International Journal of Mathematical Sciences and Computing @ijmsc
Статьи журнала - International Journal of Mathematical Sciences and Computing
Все статьи: 258
Статья научная
Standard collocation (SCM) and perturbed collocation (PCM) are utilized as effective numerical techniques for solving fractional-order differential equations (FODEs) which focus on constructing orthogonal polynomials to serve as basis functions for approximating the solutions to these equations. The approach began by assuming an approximate solution, expressed in the constructed orthogonal polynomials. These assumed solutions were then substituted into the original FODEs. Following this, the problem was converted into a system of algebraic linear equations by collocating the equations at evenly spaced interior points. Numerical examples and the results indicated that the SCM and PCM are easy, efficient, and in good agreement compared with some existing methods and the results presented in the tables and graphs unequivocally demonstrate the efficacy of the proposed methods in solving fractional-order differential equations, yielding solutions of remarkable accuracy. However, the SCM and PCM exhibit comparable accuracy, making it difficult to identify a single superior approach, we conclude that both the proposed methods are effective and viable options for solving fractional order differential equations.
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Design Approaches for a Novel Reversible 4-bit Comparator
Статья научная
Reversible logic has shown considerable acceptance and growth in the research fields like quantum computing, Nano computing and optical computing promising lower power dissipation. This paper proposes an optimised design single-bit reversible comparator called SKAR gate with a purpose of reducing quantum cost. Besides, this novel SKAR gate is used as a single-bit reversible comparator to construct an optimised design for a four-bit reversible comparator. The paper discusses two designs, one with the use of SKAR gate and other one using a derivative gate constructed from SKAR gate. Since the reversible logic aims at reducing the value of its fundamental parameters viz. quantum cost, garbage outputs, ancillary inputs, delay and number of gates; Both the proposed designs for single-bit and four-bit reversible comparator are compared with other existing designs on the basis of elementary parameters of reversible logic.
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Design and Development of Multidimensional Chaotic Maps with Genetic Operator
Статья научная
Security of a digital image can be achieved in number of ways including image Encryption and Decryption. Encryption technique tries to convert a plain image into the cipher image which is hard to understand. The decryption technique tries to convert a cipher image into the plain image. The image encryption is done inorder to provide security from attacks. In this work we aim to develop an image encryption technique based on multidimensional chaotic map with genetic operator. One of the powerful features of genetic operator is crossover which is used to confuse the pixels of the image. A combination of multidimensional chaotic maps, namely, Logistic, Henon and Chebyshev will be used to generate pseudorandom sequence which will be XOR'ed to obtain an unpredictable sequence. This sequence will be then applied to the Crossover unit and upon XOR'ed to obtain an encrypted image. Later the same upredictable sequence is generated while decrypting the image. By combining the entire different dimensional chaotic map namely Logistic, Henon, Chebyshev map along with the gentic operator called crossover will enhance the extra security to the digital image.
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Desirable Dog-Rabies Control Methods in an Urban setting in Africa -a Mathematical Model
Статья научная
Rabies is a fatal, zoonotic, viral disease that causes an acute inflammation of the brain in humans and other mammals. It is transmitted through contact with bodily fluids of infected mammals, usually via bites or scratches. In this paper, we formulate a deterministic model which measures the effects of different rabies control methods (mass-culling and vaccination of dogs) for urban areas near wildlife, using the Arusha region in Tanzania as an example. Values for various parameters were deduced from five years’ worth of survey data on Arusha’s dog population. Data included vaccination coverage, dog bites and rabies deaths recorded by a local non-governmental organization and the Ministry of Agriculture, Livestock Development and Fisheries of the United Republic of Tanzania. The basic reproduction number R_0 and effective reproduction number Re were computed and found to be 1.9 and 1.2 respectively. These imply that the disease is endemic in Arusha. The numerical simulation of the reproduction number shows that vaccination is the most appropriate control method for rabies transmission in urban areas near wildlife reservoirs. The disease free equilibrium ε_0 is also computed. If the effective reproduction number R_e is computed and found to be less than 1, it implies that it is globally asymptotically stable in the feasible region Φ. If R_e> 1 it is implied that there is one equilibrium point which is endemic and it is locally asymptotically stable.
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Статья научная
The article provides a method for determining some of the operational characteristics of the information search engine in the Directive document database. During this time the life cycle of the system was studied, the schedule of time dependence of the system interruptions intensity was studied. The article states that although there are many interruptions and malfunctions at the start of operation, they are rapidly decreasing over time, and the interruption during the system's normal operation period is random. During the last wear and breakdown of system operation, the intensity of interruptions begins to increase. It also lists one of the possible structures of information search engine relationships. In practice, the basic structure of medium-sized information search engine relations in directive document databases can be represented in the article. Although the Database is located on a local network, the system may have different sources of information and can be located both on the local network and on the global Internet. Monitoring of information search engine operations is organized on the system server. According to the monitoring results, some operational characteristics of the system are calculated and refined over time. During the monitoring process, various operating characteristics are calculated, starting with the commissioning of the system. This includes the total number of queries, the number of successful and failed surveys, the time intervals between different types of surveys and survey results. such as settings. These parameters calculate the experimental operation characteristics of the information search engine in the directive document database. The calculated characteristics become clearer with time and approach their theoretical estimates. Therefore, it will take some time before the practical results are obtained. However, the results obtained in the article can be used successfully from the start of system operation.
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Determination of Optimal Smoothing Constants for Foreign Remittances in Bangladesh
Статья научная
Remittance is the tie that is sent to the country by earning money from abroad. In present Bangladesh, remittance is playing an important role in increasing reserves and revenue. For about two decades remittance has been contributing a huge portion of export earnings. Remittances have a significant impact on the budget of Bangladesh and also the budget depends a lot on remittances. So it is very crucial to know the future remittance to make an annual budget for upcoming year. This paper concentrates on choosing the appropriate smoothing constants for foreign remittances forecasting by Holt’s method. This method is very popular quantitative skilled in forecasting. The forecasting of this deftness depends on optimal smoothing constants. So, choosing an optimal smoothing constant is very important to minimize the error of forecasting. We have demonstrated the techniques by presenting actual remittances and also presented graphical comparisons between actual and forecasting remittances for the optimal smoothing constants.
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Development of a secure SMS application using Advanced Encryption Standard (AES) on android platform
Статья научная
When we live in a global village, then maintaining privacy and confidentiality becomes reasonably challenging. Short Message Service (SMS) is the oldest application for exchanging messages between communicating parties in cellular network used by mobile phones. These messages are encrypted over-the-air with A5/1 algorithm and stored as clear text at network operator. Recent developments have shown that this algorithm is not secure any more. Compromising an access to network operator registers gains access to SMS also. Current scenarios of hacks and exploitation demands confidentiality, and encryption is one of the techniques, which is used, in this subsequent project of designing a secure SMS android application. Cryptographic manipulation of the data is performed using AES 128 -bit algorithm to secure the data, which is essential to us and the safe transmission of confidential data over the GSM network. AES (Advanced Encryption Standards) algorithm is the considered impregnable even to super computers brute force attacks. The AES algorithm technique uses very befuddled and sporadic encryption making data impregnable to attackers or hackers. This android app will allow the user to encrypt and decrypt the SMS (Short Message Service) efficiently and just at one click. Subsequent explanation is given afterwards.
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Development of an Effective Method of Data Collection for Advertising and Marketing on the Internet
Статья научная
The Internet advertising has more capabilities than other advertising tools. Taking into consideration the broad spectrum of the Internet, the study of the effectiveness indicators of the Internet advertising and the identification of problems in this field are considered to be topical issues. The article analyzes the key effectiveness indicators (KEA) to evaluate the effectiveness of the Internet advertising. Moreover, proposals for the effective use of advertising and marketing systems are also provided. Reducing the number of indicators to simplify the effective collection and analysis of the effectiveness indicators of Internet advertising can be promising. In this regard, some statistical and spectral operations are performed on the efficiency values, and effectiveness signs vector is determined. The Euclidean distance between these vectors is seen as the closeness between the two performance measures. The difference from other methods lies in the collection and distribution in the storage area, the distribution of data by the subsystem in the appropriate analysis systems. The processed information consists of numerical, temporary, logical and text data. The article uses a systematic approach and methodology for the scientific analysis of problems and ways to solve them, as well as for summing up
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Статья научная
Stroke prediction is paramount in healthcare to enable timely intervention and reduce the burden of this devastating condition. This research paper examines the prediction of strokes using machine learning methods, aiming to enhance accuracy and efficiency in risk assessment. Numerous Machine Learning (ML) techniques, such as Support Vector Machine (SVM), XGBoost, Random Forest, Linear Regression, and Gaussian Naive Bayes, are explored using a comprehensive dataset containing patient demographics, medical history, lifestyle factors, and clinical measurements. Based on different ML models, an Enhanced Stroke Prediction Model (ESPM) is proposed. Grid search, Randomized search, and Bayesian optimization are employed as hyperparameter tuning techniques, and parameters like accuracy, precision, recall, and F1 score are analyzed. It is observed that SVM with Grid Search hyperparameter tunning performs well with an accuracy of 94.129%; Positive Predictive Value (PPV), True Positive Rate(TPR), and F1 Score achieved are 89%, 94%, and 91%, respectively. The outcomes demonstrate the suitability of these models for different aspects of stroke prediction, such as handling complex patterns, capturing non-linearity, robustness to noisy data, and modeling continuous risk scores.
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EUR/USD Exchange Rate Prediction Using Machine Learning
Статья научная
Nowadays artificial intelligence is used in almost every sector of our day-to-day life. AI is used in preventative maintenance, quality control, demand forecasting, rapid prototyping, and inventory management among other places. Also, its use in the economic market has gained widespread. The use of artificial intelligence has made a huge contribution to price forecasting in the currency market or the stock market. This research work explores and analyzes the use of machine learning techniques as a linear regression in the EUR/USD exchange rate in the global forex market to predict future movements and compare daily and hourly data forecasts. As a reason for comparison, linear regression was applied in both hourlies and daily's almost equivalent data sets of the EUR/USD exchange rate and showed differences in results. Which has opened a new door of research on this market. It has been found that the percentage of accuracy of the daily data forecast is higher than the hourly data forecast at the test stage.
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Edge stable sets and secured edge stable sets in hypergraphs
Статья научная
In this paper, we have proved several results regarding edge stable sets and maximal edge stable sets in hypergraphs. We have also proved various results regarding edge stable sets and maximal edge stable sets in partial subhypergraphs. We have introduced the concept of secured edge stable set, maximum secured edge stable set and i_(s )^1- Set in this paper and proved several results about them.
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Effect Neural Networks on Selected Feature by Meta Heuristic Algorithms
Статья научная
Feature selection is one of the issues that have been raised in the discussion of machine learning and statistical identification model. We have provided definitions for feature selection and definitions needed to understand this issue, we check. Then, different methods for this problem were based on the type of product, as well as how to evaluate candidate subsets of features, we classify the following categories. As in previous studies may not have understood that different methods of assessment data into consideration, We propose a new approach for assessing similarity of data to understand the relationship between diversity and stability of the data is selected. After review and meta-heuristic algorithms to implement the algorithm found that the cluster algorithm has better performance compared with other algorithms for feature selection sustained.
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Efficient Optimization of Edge Server Selection Technique in Content Delivery Network
Статья научная
Cloud Computing provides the infrastructure as a "Cloud" from which businesses and users are permit to access applications from anywhere in the world on demand. Thus, the computing world is rapidly transforming towards developing software for millions to consume as a service, rather than to run on their individual computers. But many users could not satisfy on cloud services completely due to their uncovering security purpose for handling large numbers of data. Even the network becomes uncontrollable, when large numbers of user's request to the server create network congestion and data losses vigorously. Content Delivery Network OR CDN is an eminent solution of this problem. Our objective is to create optimized method for edge selection technique in Content Delivery Network to deliver and direct the user request to the nearest edge server and establish the connection between them and transfer the respective content
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Emoji Prediction Using Emerging Machine Learning Classifiers for Text-based Communication
Статья научная
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
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Статья научная
Mobile phones and handsets enable us to communicate our voice, data and video messages with individuals that are far-off from us. When an active call is initiated by someone using a mobile phone, it is transmitted through a nearby Base Station (BS) transmitter to another BS until the call gets to its intended receiver. Any time a caller initiates and loses a connection to a BS while on conversation, the call is said to be dropped. The initiation and completion of an active call without any form of disconnection or termination is a key service quality parameter in telecommunication system networks. Robust statistical estimation, modelling and characterization of call drop rates is of high importance to the network operators and radio frequency engineers for effective re-planning and performance management process of telecommunication system networks. This work was designed to determine the optimal probability distribution model for drop call rates based on a five week acquired rate of drop calls data sample in the Southern regions of Nigeria. To accomplish the aim, eight probability distributions namely logistic, log-logistic, normal, log-normal, exponential, Rayleigh, rician and Gumbel max were explored and based on the combined scores of three goodness of fit statistical tests, the log-logistic distribution was found to be the optimal probability distribution for the weekly rate of drop call prognostic analysis. The results could be of immense assistance to radio frequency engineers for optimal statistical modelling and design of cellular systems channels.
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Energy Efficient Multipath Routing in Zone-based Mobile Ad-hoc Networks: Mathematical Formulation
Статья научная
A wireless mobile ad hoc network (MANET) is a dynamic network that can be built without the need for any central governance system and pre-existing infrastructure, in which each node can act as a router. During the transmission of information in any network, energy consumption is an important factor for the efficiency and lifetime of the network. A reduction in energy consumption is achieved by detecting the energy consumption at the node at each stage of transmission. The main objective of this paper is to formulate mathematical models of energy consumption. A mathematical model of the energy consumption of a network is to be built on the basis of available nodes and links to formulate mathematical models related to energy. When constructing this mathematical model for the challenge related to mobility and low connectivity due to limited battery power in the network, the failure of the links present in the network and the estimated energy consumption are taken into account. Due to the greater mobility of this type of network, nodes rapidly change their positions, causing nodes to drain the battery very quickly, thus reducing network performance. So we need a mathematical model which helps in developing a mathematical model after developing a conceptual model. Which helps in predicting the quantitative behavior of a system. Weaknesses and strengths of a model can be identified from the quantitative results of a mathematical model.
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Enhanced E-recruitment using Semantic Retrieval of Modeled Serialized Documents
Статья научная
Retrieval in existing e-recruitment system is on exact match between applicants' stored profiles and inquirer's request. These profiles are captured through online forms whose fields are tailored by recruiters and hence, applicants sometimes do not have privilege to present details of their worth that are not captured by the tailored fields thereby, leading to their disqualification. This paper presents a 3-tier system that models serialized documents of the applicants' worth and they are analyzed using document retrieval and natural language processing techniques for a human-like assessment. Its presentation tier was developed using java server pages and middle tier functionalities using web service technology. The data tier models résumés that have been tokenized and tagged using Brill Algorithm with my sequel. Within the middle tier, indexing was achieved using an inverted index whose terms are noun phrases extracted from résumés that have been tokenized and tagged using Brill Algorithm.
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Evaluating the impact of Test-Driven Development on Software Quality Enhancement
Статья научная
In the software development industry, ensuring software quality holds immense significance due to its direct influence on user satisfaction, system reliability, and overall end-users. Traditionally, the development process involved identifying and rectifying defects after the implementation phase, which could be time-consuming and costly. Determining software development methodologies, with a specific emphasis on Test-Driven Development, aims to evaluate its effectiveness in improving software quality. The study employs a mixed-methods approach, combining quantitative surveys and qualitative interviews to comprehensively investigate the impact of Test-Driven Development on various facets of software quality. The survey findings unveil that Test-Driven Development offers substantial benefits in terms of early defect detection, leading to reduced costs and effort in rectifying issues during the development process. Moreover, Test-Driven Development encourages improved code design and maintainability, fostering the creation of modular and loosely coupled code structures. These results underscore the pivotal role of Test-Driven Development in elevating code quality and maintainability. Comparative analysis with traditional development methodologies highlights Test-Driven Development's effectiveness in enhancing software quality, as rated highly by respondents. Furthermore, it clarifies Test-Driven Development's positive impact on user satisfaction, overall product quality, and code maintainability. Challenges related to Test-Driven Development adoption are identified, such as the initial time investment in writing tests and difficulties adapting to changing requirements. Strategies to mitigate these challenges are proposed, contributing to the practical application of Test-Driven Development. Offers valuable insights into the efficacy of Test-Driven Development in enhancing software quality. It not only highlights the benefits of Test-Driven Development but also provides a framework for addressing challenges and optimizing its utilization. This knowledge is invaluable for software development teams, project managers, and quality assurance professionals, facilitating informed decisions regarding adopting and implementing Test-Driven Development as a quality assurance technique in software development.
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Evidential paradigm and SAD systems: features and peculiarities
Статья научная
Research on automated reasoning systems based on a number of paradigms that support human activity in formalized text processing began in the late 1950s – early 1960s, when computer performance and memory space became sufficient for programming of complex intelligent processes. The so-called evidential paradigm was among them and it can be viewed as a way for integrating all reasonable paradigms oriented to the development of computer languages for representing formalized texts in the form most suitable for a user, formalization and development of the evidence of a computer-made proof step, creation of the information environment having influence on a current evidence of a machine proof step, and an active human-machine interaction. This work contains a brief description of the evidential paradigm and its implementation in the form of intelligent systems intended for the symbolic and deductive processing of mathematical texts focusing main attention on their features and peculiarities.
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Exact Analytical Solution of Boundary Value Problem in a Form of an Infinite Hypergeometric Series
Статья научная
This paper proposes an exact solution of the classical Graetz problem in terms of an infinite series represented by a nonlinear partial differential equation considering two space variables, two boundary conditions and one initial condition. The mathematical derivation is based on the method of separation of variables whose several stages were illustrated to reach the solution of the Graetz problem.
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