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Keyword: Machine learningAnalysis of Wireless Traffic Data through Machine Learning
The paper presents an analytical study on a wireless traffic dataset carried out under the different approaches of machine learning including the backpropagation feedforward neural network, the time-series NARX network, the self-organizing map and the principal component analyses. These approaches are well-known for their usefulness in the modeling and in transforming a high dimensional data…
Read MoreThe Class Imbalance Problem in the Machine Learning Based Detection of Vandalism in Wikipedia across Languages
This paper analyses the impact of current trend in applying machine learning in detection of vandalism, with the specific aim of analyzing the impact of the class imbalance in Wikipedia articles. The class imbalance problem has the effect that almost all the examples are labelled as one class (legitimate editing); while far fewer examples are…
Read MoreProposal and Implementation of Seawater Temperature Prediction Model using Transfer Learning Considering Water Depth Differences
Aquaculture is one of the most important industries worldwide, and most marine products are produced by aquaculture. On the other hand, the aquaculture farmers are faced on the challenge of damage to marine products due to abnormal seawater temperatures. Research on seawater temperature prediction have been conducted, but many of them require a large amount…
Read MoreEvaluation of Various Deep Learning Models for Short-Term Solar Forecasting in the Arctic using a Distributed Sensor Network
The solar photovoltaic (PV) power generation industry has experienced substantial, ongoing growth over the past decades as a clean, cost-effective energy source. As electric grids use ever-larger proportions of solar PV, the technology’s inherent variability—primarily due to clouds—poses a challenge to maintaining grid stability. This is especially true for geographically dense, electrically isolated grids common…
Read MoreAn Adaptive Heterogeneous Ensemble Learning Model for Credit Card Fraud Detection
The proliferation of internet economies has given the corporate world manifold advantages to businesses, as they can now incorporate the latest innovations into their operations, thereby enhancing ease of doing business. For instance, financial institutions have leveraged credit card usage on the aforesaid proliferation. However, this exposes clients to cybercrime, as fraudsters always find ways…
Read MoreDetecting CTC Attack in IoMT Communications using Deep Learning Approach
Cyber security is based on different principles such as confidentiality and integrity of transmitted data. One of the main methods to send confidential messages is to use a shared secret to encrypt and decrypt them. Even if the amortized computational complexity of the hashing functions is Ο(1), there are several situations when it is not…
Read MoreA Multiplatform Application for Automatic Recognition of Personality Traits in Learning Environments
The present work shows the development of a data collection platform that allows the researcher to collect new video and voice data sets in Spanish. It also allows the application of a standardized personality test and stores this information to analyze the effectiveness of the automatic personality recognizers concerning the results of a standardized personality…
Read MoreTransfer and Ensemble Learning in Real-time Accurate Age and Age-group Estimation
Aging is considered to be a complex process in almost every species’ life, which can be studied at a variety of levels of abstraction as well as in different organs. Not surprisingly, biometric characteristics from facial images play a significant role in predicting human’s age. Specifically, automatic age estimation in real-time situation has begun to…
Read MoreBER Performance Evaluation Using Deep Learning Algorithm for Joint Source Channel Coding in Wireless Networks
In the time past, virtually all the contemporary communication systems depend on distinct source and channel encoding schemes for data transmission. Irrespective of the recorded success of the distinct schemes, the new developed scheme known as joint source channel coding technique has proven to have technically outperformed the conventional schemes. The aim of the study…
Read MoreEnsemble Learning of Deep URL Features based on Convolutional Neural Network for Phishing Attack Detection
The deep learning-based URL classification approach using massive observations has been verified especially in the field of phishing attack detection. Various improvements have been achieved through the modeling of character and word sequence of URL based on convolutional and recurrent neural networks, and it has been proven that an ensemble approach of each model has…
Read MoreFault Diagnosis and Noise Robustness Comparison of Rotating Machinery using CWT and CNN
For systems using rotating machinery, diagnosing the faults of the rotating machinery is critical for system maintenance. Recently, a machine learning algorithm has been employed as one of the methods for diagnosing the faults of rotating machinery. This algorithm has an advantage of automatically classifying faults without an expert knowledge. However, despite a good training…
Read MoreA Recommendation Approach in Social Learning Based on K-Means Clustering
E-learning, among the most prominent modes of learning, offers learners the opportunity to attend online courses. To improve the quality of online learning, social learning through social networks promotes interaction and collaboration among learners. As part of the learning process management in these environments, the implementation of recommendation systems facilitates the provision of content adapted…
Read MoreHandling Priority Data in Smart Transportation System by using Support Vector Machine Algorithm
In an intelligent transportation system (ITS), time is a big challenge since processing a huge amount of data in a short time is very difficult, especially when the processed data is heterogeneous, consisting of a mixture of emergency data, normal data, and noise. In an ITS, an ambulance is one of the priority vehicles, and…
Read MoreComparison of Support Vector Machine-Based Equalizer and Code-Aided Expectation Maximization on Fiber Optic Nonlinearity Compensation Using a Proposed BER Normalized by Power and Distance Index
Advances in optimizing optical fiber communications have been on the rise these recent years due to the increasing demand for larger data bandwidths and overall better efficiency. Coherent optics have focused on many kinds of research due to its ability to transport greater amounts of information, have better flexibility in network implementations, and support different…
Read MoreSupervised Learning Techniques for Stress Detection in Car Drivers
In this paper we propose the application of supervised learning techniques to recognize stress situations in drivers by analyzing their Skin Potential Response (SPR) and the Electrocardiogram (ECG). A sensing device is used to acquire the SPR from both hands of the drivers, and the ECG from their chest. We also consider a motion artifact…
Read MoreFPGA Acceleration of Tree-based Learning Algorithms
Machine learning classifiers provide many promising solutions for data classification in different disciplines. However, data classification at run time is still a very challenging task for real-time applications. Acceleration of machine-learning hardware solutions is needed to meet the requirements of real-time applications. This paper proposes a new implementation of a machine learning classifier on Field…
Read MoreDeep Learning Approach for Automatic Topic Classification in an Online Submission System
Topic classification is a crucial task where knowledge categories exist within hierarchical information systems designed to facilitate knowledge search and discovery. An application of topic classification is article (e.g., journal/conference paper) classification which is very useful for online submission systems. In fact, numerous online journals/magazine submission systems usually receive thousands of article submissions or even…
Read MoreClustering of Mindset towards Self-Regulated Learning of Undergraduate Students at the University of Phayao
The effects of Covid-19 severely affected the Thai higher education model. Therefore, there are three significant objectives in this research: (1) to cluster the mindsets and attitudes toward self-regulated learning styles of undergraduate students at the University of Phayao. (2) to construct a predictive model for recommending an appropriate student learning clusters. (3) to evaluate…
Read MoreCorrelation-Based Incremental Learning Network for Gas Sensors Drift Compensation Classification
A gas sensor array is used for gas analysis to aid in an inspection. The signals from the sensor array are fed into machine learning models for learning and classification. These signals are characterized by time series fluctuating according to the environment or drift. When an unseen pattern is entered, the classification may be incorrect,…
Read MoreComputational Intelligence and Statistical Learning Performances on Predicting Dengue Incidence using Remote Sensing Data
Dengue is a viral infection disease transmitted to people through the bite of specific mosquito species living in a tropical zone. According to the World Health Organization, dengue has been listed among the top-ten diseases for 2019 as it makes 3.9 billion people in 128 countries be at risk of infection. One major cause of…
Read MoreMalware Classification Based on System Call Sequences Using Deep Learning
Malware has always been a big problem for companies, government agencies, and individuals because people still use it as a primary tool to influence networks, applications, and computer operating systems to gain unilateral benefits. Until now, malware detection with heuristic and signature-based methods are still struggling to keep up with the evolution of malware. Machine…
Read MoreQ-Learning versus SVM Study for Green Context-Aware Multimodal ITS Stations
Intelligent Transportation Systems (ITS) applications can take big advantage of Context Awareness approaches. Parameters such as user mobility, passengers comfort reaction and pollution emission levels (CO2) can enrich such applications during the decision making phase. Moreover, the expanding in ITS services offers great opportunities for travelers to find the best route to reach their destinations…
Read MoreComputationally Efficient Explainable AI Framework for Skin Cancer Detection
Skin cancer stands among some of the fastest growing and fatal malignancies of the world as a result early and accurate diagnosis of skin cancer is essential in order to enhance patient survival and treatment prognosis. Conventional methods of diagnosis including dermoscopy and histopathological examinations are expensive and time consuming also subject to inter-observer error.…
Read MoreStradNet: Automated Structural Adaptation for Efficient Deep Neural Network Design
Deep neural networks (DNNs) have demonstrated remarkable success across a wide range of machine learning tasks. However, determining an effective network architecture, particularly the sizes of the hidden layers, remains a significant challenge and often relies on inefficient trial-and-error experimentation. In this paper, we propose an automated architecture design approach based on structurally adaptive DNNs,…
Read MorePredictive Analytics in Marketing: Evaluating its Effectiveness in Driving Customer Engagement
Understanding and responding to customer feedback is critical for business success. Customer response data offers valuable insights into preferences, behaviours, and sentiment. By analysing this data, businesses can optimize strategies, enhance customer experiences, and drive growth. Many analysis have been conducted in this field, while the review covers a broad range of AI and ML…
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