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Research ArticleOpen accessIn the abstractEfficient Music Auto-Tagging with Convolutional Neural NetworksShaleen Bengani, S. Vadivel, J. Angel Arul JothiTechnology is revolutionizing the way in which music is distributed and consumed. As a result, millions of songs are instantly available to millions of people, on the Internet. This has created the need for novel music search and discovery services. Music is often searched using descriptive keywords, or tags, based on the content of the song. Hence, one very important … …Journal of Computer Science, Vol. 15, Issue 8 · 27 Aug 2019 · 7,847 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrating Lowest Priority Approach with Largest Point Scheme for Faster Feasibility AnalysisNasro Min-AllahRecently many solutions have been proposed to lower the computational cost of feasibility analysis for real-time systems. The computational cost of feasibility tests can be lowered by strategies such as lowering the number of scheduling points needed during analysis, starting feasibility analysis from lowest priority, or starting schedulability tests for a task with larger scheduling point. All these techniques significantly … …Journal of Computer Science, Vol. 15, Issue 4 · 26 Apr 2019 · 7,250 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT Intrusion Detection using Auto-Encoder and Machine Learning TechniquesAhmed Ridha Khudhu, Khairulmizam SamsudinIoTnetwork refers to the capability of connecting smart and various devices to asingle network for the sake of performing a particular task. Similar toconventional networks, IoT networks are vulnerable to several attacks.Therefore, IoT Intrusion Detection has caught much research attention. Severalstudies have examined the task of intrusion detection for IoT networks. Withinsuch studies, the focus was set to accommodate a … …Journal of Computer Science, Vol. 18, Issue 10 · 27 Sep 2022 · 6,463 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Backpropagation Neural Network for Splitting IdentifiersAhmed Sabah Ahmed AL-Jumaili, Huda Kadhim Tayyeh, Ruqaia Jawad KadhemSplitting identifiers is a task that has been addressed in the past few years in order to contribute toward improving the Feature Location task. Feature Location aims at determining the exact position of a specific feature within a source code. Several research studies have addressed the process of splitting multi-word identifiers. However, one of the endure gaps that still face … …Journal of Computer Science, Vol. 14, Issue 10 · 31 Oct 2018 · 7,234 accessesView PDFCite
Research ArticleOpen accessIn the abstractSQL Generation from Natural Language: A Sequence-to-Sequence Model Powered by the Transformers Architecture and Association RulesYoussef Mellah, Abdelkader Rhouati, El Hassane Ettifouri et al.Using Natural Language (NL) to interacting with relational databases allows users from any background to easily query and analyze large amounts of data. This requires a system that understands user questions and automatically converts them into structured query language such as SQL. The best performing Text-to-SQL systems use supervised learning (usually formulated as a classification problem) by approaching this task … …Journal of Computer Science, Vol. 17, Issue 5 · 23 May 2021 · 10,034 accessesView PDFCite
Research ArticleOpen accessIn the abstractTransfer Learning in Attack Avoidance GamesEdwin Torres, Fernando LozanoTransfer knowledge is a human characteristic that has been replicated in machine learning algorithms to improve learning performance measures. However, little success has been accomplished in reinforcement learning tasks when a function approximation is needed to estimate the value functions. In this study, we present a new strategy to facilitate knowledge transfer when an agent is learning to solve a … …Journal of Computer Science, Vol. 16, Issue 10 · 13 Nov 2020 · 6,583 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Survey on Event Detection Models for Text Data StreamsWafa Zubair AL-Dyani, Farzana Kabir Ahmad, Siti Sakira KamaruddinEvent Detection (ED) is a study area that attracts the attention of decision-makers from various disciplines in order to help them in taking the right decision. ED has been examined on various text streams like Twitter, Facebook, Emails, Blogs, Web Forums and newswires. Many ED models have been proposed in literature. In general, ED model consists of six main phases: … …Journal of Computer Science, Vol. 16, Issue 7 · 14 Jul 2020 · 7,044 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring Learning Capability of an Agent in SOAR: Using 8-Queens ProblemNeha Rajan, Sunderrajan SrinivasanCognitive architecture deals with describing the intelligent behavior of an agent. The description of intelligent behavior states how well an agent can solve and represent variety of problems of the domain-independent task. The intelligence of an agent is considered in terms of its learning capabilities. In this study, we are exploring solving 8-Queens combinatorial problem using SOAR symbolic cognitive architecture. … …Journal of Computer Science, Vol. 16, Issue 5 · 25 May 2020 · 7,072 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparison between Conditional Random Field and Structured Support Vector Machine for Arabic Named Entity RecognitionMarwa Muhammad, Muhammad Rohaim, Alaa Hamouda, Salah Abdel-MageidThe Named Entity Recognition (NER) is an integrated task in many NLP applications such as machine translation, Information extraction and question answering. Arabic is one of the authorised spoken languages in the united nation. Currently, there is much Arabic information on the internet, so, nowadays the need for tools which process this information becomes significant. In this study, we have … …Journal of Computer Science, Vol. 16, Issue 1 · 30 Jan 2020 · 8,120 accessesView PDFCite
Research ArticleOpen accessIn the abstractExplainability Aware Heterogeneous Temporal Graph Transformer for Automated Genetic Disorder Detection from Genomic DataPuvaneswari Subramaniapillai, Indirani Govindasamy, Revathy GurumurthyGenetic disorders affect millions worldwide, posing major challenges for accurate diagnosis and effective treatments. New developments in genomic technologies, especially Next-Generation Sequencing (NGS), have enhanced the classification of genetic modification and improved diagnostic abilities. Moreover, the Machine Learning (ML) and Deep Learning (DL) methods emerged as efficient tools for evaluating the intricate genomic data and determining the patterns, which can … …Journal of Computer Science, Vol. 22, Issue 11 · 14 Oct 2026 · 581 accessesView PDFCite