International Journal of Information Technology and Computer Science @ijitcs
Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1227
Design optimization of 6-RUS parallel manipulator using hybrid algorithm
Статья научная
In this paper, we present a study on the design optimization of the 6-RUS Stewart platform using a hybrid algorithm. The geometric and kinematic models are calculated. The optimization problem is formulated after determining the design parameters and defining a set of cost functions related to the size of the workspace and to the indices of the kinematic and static performance, which are the global conditioning index (GCI) and the global stiffness index (GSI). We started by studying the relation between the design parameters and the proposed cost functions, and then we invested the genetic algorithm to optimize each cost function separately. Moreover, we adopted a weighted cost function method to solve the Multi-Objective optimization problem. The convergence performance of the genetic algorithm (GA) and the particle swarm optimization (PSO) were compared, where the PSO algorithm showed better performance. Based on this, a hybrid PSO–PS method was proposed and the results are highly competitive as we obtained better general convergence performance.
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Статья научная
Fuzzy logic is a new and innovative technology that was used in order to develop a realization of engineering control. In recent years, fuzzy logic proved its great potential especially applied to automatization of industrial process control, where it enables the control design to be formed based on experience of experts and results of experiments. The projects that have been realized reveal that the application of fuzzy logic in the technological process control has already provided us with better decisions compared to that of standard control technique. Fuzzy logic provides an opportunity to design an advisory system for decision-making based on operator experience and results of experiments not taking a mathematical model as a basis. The present work deals with a specific technological process ─ designing a support decision making information system for the operational control of the lime kiln with the use of fuzzy logic based on creation of the relevant expert-objective knowledge base.
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Designing a rule based expert systems for contact lenses patients
Статья научная
Expert systems that bring facts and valuable experiences together and make some deductions possible. Expression of relevant knowledge and experience in these structures may be in a set of rules. Learning problems are valid with expert systems. Therefore, they cannot add new rules and information automatically by themselves. Rules are created by human experts on the way and added upon the system. Classification datasets are collections of data commonly used in machine learning that contain and classify the previously obtained experiences. In this study, rules were obtained by using Part, NNge, Prism rule classifier algorithms, and a knowledge base of expert systems was systematically created to achieve enrichment. Enrichment and rule deduction process needs careful and sensitive attention. A combined methodology and study was revealed during this sensitive process. In this context, studies were conducted on five widely used datasets. It was aimed to reduce the redundant, conflicting, subsumed and circular rules in order to create a consistent and complete knowledge base. In this way, a methodology was developed to establish more powerful and richer contents of knowledge base that have higher quality.
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Статья научная
The primary objective of this paper is to design a SmartCart mobile application. The proposal centres around designing a mobile app that allows customers to engage in collaborative shopping with their family members or friends, effectively shopping together in a group. This project seeks to improve upon existing shopping mobile apps that predominantly focus on online shopping. Through the development of the SmartCart mobile application, users will have the capability to shop in physical stores while collaborating with others or their group. The application adheres to the Mobile Application Development Life Cycle (MADLC) methodology, focusing on the phases of identification, design, development, prototyping, and testing. This paper provides an in-depth description of each step within the methodology, commencing with the identification stage and culminating in the testing phase. To evaluate the application's usability, ten users from various backgrounds took part in the testing process, and their feedback, measured through the System Usability Scale (SUS), indicated a positive reception of the application. The paper presents the initial framework and design concept that preceded the development of the final SmartCart mobile application design. From a pool of around 50 paper prototypes, 18 were selected as pertinent and fitting for advancement to the subsequent stage. In this subsequent phase, the chosen designs were transformed into a medium-fidelity prototype before progressing to the actual development of the SmartCart mobile application. This paper fulfils an identified need to study how collaborative shopping mobile applications can be developed and prototyped.
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Detecting Pirated Movie’s with Similarity Assessment Based on Earth Mover’s Distance
Статья научная
Piracy is no new lesson to every user of technology. It is a giant existing in the industry of technology numbing the heights software is reaching in terms of efficiency and use in all the sectors to an extent where even the industry of enterprise, beaurocracy, technology etc. depend upon the use of software in various ways to contribute their needs and success. Dollars are running at stakes of any industry while the piracy is acting as a dominator of all illegal transactions indirectly by giving easy and such illegal access to many users. One such victim is the entertainment industry where movies are being pirated and accessed to users causing millions of dollars of loss to the entertainment industry. Many researchers and technical specialists have made their contributions to save technology. Our paper is another potential solution with a promise of accuracy rate in detecting the pirated movies. It is a known fact that primary detection is the source of prevention. Our paper puts forth a technique that efficiency detects piracy to reduce such illegal downloads using the efficient measures of signature generation, normalization in an effective manner.
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Detecting and Preventing Common Web Application Vulnerabilities: A Comprehensive Approach
Статья научная
Web applications are becoming very important in our lives as many sensitive processes depend on them. Therefore, it is critical for safety and invulnerability against malicious attacks. Most studies focus on ways to detect these attacks individually. In this study, we develop a new vulnerability system to detect and prevent vulnerabilities in web applications. It has multiple functions to deal with some recurring vulnerabilities. The proposed system provided the detection and prevention of four types of vulnerabilities, including SQL injection, cross-site scripting attacks, remote code execution, and fingerprinting of backend technologies. We investigated the way worked for every type of vulnerability; then the process of detecting each type of vulnerability; finally, we provided prevention for each type of vulnerability. Which achieved three goals: reduce testing costs, increase efficiency, and safety. The proposed system has been validated through a practical application on a website, and experimental results demonstrate its effectiveness in detecting and preventing security threats. Our study contributes to the field of security by presenting an innovative approach to addressing security concerns, and our results highlight the importance of implementing advanced detection and prevention methods to protect against potential cyberattacks. The significance and research value of this survey lies in its potential to enhance the security of online systems and reduce the risk of data breaches.
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Detection of Plagiarism in Arabic Documents
Статья научная
Many language-sensitive tools for detecting plagiarism in natural language documents have been developed, particularly for English. Language-independent tools exist as well, but are considered restrictive as they usually do not take into account specific language features. Detecting plagiarism in Arabic documents is particularly a challenging task because of the complex linguistic structure of Arabic. In this paper, we present a plagiarism detection tool for comparison of Arabic documents to identify potential similarities. The tool is based on a new comparison algorithm that uses heuristics to compare suspect documents at different hierarchical levels to avoid unnecessary comparisons. We evaluate its performance in terms of precision and recall on a large data set of Arabic documents, and show its capability in identifying direct and sophisticated copying, such as sentence reordering and synonym substitution. We also demonstrate its advantages over other plagiarism detection tools, including Turnitin, the well-known language-independent tool.
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Detection of anomalies in fetus using convolution neural network
Статья научная
Parental diagnosis is required during mid-pregnancy period from 18-22 weeks in order to know the well-being of the fetus. This diagnosis is usually done through ultrasound scanning. Ultrasound scanning which is also called as sonogram, is an ultrasound based medical imagining technique used to envision the fetus and its development during the gestation period. If there is an abnormality in the diagnosed fetus then the parents and the doctors can do emergency parental care. Anomalies in Fetus occur before birth. Detecting fetal anomalies is a difficult task since it needs expertise and also requires a considerable amount of time, which will not be convenient at an emergency situation. In order to improve the diagnosis accuracy and to reduce the diagnosis time, it has become a demanding issue to develop an efficient and reliable medical decision support system. In this paper we present machine learning approach, such as convolution neural network which is most commonly applied to examine visual pretense. The main motive behind using CNN is due to their accuracy, fewer memory requirements and better training of images. This approach have shown great potential to be applied in the development of medical decision support system for Fetal anomalies which need immediate care.
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Determination of representativity for Bangla vowel perceptual space
Статья научная
In this article, representativity between two multidimensional acoustical spaces of vowel has been formulated based on the geometric mean of correlation of average directional vector, variance-covariance matrices, and Mahalanobis distance. Generally, the multidimensional spaces formed by different combinations of acoustical features of vowel are considered as the vowel perceptual spaces. Therefore, ten bangla vowel-sounds (/অ/ [/a/], /আ/ [/ã/], / ই/ [/i/] , /ঈ/ [/ĩ/], /উ/ [/u/], / ঊ/ /ũ/, /এ/ [/e/], /ঐ/ [/ai/] , /ও/ [/o/] and /ঔ/ [/au/]) are collected from each native Bengali speaker to build the perceptual space of the speaker using the acoustical features of vowels. Similarly, total nine perceptual spaces are constructed from nine speakers and these are utilized to evaluate representativity. Using the proposed method, representativities of differently constructed perceptual spaces have been evaluated and compared numerically. Furthermore, dominating and representative acoustical features are also identified from the principal components of the perceptual spaces.
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Determining Contribution of Features in Clustering Multidimensional Data Using Neural Network
Статья научная
Feature contribution means that what features actually participates more in grouping data patterns that maximizes the system’s ability to classify object instances. In this paper, modified K-means fast learning artificial neural network (K-FLANN) was used to cluster multidimensional data. The operation of neural network depends on two parameters namely tolerance (δ) and vigilance (ρ). By setting the vigilance parameter, it is possible to extract significant attributes from an array of input attributes and thus determine the principal features that contribute to the particular output. Exhaustive search and Heuristic search techniques are applied to determine the features that contribute to cluster data. Experiments are conducted to predict the network's ability to extract important factors in the presented test data and comparisons are made between two search methods.
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Determining the Degree of Knowledge Processing in Semantics through Probabilistic Measures
Статья научная
World Wide Web is a huge repository of information. Retrieving data patterns is facile by using data mining techniques. However identifying the knowledge is tough, tough because the knowledge should be meaningful. Semantics, a branch of linguistics, defines the process of supplying knowledge to the computer system. The underlying idea of semantics is to understand the language model and its correspondence with the meaning associability. Though semantics indicates a crucial ingredient for language processing, the degree of work composition done in this area is minimal. This paper presents an ongoing semantic research problem thereby investigating the theory and rule representation. Probabilistic approach for semantics is demonstrated to address the semantics knowledge representation. The inherit requirement for our system is to have the language syntactically correct. This approach identifies the meaning of the sentence at word-level. The accuracy of the proposed architecture is studied in terms of recall and precision measures. From the experiments conducted, it is clear that the probabilistic model for semantics is able to associate the language model at a preliminary level.
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Determining the Optimum Time Quantum Value in Round Robin Process Scheduling Method
Статья научная
The process scheduling, is one of the most important tasks of the operating system. One of the most common scheduling algorithms used by the most operating systems is the Round Robin method in which, the ready processes waiting in ready queue, seize the processor for a short period of time known as the quantum (or time slice) circularly. In this paper, a non-linear programming mathematical model is developed to determine the optimum value of the time quantum, in order to minimize the average waiting time of the processes. The model is implemented and solved by Lingo 8.0 software on four selected problems from the literature.
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Developing a Virtual Group Decision Support System Based on Fuzzy Hybrid MCDM Approach
Статья научная
Organizational decisions involve with unusually vague and conflicting criteria. This controversy increases empirical uncertainties, disputes, and the resulting consequences of these decisions. One possible method in subduing this problem is to apply quantitative approaches to provide a transparent process for resolute conclusions which enables decision makers to formulate accurate and decisive on time decisions. Although numerous methods are presented in the literature, the majority of them aim to develop theoretical models. However, this article aims to develop and implement an integrated fuzzy virtual MCDM model based on fuzzy AHP and fuzzy TOPSIS as a decision support system (DDS). Preventing disadvantageous face-to-face decision-making by achieving positive benefit from virtual decision making causes the proposed DDS to be suitable for making crucial decisions such as supplier selection, employee selection, employee appraisal, R&D project selection, etc. The proposed DDS has been implemented in an optical company in Iran.
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Developing an Efficient Model for Building Data Warehouse Using Mobile Agent
Статья научная
Data-warehouse is an emerging technology with great potential. Nowadays, businesses are competing fiercely to dominate the market where profitability is promising using every available means to reach their goal. Performance and storage are big challenges in building data-warehouse focusing by researchers recent years. In this paper a new model for developing an efficient data warehouse by using mobile agent technology has been proposed. The main idea behind this model is to use the mobile agent to extract and analyze operational data in their location. So, instead of using ETL, the mobile agent will be used. After the mobile agent completing its journey among operational databases, all tasks of ETL will be performed. By this way no need high storage media to extract the data from the operational database. As cost of time, the model proves less consuming of time. The model has been implemented using .Net Framework and C# and the results have been presented and discussed.
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Статья научная
This computing which runs on a web browser. It provides access to a number of web applications through internet without booting the whole OS. The purpose behind Cloud Operating System is that the full system is running on the Web browser and lives on it. Cloud OS is thought of as a new era of an Operating System in which everything inside an Operating System can be accessed from everywhere inside a specific network. The user just need to login onto the web browser and thus can have access to his personalized web-tops where all the applications and data is stored. In this paper it will discuss what is the difference between the Cloud OS and a simple Operating System and how the Cloud OS is developed defining all the requirements and functionalities of a cloud OS. We will also discuss in detail about the load balancing, Geo-replication Data Storage and Virtualization in Cloud OS.
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Development of Data Acquisition Console and Web Server Using Raspberry Pi for Marine Platforms
Статья научная
Marine vessels in today's age are fitted with a number of state of the art systems required for their smooth operation. The compartments which house such systems along with the restricted compartments onboard ships such as the ships galley, dry rations store, cold rooms, battery compartments etc are required to be monitored on real time basis for temperature, pressure, humidity for detecting various hazards like fire, flooding etc. In addition, military platforms also need to monitor compartments such as the armory and magazines to avoid damage to munitions and prevent unauthorized access. The present project aims to develop a proof of concept prototype real time parameter monitoring and motion detection system for critical/restricted compartments on marine platforms with data logging capability. Various sensors forming a sensor suite have been interfaced to the Raspberry Pi board, forming the Data Acquisition Console which is the nodal control center. As most marine vessels are fitted with a shipboard Local Area Network, the project utilizes this existing network for relaying data. The console is placed in the compartment where parameters are to be monitored and the measured data is acquired and transferred via wireless (using Access Points (APs) operating on Wi-Fi/ 802.11 network) or via wired connectivity with the nearest switch and be accessed by concerned personnel at various nodes/ computer on the . The performance of the DAC was successfully ascertained by comparison of sensor performance with other independent sensor readings. The measurement errors were found to be within the permissible accuracy limits of the sensors. Motion detection was achieved by using PIR motion The probability of detection (Pd) for the motion sensor was calculated by conducing iterative motion tests with favorable results. Data is displayed in a web-based dashboard Graphical User Interface. Further, provision has also been made to set visual alarms whenever a particular sensor reading crosses a pre-designated safe limit.
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Статья научная
UN Department of Economics and Social Affairs predicted that the world population will increase by 2 billion in 2050 with over 50% from the Sub-Saharan Africa (SSA). Considering the level of poverty and food insecurity in the region, there is an urgent need for a sustainable increase in agricultural produce. However, farming approach in the region is primarily traditional. Traditional farming is characterized by high labor costs, low production, and under/oversupply of farm inputs. All these factors make farming unappealing to many. The use of digital technologies such as broadband, Internet of Things (IoT), Cloud computing, and Big Data Analytics promise improved returns on agricultural investments and could make farming appealing even to the youth. However, initial cost of smart farming could be high. Therefore, development of a dedicated IoT cloud-based platform is imperative. Then farmers could subscribe and have their farms managed on the platform. It should be noted that majority of farmers in SSA are smallholders who are poor, uneducated, and live in rural areas but produce about 80% of the food. They majorly use 2G phones, which are not internet enabled. These peculiarities must be factored into the design of any functional IoT platform that would serve this group. This paper presents the development of such a platform, which was tested with smart irrigation of maize crops in a testbed. Besides the convenience provided by the smart system, it recorded irrigation water saving of over 36% compared to the control method which demonstrates how irrigation is done traditionally.
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Development of Myanmar-English Bilingual WordNet like Lexicon
Статья научная
A bilingual concept lexicon is of significance for Information Extraction (IE), Machine Translation (MT), Word Sense Disambiguation (WSD) and the like. Myanmar-English Bilingual WordNet like Lexicon (MEBWL) is developed to fulfill the requirements of Language Acquisition (LA). However, it is reasonably difficult to build such a lexicon is quite challenging in time and cost consuming. To overcome this challenging, this paper integrates linguistic resources, including Myanmar-English dictionary, English-Myanmar dictionary and WordNet to construct a Myanmar-English WordNet like lexicon by acquiring the lexical and conceptual knowledge from WordNet and Myanmar English Machine Readable Dictionaries (MRDs). The system includes three phases which include the MRD extraction phase, the link analyzing phase and the WordNet construction phase. The first phase converts the data from multiple resources with different format into a common format and joins and aligns the scattered data for smoothly access and group the data according their part of speech (POS). The link analyzing phase analyzes, classifies and generates candidates of translation links. In the constructing phase, MEBWL is constructed from the verified translation link and WordNet. Beside then, to support the inflected word of Myanmar to English words, morphological processor is designed.
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Development of Neuro-fuzzy System for Early Prediction of Heart Attack
Статья научная
This work is aimed at providing a neuro-fuzzy system for heart attack detection. Theneuro-fuzzy system was designed with eight input field and one output field. The input variables are heart rate, exercise, blood pressure, age, cholesterol, chest pain type, blood sugar and sex. The output detects the risk levels of patients which are classified into 4 different fields: very low, low, high and very high. The data set used was extracted from the database and modeled in order to make it appropriate for the training, then the initial FIS structure was generated, the network was trained with the set of training data after which it was tested and validated with the set of testing data. The output of the system was designed in a way that the patient can use it personally. The patient just need to supply some values which serve as input to the system and based on the values supplied the system will be able to predict the risk level of the patient.
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Статья научная
Superior garbage collection algorithms are needed for deterministic runtime system in complex embedded systems to explore the benefits of contemporary and conquered application programming language. Android embedded operating system is greatly used world wide as a mobile platform without denying this fact it also attracted researchers and engineers to integrate in other embedded real-time systems. It exploits Java language for embedded application development and it can also enhance a certain real time capability with the adoption of real-time support at Dalvik Virtual Machine (DVM). Need for Real-time garbage collection algorithms in embedded systems is identified by achieving new insights into the existing garbage collection algorithms through finding blemishes in it. The space based technique is used in proposed new Real-time GC algorithm for execution runtime system and Real time Garbage Collection (GC) schedulability issue is also addressed. The intuitive performance analysis result demonstrates reduction in the response time and also describes the determinism characteristic of the real time applications using proposed solution.
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