Статьи журнала - International Journal of Mathematical Sciences and Computing

Все статьи: 184

Cryptographic Security using Various Encryption and Decryption Method

Cryptographic Security using Various Encryption and Decryption Method

Ritu Goyal, Mehak Khurana

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

Cyber Bullying Detection and Classification using Multinomial Naïve Bayes and Fuzzy Logic

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

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

Data Privacy System Using Steganography and Cryptography

Olawale Surajudeen Adebayo, Shefiu Olusegun Ganiyu, Fransic Bukie Osang, Salawu Sule Ajiboye, Kasim Mustapha Olamilekan, Lateefah Abdulazeez

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

Data- and Workflow Customer-Oriented Software Process Models

Yazan Al-Masaf'ah, Ali M. Meligy, Alaa S. Farhat

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

Deep Classifier for Conjunctivitis – A Three-Fold Binary Approach

Subhash Mondal, Suharta Banerjee, Subinoy Mukherjee, Ankur Ganguly, Diganta Sengupta

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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Deplyoing advance data analytics techniques with conversational analytics outputs for fraud detection

Deplyoing advance data analytics techniques with conversational analytics outputs for fraud detection

Sunil Kappal

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

Design Approaches for a Novel Reversible 4-bit Comparator

Harpreet Singh, Chakshu Goel

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

Desirable Dog-Rabies Control Methods in an Urban setting in Africa -a Mathematical Model

Edwiga Kishinda Renald, Dmitry Kuznetsov, Katharina Kreppel

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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Determination Method of Some Operational Characteristics of Information Search System in Directive Document Database

Determination Method of Some Operational Characteristics of Information Search System in Directive Document Database

Fahrad H. Pashayev, Sevinj E. Pashayeva, Jahangir M. Jafarov, Pashayev I. Farhad

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

Determination of Optimal Smoothing Constants for Foreign Remittances in Bangladesh

Md. Nayan Dhalia, Md. Biddut Rana, Nazrul Islam, Deepa Roy, Mst. Sharmin Banu

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

Development of a secure SMS application using Advanced Encryption Standard (AES) on android platform

Muhammad Noman Riaz, Adeel Ikram

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

Development of an Effective Method of Data Collection for Advertising and Marketing on the Internet

Hashimova Kamala

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

EUR/USD Exchange Rate Prediction Using Machine Learning

Md. Soumon Aziz Sarkar, U.A. Md. Ehsan Ali

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

Edge stable sets and secured edge stable sets in hypergraphs

D. K. Thakkar, V. R. Dave

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

Effect Neural Networks on Selected Feature by Meta Heuristic Algorithms

Maysam Toghraee, Farhad rad, Hamid parvin

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

Efficient Optimization of Edge Server Selection Technique in Content Delivery Network

Debabrata Sarddar, Enakshmi Nandi

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

Emoji Prediction Using Emerging Machine Learning Classifiers for Text-based Communication

Sayan Saha, Kakelli Anil Kumar

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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Empirical and Statistical Determination of Optimal Distribution Model for Radio Frequency Mobile Networks Using Realistic Weekly Block Call Rates Indicator

Empirical and Statistical Determination of Optimal Distribution Model for Radio Frequency Mobile Networks Using Realistic Weekly Block Call Rates Indicator

Divine O. Ojuh, Joseph Isabona

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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Enhanced E-recruitment using Semantic Retrieval of Modeled Serialized Documents

Enhanced E-recruitment using Semantic Retrieval of Modeled Serialized Documents

Alaba T. Owoseni, Olatunbosun Olabode, B. A. Ojokoh

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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Evidential paradigm and SAD systems: features and peculiarities

Evidential paradigm and SAD systems: features and peculiarities

Alexander Lyaletski, Alexandre Lyaletsky, Andrei Paskevich

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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