Статьи журнала - International Journal of Mathematical Sciences and Computing
Все статьи: 198
Cryptographic Security using Various Encryption and Decryption Method
Статья научная
Fast development in universal computing and the growth in radio/wireless and mobile strategies have led to the extended use of application space for Radio Frequency (RFID), wireless sensors, Internet of things (IoT). There are numerous applications that are safe and privacy sensitive. The increase of the new equipments has permitted intellectual methods of linking physical strategies and the computing worlds through numerous network interfaces. Consequently, it is compulsory to take note of the essential risks subsequent from these communications. In Wireless systems, RFID and sensor linkages are extremely organized in soldierly, profitable and locomotive submissions. With the extensive use of the wireless and mobile devices, safety has therefore become a major concern. As a consequence, need for extremely protected encryption and decryption primitives in such devices is very important than before.
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Cyber Bullying Detection and Classification using Multinomial Naïve Bayes and Fuzzy Logic
Статья научная
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.
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Data Privacy System Using Steganography and Cryptography
Статья научная
Data privacy is being breached occasionally whether in storage or in transmission. This is due to the spate of attack occasioned by the movement of data and information on an insecure internet. This study aimed to design a system that would be used by both sender and receiver of a secret message. The system used the combination of Steganography (MSB) and Cryptography (RSA) approaches to ensure data privacy protection. The system generates two keys: public and private keys, for the sender and receiver to encrypt and decrypt the message respectively. The steganography method used does not affect the size of cover image. The software was designed using python programming language in PyCharmIDE. The designed system enhanced the security and privacy of data. The results of this study reveal the effectiveness of combination of steganography and cryptography over the use of either cryptography or steganography and other existing systems.
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Data- and Workflow Customer-Oriented Software Process Models
Статья научная
This paper presents a dataflow model to control the flow of data in each phase of a customer-oriented software process model. In addition, we suggest a workflow model to describe the transaction between the model phases, and a role model to govern the personnel participation and roles. Our goal is to develop models that involve the customer frequently and effectively during project development. Testing the models using CHAOS Report and shows that our models are capable of achieving this goal.
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Deep Classifier for Conjunctivitis – A Three-Fold Binary Approach
Статья научная
Alterations in environmental and demographic equations have resulted in phenomenal rise of human centric diseases, ocular being one of them. Technological advancements have witnessed early diagnosis of much of the previously un-ciphered diseases. This paper addresses two research questions (RQs) with the study being focused on conjunctivitis (the most prevalent eye ailment in adults as well as minors). The motive of both the RQs rests in implementing three state-of-the art deep learning framework for classification of the ocular disease and validation of the frameworks. Validation of the frameworks is seconded by improvised proposals for enhancements. RQ1 establishes and validates whether the three off the shelf Deep Learning frameworks VGG19, ResNet50, and Inception V3 properly classify the disease or not. RQ2 analyses the effectiveness of each classifier with further enhancement proposals. The algorithms were implemented on 210 images and generated an accuracy of 87.3%, 93.6%, and 95.2% for VGG19, ResNet50, and Inception V3 using Adam optimizer, with slightly variant results when applying Adadelta optimizer. These results were typical of the classification frameworks with enhancements. With pervasive penetration of Artificial Intelligence in healthcare, this paper presents the efficacy of Deep Learning Frameworks in conjunctivitis classification.
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Статья научная
This paper outlines the application of various classification methods and analytical techniques to identify a potential fraud. The aim of this document is to showcase the usefulness of such classification and analytical techniques for fraud detection. Considering the fact that there are hundreds of statistical methods and procedures to perform such analysis. In this paper, I would like to present a hybrid fraud detection method by using the Bayesian Classification technique to identify the risk group; followed by Benford's Law (The Law of First Digit) to detect a fraudulent transaction done by the identified risk group. Though this analysis focuses on the healthcare dataset, however, this technique can be replicated in any industry setup. Also, by adding the Voice of the Customer data to these classification and statistical methods, makes this analysis even more powerful and robust with improved accuracy.
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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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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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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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