Online game addiction has become a serious global public health problem among adolescents. However, its influencing factors and mediating mechanisms remain ambiguous....
Green plants emerge from the soil, their roots intertwine, and microbial communities hide in them, weaving together the symphony of life. This is not only a depiction...
The development of Radar Absorbing Materials is crucial to minimize the electromagnetic pollution in the environment. Several researches focus on carbon nanotubes,...
Beijing (China) and Henderson (USA) – Tsinghua University Press (TUP) and Tech Science Press (TSP) are excited to announce a new collaboration that will see 11 of TSP's esteemed STM journals...
We are pleased to announce that Tech Science Press journals have entered into a collaboration with the PubScholar platform, a publicly funded academic resource established by the Chinese Academy...
Conventional fault diagnosis systems have constrained the automotive industry to damage vehicle maintenance and component longevity critically. Hence,...
Magneto-electro-elastic (MEE) materials are a specific class of advanced smart materials that simultaneously manifest the coupling behavior under electric,...
The emergence of various technologies such as terahertz communications, Reconfigurable Intelligent Surfaces (RIS), and AI-powered communication services...
As Natural Language Processing (NLP) continues to advance, driven by the emergence of sophisticated large language models such as ChatGPT, there has been...
Time series segmentation has attracted more interests in recent years, which aims to segment time series into different segments, each reflects a state...
The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles (IoV) technology. The functional...
Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding...
Since the 1950s, when the Turing Test was introduced, there has been notable progress in machine language intelligence. Language modeling, crucial for...
Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item. From ancient times to the present,...
Image steganography is one of the prominent technologies in data hiding standards. Steganographic system performance mostly depends on the embedding strategy....
COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus. The foremost and most prime sector among those affected...
The International Skin Imaging Collaboration (ISIC) datasets are pivotal resources for researchers in machine learning for medical image analysis, especially...
Federated learning is an innovative machine learning technique that deals with centralized data storage issues while maintaining privacy and security....
This review describes the mechanisms of natural coagulants. It provides a good understanding of the two key processes of coagulation-flocculation: adsorption...
Bio-based cyclodextrins (CDs) are a common research object in supramolecular chemistry. The special cavity structure of CDs can form supramolecular self-assemblies...
This paper expounds upon a novel target detection methodology distinguished by its elevated discriminatory efficacy, specifically tailored for environments...
The tumor microenvironment encompasses not only the tumor cells themselves, but also the surrounding fibroblasts, immunological and inflammatory cells,...
Machine vision detection and intelligent recognition are important research areas in computer vision with wide-ranging applications in manufacturing,...
Object detection and tracking in videos has become an increasingly important area of research due to its potential applications in a variety of domains...
With the progress of science and technology, more and more complex engineering structures are serving in extreme environments. In the service life of...
Extracellular vesicles (EVs) are phospholipid bilayer vesicles released from tumor and non-tumor cells for intercellular communication. EVs contain...
The peridynamics proposed by Silling [1] is a non-local theory of solid mechanics. It redefines the problems by using integral equations rather than partial...
In modern time, experts started to use interdisciplinary properties with the developing of technology and science. Thus, these disciplines provide more...
More than half of the world population is living in cities. It requires extended infrastructure and various services to support the densely concentrated...
Conventional fault diagnosis systems have constrained the automotive industry to damage vehicle maintenance and component longevity critically. Hence,...
Magneto-electro-elastic (MEE) materials are a specific class of advanced smart materials that simultaneously manifest the coupling behavior under electric,...
The emergence of various technologies such as terahertz communications, Reconfigurable Intelligent Surfaces (RIS), and AI-powered communication services...
As Natural Language Processing (NLP) continues to advance, driven by the emergence of sophisticated large language models such as ChatGPT, there has been...
Time series segmentation has attracted more interests in recent years, which aims to segment time series into different segments, each reflects a state...
The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles (IoV) technology. The functional...
Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding...
Since the 1950s, when the Turing Test was introduced, there has been notable progress in machine language intelligence. Language modeling, crucial for...
Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item. From ancient times to the present,...
Image steganography is one of the prominent technologies in data hiding standards. Steganographic system performance mostly depends on the embedding strategy....
COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus. The foremost and most prime sector among those affected...
The International Skin Imaging Collaboration (ISIC) datasets are pivotal resources for researchers in machine learning for medical image analysis, especially...
Federated learning is an innovative machine learning technique that deals with centralized data storage issues while maintaining privacy and security....
This review describes the mechanisms of natural coagulants. It provides a good understanding of the two key processes of coagulation-flocculation: adsorption...
Bio-based cyclodextrins (CDs) are a common research object in supramolecular chemistry. The special cavity structure of CDs can form supramolecular self-assemblies...
This paper expounds upon a novel target detection methodology distinguished by its elevated discriminatory efficacy, specifically tailored for environments...
The tumor microenvironment encompasses not only the tumor cells themselves, but also the surrounding fibroblasts, immunological and inflammatory cells,...
Machine vision detection and intelligent recognition are important research areas in computer vision with wide-ranging applications in manufacturing,...
Object detection and tracking in videos has become an increasingly important area of research due to its potential applications in a variety of domains...
With the progress of science and technology, more and more complex engineering structures are serving in extreme environments. In the service life of...
Extracellular vesicles (EVs) are phospholipid bilayer vesicles released from tumor and non-tumor cells for intercellular communication. EVs contain...
The peridynamics proposed by Silling [1] is a non-local theory of solid mechanics. It redefines the problems by using integral equations rather than partial...
In modern time, experts started to use interdisciplinary properties with the developing of technology and science. Thus, these disciplines provide more...
More than half of the world population is living in cities. It requires extended infrastructure and various services to support the densely concentrated...
Redundancy, correlation, feature irrelevance, and missing samples are just a few problems that make it difficult to analyze software defect data. Additionally, it might be challenging to maintain an even distribution of data relating to both defective and non-defective software. The latter software class’s data are predominately present in the dataset in the majority of experimental situations. The objective of this review study is to demonstrate the effectiveness of combining ensemble learning and feature selection…
The rapid adoption of Internet of Things (IoT) technologies has introduced significant security challenges across the physical, network, and application layers, particularly with the widespread use of the Message Queue Telemetry Transport (MQTT) protocol, which, while efficient in bandwidth consumption, lacks inherent security features, making it vulnerable to various cyber threats. This research addresses these challenges by presenting a secure, lightweight communication proxy that enhances the scalability and security of MQTT-based Internet of Things (IoT)…
The high coverage and all-weather capabilities of Synthetic Aperture Radar (SAR) image ship detection make it a widely accepted method for maritime ship positioning and identification. However, SAR ship detection faces challenges such as indistinct ship contours, low resolution, multi-scale features, noise, and complex background interference. This paper proposes a lightweight YOLOv8 model for small object detection in SAR ship images, incorporating key structures to enhance performance. The YOLOv8 backbone is replaced by the Slim…
In enterprise operations, maintaining manual rules for enterprise processes can be expensive, time-consuming, and dependent on specialized domain knowledge in that enterprise domain. Recently, rule-generation has been automated in enterprises, particularly through Machine Learning, to streamline routine tasks. Typically, these machine models are black boxes where the reasons for the decisions are not always transparent, and the end users need to verify the model proposals as a part of the user acceptance testing to trust…
More businesses are deploying powerful Intrusion Detection Systems (IDS) to secure their data and physical assets. Improved cyber-attack detection and prevention in these systems requires machine learning (ML) approaches. This paper examines a cyber-attack prediction system combining feature selection (FS) and ML. Our technique’s foundation was based on Correlation Analysis (CA), Mutual Information (MI), and recursive feature reduction with cross-validation. To optimize the IDS performance, the security features must be carefully selected from multiple-dimensional datasets,…
This paper introduces the integration of the Social Group Optimization (SGO) algorithm to enhance the accuracy of software cost estimation using the Constructive Cost Model (COCOMO). COCOMO’s fixed coefficients often limit its adaptability, as they don’t account for variations across organizations. By fine-tuning these parameters with SGO, we aim to improve estimation accuracy. We train and validate our SGO-enhanced model using historical project data, evaluating its performance with metrics like the mean magnitude of relative
This work aims to examine the vulnerabilities and threats in the applications of intelligent transport systems, especially collision avoidance protocols. It focuses on achieving the availability of network communication among traveling vehicles. Finally, it aims to find a secure solution to prevent blackhole attacks on vehicular network communications. The proposed solution relies on authenticating vehicles by joining a blockchain network. This technology provides identification information and receives cryptography keys. Moreover, the ad hoc on-demand distance vector…
Users of social networks can readily express their thoughts on websites like Twitter (now X), Facebook, and Instagram. The volume of textual data flowing from users has greatly increased with the advent of social media in comparison to traditional media. For instance, using natural language processing (NLP) methods, social media can be leveraged to obtain crucial information on the present situation during disasters. In this work, tweets on the Uttarakhand flash flood are analyzed using…
Layout synthesis in quantum computing is crucial due to the physical constraints of quantum devices where quantum bits (qubits) can only interact effectively with their nearest neighbors. This constraint severely impacts the design and efficiency of quantum algorithms, as arranging qubits optimally can significantly reduce circuit depth and improve computational performance. To tackle the layout synthesis challenge, we propose an algorithm based on integer linear programming (ILP). ILP is well-suited for this problem as it…
The number of blogs and other forms of opinionated online content has increased dramatically in recent years. Many fields, including academia and national security, place an emphasis on automated political article orientation detection. Political articles (especially in the Arab world) are different from other articles due to their subjectivity, in which the author’s beliefs and political affiliation might have a significant influence on a political article. With categories representing the main political ideologies, this problem…
This study conducts a systematic literature review (SLR) of blockchain consensus mechanisms, an essential protocols that maintain the integrity, reliability, and decentralization of distributed ledger networks. The aim is to comprehensively investigate prominent mechanisms’ security features and vulnerabilities, emphasizing their security considerations, applications, challenges, and future directions. The existing literature offers valuable insights into various consensus mechanisms’ strengths, limitations, and security vulnerabilities and their real-world applications. However, there remains a gap in synthesizing and analyzing…
Quadrotor unmanned aerial vehicles (UAVs) are widely used in inspection, agriculture, express delivery, and other fields owing to their low cost and high flexibility. However, the current UAV control system has shortcomings such as poor control accuracy and weak anti-interference ability to a certain extent. To address the control problem of a four-rotor UAV, we propose a method to enhance the controller’s accuracy by considering underactuated dynamics, nonlinearities, and external disturbances. A mathematical model is…
In the contemporary era, the death rate is increasing due to lung cancer. However, technology is continuously enhancing the quality of well-being. To improve the survival rate, radiologists rely on Computed Tomography (CT) scans for early detection and diagnosis of lung nodules. This paper presented a detailed, systematic review of several identification and categorization techniques for lung nodules. The analysis of the report explored the challenges, advancements, and future opinions in computer-aided diagnosis CAD systems…
A data lake (DL), abbreviated as DL, denotes a vast reservoir or repository of data. It accumulates substantial volumes of data and employs advanced analytics to correlate data from diverse origins containing various forms of semi-structured, structured, and unstructured information. These systems use a flat architecture and run different types of data analytics. NoSQL databases are nontabular and store data in a different manner than the relational table. NoSQL databases come in various forms, including…
Forecasting travel demand requires a grasp of individual decision-making behavior. However, transport mode choice (TMC) is determined by personal and contextual factors that vary from person to person. Numerous characteristics have a substantial impact on travel behavior (TB), which makes it important to take into account while studying transport options. Traditional statistical techniques frequently presume linear correlations, but real-world data rarely follows these presumptions, which may make it harder to grasp the complex interactions. Thorough…
Incredible progress has been made in human action recognition (HAR), significantly impacting computer vision applications in sports analytics. However, identifying dynamic and complex movements in sports like badminton remains challenging due to the need for precise recognition accuracy and better management of complex motion patterns. Deep learning techniques like convolutional neural networks (CNNs), long short-term memory (LSTM), and graph convolutional networks (GCNs) improve recognition in large datasets, while the traditional machine learning methods like SVM…
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