International Journal of Mathematical Sciences and Computing @ijmsc
Статьи журнала - International Journal of Mathematical Sciences and Computing
Все статьи: 264
Enhanced Hybrid Pseudo Random Number Generator – Chaotic HPRNG
Статья научная
Pseudo Random Number Generators (PRNGs) are deterministic and periodic in nature. Hybrid Pseudo Random Number Generators (HPRNGs) address some limitations by using time-based seeding with a modified Linear Congruential Generator (LCG). While HPRNGs improve upon the deterministic nature by using dynamic time-based seeds, they still suffer from periodicity and potential seed-related issues. This study addresses the deterministic nature further as well as the periodicity of PRNGs by proposing an enhanced HPRNG, making it more suitable for high-security applications.
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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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Ferrer diagram based partitioning technique to decision tree using genetic algorithm
Статья научная
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.
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Fixed Point Results in the Fuzzy Multiplicative Metric Spaces and Application
Статья научная
This paper presents the development of fuzzy multiplicative metric spaces, an extended framework that combines the principles of multiplicative metric spaces with fuzzy logic to better address uncertainty and imprecision inherent in many real-world problems. By replacing additive distance measures with multiplicative ones, this approach proves particularly effective in contexts where relative variations or proportional relationships are more meaningful than absolute differences. Within this generalized setting, we establish a series of fixed-point theorems of Banach, Kannan, and Chatterjee types, along with related corollaries, each supported by concrete examples. The theoretical results are further validated through their application to the solution of nonlinear integral equations, demonstrating the versatility and applicability of the proposed framework across mathematical analysis and applied disciplines.
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Forecasting Natural Gas Prices Using Nonlinear Autoregressive Neural Network
Статья научная
When forecasting time series, It was found that simple linear time series models usually leave facets of economic and financial unknown in the forecasting time series due to linearity behavior, which remains the focus of empirical and applied study. The study suggested the Nonlinear Autoregressive Neural Network model and a comparison was made using the ARIMA model for forecasting natural gas prices, as obtained from the analysis, NAR models were better than the completed ARIMA model, measured against three performance indicators. The decision criterion for the selection of the best suited model depends on MSE, RMSE and R2. From the results of the criterion it has found that both the models are providing almost closed results but NAR is the best suited model for the forecasting of natural gas prices.
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Forecasting the Environmental Situation at Mining Company Treatment Facilities Based on Fuzzy Logic
Статья научная
This study analyzes wastewater treatment processes at a mining company in the Almaty region, Kazakhstan. Four treatment schemes were developed and assessed, with a focus on optimizing efficiency. The discharged water quality from different technological lines was evaluated using integral functions for a quantitative comparison of each scheme's performance. Additionally, an expert system was developed to validate the results and support future research in wastewater treatment.
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Future Possible Age of the Universe with Density Variation
Статья научная
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.
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Статья научная
Regression testing is used to check that changes in the some functionality of the software to not affect its old behaviours. Test case prioritization is essential for reducing the cost of regression testing. In this paper a test cases prioritization model based on fuzzy logic is presented. State machine diagram is used to capture the behaviour of the system. Risk information is associated with the states. After change in the functionality of the system new state machine diagram is designed. This new state machine diagram is converted into Weighted Extended Finite State Machine (WEFSM). Weights are assigned to nodes and edges based on change and risk exposure. Risk exposure and change information of each test case is used as input to fuzzy model. Test cases are categorized in retestable, reusable and obsolete.
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Generalized Algorithm on idiosyncrasy of Numbers
Статья научная
In this paper, using computer algebra system a new generalized algorithm is developed to study and generalize the Kaprekar’s operation which can be used for desired numbers of iterations and is also applicable to any n-digits number which is greater than or equal to two. Existing relevant results are verified with the available results in literature and further extended to examine the difference (kernel) of the obtained number during the process with the number obtained in preceding iteration after each step. Sum of the digits of an acquired number obtained after each step is also noticed and found that sum of its digits is divisible by 9. A detailed investigation is conducted for all two-digit number and the output acquired is exhibited in tabular form which has not been studied in earlier. An 8-digits number also considered and found that it does not converges to a unique kernel like 3-digits and 4-digits, but follows a regular pattern after initial iteration. Analytical illustrations are provided along with pictorial representations for 2-digits, 3-digits 4-digits and 8-digits number. This algorithm can further be employed for numbers having any number of digits.
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Graph Dynamic Threshold Model Resource Network: Key Features
Статья научная
In this paper, we describe a graph dynamic threshold model called resource network, and briefly present the main results obtained during several years of research. Resource Network is represented by a connected oriented with weighted graph with an arbitrary topology. Weights of edges denote their throughput capacities for an abstract resource. The resource is stored in vertices, which can contain its unlimited amount. Network operates in discrete time. The total amount of resource is constant, while pieces of resource are reallocating among vertices every time step, according to certain rules with threshold switching. The main objective of our research is to define for a network with an arbitrary topology all its basic characteristics: the vectors of limit state and flow for every total amount of resource W; the threshold value of total recourse T, which switches laws of operating of the network; description of these laws. It turned out that there exists several classes of networks depending on their topologies and capacities. Each class demonstrates fundamentally different behavior. All these classes and their characteristics will be reviewed below.
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Green Computing: An Era of Energy Saving Computing of Cloud Resources
Статья научная
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.
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Handling Numerical Missing Values Via Rough Sets
Статья научная
Many existing industrial and research data sets contain missing values. Data sets contain missing values due to various reasons, such as manual data entry procedures, equipment errors, and incorrect measurements. It is usual to find missing data in most of the information sources used. Missing values usually appear as "NULL" values in the database or as empty cells in the spreadsheet table. Multiple ways have been used to deal with the problem of missing data. The proposed model presents rough set theory as a technique to deal with missing data. This model can handle the missing values for condition and decision attributes, the web application was developed to predict these values.
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Hive-Based Data Encryption for Securing Sensitive Data in HDFS
Статья научная
Big Data is a new class of technology that gives businesses more insight into their massive data sets, allowing them to make better business decisions and satisfy customers. Big data systems are also a desirable target for hackers due to the aggregation of their data. Hadoop is used to handle large data sets through reading and writing application programs on a distributed system. Hadoop Distributed File System is used to store massive data. Since HDFS does not safeguard data privacy, encrypting the file is the right way to protect the stored data in HDFS but takes a long time. In this paper, regarding privacy concerns, we use different compression-type data storage file formats with the proposed user-defined function (XOR-Onetime pad with AES) to secure data in HDFS. In this way, we provide a dual level of security by masking the selective data and whole data in the file. Our experiment demonstrates that the whole process time is significantly smaller than that of a conventional method. The proposed UDF with ORC, Zlib file format gives 9-10% better performance results than 2DES and other methods. Finally, we decreased the load time of secure data and significantly improved query processing time with the Hive engine.
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Статья научная
The amount of data that is transmitted across the internet is continuously increasing. With the transmission of this huge volume of data, the need of an encryption algorithm that guarantees the data transmission speedily and in a secure manner is a must. Hence, to achieve security in wireless networks, cryptography plays a very important role. In this paper, several hybrid combinations, which combines both symmetric and asymmetric cryptographic techniques to offer high security with minimum key maintenance is presented. This hybrid combination offers several cryptographic primitives such as integrity, confidentiality and authentication, thereby enhancing the security. Various combinations of Advanced Encryption Standard (AES), Elliptical Curve Cryptography (ECC) and Rivest, Shamir and Adleman (RSA) algorithms are used to provide hybrid encryption. Secure Hash Algorithm (SHA-256) is also used to provide authentication and integrity. The experimental results show that the proposed hybrid combinations gives better performance in terms of computation time compared to individual cryptographic schemes.
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Статья научная
This research focuses on developing an automated framework for evaluating distress on flexible and rigid pavement surfaces through deep learning and algorithms, enhancing infrastructure monitoring by efficiently identifying, assessing, and measuring road distresses. The methodology begins with identifying road stretches from ground-level images, followed by capturing photos of distresses and applying algorithms to measure their dimensions accurately. A YOLOv5 model is developed to evaluate the length and width of identified distresses, with an exploration of the relationship between camera position and measurement accuracy. Physical measurements using tape are employed for validation, ensuring that the automated results align with real-world dimensions. Results indicate that the average errors of 26.1% for length and 26.9% for width for flexible pavement and the average percentage error in length is about 29% and average percentage error in width is about 1% for rigid pavement. This highlights the importance of precise measurements for effective road rehabilitation. The integration of computer vision in road maintenance, validated through physical measurements, promises significant improvements in the accuracy, efficiency, and resilience of road networks.
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Implementation of Fast and Efficient Mac Unit on FPGA
Статья научная
Floating-point arithmetic operations on digital systems have become an important aspect of research in recent times. Many architecture have been proposed and implemented by various researchers and their merits and demerits are compared. Floating point numbers are first converted into the IEEE 754 single or double precision format in order to be used in the digital systems. The arithmetic operations require various steps to be followed for the correct and accurate steps. In the proposed approach a fast and area efficient Carry Select Adder are implemented along with the parallel processing of various units used in the architecture. The result also verifies the proposed approach that shows a decrement of 27 % in the combinational path delay with an increment of around 8% in the number of LUTs used.
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Статья научная
The mortuary industry in most developing countries are in need of improvement on the receiving and releasing of deceased persons. Paper-based mortuary systems lack reliability, timely information retrieval, accountability, data security and access control; compared to computer-based, mortuaries are the norm in advanced countries. This study reports the development of a fingerprint-based biometric mortuary system for deceased identification and claiming. The system design methodology was based on the object-oriented analysis and design approach using the UML. The system was implemented with Java as the frontend and processing logic, interacting with MySQL Server at the backend for transaction management. As generated from the University of Calabar Teaching Hospital Calabar, the result of this study shows that, with the fingerprint verification technique, mortuary establishments in Nigeria and related countries can enhance the deceased claimant verification process to avoid releasing the deceased to wrong persons and reduce deceased identification anomalies. The study has shown that biometrics technology can enhance deceased identification and release in resource-constrained settings like Nigeria.
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Inhomogeneous Assessment of New Mechanism of Adaptive Detection of Partially-correlated χ2-Targets
Статья научная
Owing to its merits in fluctuating radar targets detection, the scenario of fusion structure has rapidly become a methodology of choice. The base goal of this paper is to analyze the linear type of this methodology, which is termed as linear fusion (LF). The target of interest along with fallacious ones is assumed to be fluctuating obeying χ2-model of two-degrees of freedom in their fluctuation, with particular attention on partially-correlated target returns. Closed-form expression is derived for the detection performance of the proposed processor. The analytical results are validated with computer simulation. Our simulation results demonstrate that the LF model yields impressive detection performance in terms of detection performance and CFAR loss, in comparison with the conventional schemes in the case where the operating environment is free of or contaminated with interferers. Additionally, the LF homogeneous performance outweighs that of Neyman-Pearson (N-P) detector, which is the yardstick of the CFAR world. Moreover, the LF structure has the capability of holding the rate of false alarm fixed against the presence of interferers. The ability to obtain improved performance compared to existing models is the major contribution of this research.
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