Статьи журнала - International Journal of Mathematical Sciences and Computing

Все статьи: 198

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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Energy Efficient Multipath Routing in Zone-based Mobile Ad-hoc Networks: Mathematical Formulation

Energy Efficient Multipath Routing in Zone-based Mobile Ad-hoc Networks: Mathematical Formulation

Vinay Sahu, Rani Sahu

Статья научная

A wireless mobile ad hoc network (MANET) is a dynamic network that can be built without the need for any central governance system and pre-existing infrastructure, in which each node can act as a router. During the transmission of information in any network, energy consumption is an important factor for the efficiency and lifetime of the network. A reduction in energy consumption is achieved by detecting the energy consumption at the node at each stage of transmission. The main objective of this paper is to formulate mathematical models of energy consumption. A mathematical model of the energy consumption of a network is to be built on the basis of available nodes and links to formulate mathematical models related to energy. When constructing this mathematical model for the challenge related to mobility and low connectivity due to limited battery power in the network, the failure of the links present in the network and the estimated energy consumption are taken into account. Due to the greater mobility of this type of network, nodes rapidly change their positions, causing nodes to drain the battery very quickly, thus reducing network performance. So we need a mathematical model which helps in developing a mathematical model after developing a conceptual model. Which helps in predicting the quantitative behavior of a system. Weaknesses and strengths of a model can be identified from the quantitative results of a mathematical model.

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Enhanced E-recruitment using Semantic Retrieval of Modeled Serialized Documents

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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Exact Analytical Solution of Boundary Value Problem in a Form of an Infinite Hypergeometric Series

Exact Analytical Solution of Boundary Value Problem in a Form of an Infinite Hypergeometric Series

Ali Belhocine

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

Ferrer diagram based partitioning technique to decision tree using genetic algorithm

Pavan Sai Diwakar Nutheti, Narayan Hasyagar, Rajashree Shettar, Shankru Guggari, Umadevi V.

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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Forecasting Natural Gas Prices Using Nonlinear Autoregressive Neural Network

Forecasting Natural Gas Prices Using Nonlinear Autoregressive Neural Network

Abdelkader Sahed, Mohammed Mékidiche, Hacen Kahoui

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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Future Possible Age of the Universe with Density Variation

Future Possible Age of the Universe with Density Variation

Oishi Khanam, Md. Nirab Hossain, Md. Showkat Ali

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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Fuzzy Expert System Based Test Cases Prioritization from UML State Machine Diagram using Risk Information

Fuzzy Expert System Based Test Cases Prioritization from UML State Machine Diagram using Risk Information

Wasiur Rhmann, Vipin Saxena

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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Graph Dynamic Threshold Model Resource Network: Key Features

Graph Dynamic Threshold Model Resource Network: Key Features

L. Yu. Zhilyakova

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

Green Computing: An Era of Energy Saving Computing of Cloud Resources

Shailesh Saxena, Mohammad Zubair Khan, Ravendra Singh

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

Handling Numerical Missing Values Via Rough Sets

Elsayed Sallam, T. Medhat, A.Ghanem, M. E. Ali

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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Hybrid Cryptography: Performance Analysis of Various Cryptographic Combinations for Secure Communication

Hybrid Cryptography: Performance Analysis of Various Cryptographic Combinations for Secure Communication

Zuhi Subedar, Ashwini Araballi

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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Implementation of Fast and Efficient Mac Unit on FPGA

Implementation of Fast and Efficient Mac Unit on FPGA

Sachin Raghav, Rinkesh Mittal

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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Improving Deceased Identification and Claiming System in Mortuaries Using Fingerprint: A Developing Country Perspective

Improving Deceased Identification and Claiming System in Mortuaries Using Fingerprint: A Developing Country Perspective

Iwara I. Arikpo, Chidalu Prince Egeonu

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

Inhomogeneous Assessment of New Mechanism of Adaptive Detection of Partially-correlated χ2-Targets

Mohamed Bakry El-Mashede

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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Labeling a kind of Cubic Graphs by Subgraph Embedding Method

Labeling a kind of Cubic Graphs by Subgraph Embedding Method

Yujie Bai, Shufei Wu

Статья научная

Based on a problem raised by Gao et. al. (Bull. Malays. Math. Sci. Soc., 41 (2018) 443–453.), we construct a family of cubic graphs which are double-edge blow-up of ladder graphs. We determine the full friendly index sets of these cubic graphs by embedding labeling graph method. At the same time, the corresponding labeling graphs are provided.

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Low-tech steganography for covert operations

Low-tech steganography for covert operations

Akash Nag

Статья научная

Text steganography, the art of concealing a secret text inside another innocuous text called the cover, is usually performed by insertion of whitespace, punctuation marks, misspelling words, or by arbitrarily capitalizing words or inserting synonyms, changing font-sizes & colors, etc. All of these have the disadvantage that they either arouse suspicion or are easily noticeable; and even lost if manually copied, i.e. handwritten. Furthermore, they are easily detectable by automated checkers. Still there are other methods which require a stego-key in order to decrypt the message. In covert intelligence operations, transmission of the stego-key may not be possible at all, more so when the message is urgent. Digital communications and Internet connectivity may also be lacking in certain situations, and the only mode of message passing available may be the exchange of handwritten text on paper; which effectively rules out text modifications like font-changes, whitespace insertion, etc. or any form of digital steganography like image/audio steganography. Finally, in almost all text-steganographic techniques, there is no provision to for the receiver to detect whether or not there is indeed any message embedded. This is very important in intelligence operations where a number of decoy text need to be sent with only one concealing the actual message. In this paper, we propose a new tool called STEGASSIST that can help the sender in generating the stego-text manually. It is a low-tech form of steganography that is especially suited to covert operations like espionage or under-cover journalism. In this method, the generated cover and the stego-text are identical, or in other words, there is no cover-text. Moreover, decryption does not require a stego-key, and the stego-text may be printed or even hand-written and sent via unreliable messengers, or published, without arousing any suspicion. Finally, the received stego-text can be checked by the receiver to detect whether or not there is any actual message embedded in it.

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