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Topic Review
Concept Prerequisite Learning with PTM and GNN
Prerequisite chains are crucial to acquiring new knowledge efficiently. Many studies have been devoted to automatically identifying the prerequisite relationships between concepts from educational data. Though effective to some extent, these methods have neglected two key factors: most works have failed to utilize domain-related knowledge to enhance pre-trained language models, thus making the textual representation of concepts less effective; they also ignore the fusion of semantic information and structural information formed by existing prerequisites.
  • 202
  • 04 Sep 2023
Topic Review
ProMatch: Semi-Supervised Learning with Prototype Consistency
Semi-supervised learning (SSL) methods have made significant advancements by combining consistency-regularization and pseudo-labeling in a joint learning paradigm. The core concept of these methods is to identify consistency targets (pseudo-labels) by selecting predicted distributions with high confidence from weakly augmented unlabeled samples. 
  • 307
  • 04 Sep 2023
Topic Review
P4-HLDMC
Distributed Denial of Service (DDoS) and Address Resolution Protocol (ARP) attacks pose significant threats to the security of Software-Defined Internet of Things (SD-IoT) networks. The standard Software-Defined Networking (SDN) architecture faces challenges in effectively detecting, preventing, and mitigating these attacks due to its centralized control and limited intelligence.
  • 265
  • 01 Sep 2023
Topic Review
Machine Learning in Smart Farming
Machine learning applications are having a great impact on the global economy by transforming the data processing method and decision making. Agriculture is one of the fields where the impact is significant, considering the global crisis for food supply. 
  • 650
  • 01 Sep 2023
Topic Review
Cross-Domain Sentiment Analysis in IoT
Social media is a real-time social sensor to sense and collect diverse information, which can be combined with sentiment analysis to help IoT sensors provide user-demanded favorable data in smart systems. In the case of insufficient data labels, cross-domain sentiment analysis aims to transfer knowledge from the source domain with rich labels to the target domain that lacks labels. Most domain adaptation sentiment analysis methods achieve transfer learning by reducing the domain differences between the source and target domains, but little attention is paid to the negative transfer problem caused by invalid source domains. 
  • 248
  • 01 Sep 2023
Topic Review
Machine Learning-Based Text Classification Comparison
The growth in textual data associated with the increased usage of online services and the simplicity of having access to these data has resulted in a rise in the number of text classification research papers. Text classification has a significant influence on several domains such as news categorization, the detection of spam content, and sentiment analysis. The classification of Turkish text is the research focus since only a few studies have been conducted in this context. Researchers utilize data obtained from customers’ inquiries that come to an institution to evaluate the proposed techniques. Classes are assigned to such inquiries specified in the institution’s internal procedures. The Support Vector Machine, Naïve Bayes, Long Term-Short Memory, Random Forest, and Logistic Regression algorithms were used to classify the data. The performance of the various techniques was then analyzed after and before data preparation, and the results were compared. The Long Term-Short Memory technique demonstrated superior effectiveness in terms of accuracy, achieving an 84% accuracy rate, surpassing the best accuracy record of traditional techniques, which was 78% accuracy for the Support Vector Machine technique. The techniques performed better once the number of categories in the dataset was reduced. Moreover, the findings show that data preparation and coherence between the classes’ number and the number of training sets are significant variables influencing the techniques’ performance.
  • 334
  • 01 Sep 2023
Topic Review
Prospects of Cybersecurity in Smart Cities
Smart cities are urban spaces characterized by the widespread use of Information and Communication Technologies (ICTs). They intend to improve political-economic efficiency and support human and social development, thus improving the quality of life of its citizens. Cybersecurity plays a key role in smart cities due to the increasing interconnectivity and widespread use of ICT.
  • 317
  • 01 Sep 2023
Topic Review
Robot Landing Method on Overhead P[ower Transmission Lines
Hybrid inspection robots have been attracting increasing interest in recent years, and are suitable for inspecting long-distance overhead power transmission lines (OPTLs), combining the advantages of flying robots (e.g., UAVs) and climbing robots (e.g., multiple-arm robots). Due to the complex work conditions (e.g., power line slopes, complex backgrounds, wind interference), landing on OPTL is one of the most difficult challenges faced by hybrid inspection robots.
  • 184
  • 01 Sep 2023
Topic Review
Autonomous Vehicles and Distributed Resources on Logistic Systems
The autonomous vehicle (AV) is one of the emerging technologies of the new age that has the potential to restructure transportation infrastructure. AVs are able to sense their surroundings and move around with control and self-sufficiency. AVs can contribute towards reducing traffic congestion on the roads, improving the quality of life, and achieving the highest levels of traffic safety. Thus, this type of vehicle can be integrated into the logistics industry. Due to the presence of several AVs, selecting a standard and efficient AV for logistics planning is a great challenge. The selection of an AV depends on many conflicting and essential criteria. 
  • 353
  • 31 Aug 2023
Topic Review
Communication Costs in Federated Learning
Federated learning (FL) is an emerging distributed machine learning technique that allows for the distributed training of a single machine learning model across multiple geographically distributed clients.
  • 573
  • 31 Aug 2023
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