkish Journal of Chemistry

In this study, a series of water-soluble ruthenium(II) p-cymene complexes bearing carboxylic acid-functionalized ligands (Ru1–Ru3) were synthesized, fully characterized (1H NMR, 13C NMR, and FT-IR), and evaluated in two distinct catalytic transformations: tandem nitroarene reduction/N-methylation and transfer hydrogenation. Of the catalysts tested, Ru1 exhibited superior catalytic activity in both systems. Under optimized conditions (1 mol% Ru1, 8 mmol NaBH4, 110 °C, 2 h in methanol), Ru1 promoted the one-pot tandem transformation of nitrobenzene to N-methylaniline with up to 93% conversion using methanol as a sustainable C1 and H2 source. Furthermore, Ru1 proved highly effective in the transfer hydrogenation of acetophenone …

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Samarium-Doped Ceria Catalysts For Boron-Aluminum Composite Propellants: Effect Of Synthesis Method, Di̇lara Güçtaş Gürel, Mehmet Ali̇ Faruk Öksüzömer Oct 2026

Samarium-Doped Ceria Catalysts For Boron-Aluminum Composite Propellants: Effect Of Synthesis Method, Di̇lara Güçtaş Gürel, Mehmet Ali̇ Faruk Öksüzömer

Turkish Journal of Chemistry

Solid propellants based on ammonium perchlorate (AP) are widely used in rocket and missile propulsion systems due to their high energy density and reliable combustion characteristics. Although aluminum (Al) is the conventional metal fuel in AP-based formulations, boron (B) has gained increasing attention as a partial or full substitute owing to its significantly higher volumetric energy density. However, the low combustion efficiency of boron particles remains a critical challenge, making the use of catalysts essential to enhance the thermal decomposition of AP and overall propellant-burning performance. In this study, samarium-doped ceria (SDC20) catalysts were synthesized by three different methods including …

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Rapid Synthesis Of Agcu Bimetallic Nanodendrites With Enhanced Catalytic Activity For 4-Nitrophenol Reduction, Jun Liu, Hongguang Liao, Xuanyan Liu Oct 2026

Rapid Synthesis Of Agcu Bimetallic Nanodendrites With Enhanced Catalytic Activity For 4-Nitrophenol Reduction, Jun Liu, Hongguang Liao, Xuanyan Liu

Turkish Journal of Chemistry

Herein, AgCu nanodendrites were fabricated via a facile one-step displacement reaction at ambient temperature with Zn powder as the reducing agent. The morphology, structure, and composition of the products were systematically characterized by transmission electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The results demonstrate that the structure and morphology of the catalysts are strongly dependent on the Ag/Cu molar ratio. The catalytic performance was evaluated by the reduction of 4-nitrophenol (4-NP) at room temperature, in comparison with monometallic Ag and Cu catalysts. The catalytic activity follows the order Ag1Cu1 > Ag1Cu3 > Ag3Cu1 > Ag > Cu. The optimized Ag1Cu1 catalyst achieves 98.6% …

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Effects Of Washing, Oxidation, Carboxylation, And Hydrophobicity On The Antibacterial Activity Of Graphene Oxide And Reduced Graphene Oxide, Emi̇r Boztepe, Ceren Poyraz, Ruki̇ye Taşdemi̇r, Ebru Önem, Ümran Sofu, Keri̇m Yapici Oct 2026

Effects Of Washing, Oxidation, Carboxylation, And Hydrophobicity On The Antibacterial Activity Of Graphene Oxide And Reduced Graphene Oxide, Emi̇r Boztepe, Ceren Poyraz, Ruki̇ye Taşdemi̇r, Ebru Önem, Ümran Sofu, Keri̇m Yapici

Turkish Journal of Chemistry

In this study, the effects of number of washes, oxidation degree, carboxylation, and hydrothermal reduction temperature on the antibacterial activity of graphene oxide (GO) and reduced graphene oxide (rGO) nanomaterials were investigated. GO derivatives with different numbers of washes (1–5W) and oxidation levels (3X, 6X, and 9X), carboxylated GO (GO-COOH), and rGO samples obtained at different hydrothermal reduction temperatures (100, 140, and 180 °C) were characterized by X-ray diffraction, field-emission scanning electron microscopy, Fourier-transform infrared spectroscopy, zeta potential analysis, and Raman spectroscopy, and were subsequently evaluated for antibacterial activity against gram-positive Staphylococcus aureus (S. aureus) and gram-negative Escherichia coli (E. …

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Cobalt-Substituted Hydroxyapatite As A Potential Basis Of Biomaterials: Synthesis, Crystal-Chemistry Properties And Antibacterial Activity, Maria M. Vlasova, Ksenia S. Stasenko, Evgeny Bulanov Oct 2026

Cobalt-Substituted Hydroxyapatite As A Potential Basis Of Biomaterials: Synthesis, Crystal-Chemistry Properties And Antibacterial Activity, Maria M. Vlasova, Ksenia S. Stasenko, Evgeny Bulanov

Turkish Journal of Chemistry

This paper presents the results of the synthesis of solid solutions of cobalt-substituted hydroxyapatite of the composition Ca10-xCox(PO4)6(OH)2 by the solid-phase and solution method. The formation of only the composition of Ca9.5Co0.5(PO4)6(OH)2 has been reliably established, whereas an increase in the cobalt content, as well as an increase in the temperature of synthesis and calcination of the samples prepared in solution, leads to the formation of stable mixtures of calcium and cobalt phosphates. The crystal structure has been refined for Ca9.5Co0.5(PO4)6(OH)2 (a = 9.4121(28) Å, c = 6.8762(20) Å, V = 527.54(35) Å3; R-Bragg = 2.455%) under the assumption of …

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Measurements And Analysis Of Light Non-Methane Hydrocarbon Mole Fractions In 1982–1987 At Six Remote Sites Along The Pacific Rim, A. M. Smith, C. L. Butenhoff, M. A. K. Khalil, A. L. Rice Oct 2026

Measurements And Analysis Of Light Non-Methane Hydrocarbon Mole Fractions In 1982–1987 At Six Remote Sites Along The Pacific Rim, A. M. Smith, C. L. Butenhoff, M. A. K. Khalil, A. L. Rice

Physics Faculty Publications and Presentations

Atmospheric non‐methane hydrocarbons (NMHCs) are important trace species with anthropogenic and natural sources including fugitive emissions from fossil fuel mining and distribution, biomass burning, biofuel combustion, and biogenic emissions from microbes and plants. We present previously unpublished whole air sample measurements of NMHCs collected at approximately weekly intervals from 1982 to 1987 at six stations spanning the Northern and Southern hemispheres, which sampled primarily Pacific Basin air masses as determined by back‐trajectory analysis. The four alkanes in this data set, ethane, propane, i‐ and n‐butane had a mean measured mole fraction of 712 ± 22 ppt, 245 ± 13 ppt, …

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On A Remark Of De Gennes Concerning Three-Dimensional Polyelectrolytes, Shiquan Li, Carl Mueller Oct 2026

On A Remark Of De Gennes Concerning Three-Dimensional Polyelectrolytes, Shiquan Li, Carl Mueller

Journal of Stochastic Analysis

This work is inspired by a remark of de Gennes [3] about polyelectrolytes, which are charged polymers. A common model for a polymer is a self-avoiding or self-repelling random walk or Brownian motion. For polyelectrolytes, the repelling potential is the Coulomb potential arising from pairs of charged particles. We show that in the continuous case of a Brownian motion in three dimensions, the spread of the polymer, in particular the radius of gyration of a polyelectrolyte of length T grows linearly with T, up to logarithmic corrections.

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Hidden Thermal Signatures Reveal The Microclimatic Influence Of Scheduled Cave Tourism, Matt Rowberry, John Gunn, Andrew Smith Oct 2026

Hidden Thermal Signatures Reveal The Microclimatic Influence Of Scheduled Cave Tourism, Matt Rowberry, John Gunn, Andrew Smith

International Journal of Speleology

Tourist activity is widely recognised as a source of cave microclimate disturbance, yet visitor-induced variability is difficult to distinguish from natural environmental fluctuations. The coronavirus pandemic created a natural experiment at Poole’s Cavern, United Kingdom, in which periods of complete closure could be compared with contrasting visitor access regimes. Two years of high resolution temperature records from six monitoring points were analysed. Harmonic regression and a state space model removed deterministic diurnal cycles and lower frequency temperature variability. The remaining residual variability differed systematically among visitor access regimes and between daytime and nighttime conditions. Spectral analysis of the residuals identified …

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Stewards Of Data: A Practical Handbook For Undergraduate Researchers In Engineering And Applied Sciences, Şenay Purzer, Wei Zakharov, Carla B. Zoltowski Oct 2026

Stewards Of Data: A Practical Handbook For Undergraduate Researchers In Engineering And Applied Sciences, Şenay Purzer, Wei Zakharov, Carla B. Zoltowski

Purdue University Press Books

Filled with actionable guides and real-world examples, Stewards of Data: A Practical Handbook for Undergraduate Researchers in Engineering and Applied Sciences allows readers to utilize the provided templates and guides almost immediately. In today’s world, data is ubiquitous and AI is growing exponentially. Practicing ethical data management is, therefore, crucial. Ensuring that data is findable, accessible, interoperable, and reusable is essential. This book is an interdisciplinary effort aimed at embedding ethical data life-cycle management education into undergraduate research. The authors present a Data Steward Framework, which serves as a guide for undergraduate researchers, the graduate students who mentor them, postdocs, …

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An Intelligent Sdn-Enabled Framework For Real-Time Ipv6 Ip Spoofing Detection And Prevention, Navaneethan C. Arjuman, Ahmad Fikri Sharudin, Zar Chi Hlaing, Supriyanto Praptodiyono Oct 2026

An Intelligent Sdn-Enabled Framework For Real-Time Ipv6 Ip Spoofing Detection And Prevention, Navaneethan C. Arjuman, Ahmad Fikri Sharudin, Zar Chi Hlaing, Supriyanto Praptodiyono

Journal of Informatics and Web Engineering

With the increase in the adoption of Internet Protocol version 6 (IPv6), the issue of Internet Protocol (IP) spoofing has remained a significant risk that damages the integrity of networks. Although some countermeasures, like Secure Neighbor Discovery (SEND) and Router Advertisement (RA) Guard, are available, these solutions are complex to deploy, consume high resources, and can be bypassed by advanced attacks. This paper provides a critical review of the available IPv6 spoofing prevention methods and proposes an enhanced multi-layered framework that uses improved ingress and egress filtering, Artificial Intelligence (AI)-based anomaly detection, and Software-Defined Networking (SDN) to automatically mitigate threats …

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Mask-Resilient Multi-Biometric Authentication For Healthcare, Caleb Yeo, Siew-Chin Chong, Kian-Ming Lim, Lee-Ying Chong Oct 2026

Mask-Resilient Multi-Biometric Authentication For Healthcare, Caleb Yeo, Siew-Chin Chong, Kian-Ming Lim, Lee-Ying Chong

Journal of Informatics and Web Engineering

The fast integration of digital healthcare platforms, including telemedicine and electronic health records, has created a significant need for secure, contactless authentication methods. Traditional login methods such as passwords and PINs are increasingly insufficient for ensuring the security of sensitive patient data. This paper presents a robust, lightweight Healthcare Authentication System that five biometric modules to address major challenges in facial recognition: spoofing attacks, liveness detection, and facial occlusion due to mask-wearing. The system leverages RetinaFace for face detection, a MobileNetV2 model for mask classification, a lightweight CNN for blink-based liveness verification, and MiniFASNet for spoof detection. For identity matching, …

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Structured Data Preprocessing Techniques For A Multilingual Healthcare Dataset In Machine Learning Applications, Md. Abu Nishan, Choo-Yee Ting, Chih-Yang Pee, Helmi Zakariah, Thanh-Trung Nguyen Oct 2026

Structured Data Preprocessing Techniques For A Multilingual Healthcare Dataset In Machine Learning Applications, Md. Abu Nishan, Choo-Yee Ting, Chih-Yang Pee, Helmi Zakariah, Thanh-Trung Nguyen

Journal of Informatics and Web Engineering

Data preprocessing is a foundational stage in any machine learning (ML) workflow, especially when dealing with complex, multilingual, and real-world healthcare datasets. The quality, consistency, and structure of input data strongly influence the accuracy, fairness, and interpretability of predictive models. This paper presents a comprehensive and structured preprocessing framework designed for a large multilingual healthcare dataset containing 19,536 patient records with 67 features encompassing demographic, clinical, and socioeconomic information. The framework systematically addresses data heterogeneity, linguistic diversity, and structural inconsistencies through multiple stages of cleaning and transformation. The preprocessing process includes translation of Malay text into English to ensure linguistic …

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Comparative Analysis Of Time Series Forecasting Models For Stock Price Prediction: Arima, Lstm, And Prophet, Muhammad Syahid Pebriadi, Tino Kemal Fattah, Putriana Salman, Rizky Amelia Oct 2026

Comparative Analysis Of Time Series Forecasting Models For Stock Price Prediction: Arima, Lstm, And Prophet, Muhammad Syahid Pebriadi, Tino Kemal Fattah, Putriana Salman, Rizky Amelia

Journal of Informatics and Web Engineering

Stock price forecasting with a uniform approach is a challenging process due to nonlinearity, regime changes, and seasonality. The following paper would like to address the practical problem of selecting an appropriate model through comparing three widely used models such as Auto Regressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Prophet based on how they are applied to different attributes of data and forecast-related tasks. The structured direct comparison will be our proposal, as to be able to identify the strengths and shortcomings in abiding by each model. Each of the model is methodologically trained and tested on …

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Haptic Technology In Networked Digital Applications: A Literature Review, Tharanitharan Chandran, Ngu War Hlaing, Athirah Mohd Ramly Oct 2026

Haptic Technology In Networked Digital Applications: A Literature Review, Tharanitharan Chandran, Ngu War Hlaing, Athirah Mohd Ramly

Journal of Informatics and Web Engineering

Haptic-enhanced network applications provide a breakthrough merger of haptic technology with digital environments, allowing for immersive and responsive interactions. In contrast to traditional interfaces that rely primarily on visual and auditory feedback, these applications add tactile sensations, boosting user engagement in domains such as telemedicine, Virtual Reality (VR), Augmented Reality (AR), gaming, and remote collaboration. This study adopts a systematic literature review methodology to identify, filter, and analyse relevant academic sources published between 1998 to 2024, to examine accomplishments, challenges, and future directions of haptic technology in network applications. The study investigates actuator technology, tiny haptic devices, and adaptive algorithms …

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A Comparative Study Of Machine Learning Algorithms For Customer Churn Prediction In Ecommerce, Tan Yi Qi, Lew Sook Ling, Ram Avtar Oct 2026

A Comparative Study Of Machine Learning Algorithms For Customer Churn Prediction In Ecommerce, Tan Yi Qi, Lew Sook Ling, Ram Avtar

Journal of Informatics and Web Engineering

Customer churn rate is one of the main challenges that e-Commerce businesses must address, as it may affect revenue and long-term growth. In this paper, predictive analysis was used to identify potential customers who would be lost. It uses two different types of data to evaluate and compare the performance of five Machine Learning (ML) models, namely logistic regression, decision tree, support vector machine, gradient boost and random forest. Accuracy, precision, recall rate and F1 score are used as indicators of model performance. Among them, random forest achieved the highest performance across both datasets, demonstrating superior predictive power and consistency. …

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Recycle Tracker Application: A Gamified Mobile Platform To Enhance Recycling Behaviour, Yi Han Ng, Pey Yun Goh, Lee Yeng Ong, Kian Ming Lim Oct 2026

Recycle Tracker Application: A Gamified Mobile Platform To Enhance Recycling Behaviour, Yi Han Ng, Pey Yun Goh, Lee Yeng Ong, Kian Ming Lim

Journal of Informatics and Web Engineering

Malaysia's recycling efforts have long been challenged by limited accessibility, low motivation, and insufficient environmental awareness among the public. Despite various national campaigns, recycling participation rates remain inconsistent, highlighting the need for more engaging and user-centred approaches. To address these challenges, this paper presents the Recycle Tracker Application, a gamified mobile solution designed to encourage consistent recycling behaviour and strengthen environmental responsibility among Malaysians. The application integrates multiple core features, including a real-time interactive map of recycling centres, an educational waste-sorting and DIY recycling guide, personalized eco-goal setting, and an innovative Dino Evolution gamification system that rewards users as they …

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Sql Optimization In E-Commerce Platforms Using Large Language Models: A Multi-Pattern Query Empirical Study, Min Ming Lee, Nabhan Salih Oct 2026

Sql Optimization In E-Commerce Platforms Using Large Language Models: A Multi-Pattern Query Empirical Study, Min Ming Lee, Nabhan Salih

Journal of Informatics and Web Engineering

The rapid expansion in e-Commerce domains has presented an unprecedented challenge to database systems that support the execution of complex analytic queries on multi-billion transaction data stream while keeping queries’ response latency under one second. It is commonly observed that Large Language Models (LLMs) are very good at processing natural language queries, rather than struggling with syntax or semantics. This feature is instrumental to various tasks like analytics acceleration, transaction speed-up and handling large workloads across different domains. In this paper, a detailed examination of how LLMs can be employed as intelligent assistants for Structure Query Language (SQL) query optimization …

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Leveraging Meaningful Intrusion Detection Mechanism For Voice Traffic Patterns, Aizam Nazmien Alinoordin, Liana Ameerah Rosli, Sin-Ban Ho, Said Suleiman Naseer Al Harthy, Ian Chai Oct 2026

Leveraging Meaningful Intrusion Detection Mechanism For Voice Traffic Patterns, Aizam Nazmien Alinoordin, Liana Ameerah Rosli, Sin-Ban Ho, Said Suleiman Naseer Al Harthy, Ian Chai

Journal of Informatics and Web Engineering

Voice over IP (VoIP) communication has emerged as an important way of communicating as a modern digital medium but it has been facing a lot of cyber threats because of the protocols involved and the real-time aspect associated with it. conventional Intrusion Detection Systems (IDS) do not cope well with VoIP traffic, as signature-based solutions fail to handle various types of intrusions, while anomaly-based approaches tend to produce a high false positive rate. In this research, a hybrid intrusion detection mechanism is integrated, a lightweight and application-based system built around signature matching and anomaly detection to offer advanced protection to …

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A Web-Based Multi-Modal Ai Framework For Intelligent Content Moderation With Constructive Feedback, Marwah Zaid Mohammed Al-Helali, Naveen Palanichamy, Su-Cheng Haw, Subhashini Gopal Oct 2026

A Web-Based Multi-Modal Ai Framework For Intelligent Content Moderation With Constructive Feedback, Marwah Zaid Mohammed Al-Helali, Naveen Palanichamy, Su-Cheng Haw, Subhashini Gopal

Journal of Informatics and Web Engineering

Traditional content moderation systems primarily rely on strict measures that focus on removing offending or inappropriate content without offering users any form of educational feedback or guidance. This lack of constructive interaction often leads to a poor user experience, leaving users frustrated and uninformed regarding the reasons behind content removal. Moreover, such a system fails to encourage long-term positive behavioural changes within online communities, as users do not gain insights on how to improve their conduct. This paper proposes a new constructive Artificial Intelligence (AI) intervention system that integrates a number of AI models in order to conceptualize content moderation …

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Empirical Evaluation Of Feature Selection Strategies For Interpretable And Robust Healthcare Machine Learning, Md. Abu Nishan, Choo-Yee Ting, Chih-Yang Pee, Helmi Zakariah, Thanh-Trung Nguyen Oct 2026

Empirical Evaluation Of Feature Selection Strategies For Interpretable And Robust Healthcare Machine Learning, Md. Abu Nishan, Choo-Yee Ting, Chih-Yang Pee, Helmi Zakariah, Thanh-Trung Nguyen

Journal of Informatics and Web Engineering

Feature Section (FS) is a fundamental step in developing accurate, robust, and interpretable Machine Learning (ML) models, especially when working with high-dimensional structured datasets commonly found in healthcare, finance, and other dataintensive domains. Selecting the most relevant subset of features not only improves predictive performance but also enhances computational efficiency and model transparency. This paper presents a comprehensive and systematic study of widely adopted feature selection strategies, including filter, wrapper, embedded, model-agnostic methods, and dimensionality reduction techniques. Each category is examined through experimental evaluations across multiple classifiers and benchmark datasets to understand how different feature selection mechanisms affect model performance, …

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Benchmarking Hybrid Learning Models For Personalized Risk Classification And Prediction In Oncology, Tshikutu Bikengela Anaclet, Nkongolo Kenda Simon, Biduaya Symphorien, Mabela Matendo Rostin, Mbuyi Mukendi Eugène Oct 2026

Benchmarking Hybrid Learning Models For Personalized Risk Classification And Prediction In Oncology, Tshikutu Bikengela Anaclet, Nkongolo Kenda Simon, Biduaya Symphorien, Mabela Matendo Rostin, Mbuyi Mukendi Eugène

Journal of Informatics and Web Engineering

In the field of oncology, and specifically regarding prostate cancer, recent breakthroughs in artificial intelligence have opened fascinating possibilities for risk classification and prediction. However, moving from theoretical success to actual clinical practice remains a significant challenge. In this study, we evaluated several architectures (generative, discriminant, and hybrid models) to assess their real-world relevance in the context of longitudinal medical data, which is often noisy or incomplete. Our analysis does not merely measure raw performance; it seeks to understand the critical balance between statistical precision and the interpretability that clinicians require for daily decision-making. By examining the inherent strengths and …

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Next-Gen Fitness: Ai-Based Diet Plans And Real-Time Exercise Monitoring With Gradient Boosting, Gaussian Mixture Models And Mediapipe, I. Kavitha, B. Vanathi, K. Revathi, K. Sanjaikumar Oct 2026

Next-Gen Fitness: Ai-Based Diet Plans And Real-Time Exercise Monitoring With Gradient Boosting, Gaussian Mixture Models And Mediapipe, I. Kavitha, B. Vanathi, K. Revathi, K. Sanjaikumar

Journal of Informatics and Web Engineering

Global shifts toward sedentary habits and refined dietary choices are magnifying public-health pressures from obesity, metabolic dysregulation, and cardiovascular disease, positioning targeted, personalized fitness coaching tools at the forefront of preventive-care strategy. By embedding tailored nutritional and physical-activity plans into daily life, these tools reinforce adherence, enhance intrinsic motivation, and catalyze sustained wellness achievements—each moderated by real-time analytics, feedback loops, and progressive adaptation to evolving behavior and physiology. Their leading benefits include prolonged engagement, diminished risk of relapse, and deep integration of healthful routines, culminating in lowered lifetime healthcare costs and improved individual life satisfaction. Current machine-learning approaches deliver commendable …

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