International Journal of Mathematical Sciences and Computing (IJMSC)

ISSN: 2310-9025 (Print)

ISSN: 2310-9033 (Online)

DOI: https://doi.org/10.5815/ijmsc

Website: https://www.mecs-press.org/ijmsc

Published By: MECS Press

Frequency: 4 issues per year

Number(s) Available: 39

(IJMSC) in Google Scholar Citations / h5-index

IJMSC is committed to bridge the theory and practice of mathematical sciences and computing. IJMSC publishes original, peer-reviewed, and high quality articles in the areas of mathematical sciences and computing. IJMSC is a well-indexed scholarly journal and is indispensable reading and references for people working at the cutting edge of mathematical sciences and computing applications.

 

IJMSC has been abstracted or indexed by several world class databases:Google Scholar, Microsoft Academic Search, CrossRef, CNKI, Baidu Wenku,  JournalTOCs, etc..

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IJMSC Vol. 10, No. 1, Feb. 2024

REGULAR PAPERS

The Construction of two classes of 4-valent tri- Cayley Graphs over Cyclic Group

By Xiaohan Ye Huanzhi Zhang

DOI: https://doi.org/10.5815/ijmsc.2024.01.01, Pub. Date: 8 Feb. 2024

The symmetry of the graph has always been a hot topic in graph theory and the vertex-transitive graphs are a class of graphs with high symmetry. Cayley graphs which are the highly symmetrical graphs play an important role and much work has been done in the study. The tri-Cayley graph is a natural generalization of the Cayley graph. A graph is said to be a tri-Cayley graph if it admits a semiregular subgroup of automorphisms having three orbits of equal length. Koács et al. classified the cubic symmetric tricirculants in 2012 and Potočnik et al. classified the cubic vertex-transitive tricirculants in 2018. Currently, there is no research on the classification of 4-valent tri-Cayley graphs over cyclic group. In this paper, we will construct two classes of 4-valent tri-Cayley graphs over cyclic group and discuss their automorphism groups. In addition, the vertex transitivity, edge transitivity and arc transitivity are proved.

[...] Read more.
A Rigorous Euclidean Geometric Proof of the Cube Duplication Impossibility

By Alex Mwololo Kimuya

DOI: https://doi.org/10.5815/ijmsc.2024.01.02, Pub. Date: 8 Feb. 2024

This paper introduces a rigorous impossibility proof in Euclidean geometry, presenting a scrupulous demonstration of the unattainability of doubling the volume of a cube through any given procedure. The proof methodically follows the rigorous principles of classical geometry, offering clarity and insight into a longstanding mathematical challenge. The paper further emphasizes the historical misconceptions and varied solutions that have emerged due to the lack of a definitive Euclidean geometric proof. It highlights the enduring strengths, independence, and richness of Euclidean geometry while dispelling the notion that algebraic methods are the exclusive avenue to tackle geometric impossibilities. The results obtained throughout this proof solidify the position of Euclidean geometry as a potent and illuminating tool, reaffirming its pivotal role in the world of mathematics. This work contributes not only to the resolution of a specific mathematical challenge but also to the broader understanding of the unique virtues and capabilities of Euclidean geometry in tackling complex geometric problems.

[...] Read more.
Application of Mathematical Modeling: A Mathematical Model for Dengue Disease in Bangladesh

By Nazrul Islam J. R. M. Borhan Rayhan Prodhan

DOI: https://doi.org/10.5815/ijmsc.2024.01.03, Pub. Date: 8 Feb. 2024

A virus spread by mosquitoes called dengue fever affects millions of people each year and is a serious threat to world health. More than 140 nations are affected by the illness of dengue fever. Therefore, in this paper, a Susceptible-Infectious-Recovered (SIR) mathematical model for the host (human) and vector (dengue mosquitoes) has been presented to describe the transmission of dengue in Bangladesh. In the model the vector are related with two compartments that are susceptible and infective and host are related with three compartments that are susceptible, infective, and recovered. By these five compartments, five connected nonlinear ordinary differential equations (ODEs) are produced. As a result of non dimensionalization, a system of three nonlinear ODEs has been generated. The reproductive number and equilibrium points have been estimated for different cases. In order to compute the infection rate, data for infected human populations have been gathered from multiple health institutes in Bangladesh. MATLAB has been utilized to construct numerical simulations of different compartments in order to examine the impact of critical parameters on the disease’s propagation and to bolster the analytical findings. The simulated outcomes for susceptible, infected, and eliminated in graphical formats have been displayed. The paper’s main goal is to emphasize the uniqueness of computational analysis of the SIR mathematical model for the dengue fever.

[...] Read more.
An Unorthodox Trapdoor Function

By Awnon Bhowmik

DOI: https://doi.org/10.5815/ijmsc.2024.01.04, Pub. Date: 8 Feb. 2024

At the bedrock of cryptosystems lie trapdoor functions, serving as the fundamental building blocks that determine the security and efficacy of encryption mechanisms. These functions operate as one-way transformations, demonstrating an inherent asymmetry: they are designed to be easily computable in one direction, while proving computationally challenging, if not infeasible, in the opposite direction. This paper contributes to the evolving landscape of cryptographic research by introducing a novel trapdoor function, offering a fresh perspective on the intricate balance between computational efficiency and security in cryptographic protocols.
The primary objective of this paper is to present and scrutinize the proposed trapdoor function, delving into a comprehensive analysis that unveils both its strengths and weaknesses. By subjecting the function to rigorous examination, we aim to shed light on its robustness as well as potential vulnerabilities, contributing valuable insights to the broader cryptographic community. Understanding the intricacies of this new trapdoor function is essential for assessing its viability in practical applications, particularly in securing sensitive information in real-world scenarios.
Moreover, this paper does not shy away from addressing the pragmatic challenges associated with deploying the proposed trapdoor function at scale. A thorough discussion unfolds, highlighting the potential hurdles and limitations when attempting to integrate this function into large-scale environments. Considering the practicality and scalability of cryptographic solutions is pivotal, and our analysis strives to provide a clear understanding of the circumstances under which the proposed trapdoor function may encounter obstacles in widespread implementation.
In essence, this paper contributes to the ongoing discourse surrounding trapdoor functions by introducing a new entrant into the cryptographic arena. By meticulously exploring its attributes, strengths, and limitations, we aim to foster a deeper understanding of the intricate interplay between cryptographic theory and real-world applicability.

[...] Read more.
A Novel Model for Recommending Information Systems with Suitable Cloud Computing Provider

By Samah Ibrahim Abdel Aal

DOI: https://doi.org/10.5815/ijmsc.2024.01.05, Pub. Date: 8 Feb. 2024

Cloud computing has been adopted widely by information systems due to its scalability and availability of resources and services. Cloud computing can provide different types of services through internet for Information Systems (IS). There are many cloud computing providers such as Google, Microsoft, and IBM are seeking for adopting of cloud services. Selecting the suitable cloud provider can maximize the benefits of cloud services. There is a need to determine the suitable cloud computing provider to achieve organizations' goals and maximize the benefits of cloud services. This work aims to introduce a decision support model based on trapezoidal neutrosophic numbers for determining the suitable cloud computing provider. The proposed model is applied by the Zagazig University (ZU) and the results indicated that the model can provide flexible method that can handle uncertainty in decision making for detecting the suitable provider. Also, the results show that the proposed model can support information systems in the choosing the suitable cloud computing provider.

[...] Read more.
Performance Evaluation of Industrial and Commercial bank of China based on DuPont Analysis

By Qiaopeng Ma Xi Wang

DOI: https://doi.org/10.5815/ijmsc.2023.01.04, Pub. Date: 8 Feb. 2023

With the reform of Chinese economic system, the development of enterprises is facing many risks and challenges. In order to understand the state of operation of enterprises, it is necessary to apply relevant methods to evaluate the enterprise performance. Taking Industrial and Commercial Bank of China as an example, this paper selects its financial data from 2018 to 2021. Firstly, DuPont analysis is applied to decompose the return on equity into the product of profit margin on sales, total assets turnover ratio and equity multiplier. Then analyzes the effect of the changes of these three factors on the return on equity respectively by using the Chain substitution method. The results show that the effect of profit margin on sales on return on equity decreases year by year and tends to be positive from negative. The effect of total assets turnover ratio on return on equity changes from positive to negative and then to positive, while the effect of equity multiplier is opposite. These results provide a direction for the adjustment of the return on equity of Industrial and Commercial Bank of China. Finally, according to the results, some suggestions are put forward for the development of Industrial and Commercial Bank of China.

[...] Read more.
Green Computing: An Era of Energy Saving Computing of Cloud Resources

By Shailesh Saxena Mohammad Zubair Khan Ravendra Singh

DOI: https://doi.org/10.5815/ijmsc.2021.02.05, Pub. Date: 8 Jun. 2021

Cloud computing is a widely acceptable computing environment, and its services are also widely available. But the consumption of energy is one of the major issues of cloud computing as a green computing. Because many electronic resources like processing devices, storage devices in both client and server site and network computing devices like switches, routers are the main elements of energy consumption in cloud and during computation power are also required to cool the IT load in cloud computing. So due to the high consumption, cloud resources define the high energy cost during the service activities of cloud computing and contribute more carbon emissions to the atmosphere. These two issues inspired the cloud companies to develop such renewable cloud sustainability regulations to control the energy cost and the rate of CO2 emission. The main purpose of this paper is to develop a green computing environment through saving the energy of cloud resources using the specific approach of identifying the requirement of computing resources during the computation of cloud services. Only required computing resources remain ON (working state), and the rest become OFF (sleep/hibernate state) to reduce the energy uses in the cloud data centers. This approach will be more efficient than other available approaches based on cloud service scheduling or migration and virtualization of services in the cloud network. It reduces the cloud data center's energy usages by applying a power management scheme (ON/OFF) on computing resources. The proposed approach helps to convert the cloud computing in green computing through identifying an appropriate number of cloud computing resources like processing nodes, servers, disks and switches/routers during any service computation on cloud to handle the energy-saving or environmental impact. 

[...] Read more.
Concepts of Bezier Polynomials and its Application in Odd Higher Order Non-linear Boundary Value Problems by Galerkin WRM

By Nazrul Islam

DOI: https://doi.org/10.5815/ijmsc.2021.01.02, Pub. Date: 8 Feb. 2021

Many different methods are applied and used in an attempt to solve higher order nonlinear boundary value problems (BVPs). Galerkin weighted residual method (GWRM) are widely used to solve BVPs. The main aim of this paper is to find the approximate solutions of fifth, seventh and ninth order nonlinear boundary value problems using GWRM. A trial function namely, Bezier Polynomials is assumed which is made to satisfy the given essential boundary conditions. Investigate the effectiveness of the current method; some numerical examples were considered. The results are depicted both graphically and numerically. The numerical solutions are in good agreement with the exact result and get a higher accuracy in the solutions. The present method is quit efficient and yields better results when compared with the existing methods. All problems are performed using the software MATLAB R2017a.

[...] Read more.
A Decision-Making Technique for Software Architecture Design

By Jubayer Ahamed Dip Nandi

DOI: https://doi.org/10.5815/ijmsc.2023.04.05, Pub. Date: 8 Dec. 2023

The process of making decisions on software architecture is the greatest significance for the achievement of a software system's success. Software architecture establishes the framework of the system, specifies its characteristics, and has significant and major effects across the whole life cycle of the system. The complicated characteristics of the software development context and the significance of the problem have caused the research community to build various methodologies focused on supporting software architects to improve their decision-making abilities. With these efforts, the implementation of such systematic methodologies looks to be somewhat constrained in practical application. Moreover, the decision-makers must overcome unexpected difficulties due to the varying software development processes that propose distinct approaches for architecture design. The understanding of these design approaches helps to develop the architectural design framework. In the area of software architecture, a significant change has occurred wherein the focus has shifted from primarily identifying the result of the architecting process, which was primarily expressed through the representation of components and connectors, to the documentation of architectural design decisions and the underlying reasoning behind them. This shift finally concludes in the creation of an architectural design framework. So, a correct decision- making approach is needed to design the software architecture. The present study analyzes the design decisions and proposes a new design decision model for the software architecture. This study introduces a new approach to the decision-making model, wherein software architecture design is viewed based on specific decisions.

[...] Read more.
Comparison of Fog Computing & Cloud Computing

By Vishal Kumar Asif Ali Laghari Shahid Karim Muhammad Shakir Ali Anwar Brohi

DOI: https://doi.org/10.5815/ijmsc.2019.01.03, Pub. Date: 8 Jan. 2019

Fog computing is extending cloud computing by transferring computation on the edge of networks such as mobile collaborative devices or fixed nodes with built-in data storage, computing, and communication devices. Fog gives focal points of enhanced proficiency, better security, organize data transfer capacity sparing and versatility. With a specific end goal to give imperative subtle elements of Fog registering, we propose attributes of this region and separate from cloud computing research. Cloud computing is developing innovation which gives figuring assets to a specific assignment on pay per utilize. Cloud computing gives benefit three unique models and the cloud gives shoddy; midway oversaw assets for dependable registering for performing required errands. This paper gives correlation and attributes both Fog and cloud computing differs by outline, arrangement, administrations and devices for associations and clients. This comparison shows that Fog provides more flexible infrastructure and better service of data processing by consuming low network bandwidth instead of shifting whole data to the cloud.

[...] Read more.
Emoji Prediction Using Emerging Machine Learning Classifiers for Text-based Communication

By Sayan Saha Kakelli Anil Kumar

DOI: https://doi.org/10.5815/ijmsc.2022.01.04, Pub. Date: 8 Feb. 2022

We aim to extract emotional components within statements to identify the emotional state of the writer and assigning emoji related to the emotion. Emojis have become a staple part of everyday text-based communication. It is normal and common to construct an entire response with the sole use of emoji. It comes as no surprise, therefore, that effort is being put into the automatic prediction and selection of emoji appropriate for a text message. Major companies like Apple and Google have made immense strides in this, and have already deployed such systems into production (for example, the Google Gboard). The proposed work is focused on the problem of automatic emoji selection for a given text message using machine learning classification algorithms to categorize the tone of a message which is further segregated through n-gram into one of seven distinct categories. Based on the output of the classifier, select one of the more appropriate emoji from a predefined list using natural language processing (NLP) and sentimental analysis techniques. The corpus is extracted from Twitter. The result is a boring text message made lively after being annotated with appropriate text messages

[...] Read more.
Predictive Analytics of Employee Attrition using K-Fold Methodologies

By V. Kakulapati Shaik Subhani

DOI: https://doi.org/10.5815/ijmsc.2023.01.03, Pub. Date: 8 Feb. 2023

Currently, every company is concerned about the retention of their staff. They are nevertheless unable to recognize the genuine reasons for their job resignations due to various circumstances. Each business has its approach to treating employees and ensuring their pleasure. As a result, many employees abruptly terminate their employment for no apparent reason. Machine learning (ML) approaches have grown in popularity among researchers in recent decades. It is capable of proposing answers to a wide range of issues. Then, using machine learning, you may generate predictions about staff attrition. In this research, distinct methods are compared to identify which workers are most likely to leave their organization. It uses two approaches to divide the dataset into train and test data: the 70 percent train, the 30 percent test split, and the K-Fold approaches. Cat Boost, LightGBM Boost, and XGBoost are three methods employed for accuracy comparison. These three approaches are accurately generated by using Gradient Boosting Algorithms.

[...] Read more.
Machine Learning Applied to Cervical Cancer Data

By Dhwaani Parikh Vineet Menon

DOI: https://doi.org/10.5815/ijmsc.2019.01.05, Pub. Date: 8 Jan. 2019

Cervical Cancer is one of the main reason of deaths in countries having a low capita income. It becomes quite complicated while examining a patient on basis of the result obtained from various doctor’s preferred test for any automated system to determine if the patient is positive with the cancer. There were 898 new cases of cervical cancer diagnosed in Australia in 2014. The risk of a woman being diagnosed by age 85 is 1 in 167. We will try to use machine learning algorithms and determine if the patient has cancer based on numerous factors available in the dataset. Predicting the presence of cervical cancer can help the diagnosis process to start at an earlier stage.

[...] Read more.
Cyber Bullying Detection and Classification using Multinomial Naïve Bayes and Fuzzy Logic

By Arnisha Akhter Uzzal K. Acharjee Md Masbaul A. Polash

DOI: https://doi.org/10.5815/ijmsc.2019.04.01, Pub. Date: 8 Nov. 2019

The advent of different social networking sites has enabled people to easily connect all over the world and share their interests. However, Social Networking Sites are providing opportunities for cyber bullying activities that poses significant threat to physical and mental health of the victims. Social media platforms like Facebook, Twitter, Instagram etc. are vulnerable to cyber bullying and incidents like these are very common now-a-days. A large number of victims may be saved from the impacts of cyber bullying if it can be detected and the criminals are identified. In this work, a machine learning based approach is proposed to detect cyber bullying activities from social network data. Multinomial Naïve Bayes classifier is used to classify the type of bullying. With training, the algorithm classifies cyber bullying as- Shaming, Sexual harassment and Racism. Experimental results show that the accuracy of the classifier for considered data set is 88.76%. Fuzzy rule sets are designed as well to specify the strength of different types of bullying.

[...] Read more.
Ferrer diagram based partitioning technique to decision tree using genetic algorithm

By Pavan Sai Diwakar Nutheti Narayan Hasyagar Rajashree Shettar Shankru Guggari Umadevi V

DOI: https://doi.org/10.5815/ijmsc.2020.01.03, Pub. Date: 8 Feb. 2020

Decision tree is a known classification technique in machine learning. It is easy to understand and interpret and widely used in known real world applications. Decision tree (DT) faces several challenges such as class imbalance, overfitting and curse of dimensionality. Current study addresses curse of dimensionality problem using partitioning technique. It uses partitioning technique, where features are divided into multiple sets and assigned into each block based on mutual exclusive property. It uses Genetic algorithm to select the features and assign the features into each block based on the ferrer diagram to build multiple CART decision tree. Majority voting technique used to combine the predicted class from the each classifier and produce the major class as output. The novelty of the method is evaluated   with 4 datasets from UCI repository and shows approximately 9%, 3% and 5% improvement as compared with CART, Bagging and Adaboost techniques.

[...] Read more.
Performance Evaluation of Industrial and Commercial bank of China based on DuPont Analysis

By Qiaopeng Ma Xi Wang

DOI: https://doi.org/10.5815/ijmsc.2023.01.04, Pub. Date: 8 Feb. 2023

With the reform of Chinese economic system, the development of enterprises is facing many risks and challenges. In order to understand the state of operation of enterprises, it is necessary to apply relevant methods to evaluate the enterprise performance. Taking Industrial and Commercial Bank of China as an example, this paper selects its financial data from 2018 to 2021. Firstly, DuPont analysis is applied to decompose the return on equity into the product of profit margin on sales, total assets turnover ratio and equity multiplier. Then analyzes the effect of the changes of these three factors on the return on equity respectively by using the Chain substitution method. The results show that the effect of profit margin on sales on return on equity decreases year by year and tends to be positive from negative. The effect of total assets turnover ratio on return on equity changes from positive to negative and then to positive, while the effect of equity multiplier is opposite. These results provide a direction for the adjustment of the return on equity of Industrial and Commercial Bank of China. Finally, according to the results, some suggestions are put forward for the development of Industrial and Commercial Bank of China.

[...] Read more.
Concepts of Bezier Polynomials and its Application in Odd Higher Order Non-linear Boundary Value Problems by Galerkin WRM

By Nazrul Islam

DOI: https://doi.org/10.5815/ijmsc.2021.01.02, Pub. Date: 8 Feb. 2021

Many different methods are applied and used in an attempt to solve higher order nonlinear boundary value problems (BVPs). Galerkin weighted residual method (GWRM) are widely used to solve BVPs. The main aim of this paper is to find the approximate solutions of fifth, seventh and ninth order nonlinear boundary value problems using GWRM. A trial function namely, Bezier Polynomials is assumed which is made to satisfy the given essential boundary conditions. Investigate the effectiveness of the current method; some numerical examples were considered. The results are depicted both graphically and numerically. The numerical solutions are in good agreement with the exact result and get a higher accuracy in the solutions. The present method is quit efficient and yields better results when compared with the existing methods. All problems are performed using the software MATLAB R2017a.

[...] Read more.
A Review of Quantum Computing

By Arebu Dejen Murad Ridwan

DOI: https://doi.org/10.5815/ijmsc.2022.04.05, Pub. Date: 8 Oct. 2022

Quantum computing is a computational framework based on the Quantum Mechanism, which has gotten a lot of attention in the past few decades. In comparison to traditional computers, it has achieved amazing performance on several specialized tasks. Quantum computing is the study of quantum computers that use quantum mechanics phenomena such as entanglement, superposition, annealing, and tunneling to solve problems that humans cannot solve in their lifetime. This article offers a brief outline of what is happening in the field of quantum computing, as well as the current state of the art. It also summarizes the features of quantum computing in terms of major elements such as qubit computation, quantum parallelism, and reverse computing. The study investigates the cause of a quantum computer's great computing capabilities by utilizing quantum entangled states. It also emphasizes that quantum computer research requires a combination of the most sophisticated sciences, such as computer technology, micro-physics, and advanced mathematics.

[...] Read more.
An Individualized Face Pairing Model for Age-Invariant Face Recognition

By Joseph Damilola Akinyemi Olufade F. W. Onifade

DOI: https://doi.org/10.5815/ijmsc.2023.01.01, Pub. Date: 8 Feb. 2023

Among other factors affecting face recognition and verification, the aging of individuals is a particularly challenging one. Unlike other factors such as pose, expression, and illumination, aging is uncontrollable, personalized, and takes place throughout human life. Thus, while the effects of factors such as head pose, illumination, and facial expression on face recognition can be minimized by using images from controlled environments, the effect of aging cannot be so controlled. This work exploits the personalized nature of aging to reduce the effect of aging on face recognition so that an individual can be correctly recognized across his/her different age-separated face images. To achieve this, an individualized face pairing method was developed in this work to pair faces against entire sets of faces grouped by individuals then, similarity score vectors are obtained for both matching and non-matching image-individual pairs, and the vectors are then used for age-invariant face recognition. This model has the advantage of being able to capture all possible face matchings (intra-class and inter-class) within a face dataset without having to compute all possible image-to-image pairs. This reduces the computational demand of the model without compromising the impact of the ageing factor on the identity of the human face. The developed model was evaluated on the publicly available FG-NET dataset, two subsets of the CACD dataset, and a locally obtained FAGE dataset using leave-one-person (LOPO) cross-validation. The model achieved recognition accuracies of 97.01%, 99.89%, 99.92%, and 99.53% respectively. The developed model can be used to improve face recognition models by making them robust to age-variations in individuals in the dataset.

[...] Read more.
Accuracy Analysis for the Solution of Initial Value Problem of ODEs Using Modified Euler Method

By Mohammad Asif Arefin Nazrul Islam Biswajit Gain Md. Roknujjaman

DOI: https://doi.org/10.5815/ijmsc.2021.02.04, Pub. Date: 8 Jun. 2021

There exist numerous numerical methods for solving the initial value problems of ordinary differential equations. The accuracy level and computational time are not the same for all of these methods. In this article, the Modified Euler method has been discussed for solving and finding the accurate solution of Ordinary Differential Equations using different step sizes. Approximate Results obtained by different step sizes are shown using the result analysis table. Some problems are solved by the proposed method then approximated results are shown graphically compare to the exact solution for a better understanding of the accuracy level of this method. Errors are estimated for each step and are represented graphically using Matlab Programming Language and MS Excel, which reveals that so much small step size gives better accuracy with less computational error. It is observed that this method is suitable for obtaining the accurate solution of ODEs when the taken step sizes are too much small.

[...] Read more.
Green Computing: An Era of Energy Saving Computing of Cloud Resources

By Shailesh Saxena Mohammad Zubair Khan Ravendra Singh

DOI: https://doi.org/10.5815/ijmsc.2021.02.05, Pub. Date: 8 Jun. 2021

Cloud computing is a widely acceptable computing environment, and its services are also widely available. But the consumption of energy is one of the major issues of cloud computing as a green computing. Because many electronic resources like processing devices, storage devices in both client and server site and network computing devices like switches, routers are the main elements of energy consumption in cloud and during computation power are also required to cool the IT load in cloud computing. So due to the high consumption, cloud resources define the high energy cost during the service activities of cloud computing and contribute more carbon emissions to the atmosphere. These two issues inspired the cloud companies to develop such renewable cloud sustainability regulations to control the energy cost and the rate of CO2 emission. The main purpose of this paper is to develop a green computing environment through saving the energy of cloud resources using the specific approach of identifying the requirement of computing resources during the computation of cloud services. Only required computing resources remain ON (working state), and the rest become OFF (sleep/hibernate state) to reduce the energy uses in the cloud data centers. This approach will be more efficient than other available approaches based on cloud service scheduling or migration and virtualization of services in the cloud network. It reduces the cloud data center's energy usages by applying a power management scheme (ON/OFF) on computing resources. The proposed approach helps to convert the cloud computing in green computing through identifying an appropriate number of cloud computing resources like processing nodes, servers, disks and switches/routers during any service computation on cloud to handle the energy-saving or environmental impact. 

[...] Read more.
Emoji Prediction Using Emerging Machine Learning Classifiers for Text-based Communication

By Sayan Saha Kakelli Anil Kumar

DOI: https://doi.org/10.5815/ijmsc.2022.01.04, Pub. Date: 8 Feb. 2022

We aim to extract emotional components within statements to identify the emotional state of the writer and assigning emoji related to the emotion. Emojis have become a staple part of everyday text-based communication. It is normal and common to construct an entire response with the sole use of emoji. It comes as no surprise, therefore, that effort is being put into the automatic prediction and selection of emoji appropriate for a text message. Major companies like Apple and Google have made immense strides in this, and have already deployed such systems into production (for example, the Google Gboard). The proposed work is focused on the problem of automatic emoji selection for a given text message using machine learning classification algorithms to categorize the tone of a message which is further segregated through n-gram into one of seven distinct categories. Based on the output of the classifier, select one of the more appropriate emoji from a predefined list using natural language processing (NLP) and sentimental analysis techniques. The corpus is extracted from Twitter. The result is a boring text message made lively after being annotated with appropriate text messages

[...] Read more.
An Improved Security Schematic based on Coordinate Transformation

By Awnon Bhowmik Mahmudul Hasan

DOI: https://doi.org/10.5815/ijmsc.2023.02.01, Pub. Date: 8 May 2023

An earlier research project that dealt with converting ASCII codes into 2D Cartesian coordinates and then applying translation and rotation transformations to construct an encryption system, is improved by this study. Here, we present a variation of the Cantor Pairing Function to convert ASCII values into distinctive 2D Coordinates. Then, we apply some novel methods to jumble the ciphertext generated as a result of the transformations. We suggest numerous improvements to the earlier research via simple tweaks in the existing code and by introducing a novel key generation protocol that generates an infinite integral key space with no decryption failures. The only way to break this protocol with no prior information would be brute force attack. With the help of elementary combinatorics and probability topics, we prove that this encryption protocol is seemingly infeasible to overcome by an unwelcome adversary.

[...] Read more.
Predictive Analytics of Employee Attrition using K-Fold Methodologies

By V. Kakulapati Shaik Subhani

DOI: https://doi.org/10.5815/ijmsc.2023.01.03, Pub. Date: 8 Feb. 2023

Currently, every company is concerned about the retention of their staff. They are nevertheless unable to recognize the genuine reasons for their job resignations due to various circumstances. Each business has its approach to treating employees and ensuring their pleasure. As a result, many employees abruptly terminate their employment for no apparent reason. Machine learning (ML) approaches have grown in popularity among researchers in recent decades. It is capable of proposing answers to a wide range of issues. Then, using machine learning, you may generate predictions about staff attrition. In this research, distinct methods are compared to identify which workers are most likely to leave their organization. It uses two approaches to divide the dataset into train and test data: the 70 percent train, the 30 percent test split, and the K-Fold approaches. Cat Boost, LightGBM Boost, and XGBoost are three methods employed for accuracy comparison. These three approaches are accurately generated by using Gradient Boosting Algorithms.

[...] Read more.
Future Possible Age of the Universe with Density Variation

By Oishi Khanam Md. Nirab Hossain Md. Showkat Ali

DOI: https://doi.org/10.5815/ijmsc.2022.04.07, Pub. Date: 8 Oct. 2022

A fundamental principle and assumption of cosmology says that the universe is homogeneous and isotropic when viewed on a large scale. According to the cosmological principle, space might be flat, or have a negative or positive curvature in cosmological model. Positively curved universe denotes the closed universe and negatively curved universe denotes the open universe. Our universe type is flat because it expands in every direction neither curving positively nor negatively. We have observed that the progression of the universe is based on radiation and matter domination. In this paper we also have observed that future possible upper limit age of the universe is 9.4203×〖10〗^10 years which varies with density.

[...] Read more.