Cyber Security Intrusion Detection Using a Deep Learning Method by Basheer Ullah, Shafiq-ur-Rehman Massan, M. Abdul Rehman, Rabia Ali Khan

“…The new techniques of deep learning are poised to succeed for detecting intrusion by employing different algorithms of detection and prevention. This paper proposes a deep neural network (DNN) for intrusion detection by the use of Kaggle NLS-KDD dataset with the highest attained accuracy of 92%. …”
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Biomimic models for in vitro glycemic index: Scope of sensor integration and artificial intelligence by Mohammed Salman C K, Muskan Beura, Archana Singh, Anil Dahuja, Vinayak B. Kamble, Rajendra P. Shukla, Sijo Joseph Thandapilly, Veda Krishnan

“…Non-enzymatic sensors offer superior stability and repeatability in complex matrices, enabling real-time glucose quantification across multiple timepoints without enzyme degradation constraints. Machine learning algorithms, both supervised and unsupervised, enhance predictive accuracy by elucidating complex relationships within digestion data. …”
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Integration of clinical, pathological, radiological, and transcriptomic data improves prediction for first-line immunotherapy outcome in metastatic non-small cell lung cancer by Nicolas Captier, Marvin Lerousseau, Fanny Orlhac, Narinée Hovhannisyan-Baghdasarian, Marie Luporsi, Erwin Woff, Sarah Lagha, Paulette Salamoun Feghali, Christine Lonjou, Clément Beaulaton, Andrei Zinovyev, Hélène Salmon, Thomas Walter, Irène Buvat, Nicolas Girard, Emmanuel Barillot

“…In this study, we explore the benefits of multimodal approaches to predict immunotherapy outcome using multiple machine learning algorithms and integration strategies. We analyze baseline multimodal data from a cohort of 317 metastatic NSCLC patients treated with first-line immunotherapy, including positron emission tomography images, digitized pathological slides, bulk transcriptomic profiles, and clinical information. …”
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Functional protein mining with conformal guarantees by Ron S. Boger, Seyone Chithrananda, Anastasios N. Angelopoulos, Peter H. Yoon, Michael I. Jordan, Jennifer A. Doudna

“…Our method (1) lets users select many biologically-relevant loss metrics (i.e. false discovery rate) and assigns reliable functional probabilities for annotating genes of unknown function; (2) achieves state-of-the-art performance in enzyme classification without training new models; and (3) robustly and rapidly pre-filters proteins for computationally intensive structural alignment algorithms. Our framework enhances the reliability of protein homology detection and enables the discovery of uncharacterized proteins with likely desirable functional properties.…”
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ImageDoubler: image-based doublet identification in single-cell sequencing by Kaiwen Deng, Xinya Xu, Manqi Zhou, Hongyang Li, Evan T. Keller, Gregory Shelley, Annie Lu, Lana Garmire, Yuanfang Guan

“…This advancement highlights the potential of using imaging to glean insight into developing doublet detection algorithms and exposes the limitations inherent in current genomic-based techniques.…”
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A fault diagnosis method for rolling bearing based on gram matrix and multiscale convolutional neural network by Xinyan Zhang, Shaobin Cai, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…In the last few years, there have been significant advances in the algorithms for intelligent fault diagnosis of bearings. …”
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Smart HVAC Control in IoT: Energy Consumption Minimization with User Comfort Constraints by Jordi Serra, David Pubill, Angelos Antonopoulos, Christos Verikoukis

“…In particular, the user may decide remotely the temperature of comfort, while the temperature and energy consumption information is sent through Internet and displayed at the end user’s device. The proposed algorithms have been implemented in a real testbed, highlighting the potential gains that can be achieved in terms of both energy and cost.…”
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Bus Priority Signal Control Considering Delays of Passengers and Pedestrians of Adjacent Intersections by Jiali Li, Yugang Liu, Hongtai Yang, Bin Chen

“…Secondly, models with the goal of maximizing the reduced total delays are established. Thirdly, three algorithms are used to solve the problem to obtain the optimal signal timing adjustment scheme at upstream intersections. …”
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Intelligent Sensor for Measurement Systems with Sinusoidal Excitation Response by U. A. Mikitsevich, A. I. Svistun, A. V. Samarina, K. U. Pantsialeyeu, A. L. Zharin

“…The aim of the work was to develop the optimal architecture and algorithms for the operation of intelligent sensors intended for use in measuring systems operating according to the sinusoidal excitation – response scheme.This paper describes the approach proposed by the authors to the construction of intelligent sensors based on modern microcontrollers, the distinctive feature of which is the continuous generation of sinusoidal excitation and reading responses in the background, as well as setting the readiness flags for data processing in the main process of the microprocessor, which ensures uninterrupted execution of background processes, the main of which is the generation of a sinusoidal excitatory action.This approach has been tested in the development of charge-sensitive surface mapping systems, such as the Kelvin probe based on a vibrating capacitor, and the surface photo voltage probe for the case of semiconductors.…”
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Artificial intelligence in kidney transplantation: a 30-year bibliometric analysis of research trends, innovations, and future directions by Ying Jia He, Pin Lin Liu, Tao Wei, Tao Liu, Yi Fei Li, Jing Yang, Wen Xing Fan

“…Key research themes include AI-driven advancements in donor matching, deep learning for post-transplant monitoring, and machine learning algorithms for personalized immunosuppressive therapies. …”
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A Survey of Deep Learning Techniques for Arabic Aspect-Based Sentiment Analysis by Dalal Alqusair, Mounira Taileb, and Hassanin Al-Barhamtoshy

“…In addition to ascertaining potential future directions that would encourage researchers to contribute to Arabic ABSA studies and generate more effective algorithms.…”
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Low-threshold dual-polarization electro-optic nonlinear activation functions by Tao Jin, Jian Lin, Pengjun Wang, Qiang Fu, Yuhan Sun, Yi Zou, Shixun Dai, Weiwei Chen, Jun Li, Tingge Dai, Jianyi Yang

“…This scheme relies on a structure composed of an optical power splitter and a thermo-optic modulator based on Mach–Zehnder interferometer, which are optimized by using direct binary search and particle swarm optimization algorithms. When a fixed proportion of the input optical signal is transformed into the electrical signal and the remaining input optical signal is modulated by using the thermo-optic effect, the rectified linear unit activation function with a low-threshold power of 0.2 mW for transverse-electric polarization and the Gaussian activation function with a low-threshold power of 0.1 mW for transverse-magnetic polarization can be measured separately. …”
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Automating airborne pollen classification: Identifying and interpreting hard samples for classifiers by Manuel Milling, Simon D.N. Rampp, Andreas Triantafyllopoulos, Maria P. Plaza, Jens O. Brunner, Claudia Traidl-Hoffmann, Björn W. Schuller, Athanasios Damialis

“…To shed some light on this issue, we conducted a sample-level difficulty analysis based on the likelihood for one of the largest automatically-generated datasets of pollen grains on microscopy images and investigated the reason for which certain airborne samples and specific pollen taxa pose particular problems to deep learning algorithms. It is here concluded that the main challenges lie in A) the (partly) co-occurring of multiple pollen grains in a single image, B) the occlusion of specific markers through the 2D capturing of microscopy images, and C) for some taxa, a general lack of salient, unique features. …”
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Deep learning based gasket fault detection: a CNN approach by S. Arumai Shiney, R. Seetharaman, V. J. Sharmila, S. Prathiba

“…The suggested method uses deep learning approaches to recognize and evaluate radiator images, with a focus on identifying misaligned or incorrectly installed gaskets. Deep learning algorithms are specific for feature extraction and classification together with a convolutional neural network (CNN) module that allows for seamless connection. …”
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Impact of facial tattoos and paintings on face recognition systems by Mathias Ibsen, Christian Rathgeb, Thomas Fink, Pawel Drozdowski, Christoph Busch

“…The authors’ work is an initial case study and indicates a need to design algorithms which are robust to the visual changes caused by facial tattoos and paintings.…”
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Compensation of Linear Multiscale Doppler for OFDM-Based Underwater Acoustic Communication Systems by A. E. Abdelkareem, B. S. Sharif, C. C. Tsimenidis, J. A. Neasham

“…Based on this fine-tuned timing synchronization, an extension to the improved receiver is presented to assess the performance of two point correlations. The proposed algorithms' performances were investigated using real data obtained from an experiment that took place in the North Sea in 2009.…”
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Research Progress on the Application of Near Infrared Spectroscopy in Cereal Detection by WANG Zixi, SHEN Qun, ZHAO Qingyu

“…This paper aims to review the current status of the application of near infrared spectroscopy in the detection of cereals nutrients (starch, fat, protein and bioactive compounds), physicochemical properties (starch viscosity, hardness and farinograph parameters), mold contamination and other aspects (freshness, variety identification, heavy metals and pesticide residues), summarize and compare the advantages and disadvantages of common model algorithms, and propose some problems and future trends in the application of near infrared spectroscopy in cereal detection, in order to provide a reference for further improvement of near infrared spectroscopy in the detection of cereals.…”
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QCA: Quantum Computational Approach for Internet of Things with 5G Connectivity by Shitharth Selvarajan, Hariprasath Manoharan, Adil O. Khadidos, Alaa O. Khadidos

“…Hence, in the proposed method, quantum information processing protocols and quantum algorithms are integrated where data transmissions are maximized. …”
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Generative Elastic Networks (GENs) and Application on Classification of Single-Lead Electrocardiogram by Nan Xiao, Kun Zhao, Hao Zhang

“…This paper proposes a white-box model named Generative Elastic Network (GEN) and the algorithms for training, validation, and testing, featuring inherent interpretability in its computational process and network architecture. …”
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Custom YOLO Object Detection Model for COVID-19 Diagnosis by Noor Najah Ali, Aseel Hameed, Asanka G. Perera, Ali Al_Naji

“…Clinical staff can benefit from Computer Aided Diagnostics (CAD) systems that combine deep learning algorithms and image processing technologies as diagnostic tools for COVID-19. …”
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