Neighbor Similarity Based Agglomerative Method for Community Detection in Networks by Jianjun Cheng, Xing Su, Haijuan Yang, Longjie Li, Jingming Zhang, Shiyan Zhao, Xiaoyun Chen

“…The results show that the proposed method can detect high-quality community structures from networks steadily and efficiently and outperform the comparison algorithms significantly.…”
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A hybrid super learner ensemble for phishing detection on mobile devices by Routhu Srinivasa Rao, Cheemaladinne Kondaiah, Alwyn Roshan Pais, Bumshik Lee

“…Phish-Jam utilizes a super learner ensemble that combines predictions from diverse Machine Learning (ML) algorithms to classify legitimate and phishing websites. …”
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A Comprehensive Review on Sensor-Based Electronic Nose for Food Quality and Safety by Teodora Sanislav, George D. Mois, Sherali Zeadally, Silviu Folea, Tudor C. Radoni, Ebtesam A. Al-Suhaimi

“…This has led to the emergence of many research works that focus on automating and streamlining the assessment of food quality. …”
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Challenges and opportunities for precision livestock farming applications in the rabbit production sector by Tomás Norton, María Cambra-López

“…Precision livestock farming (PLF) is an established field in many livestock sectors. However, when it comes to rabbit production, it is still emerging. …”
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Dengue Contingency Planning: From Research to Policy and Practice. by Silvia Runge-Ranzinger, Axel Kroeger, Piero Olliaro, Philip J McCall, Gustavo Sánchez Tejeda, Linda S Lloyd, Lokman Hakim, Leigh R Bowman, Olaf Horstick, Giovanini Coelho

“…<h4>Background</h4>Dengue is an increasingly incident disease across many parts of the world. In response, an evidence-based handbook to translate research into policy and practice was developed. …”
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Geographical Peer Matching for P2P Energy Sharing by Romaric Duvignau, Vincenzo Gulisano, Marina Papatriantafilou, Ralf Klasing

“…Our experimental study, based on real-world energy data, demonstrates that our proposed solutions are efficient both in terms of cost savings achieved by the peers and in terms of communication and computing requirements. Our scalable algorithms thus provide one core building block for practical and data-efficient peer-to-peer energy sharing communities within large-scale optimization systems.…”
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GDDKIA xml service, road traffic incidents data: availability and quality research by Natalia Dziuba, Stanisław Szombara

“…To improve accuracy, additional algorithms were applied that automatically corrected the position of the points to match the nearest roads. …”
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Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review by Dhekre Saber Saleh, Mohd Shahizan Othman

“…By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. …”
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Optimizing microgrid performance a multi-objective strategy for integrated energy management with hybrid sources and demand response by Mohsen Moosavi, Javad Olamaei, Hossein Mohmmadnezhad Shourkaei

“…When compared to leading optimization algorithms, the proposed approach showed better performance. …”
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TS-PAID: A Two-Stage PUF-Based Lightweight Authentication Protocol for Internet of Drones by Shehzad Ashraf Chaudhry, Azeem Irshad, Bander A. Alzahrani, Ahmad Alhindi, Mohd Shariq, Ashok Kumar Das

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Comprehensive evaluation of machine learning models for predicting the cognitive status of Alzheimer's disease subjects and susceptible by Lucien Gnegne Meteumba, Vaghawan Prasad Ojha, Shantia Yarahmadian

“…The data we use is provided by the National Alzheimer’s Coordinating Center (NACC) and contain many clinical and demographic predictors by which we characterize and model the cognitive status of the subjects. …”
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The invariance of current energy fourier spectrum of discrete real signals on finite intervals by V. A. Ponomarev, O. V. Ponomareva

“…The paper deals with the problems of measuring Fourier spectrum of signals in the base of discrete exponential functions. Methods and algorithms of sliding measurements of energy Fourier spectrum of signals on finite intervals were described. …”
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Hankel Tensor Subspace Representation for Remotely Sensed Image Fusion by Fei Ma, Qiang Qu, Feixia Yang, Guangxian Xu

“…As an illposed inverse problem, however, current multisensor data fusion faces many challenges. Exactly, traditional matrix-factorization-based algorithms often result in the loss of cubic structure knowledge in hyperspectral data, while deep neural networks are susceptible to noise accumulation and lack of large-scale labeled data. …”
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Advanced Multiplier Architecture Optimization for Accelerated Arithmetic Operations and its Integration in Wireless Sensor Network Applications by Nirmal Kumar R., Valarmathi R. S., Kalamani M.

“…Wireless sensor networks (WSNs) are becoming more valuable in environmental monitoring and industrial automation. Many WSN applications need high-performance adders and multipliers for efficient computation. …”
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Intrusion Detection System Framework for SDN-Based IoT Networks Using Deep Learning Approaches With XAI-Based Feature Selection Techniques and Domain-Constrained Features by Manlaibaatar Tserenkhuu, Md Delwar Hossain, Yuzo Taenaka, Youki Kadobayashi

“…The proliferation of Internet of Things (IoT) applications impact many aspects of life, including smart homes, smart offices, and smart cities, among others. …”
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Performance Estimation of Low Power and Area-Efficient Parallel Pipelined FFT by Surya P, Arunachalaperumal C, Dhilipkumar S

“…It is also used in image and video processing and is critical for algorithms that manipulate pixels, scale, and compress data when many multiplications need to be performed quickly. …”
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Optimising laboratory monitoring of chronic conditions in primary care: a quality improvement framework by Alex J Walker, Richard Croker, Jessica Watson, Andy Brogan, Darunee Whiting, Tom Lewis

“…The main difference from previous general practitioner practice algorithms was removing the requirement for full blood count and liver function test monitoring for many conditions. …”
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Enhancing Unmanned Aerial Vehicle Object Detection via Tensor Decompositions and Positive–Negative Momentum Optimizers by Ruslan Abdulkadirov, Pavel Lyakhov, Denis Butusov, Nikolay Nagornov, Dmitry Reznikov, Anatoly Bobrov, Diana Kalita

“…The current development of machine learning has advanced many fields in applied sciences and industry, including remote sensing. …”
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Significance of Chest Computed Tomography Scan Findings at Time of Diagnosis in Patients with COVID-19 Pneumonia by Rajaa Suhail Najim, Ahmed Diaa Abdulwahab, Dina Nasih Tawfeeq

“…Various CT algorithms including CT scoring system were used to assess quantitively and qualitatively the severity of COVID-19 pneumonia. …”
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Data augmentation of time-series data in human movement biomechanics: A scoping review. by Christina Halmich, Lucas Höschler, Christoph Schranz, Christian Borgelt

“…However, the field faces challenges such as limited large-scale data sets, high data acquisition costs, and restricted participant access that hinder the development of robust algorithms. Additional issues include variability in sensor placement, soft tissue artifacts, and low diversity in movement patterns. …”
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