Integrating Machine Learning and IoT for Effective Plant Disease Management by Bhoi Manjulata, Dubey Ahilya

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Enhancing DDoS Attack Classification through SDN and Machine Learning: A Feature Ranking Analysis by Aymen AlAwadi, Kawthar Rasoul ALesawi

“…Machine learning (ML) offers a promising way for early DDoS attack detection due to its ability to analyze large datasets and identify patterns. However, adding too many features to the ML might reduce its effectiveness in identifying the attacks provided by central network paradigms such as the Software-Defined Network (SDN). …”
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Prescribing the Future: The Role of Artificial Intelligence in Pharmacy by Hesham Allam

“…Systematic data scoping incorporated diverse perspectives from medical, pharmaceutical, and computer science domains, leveraging natural language processing for trend analysis and thematic content coding to identify patterns, challenges, and emerging applications. Modern visualization tools synthesized the findings into explicit graphical representations, offering a comprehensive view of the key role of AI in shaping the future of pharmacy and healthcare.…”
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Application of artificial intelligence technologies in HR management by S. V. Okladnikova, A. S. Pankrashov

“…Within the framework of the conducted research, the historical patterns that led the field of personnel management to transformation and which made the use of AI technologies relevant in this area were considered. …”
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South-Oriented PV Trackers: A Solution for Tree Plantations? by Jean-Baptiste Pasquier, Jules Chéron, Farida Amichi

“…Using a modelling framework and meteorological data from Aix-en-Provence, France, we demonstrate that N-S trackers create distinct shading patterns on the ground that shift throughout the year due to varying solar zenith angles. …”
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Dataset creation of thermal images of pomegranate for internal defect detectionMendeley Data by Ashvini Gaikwad, Manoj Deshpande, Varsha Bhole

“…A model learns patterns and relationships from the data it is exposed to. …”
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Predicting Alzheimer's Disease onset: A machine learning framework for early diagnosis using biomarker data by Shehu Mohammed, Neha Malhotra

“…The importance of this work is in the opportunity to shift diagnostic paradigms by employing deep learning algorithms, including CNNs, LSTM networks, and GNNs to analyze spatial, temporal, and relational patterns across multi-modal data. …”
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Validating a smart bed against polysomnography for sleep apnea detection by Farzad Siyahjani, Kostiantyn Kalenyk, Gary Garcia-Molina, Saeed Babaeizadeh

“…Visual inspection of signals during apnea episodes, particularly those related to CSA, confirmed the algorithm’s capability to capture meaningful physiological patterns. …”
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Restoring flowcell type and basecaller configuration from FASTQ files of nanopore sequencing data by Jun Mencius, Wenjun Chen, Youqi Zheng, Tingyi An, Yongguo Yu, Kun Sun, Huijuan Feng, Zhixing Feng

“…While these data hold immense potential for advancing genomic research, their utility is compromised by the absence of flowcell type and basecaller configuration in about 85% of the data and associated publications. …”
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Classification Model for Bot-IoT Attack Detection Using Correlation and Analysis of Variance by Firgiawan Faira, Dandy Pramana Hostiadi

“…Industry 4.0 requires secure networks as the advancements in IoT and AI exacerbate the challenges and vulnerabilities in data security. This research focuses on detecting Bot-IoT activity using the Bot-IoT UNSW Canberra 2018 dataset. …”
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Clinical Characterization of Patients with Syncope of Unclear Cause Using Unsupervised Machine-Learning Tools: A Pilot Study by María-José Muñoz-Martínez, Manuel Casal-Guisande, María Torres-Durán, Bernardo Sopeña, Alberto Fernández-Villar

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Analyzing the performance of biomedical time-series segmentation with electrophysiology data by Richard Redina, Jakub Hejc, Marina Filipenska, Zdenek Starek

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Melanoma Skin Lesion Classification Using Neural Networks: A systematic review by ahmed hammo, Mohammed Younis

“…Given neural networks' evolutionary patterns, updated, changed, and integrated networks are expected to increase the performance of such systems. …”
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Development of an Optimal Machine Learning Model to Predict CO₂ Emissions at the Building Demolition Stage by Gi-Wook Cha, Choon-Wook Park

“…The GBM model also showed excellent results in generalization performance, and it effectively learned the data patterns without overfitting in residual analysis and mean absolute error (MAE) evaluation. …”
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Utilization of Deep Learning YOLO V9 for Identification and Classification of Toraja Buffalo Breeds by Abdul Rachman Manga', Herawati Herawati, Purnawansyah Purnawansyah

“…This system can assist in maintaining the accuracy and consistency of buffalo classification according to local customs. Future research is recommended to explore broader datasets, compare alternative object detection algorithms, and develop an integrated application for practical field use.…”
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Predicting the prognosis of patients with sudden sensorineural hearing loss by analyzing the audiometric curve of the unaffected ear by Xuan Sun, Yahan Zhao, Yi Li

“…Utilizing Python, the research team conducts a cluster analysis on the 229 patients’ audiometric characteristics and trains the clustering results into an algorithm model. …”
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The Convergence of AI and animal-inspired robots for ecological conservation by Naqash Afzal, Mobeen ur Rehman, Lakmal Seneviratne, Irfan Hussain

“…By harnessing the capabilities of AI-driven animal robots, researchers can gain a multifaceted toolkit to explore and understand the behaviors, communication patterns, and ecological roles of various species. …”
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Vibration Signal Forecasting on Rotating Machinery by means of Signal Decomposition and Neurofuzzy Modeling by Daniel Zurita-Millán, Miguel Delgado-Prieto, Juan José Saucedo-Dorantes, Jesus Adolfo Cariño-Corrales, Roque A. Osornio-Rios, Juan Antonio Ortega-Redondo, Rene de J. Romero-Troncoso

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Public Perceptions of Ethical Challenges and Opportunities for Enterprises in the Digital Age by Ahmad Mansour, Khaled Alshaketheep, Hind Al-Ahmed, Ahmad Shajrawi, Arafat Deeb

“…The quantitative analysis methods used in this study encompassed descriptive statistical analysis, inferential statistical analysis, correlation analysis, hypothesis testing, and regression analysis to establish patterns of relationships.  Results: The leading ethical issues for participants were: personal data protection (mean score = 4.2), ethical usage of AI algorithms (mean score = 3.9), job displacement due to AI technology (mean score = 3.1), and the digital divide. …”
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Optimizing solar maximum power point tracking with adaptive PSO: A comparative analysis of inertia weight and acceleration coefficient strategies by Denesh Sooriamoorthy, Aaruththiran Manoharan, Siva Kumar Sivanesan, Soon Kian Lun, Alexander Chee Hon Cheong, Sathish Kumar Selva Perumal

“…The individual and combined performance of adaptive w, c1 and c2 are evaluated, especially with small and narrow w operational range studied as it contributes to high convergence, especially under fast-changing shading patterns. The results demonstrate that linear adaptive w combined with trigonometric adaptive c1 and c2 consistently achieves high tracking accuracy (99.4%) with minimal steady-state oscillations and faster convergence times (average 0.0642 s), outperforming conventional PSO and P&O algorithms. …”
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