Статьи журнала - International Journal of Mathematical Sciences and Computing
Все статьи: 198
A 4-D HyperChaotic DNA Encryption/Decryption Algorithm for Securing Students Data System
Статья научная
Data security has become a significant issue nowadays with the increase of information capacity and its transmission rate. The most common and widely used techniques in the data security fields is cryptography. Cryptography is the process of concealing and transmitting data in an appropriate format, so that only authorized people can access and process it. The main goal of the cryptographic process is protecting data from being hijacked and altered. This paper proposes an algorithm for encrypting data through the use of Deoxyribo Nucleic Acid (DNA) sequence and four-dimensional hyper chaotic system. Whereby, the hyper chaotic system is applied to generate a binary sequence which is later passed to a permutation function for the key generation of the first level encryption. The proposed encryption algorithm includes several intermediate steps, which are binary-coded form and the generation of arbitrary keys. Experimental results were analyzed by calculating encryption time, key generation time, histogram and correlation coefficient entropy. Furthermore, the proposed text encryption algorithm is implemented on two different students’ datasets to improve the security of educational systems. Finally, experimental and comparative studies have shown that, the proposed encryption algorithm reported a uniform encrypted text distribution and correlation coefficient values nearer to ‘0’, which are close to the theoretical optimal value.
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A Comparative Analysis among Online and On-Campus Students Using Decision Tree
Статья научная
COVID-19 hit the world unexpectedly, forcing humans to isolate themselves. It has placed the lives of people in jeopardy with its fury. The global pandemic had a detrimental effect on the worlds' education spheres. It has imposed a global lockdown, with a negative impact on the students' lives. Continuing regular classes on-campus was out of the question. At that moment, online learning came to us as a savior. The quality of online education was yet to be tested on a large scale compared to regular schooling. Educational data mining is a modern arena that holds promise for those who work in education. Data mining strategies are developed to uncover latent information and identify valuable trends that can increase students' performance and, in turn, contribute to the improvement of the educational system in the long run. This research mainly aims to identify a comparative analysis of the students' academic performance between online and on-campus environments and distinguish the significant characteristics that influence their academic endeavors. The impact of the factors on the students' performance is visualized with the help of the Decision Tree Classification Model. This paper will assist in giving a good overview that influences the distinguished factors on students' academic performance. Moreover, educators will also be benefited from this paper while making any important decision regarding the educational activity.
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Статья научная
The majority of failure cases may occur because of the wrong selection of inappropriate material in the manufacture of wind turbine blades. Composites are used to increase reliability and reduce wind turbine manufacturing costs. Therefore, this research focuses on comparing the use of Epoxy S-Glass UD and Epoxy Carbon UD as manufacturing materials for wind turbine blades using 3D finite element analysis; to find out which of these materials have the best performance for its use as a manufacturing material for wind turbine blades. The distribution of Von Mises stresses in wind turbine blade models was investigated using Epoxy S-Glass UD and Epoxy Carbon UD under the wind loads that affect the blade of the turbine. The results showed that the value of the maximum stresses in the epoxy glass model was 3.495 × 107 Pa, while this value was in the epoxy carbon model 4.0494 × 107 Pa. As for the value of the minimum stresses, it was in the epoxy glass model 7431.8 Pa, while the value in another material model 17323 Pa. Therefore, it is not recommended to use Epoxy Carbon UD as a manufacturing material for wind turbine blades, but it is recommended to use Epoxy S-Glass UD, which reduces induced stresses and thus to prolong its lifespan.
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A Fast Heuristic Algorithm for Solving High-Density Subset-Sum Problems
Статья научная
The subset sum problem is to decide whether for a given set of integers A and an integer S, a possible subset of A exists such that the sum of its elements is equal to S. The problem of determining whether such a subset exists is NP-complete; which is the basis for cryptosystems of knapsack type. In this paper a fast heuristic algorithm is proposed for solving subset sum problems in pseudo-polynomial time. Extensive computational evidence suggests that the algorithm almost always finds a solution to the problem when one exists. The runtime performance of the algorithm is also analyzed.
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Статья научная
Today unauthorized access to sensitive information and cybercrimes is rising because of increasing access to the Internet. Improvement in software and hardware technologies have made it possible to detect some attacks and anomalies effectively. In recent years, many researchers have considered flow-based approaches through machine learning algorithms and techniques to reveal anomalies. But, they have some serious defects. By way of illustration, they require a tremendous amount of data across a network to train and model network’s behaviors. This problem has been caused these methods to suffer from desirable performance in the learning phase. In this paper, a technique to disclose intrusions by Support Vector Regression (SVR) is suggested and assessed over a standard dataset. The main intension of this technique is pruning the remarkable portion of the dataset through mathematics concepts. Firstly, the input dataset is modeled as a Directed Graph (DG), then some well-known features are extracted in which these ones represent the nature of the dataset. Afterward, they are utilized to feed our model in the learning phase. The results indicate the satisfactory performance of the proposed technique in the learning phase and accuracy over the other ones.
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A Fuzzy Approach for Text Mining
Статья научная
Document clustering is an integral and important part of text mining. There are two types of clustering, namely, hard clustering and soft clustering. In case of hard clustering, data item belongs to only one cluster whereas in soft clustering, data point may fall into more than one cluster. Thus, soft clustering leads to fuzzy clustering wherein each data point is associated with a membership function that expresses the degree to which individual data points belong to the cluster. Accuracy is desired in information retrieval, which can be achieved by fuzzy clustering. In the work presented here, a fuzzy approach for text classification is used to classify the documents into appropriate clusters using Fuzzy C Means (FCM) clustering algorithm. Enron email dataset is used for experimental purpose. Using FCM clustering algorithm, emails are classified into different clusters. The results obtained are compared with the output produced by k means clustering algorithm. The comparative study showed that the fuzzy clusters are more appropriate than hard clusters.
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A Hybrid Approach based on Classification and Clustering for Intrusion Detection System
Статья научная
Computer security plays an important role in everybody's life. Therefore, to protect the computer and sensitive information from the untrusted parties have great significance. Intrusion detection system helps us to detect these malicious activities and sends the reports to the administration. But there is a problem of high false positive rate and low false negative rate. To eliminate these problems, hybrid system is proposed which is divided into two main parts. First, cluster the data using K-Mean algorithm and second, is to classify the train data using Adaptive-SVM algorithm. The experiments is carried out to evaluate the performance of proposed system is on NSL-KDD dataset. The results of proposed system clearly give better accuracy and low false positive rule and high false negative rate.
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A Hybrid Spectral Conjugate Gradient Method with Global Convergence
Статья научная
The spectral conjugate gradient (SCG) method is one of the most commonly used methods to solve large- scale nonlinear unconstrained optimization problems. It is also the research and application hot spot of optimization theorists and optimization practitioners. In this paper, a new hybrid spectral conjugate gradient method is proposed based on the classical nonlinear spectral conjugate gradient method. A new parameter is given. Under the usual assumptions, the descending direction independent of any line search is generated, and it has good convergence performance under the strong Wolfe line search condition . On a set of test problems, the numerical results show that the algorithm is effective.
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A LSB Based Image Steganography Using Random Pixel and Bit Selection for High Payload
Статья научная
Security in digital communication is becoming more important as the number of systems is connected to the internet day by day. It is necessary to protect secret message during transmission over insecure channels of the internet. Thus, data security becomes an important research issue. Steganography is a technique that embeds secret information into a carrier such as images, audio files, text files, and video files so that it cannot be observed. In this paper, based on spatial domain, a new image steganography method is proposed to ensure the privacy of the digital data during transmission over the internet. In this method, least significant bit substitution is proposed where the information embedded in the random bit position of a random pixel location of the cover image using Pseudo Random Number Generator (PRNG). The proposed method used a 3-3-2 approach to hide a byte in a pixel of a 24 bit color image. The method uses Pseudo Random Number Generator (PRNG) in two different stages of embedding process. The first one is used to select random pixels and the second PRNG is used select random bit position into the R, G and B values of a pixel to embed one byte of information. Due to this randomization, the security of the system is expected to increase and the method achieves a very high maximum hiding capacity which signifies the importance of the proposed method.
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Статья научная
Given that divorce has become a recurring challenge with increasing intensity in our world today accompanying broken families, economy and social contagion, as well as the existence of difference in happiness between the couple and their children. Thus, a mathematical model for predicting the rate of divorce tendencies in the Nigerian society is hereby developed. Factors influencing the rate of divorce were outlined and mathematical relationships between these factors were established. Afterwards, the developed model was validated and the real life data collected were contrasted with the model data predictions using suitable statistical tools. The findings from the comparison showed that the real life data and the model data predictions have a higher degree of correlation; consequently, recommending the model as a benchmark measure for predicting rate of divorce/marital instability in Nigeria. In the same vein, recommendations were made at the end of the model analysis which when adhered to would yield.
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Статья научная
Preparing a class timetable or routine is a difficult task because it requires an iterative trial and error method to handle all the constraints. Moreover, it has to be beneficial both for the students and teachers. Therefore, the problem becomes a multi-objective optimization problem with a good number of constraints. There are two types of constraints: hard and soft constraint. As the problem is an NP-hard problem, population based multi-objective optimization algorithms (multi-objective evolutionary algorithm) is a good choice for solving the problem. There are well established hard constraints handling techniques for multi-objective evolutionary algorithms, however, the technique is not enough to solve the problem efficiently. In the paper, a smart initialization technique is proposed to generate fewer constraints violated solutions in the initial phase of the algorithm so that it can find feasible solutions quickly. An experimental analysis supports the assumption. Moreover, there are no well-known techniques available for handling soft constraints. A new soft constraints handing technique is proposed. Experimental results show a significant improvement can be achieved. Finally, proposed combined approach integrates smart initialization and soft constraints handling techniques. Better results are reported when comparing with a standard algorithm.
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A Multi-channel Character Relationship Classification Model Based on Attention Mechanism
Статья научная
Relation classification is an important semantic processing task in the field of natural language processing. The deep learning technology, which combines Convolutional Neural Network and Recurrent Neural Network with attention mechanism, has always been the mainstream and state-of-art method. The LSTM model based on recurrent neural network dynamically controls the weight by gating, which can better extract the context state information in time series and effectively solve the long-standing problem of recurrent neural network. The pre-trained model BERT has also achieved excellent results in many natural language processing tasks. This paper proposes a multi-channel character relationship classification model of BERT and LSTM based on attention mechanism. Through the attention mechanism, the semantic information of the two models is fused to get the final classification result. Using this model to process the text, we can extract and classify the relationship between the characters, and finally get the relationship between the characters included in this paper. Experimental results show that the proposed method performs better than the previous deep learning model on the SemEval-2010 task 8 dataset and the COAE-2016-Task3 dataset.
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A Multi-view Comparison of Various Metaheuristic and Soft Computing Algorithms
Статья научная
AI algorithms have been applied in a wide spectrum of articles across different domains with great success in finding solutions. There is an increasing trend of applying these techniques on newer problems. However, the numerous numbers of algorithms that are classified as AI algorithm hinder the ability of any researcher to select which algorithm is suitable for his problem. The invention of new algorithms increases the difficulty for researchers to be updated about AI algorithms. This paper is intended to provide a multi-facet comparison between various AI algorithms in order to aid researchers in understanding the differences between some of the popular algorithms and select the suitable candidate for their problems.
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A Natural Language Query Builder Interface for Structured Databases Using Dependency Parsing
Статья научная
A natural language query builder interface retrieves the required data in structured form from database when query is entered in natural language. The user need not necessarily have sufficient technical knowledge of structured query language statements so nontechnical users can also use this proposed model. In natural language parsing, getting highly accurate syntactic analysis is a crucial step. Parsing of natural languages is the process of mapping an input string or a natural language sentence to its syntactic representation. Constituency parsing approach takes more time for parsing. So, natural language query builder interface is developed in which the parsing of natural language sentence is done by using dependency parsing approach. Dependency parsing technique is widespread in natural language domain because of its state-of-art accuracy and efficiency and also it performs best. In this paper, the buffering scheme is also proposed for natural language statements which will not load the whole sentence if it was done previously. Also there was a need of generalized access to all tables from database which is handled in this system.
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A New Method of Generating Optimal Addition Chain Based on Graph
Статья научная
In many number theoretic cryptographic algorithms, encryption and decryption is of the form xn mod p, where n and p are integers. Exponentiation normally takes more time than any arithmetic operations. It may be performed by repeated multiplication which will reduce the computational time. To reduce the time further fewer multiplications are performed in computing the same exponentiation operation using addition chain. The problem of determining correct sequence of multiplications requires in performing modular exponentiation can be elegantly formulated using the concept of addition chains. There are several methods available in literature in generating the optimal addition chain. But novel graph based methods have been proposed in this paper to generate the optimal addition chain where the vertices of the graph represent the numbers used in the addition chain and edges represent the move from one number to another number in the addition chain. Method 1 termed as GBAPAC which generates all possible optimum addition chains for the given integer n by considering the edge weight of all possible numbers generated from every number in addition chain. Method 2 termed as GBMAC which generates the minimum number of optimum addition chains by considering mutually exclusive edges starting from every number. Further, the optimal addition chain generated for an integer using the proposed methods are verified with the conjectures which already existed in the literature with respect to addition chains.
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Статья научная
Picture fuzzy set is an extension of fuzzy sets and intuitionistic sets. It is demonstrated have a wide application in the fact and theoretical. In this paper, we propose some novel similarity measures between picture fuzzy sets. The novel similarity measure is constructed by combining negative functions of each degree membership of picture fuzzy set. This similarity is shown that is better other similarity measures of picture fuzzy sets in some cases. Next, we apply them in several pattern recognition problems. Finally, we apply them to find the fault diagnosis of the steam turbine.
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A Note on Quasi-coincidence for Fuzzy Points of Fuzzy Topology on the Basis of Reference Function
Статья научная
In this article our main aim is to revisit the definition of fuzzy point and fuzzy quasi-coincident of fuzzy topology which is accepted in the literature of fuzzy set theory. We analyse some results and also prove some proposition with extended definition of complementation of fuzzy sets on the basis of reference function and some new definitions have also been introduced whenever possible. In this work the main efforts have been made to show that the existing definition of complement of fuzzy point and definition of fuzzy quasi-coincident are not acceptable.
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A Novel Mathematical Model for Cross Dock Open-Close Vehicle Routing Problem with Splitting
Статья научная
Cross docks play an important role in goods distribution. In most of the common models, the capacity of vehicles is not completely used as they assume that each node is met only by one vehicle. Also, due to high cost of purchasing vehicles with high capacity, rental vehicles are used in collecting section. In this paper, a novel mathematical model is presented in which, each node can be possibly visited by different vehicles (splitting). Besides, in the proposed model, existence of open routes in pickup section has been supposed. Then, one meta-heuristic method based on the simulation annealing algorithm with two different approaches has been developed. For testing the performance of the proposed algorithm, the obtained results compared with the exact answers in both small and large scales. The outcomes show that the algorithm works properly.
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A Novel Verifiable Secret Sharing with Detection and Identification of Cheaters' Group
Статья научная
Shamir's (t, n)-SS scheme is very simple to generate and distribute the shares for a secret among n participants by using such polynomial. We assume the dealer a mutually trust parity when he distributes the shares to participants securely. In addition when the participants pooling their shares in the secret reconstruction phase a honest participants can always reconstruct the real secret by Pooling areal shares. The property of verifiability enables participants to verify that their shares are consistent. Tompa and Woll suggested an important cheating scenario in Shamir's secret reconstruction. They found a solution to remove a single cheater with small probability, unfortunately, their scheme is based on computational assumptions. In addition each participants will receive a huge number of shares. In this paper we will construct scheme to be information-theoretically secure verifiable secret sharing which does not contain a single cheater. On the other hand we will eliminate these problems in Tompa and Woll scheme. Our proposed scheme is not only to detect and identify a cheater, but to prevent him from recovering the secret when the honest participants cannot.
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Статья научная
High costs of medical equipment and insufficient number of medical specialists have immensely contributed to the increment of death rate especially in rural areas of most developing countries. According to Roll Back Malaria there are 300 million acute cases of malaria per year worldwide, causing more than one million deaths. About 90% of these deaths happen in Africa, majorly in young children. Besides malaria when tested; a large number is coinfected with typhoid. Most often, symptoms of malaria and typhoid fevers do have common characteristics and clinicians do have difficulties in distinguishing them. For instance in Nigeria the existing diagnostic systems for malaria and typhoid in rural settlements are inefficient thereby making the result to be inaccurate and resulting to treatment of wrong ailments. Therefore in this paper, a predictive symptoms-based system for malaria and typhoid coinfection using Support Vector Machines (SVMs) is proposed for an improved classification results and the system is implemented using Microsoft Visual Basic 2013. Relatively high performance accuracy was achieved when tested on a reserved data set collected from a hospital. Hence the system will be of a great significant use in terms of affordable and quality health care services especially in rural settlement as an alternative and a reliable diagnostic system for the ailments.
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