Three-dimensional linkage analysis with digital PCR for genome integrity and identity of recombinant adeno-associated virus by Tam Duong, Michele Firmo, Chien-Ting Li, Bingnan Gu, Peng Wang

“…This cost-effective approach, akin to the setup of traditional 1D or 2D dPCR, holds the potential to advance the application of rAAV in cell and gene therapy for the treatment of human diseases.…”
Get full text

Detection of soluble solid content in table grapes during storage based on visible-near-infrared spectroscopy by Yuan Su, Ke He, Wenzheng Liu, Jin Li, Keying Hou, Shengyun Lv, Xiaowei He

“…The soluble solid content (SSC) in grapes significantly influences their flavour and plays an integral role in evaluation of the quality and consumer acceptance. This study employed visible near-infrared (Vis-NIR) spectroscopy to rapidly quantify SSC in table grapes during storage. …”
Get full text

The role of artificial intelligence in occupational health in radiation exposure: a scoping review of the literature by Zohreh Fazli, Mehran Sadeghi, Mohebat Vali, Parvin Ahmadinejad

“…The quality of the included studies was evaluated using the MMAT critical appraisal tool. …”
Get full text

Research on new energy power plant network traffic anomaly detection method based on EMD by Danni Liu, Shengda Wang, YutongLi, Ji Du, Jia Li

“…Methodology This research propose Network Quality Assessment (NQA) traffic management algorithms to prevent illegal access and data breaches, this involves strong security measures such as encryption, firewalls, and encrypted communication methods. …”
Get full text

Machine Learning Approaches for Software Defect Prediction by Hijab Zehra Zaidi, Ubaid Ullah, Muddassira Arshad, Hanan Aljuaid, Muhammad Arslan Rauf, Nadeem Sarwar, Rimsha Sajid

“…This paper analyses existing research about machine learning approaches in software defect prediction as a key element for improving software reliability and quality. The paper reviews the use of machine learning algorithms in software defect prediction framework’s bug prediction while assessing their performance across multiple environments. …”
Get full text

A review of machine learning and deep learning for Parkinson’s disease detection by Hajar Rabie, Moulay A. Akhloufi

“…We discuss the preprocessing methods applied, the state-of-the-art models utilized, and their performance. Our evaluation included different algorithms such as support vector machines (SVM), random forests (RF), convolutional neural networks (CNN). …”
Get full text

Dung beetle optimizer based on mean fitness distance balance and multi-strategy fusion for solving practical engineering problems by Wanru Tang, Haoze Qin, Shuang Kang

“…To comprehensively evaluate the optimizer performance of MMDBO, experiments were conducted on the IEEE CEC2017 and CEC2022 benchmark sets, comparing it with 13 other population-based optimizer algorithms. …”
Get full text

Framelet transform based edge detection for straight line detection from remote sensing images by Vidhya Rangasamy, Sulochana Subramaniam

“…Rosenfeld evaluation metric is used to measure the quality of the edge detection methods, which shows the framelet based edge detection produce sound results than other methods. …”
Get full text

Combining Kronecker-Basis-Representation Tensor Decomposition and Total Variational Constraint for Spectral Computed Tomography Reconstruction by Xuru Li, Kun Wang, Yan Chang, Yaqin Wu, Jing Liu

“…The proposed objective minimization model has been tackled using the split-Bregman algorithm. To evaluate the algorithm’s performance, both numerical simulations and realistic preclinical mouse studies were conducted. …”
Get full text

A Swarm-Based Multi-Objective Framework for Lightweight and Real-Time IoT Intrusion Detection by Hessah A. Alsalamah, Walaa N. Ismail

“…Internet of Things (IoT) applications and services have transformed the way people interact with their environment, enhancing comfort and quality of life. …”
Get full text

Artificial intelligence-assisted capsule endoscopy for detecting lesions in Crohn’s disease: a systematic review and meta-analysis by Yuling Bin, Rumei Peng, Yaqian Lee, Zhijie Lee, Yang Liu

“…However, given the limitations and heterogeneity of current research, more high-quality, large-sample studies are needed to comprehensively and thoroughly evaluate the practical application value of AI in CD diagnosis, thereby promoting its widespread adoption and optimization in clinical practice.…”
Get full text

A novel prediction model for the prognosis of non-small cell lung cancer with clinical routine laboratory indicators: a machine learning approach by Yuli Wang, Na Mei, Ziyi Zhou, Yuan Fang, Jiacheng Lin, Fanchen Zhao, Zhihong Fang, Yan Li

“…Finally, critical variables in the optimal model were screened based on the interpretable algorithms to build a decision tree to facilitate clinical application. …”
Get full text

Advanced control parameter optimization in DC motors and liquid level systems by Serdar Ekinci, Davut Izci, Mohammad H. Almomani, Kashif Saleem, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Absalom E. Ezugwu, Laith Abualigah

“…Furthermore, a new performance indicator, ZLG, is introduced to comprehensively evaluate control quality. The MGO-based approach consistently achieves lower ZLG values, showcasing its adaptability and robustness in dynamic system control and parameter optimization. …”
Get full text

Advancing soil mapping and management using geostatistics and integrated machine learning and remote sensing techniques: a synoptic review by Sunshine A. De Caires, Chaney St Martin, Melissa A. Atwell, Fuat Kaya, Glorious A. Wuddivira, Mark N. Wuddivira

“…Hybrid approaches combining geostatistics with ML algorithms (e.g., RF, Boost, SVM, ANN) demonstrate promise in addressing spatial uncertainty, while RS data enhances covariate enrichment and near-real-time applications. …”
Get full text

A Machine Learning Dataset of Artificial Inner Ring Damage on Cylindrical Roller Bearings Measured Under Varying Cross-Influences by Christopher Schnur, Payman Goodarzi, Yannick Robin, Julian Schauer, Andreas Schütze

“…In practical machine learning (ML) applications, covariate shifts and dependencies can significantly impact model robustness and prediction quality, leading to performance degradation under distribution shifts. …”
Get full text

Recommendation system for billing offers in retail business CRM of a lending agency by Alexander A. Kovalev, A.V. Mezhuev

“…The current state of research in recommender systems and their application in the financial domain is analyzed. The architecture and algorithms for developing of this system are proposed, taking into account the specifics of banking data and business processes. …”
Get full text

Neuropathic pain: proposal of a mechanism-based treatment by Laura Demartini, Cesare Bonezzi

“…Some authors have suggested that the poor results in the treatment of neuropathic pain may be related to the different mechanisms present in each patient and have tried to correlate them with clinical characteristics in order to evaluate possible targeted treatments. This approach has been used in some studies evaluating the response to specific pharmacotherapies in clusters of patients, with encouraging results but still limited applicability to clinical practice. …”
Get full text

RGB-to-Infrared Translation Using Ensemble Learning Applied to Driving Scenarios by Leonardo Ravaglia, Roberto Longo, Kaili Wang, David Van Hamme, Julie Moeyersoms, Ben Stoffelen, Tom De Schepper

“…Our synthetic images exhibit good visual quality when evaluated using metrics such as <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula>, PSNR, SSIM, and LPIPS, achieving an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> of 0.98 on the MS2 dataset and a PSNR of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>21.3</mn></mrow></semantics></math></inline-formula> dB on the Freiburg dataset. …”
Get full text

A comprehensive review on the integration of artificial intelligence in friction stir welding for monitoring, modelling, and process optimization by Mostafa Akbari, Ezatollah Hassanzadeh, Yaghuob Dadgar Asl, Amirhossein Moghanian

“…This functionality allows for immediate parameter adjustments, thus significantly improving weld consistency and quality by minimizing defects. Lastly, the third section pertains to the optimization of FSW parameters, illustrating how AI-driven algorithms analyze complex interactions among multiple variables to determine the most effective process settings. …”
Get full text

Preference learning based deep reinforcement learning for flexible job shop scheduling problem by Xinning Liu, Li Han, Ling Kang, Jiannan Liu, Huadong Miao

“…Abstract The flexible job shop scheduling problem (FJSP) holds significant importance in both theoretical research and practical applications. Given the complexity and diversity of FJSP, improving the generalization and quality of scheduling methods has become a hot topic of interest in both industry and academia. …”
Get full text