This review examines aerodynamic drag reduction strategies for road vehicles, integrating insights from both experimental investigations and numerical simulations...
This study experimentally investigates a novel jacketed shell-and-tube heat exchanger integrating phase change cold storage and condensation heat transfer. Using...
Light governs strawberry's entire life cycle through intensity, photoperiod, and spectrum. This cover illustrates how light signals orchestrate key phases from...
Tech Science Press is pleased to announce that two additional journals have been selected for inclusion in CAB Abstracts, a leading database produced by CAB International (CABI). This milestone...
Gratitude, Growth, and Global Engagement The Canadian Journal of Urology (CJU) is pleased to share its 2025 annual highlights. Over the past year, the journal has maintained steady growth,...
This study aims to mitigate crosswind-induced performance degradation in Natural Draft Dry Cooling Towers used in power plants by developing and assessing...
Fluid flow through fractured rock masses is a key process controlling the safety and performance of deep geoengineering systems, shaped by the complex...
Aerodynamic research on road cars was reviewed in this work under the thread of reducing drag, with the awareness that this may succeed in effectively...
In response to the actual demands of the energy storage type organic Rankine power generation cycle, this study proposes a new type of jacketed shell...
Heat exchangers play a crucial role in thermal energy systems, with their performance directly impacting efficiency, cost, and environmental impact. A...
Objective: Current research highlights periodontal disease as a systemic inflammatory condition that may influence extra-oral diseases such as prostatic...
Discussions about the future of energy sources and environmental sustainability are becoming critical on a global scale. The energy sector plays a central...
The increasing integration of electric vehicle (EV) loads into power systems necessitates understanding their impact on stability. Small-magnitude perturbations,...
Objectives: Loneliness among left-behind adolescents is the most frequently reported emotional problem because of parental neglect. The present study...
The development of sustainable materials has encouraged the use of biopolymers as alternatives to synthetic polymers. Polymeric films have stood out for...
As attack techniques evolve and data volumes increase, the integration of artificial intelligence-based security solutions into industrial control systems...
This paper examines a model that combines vortex generators and leading-edge tubercles for controlling the laminar separation bubble (LSB) over an airfoil...
Skin cancer remains the most commonly diagnosed malignancy worldwide, with basal cell carcinoma (BCC), cutaneous squamous cell carcinoma (cSCC), and melanoma...
Classical Hodgkin lymphoma (cHL) is characterized by rare Hodgkin/Reed-Sternberg (HRS) tumor cells that uniformly express cluster of differentiation (CD)30...
Quantitative analysis of aluminum-silicon (Al-Si) alloy microstructure is crucial for evaluating and controlling alloy performance. Conventional analysis...
Internet of Things (IoTs) devices are bringing about a revolutionary change our society by enabling connectivity regardless of time and location. However,...
Cancer remains one of the leading causes of morbidity and mortality worldwide, and its onset and progression are closely linked to dysregulated epigenetic...
We propose a special issue titled "Innovative Smart Polymeric Materials for Sustainable Energy Solutions: Bridging Advances in Energy and Biomedical...
Further advancements in the exploitation of unconventional resources, such as tight gas, shale gas, shale oil, coalbed methane, and natural gas hydrate,...
In today’s digital era, patterns are omnipresent, shaping many aspects of our lives. These patterns can be physically observed or computationally identified...
This special issue, “Applied Artificial Intelligence: Advanced Solutions for Engineering Real-World Challenges,” showcases the transformative power of...
This theme captures the essence of advanced technologies (AI, machine learning, big data), modern applications (climate change, smart cities, health research),...
The tumor microenvironment encompasses not only the tumor cells themselves, but also the surrounding fibroblasts, immunological and inflammatory cells,...
This special issue seeks original research and review articles on the roles of γδ T cells and invariant natural killer T (iNKT) cells in malignancies....
This study aims to mitigate crosswind-induced performance degradation in Natural Draft Dry Cooling Towers used in power plants by developing and assessing...
Fluid flow through fractured rock masses is a key process controlling the safety and performance of deep geoengineering systems, shaped by the complex...
Aerodynamic research on road cars was reviewed in this work under the thread of reducing drag, with the awareness that this may succeed in effectively...
In response to the actual demands of the energy storage type organic Rankine power generation cycle, this study proposes a new type of jacketed shell...
Heat exchangers play a crucial role in thermal energy systems, with their performance directly impacting efficiency, cost, and environmental impact. A...
Objective: Current research highlights periodontal disease as a systemic inflammatory condition that may influence extra-oral diseases such as prostatic...
Discussions about the future of energy sources and environmental sustainability are becoming critical on a global scale. The energy sector plays a central...
The increasing integration of electric vehicle (EV) loads into power systems necessitates understanding their impact on stability. Small-magnitude perturbations,...
Objectives: Loneliness among left-behind adolescents is the most frequently reported emotional problem because of parental neglect. The present study...
The development of sustainable materials has encouraged the use of biopolymers as alternatives to synthetic polymers. Polymeric films have stood out for...
As attack techniques evolve and data volumes increase, the integration of artificial intelligence-based security solutions into industrial control systems...
This paper examines a model that combines vortex generators and leading-edge tubercles for controlling the laminar separation bubble (LSB) over an airfoil...
Skin cancer remains the most commonly diagnosed malignancy worldwide, with basal cell carcinoma (BCC), cutaneous squamous cell carcinoma (cSCC), and melanoma...
Classical Hodgkin lymphoma (cHL) is characterized by rare Hodgkin/Reed-Sternberg (HRS) tumor cells that uniformly express cluster of differentiation (CD)30...
Quantitative analysis of aluminum-silicon (Al-Si) alloy microstructure is crucial for evaluating and controlling alloy performance. Conventional analysis...
Internet of Things (IoTs) devices are bringing about a revolutionary change our society by enabling connectivity regardless of time and location. However,...
Cancer remains one of the leading causes of morbidity and mortality worldwide, and its onset and progression are closely linked to dysregulated epigenetic...
We propose a special issue titled "Innovative Smart Polymeric Materials for Sustainable Energy Solutions: Bridging Advances in Energy and Biomedical...
Further advancements in the exploitation of unconventional resources, such as tight gas, shale gas, shale oil, coalbed methane, and natural gas hydrate,...
In today’s digital era, patterns are omnipresent, shaping many aspects of our lives. These patterns can be physically observed or computationally identified...
This special issue, “Applied Artificial Intelligence: Advanced Solutions for Engineering Real-World Challenges,” showcases the transformative power of...
This theme captures the essence of advanced technologies (AI, machine learning, big data), modern applications (climate change, smart cities, health research),...
The tumor microenvironment encompasses not only the tumor cells themselves, but also the surrounding fibroblasts, immunological and inflammatory cells,...
This special issue seeks original research and review articles on the roles of γδ T cells and invariant natural killer T (iNKT) cells in malignancies....
While Large Language Models (LLMs) possess the capability to perform a wide range of tasks, security attacks known as prompt injection and jailbreaking remain critical challenges. Existing defense approaches addressing this problem face challenges such as the over-refusal of prompts that contain harmful vocabulary but are semantically benign, and the limited accuracy improvement in machine learning-based approaches due to the ease of distinguishing benign prompts in existing datasets. Therefore, we propose a multi-LLM agent framework…
Metaheuristic optimization algorithms continue to be essential for solving complex real-world problems, yet existing methods often struggle with balancing exploration and exploitation across diverse problem landscapes. This paper proposes a novel nature-inspired metaheuristic optimization algorithm named the Painted Wolf Optimization (PWO) algorithm. The main inspiration for the PWO algorithm is the group behavior and hunting strategy of painted wolves, also known as African wild dogs in the wild, particularly their unique consensus-based voting rally mechanism,…
Amazon Web Services (AWS) CloudTrail auditing service provides detailed records of operational and security events, enabling cloud administrators to monitor user activity and manage compliance. Although signature-based threat detection methods have been enhanced with machine learning and Large Language Models (LLMs), these approaches remain limited in addressing emerging threats. This study evaluates a two-step Retrieval Augmented Generation (RAG) approach using Gemini 2.5 Pro to enhance threat detection accuracy and contextual relevance. The RAG system integrates…
Automatic and accurate medical image segmentation remains a fundamental task in computer-aided diagnosis and treatment planning. Recent advances in foundation models, such as the medical-focused Segment Anything Model (MedSAM), have demonstrated strong performance but face challenges in many medical applications due to anatomical complexity and a limited domain-specific prompt. This work introduces a methodology that enhances segmentation robustness and precision by automatically generating multiple informative point prompts, rather than relying on single inputs. The proposed…
Large Language Models (LLMs) are increasingly utilized for semantic understanding and reasoning, yet their use in sensitive settings is limited by privacy concerns. This paper presents In-Mig, a mobile-agent architecture that integrates LLM reasoning within agents that can migrate across organizational venues. Unlike centralized approaches, In-Mig performs reasoning in situ, ensuring that raw data remains within institutional boundaries while allowing for cross-venue synthesis. The architecture features a policy-scoped memory model, utility-driven route planning, and cryptographic trust enforcement.
Analyzing the driving behavior of autonomous vehicles (AV) in mixed traffic conditions at urban intersections has become increasingly important for improving intersection design, providing infrastructure-based guidance information, and developing capability-enhanced AV perception systems. This study investigated the contributing factors affecting AV driving behavior using the Waymo Open Dataset. Binarized autonomous driving stability metrics, derived via a kernel density estimation, served as the target variables for a random forest classification model. The model’s input variables included…
To support the process of grasping objects on a tabletop for the blind or robotic arm, it is necessary to address fundamental computer vision tasks, such as detecting, recognizing, and locating objects in space, and determining the position of the grasping information. These results can then be used to guide the visually impaired or to execute grasping tasks with a robotic arm. In this paper, we collected, annotated, and published the benchmark TQU-GraspingObject dataset for…
Next-Generation Networks (NGNs) demand high resilience, dynamic adaptability, and efficient resource utilization to enable ubiquitous connectivity. In this context, the Space-Air-Ground Integrated Network (SAGIN) architecture is uniquely positioned to meet these requirements. However, conventional NGN routing algorithms often fail to account for SAGIN’s intrinsic characteristics, such as its heterogeneous structure, dynamic topology, and constrained resources, leading to suboptimal performance under disruptions such as node failures or cyberattacks. To meet these demands for SAGIN, this study…
Spectrum sensing is an indispensable core part of cognitive radio dynamic spectrum access (DSA) and a key approach to alleviating spectrum scarcity in the Internet of Things (IoT). The key issue in practical IoT networks is robust sensing under the coexistence of low signal-to-noise ratios (SNRs) and non-Gaussian impulsive noise, where observations may be distorted differently across feature modalities, making conventional fusion unstable and degrading detection reliability. To address this challenge, the generalized Gaussian distribution…
Globally, diabetes and glaucoma account for a high number of people suffering from severe vision loss and blindness. To treat these vision disorders effectively, proper diagnosis must occur in a timely manner, and with conventional methods such as fundus photography, optical coherence tomography (OCT), and slit-lamp imaging, much depends on an expert’s interpretation of the images, making the systems very labor-intensive to operate. Moreover, clinical settings face difficulties with inter-observer variability and limited scalability with…
The rapid proliferation of multimodal misinformation on social media demands detection frameworks that are not only accurate but also robust to noise, adversarial manipulation, and semantic inconsistency between modalities. Existing multimodal fake news detection approaches often rely on deterministic fusion strategies, which limits their ability to model uncertainty and complex cross-modal dependencies. To address these challenges, we propose Q-ALIGNer, a quantum-inspired multimodal framework that integrates classical feature extraction with quantum state encoding, learnable cross-modal entanglement,…
It is known that correlation does not imply causality. Some relationships identified in the analysis of data are coincidental or unknown, and some are produced by real-world causality of the situation, which is problematic, since there is a need to differentiate between these two scenarios. Until recently, the proper−semantic−causality of the relationship could have been determined only by human experts from the area of expertise of the studied data. This has changed with the advance…
Multimodal emotion recognition has emerged as a key research area for enabling human-centered artificial intelligence, supported by the rapid progress in vision, audio, language, and physiological modeling. Existing approaches integrate heterogeneous affective cues through diverse embedding strategies and fusion mechanisms, yet the field remains fragmented due to differences in feature alignment, temporal synchronization, modality reliability, and robustness to noise or missing inputs. This survey provides a comprehensive analysis of MER research from 2021 to 2025,…
Alzheimer’s disease (AD) diagnosis and prognosis increasingly rely on machine learning (ML) models. Although these models provide good results, clinical adoption is limited by the need for technical expertise and the lack of trustworthy and consistent model explanations. SHAP (SHapley Additive exPlanations) is commonly used to interpret AD models, but existing studies tend to focus on explanations for isolated tasks, providing little evidence about their robustness across disease stages, model architectures, or prediction objectives. This…
As deep learning (DL) models are increasingly deployed in sensitive domains (e.g., healthcare), concerns over privacy and security have intensified. Conventional penetration testing frameworks, such as OWASP and NIST, are effective for traditional networks and applications but lack the capabilities to address DL-specific threats, such as model inversion, membership inference, and adversarial attacks. This review provides a comprehensive analysis of penetration testing for the privacy of DL models, examining the shortfalls of existing frameworks, tools,…
In this study, the multi-scale (meso and macro) modelling was used to predict the electric response of the material. Porosity was introduced through a sugar-templating process to enhance compressibility and sensitivity. Mean-field homogenization was employed to predict the electrical conductivity of the nanocomposites, which was validated experimentally through I–V characterisation, confirming stable Ohmic behavior. The homogenised material parameters were incorporated into COMSOL Multiphysics to simulate diaphragm deflection and capacitance variation under applied pressure. Experimental results showed…
Guest Editors: Qi Chen; Yunhui Tang Deadline: 31 December 2026
Guest Editors: Dawei Jiang; Miaojun Xu; Bo Jiang; Zijian Wu Deadline: 31 December 2026
Guest Editors: Changhong LINGHU; Hoon Eui Jeong; Ying Jiang; Jiangtao Su; Yangchengyi... Deadline: 30 December 2026
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Guest Editors: Daniel-Ioan Curiac; Dan Pescaru Deadline: 15 October 2026
Guest Editors: Barmak Honarvar Shakibaei Asli Deadline: 01 October 2026
Guest Editors: Antonella Petrillo; Fabio De Felice Deadline: 30 September 2026
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Guest Editors: Dulf Eva-H.; Kovacs Levente; Denes-Fazakas Lehel; Pintea Paul-Andrei Deadline: 31 August 2026
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