Journal profile
Universal Journal of Computer Sciences and Communications(UJCSC) provides readers with a compilation of stimulating and up-to-date articles within the field of computer science and communications. The focus of the journal is on high quality research that addresses paradigms, development, applications and implications in the field of computer science. All research articles in UJCSC will undergone rigorous peer review, based on initial editor screening and anonymized refereeing by an expert reviewer.
Latest Articles
A Convergence of the Muller’s Sequence
Universal Journal of Computer Sciences and Communications
2025,
4(1),
6144.
DOI: 10.31586/ujcsc.2025.6144
Abstract
In this paper, we will examine a rather complex case of the paradoxical nature of certain conclusions that may arise when studying the numerical convergence of a specific nonlinear recursive sequence, known in the literature as Muller’s sequence. To analyze the peculiar computational behavior of this sequence, it is necessary
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In this paper, we will examine a rather complex case of the paradoxical nature of certain conclusions that may arise when studying the numerical convergence of a specific nonlinear recursive sequence, known in the literature as Muller’s sequence. To analyze the peculiar computational behavior of this sequence, it is necessary to employ a powerful mathematical framework in order to understand the nontrivial issues that can arise when the software implementation of this seemingly simple mathematical problem. These challenges often stem from the limitations of numerical methods and the inherent errors in computer arithmetic, which can affect the accuracy and stability of the results, particularly when dealing with iterative methods like Muller's sequence.Full article
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Article
Advancing Preference Learning in AI: Beyond Pairwise Comparisons
Universal Journal of Computer Sciences and Communications
2025,
4(1),
6036.
DOI: 10.31586/ujcsc.2025.6036
Abstract
Preference learning plays a crucial role in AI applications, particularly in recommender systems and personalized services. Traditional pairwise comparisons, while foundational, present scalability challenges in large-scale systems. This study explores alternative elicitation methods such as ranking, numerical ratings, and natural language feedback, alongside a novel hybrid framework that dynamically integrates
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Preference learning plays a crucial role in AI applications, particularly in recommender systems and personalized services. Traditional pairwise comparisons, while foundational, present scalability challenges in large-scale systems. This study explores alternative elicitation methods such as ranking, numerical ratings, and natural language feedback, alongside a novel hybrid framework that dynamically integrates these approaches. The proposed methods demonstrate improved efficiency, reduced cognitive load, and enhanced accuracy. Results from simulated user studies reveal that hybrid approaches outperform traditional methods, achieving a 40% reduction in user effort while maintaining high predictive accuracy. These findings open pathways for deploying user-centric, scalable preference learning systems in dynamic environments.Full article
Review Article
Deep Learning-Based Sentiment Analysis: Enhancing IMDb Review Classification with LSTM Models
Universal Journal of Computer Sciences and Communications
2025,
4(1),
1249.
DOI: 10.31586/ujcsc.2025.1249
Abstract
Sentiment analysis, a vital aspect of natural language processing, involves the application of machine learning models to discern the emotional tone conveyed in textual data. The use case for this type of problem is where businesses can make informed decisions based on customer feedback, identify the sentiments of their employees,
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Sentiment analysis, a vital aspect of natural language processing, involves the application of machine learning models to discern the emotional tone conveyed in textual data. The use case for this type of problem is where businesses can make informed decisions based on customer feedback, identify the sentiments of their employees, and make decisions on hiring or retention, or for that matter, classify a text based on its topic like whether it is about a particular subject like physics or chemistry as is useful in search engines. The model leverages a sequential architecture, transforms words into dense vectors using an Embedding layer, and captures intricate sequential patterns with two Long Short-Term Memory (LSTM) layers. This model aims to effectively classify sentiments in text data using a 50-dimensional embedding dimension and 20 % dropout layers. The use of rectified linear unit (ReLU) activations enhances non-linearity, while the SoftMax activation in the output layer aligns with the multi-class nature of sentiment analysis. Both training and test accuracy were well over 80%.Full article
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Article
Achieving Maintainability, Readability & Understandability of Software Projects using Code Smell Prediction
Universal Journal of Computer Sciences and Communications
2024,
3(2),
949.
DOI: 10.31586/ujcsc.2024.949
Abstract
Maintenance of large-scale software is difficult due to large size and high complexity of code.80% of software development is on maintenance and the other 60% is on trying to understand the code. The severity of the code smells must be measured as well as fairness on it because it will
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Maintenance of large-scale software is difficult due to large size and high complexity of code.80% of software development is on maintenance and the other 60% is on trying to understand the code. The severity of the code smells must be measured as well as fairness on it because it will help the developers especially in large scale source code projects. Code smell is not a bug in the system as it doesn’t prevent the program from functioning but it may increase the risk of software failure or performance slowdown. Therefore, this paper seeks to help developers with early prediction of severity of code smells and test the level of fairness on the predictions especially in large scale source code projects. Data is the collection of facts and observations in terms of events, it is continuously growing, getting denser and more varied by the minute across different disciplines or fields. Hence, Big Data emerged and is evolving rapidly, the various types of data being processed are huge, but no one has ever thought of where this data resides, we therefore noticed this data resides in software’s and the codebases of the software’s are increasingly growing that is the size of the modules, functionalities, the size of the classes etc. Since data is growing so rapidly it also mean the codebases of software’s or code are also growing as well. Therefore, this paper seeks to discuss the 5V’s of big data in the context of software code and how to optimize or manage the big code. When we talk of "Big Code for Big Software's," we are referring to the specific challenges and considerations involved in developing, managing, and maintaining of code in large-scale software systems.Full article
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Technical Note
Systematic Research Survey on the Impact of Software Quality Measurement Scales on User Satisfaction
Universal Journal of Computer Sciences and Communications
2024,
3(1),
919.
DOI: 10.31586/ujcsc.2024.919
Abstract
A user is considered to be someone who would be actually using the system. The definition of a user is contextual and for any specific software project it depends on the software development methodology being developed. Satisfaction is the fulfillment of one’s wishes, expectations, needs or the pleasure that is
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A user is considered to be someone who would be actually using the system. The definition of a user is contextual and for any specific software project it depends on the software development methodology being developed. Satisfaction is the fulfillment of one’s wishes, expectations, needs or the pleasure that is derived from using a software product therefore “user satisfaction “is a reflection of quality from different perspective than measuring defects or code structure. Measurement in software engineering makes comparison possible and when you compare you have a choice and quality is quantified in terms of values. Therefore, this paper aims to explore the impact of software measurement scales on user satisfaction.Full article
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Review Article
Digital Forensic Investigation Standards in Cloud Computing
Universal Journal of Computer Sciences and Communications
2024,
3(1),
923.
DOI: 10.31586/ujcsc.2024.923
Abstract
Digital forensics in cloud computing environments presents significant challenges due to the distributed nature of data storage, diverse security practices employed by service providers, and jurisdictional complexities. This study aims to develop a comprehensive framework and improved methodologies tailored for conducting digital forensic investigations in cloud settings. A pragmatic research
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Digital forensics in cloud computing environments presents significant challenges due to the distributed nature of data storage, diverse security practices employed by service providers, and jurisdictional complexities. This study aims to develop a comprehensive framework and improved methodologies tailored for conducting digital forensic investigations in cloud settings. A pragmatic research philosophy integrating positivist and interpretivist paradigms guides an exploratory sequential mixed methods design. Qualitative methods, including case studies, expert interviews, and document analysis were used to explore key variables and themes. Findings inform hypotheses and survey instrument development for the subsequent quantitative phase involving structured surveys with digital forensics professionals, cloud providers, and law enforcement agencies, across the globe. The multi-method approach employs purposive and stratified random sampling techniques, targeting a sample of 100-150 participants, across the globe, for qualitative components and 300-500 for quantitative surveys. Qualitative data went through thematic and content analysis, while quantitative data were analysed using descriptive and inferential statistical methods facilitated by software such as SPSS and R. An integrated mixed methods analysis synthesizes and triangulates findings, enhancing validity, reliability, and comprehensiveness. Strict ethical protocols safeguard participant confidentiality and data privacy throughout the research process. This robust methodology contributed to the development of improved frameworks, guidelines, and best practices for digital forensics investigations in cloud computing, addressing legal and jurisdictional complexities in this rapidly evolving domain.Full article
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Article
Revolutionizing Automotive Supply Chain: Enhancing Inventory Management with AI and Machine Learning
Universal Journal of Computer Sciences and Communications
2024,
3(1),
918.
DOI: 10.31586/ujcsc.2024.918
Abstract
Consumer behavior is evolving, demanding a wide range of products with fast shipping and reliable service. The automotive aftermarket industry, worth billions, requires efficient distribution systems to stay competitive. Manufacturers strive to balance growth with product and service excellence. Distributors and retailers face the challenge of maintaining competitive pricing while
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Consumer behavior is evolving, demanding a wide range of products with fast shipping and reliable service. The automotive aftermarket industry, worth billions, requires efficient distribution systems to stay competitive. Manufacturers strive to balance growth with product and service excellence. Distributors and retailers face the challenge of maintaining competitive pricing while keeping inventory levels low. An adequate supply chain and accurate product data are crucial for product availability and reducing stock issues. This ultimately increases profits and customer satisfaction.Full article
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Article
Embedded Architecture of SAP S/4 HANA ERP Application
Universal Journal of Computer Sciences and Communications
2024,
3(1),
899.
DOI: 10.31586/ujcsc.2024.899
Abstract
The SAP HANA Application to handle operational workloads that are consistent with transactions while also supporting intricate business analytics operations. Technically speaking, the SAP HANA database is made up of several data processing engines that work together with a distributed query processing environment to provide the entire range of data
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The SAP HANA Application to handle operational workloads that are consistent with transactions while also supporting intricate business analytics operations. Technically speaking, the SAP HANA database is made up of several data processing engines that work together with a distributed query processing environment to provide the entire range of data processing capabilities. This includes graph and text processing for managing semi-structured and unstructured data within the same system, as well as classical relational data that supports both row- and column-oriented physical representations in a hybrid engine. The next-generation SAP Business Suite program designed specifically for the SAP HANA Platform is called SAP S/4HANA. The key features of SAP S/4HANA are an intuitive, contemporary user interface (SAP Fiori); planning and simulation options in many conventional transactions; simplification of business processes; significantly improved transaction efficiency; faster analytics.Full article
Review Article
Critical Success Factors of Cloud ERP in the Enterprise Business
Universal Journal of Computer Sciences and Communications
2024,
3(1),
851.
DOI: 10.31586/ujcsc.2024.851
Abstract
Both crucial success and critical failure factors are included in the current review work. The method relies on creating surveys to collect optional data. It describes the terms that are used to obtain research papers on the ERP deployment in Enterprise Business from databases and scholarly research. In order to
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Both crucial success and critical failure factors are included in the current review work. The method relies on creating surveys to collect optional data. It describes the terms that are used to obtain research papers on the ERP deployment in Enterprise Business from databases and scholarly research. In order to enhance the quality of papers, it also includes the consideration and restriction criteria. At that time, a thorough audit of the available papers is conducted to determine the impact of ERP use in Enterprise Business. Important elements are found that determine whether ERP deployments are successful or unsuccessful, as well as how they actually affect Enterprise Business (insert actual success and failure variables here aside from impact). The time span during which research publications have been evaluated limits the scope of the study presented in this paper. One implicit drawback is that it only considers the state of the art in the field of study, without taking into account an empirical investigation. Nevertheless, its findings may prove advantageous, and the directions for future research aid in expanding the field of study. This work advances the body of knowledge regarding the potential benefits and drawbacks of ERP adoption for small and medium-sized enterprises. It uses a secondary data collection strategy to identify important success factors, important failure factors, and their impact. The insights will assist Enterprise Business, Enterprise Business' stakeholders, and ERP service providers in understanding the causes of success or failure and in taking the appropriate action.Full article
Review Article
How Digital Technologies Improving Business Enterprise Applications
Universal Journal of Computer Sciences and Communications
2023,
2(1),
831.
DOI: 10.31586/ujcsc.2023.831
Abstract
The review article presents how emerging technologies improves the business enterprise applications for process management. The paper considers certain technologies of enterprise applications and justifies the updated methodological and analytical tools for assessing, selecting, and regulating business processes in a single enterprise resource planning (ERP) system. Information technology must be
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The review article presents how emerging technologies improves the business enterprise applications for process management. The paper considers certain technologies of enterprise applications and justifies the updated methodological and analytical tools for assessing, selecting, and regulating business processes in a single enterprise resource planning (ERP) system. Information technology must be used to identify products, track their movement into and out of the warehouse using code scanning technology, and streamline the product management procedure. To increase the dependability of management techniques, guarantee that the business operates flawlessly, and maintain a regular management mode, the process management form should be implemented in the enterprise management process. The implementation of digital information technology is essential for achieving effective corporate management. In addition to providing ideal operational circumstances for businesses, it is essential to analyse information technology and manage businesses economically. The foundation for implementing the enterprise applications method strategy is the creation of a process management system and an in-depth, methodical review of the enterprise as a collection of processes. Process-oriented enterprise applications should be the foundation of contemporary novel technologies for modelling business processes. It shares a tight relationship with workflow management systems (WFM), enterprise resource planning (ERP), and total quality management (TQM).Full article
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Review Article
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ISSN: 2994-7723
DOI prefix: 10.31586/ujcsc
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