Статьи журнала - International Journal of Information Technology and Computer Science

Все статьи: 1235

Simulation of the operation of induction machines at frequencies other than 50 Hz

Simulation of the operation of induction machines at frequencies other than 50 Hz

Jeroslav M. Živanić, Nenad A. Marković, Slobodan N. Bjelić

Статья научная

In the paper is proposed an induction machine model that corresponds to operating conditions at the change of frequency. The applicability of simulation method for the analysis of its operation at the frequencies other than 50 Hz was examined. The operation of the induction machine which control parameter is the frequency of controlled current was particularly analyzed. The evaluation of the proposed model was performed using the adapted subprogram in the psbdrive MATLAB Simulink package. For the verification of the results, the method of verified simulation was used, as a part of the method which was derived from the artificial intelligence algorithm. It has been confirmed that by controlling the frequencies and current of the induction machine, the ability to work in overloads can be maintained and this type of control has certain advantages in the frequency regulation of the drive with variable loads.

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Single Channel Speech Separation Using an Efficient Model-based Method

Single Channel Speech Separation Using an Efficient Model-based Method

Sonay Kammi, Mohammad Reza Karami

Статья научная

The subject of extracting multiple speech signals from a single mixed recording, which is referred to single channel speech separation, has received considerable attention in recent years and many model-based techniques have been proposed. A major problem of most of these systems is their inability to deal with the situation in which the signals are combined at different levels of energies because they assume that the data used in the test and training phase have equal levels of energies, where, this assumption hardly occurs in reality. Our proposed method based on MIXMAX approximation and sub-section vector quantization (VQ) is an attempt to overcome this limitation. The proposed technique is compared with a technique in which a gain adapted minimum mean square error estimator is derived to estimate the separated signals. Through experiments we show that our proposed method outperforms this method in terms of SNR results and also reduces computational complexity.

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Six Algorithms for Frequency Offset Estimation in OFDM Systems

Six Algorithms for Frequency Offset Estimation in OFDM Systems

Ahmed M. Alaa

Статья научная

Generally, wireless systems suffer from Carrier Frequency Offsets (CFO), which results either from the receiver’s oscillator’s impairments or Doppler shifts. The frequency offset between transmitter and receiver local oscillator is a main drawback of OFDM systems. A frequency drift in the receiver’s oscillator would result in a frequency offset in the received signal, this offset consists of two parts: a Fine offset, as a fraction of OFDM subcarrier spacing, and a Coarse offset that is equal to an integer multiple of the subcarrier spacing. Coarse offsets results in two problems; firstly, the modulation symbols are located on the wrong frequency bins, secondly, the pilots used for channel estimation are misplaced leading to a faulty channel estimate and severe signal distortion by the Equalizer. Fine Offsets result in a loss of orthogonality and thus ICI (Inter-Carrier Interference), as the frequency bin of a certain modulation symbol would contain some information about the neighboring symbol bin.

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Smart Agent Learning based Hotel Search System- Android Environment

Smart Agent Learning based Hotel Search System- Android Environment

Wayne Lawrence, Suresh Sankaranarayanan

Статья научная

The process of finding the finest hotel in central location is time consuming, information overload and overwhelming and in some cases poses a security risk to the client. Over time with competition in the market among travel agents and hotels, the process of hotel search and booking has improved with the advances in technology. Various web sites allow a user to select a destination from a pull-down list along with several categories to suit one’s preference.. Some of the more advanced web sites allow for a search of the destination via a map for example hotelguidge.com and jamaica.hotels.hu. Recently good amount of work been carried in the use of Intelligent agents towards hotel search on J2ME based mobile handset which still has some weakness. The proposed system so developed uses smart software agents that overcomes the weakness in the previous system by collaborating among themselves and search Google map based on criteria selected by the user and return results to the client that is precise and best suit the user requirements. In addition, the agent possesses learning capability of searching the hotels too which is based on past search experience. The booking of hotel involving cryptography has not been incorporated in this research paper and been published elsewhere. This will be facilitated on Android 2.2-enabled mobile phone using JADE-LEAP Agent development kit.

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Smart PCS Based System for Oxygen Content Measurement

Smart PCS Based System for Oxygen Content Measurement

Vaibhav Bhatia, Pawan Whig, Syed Naseem Ahmad

Статья научная

This paper presents the performance analysis of smart PCS based system for an accurate oxygen content measurement in the aqueous electrolyte solution. The system intends to measure the photo catalytic activity of the PCS which is sensitive to O2 by integrating the software and hardware design technique for more accurate results. The threshold voltage of the PCS changes due to photo catalysis process causing fluctuations in the PCS readout which is sensed by the microcontroller via an inbuilt 10 bit A/D converter. The digitized signal is processed and converted into corresponding value of O2 content. The proposed digital system is fast as compared to conventional flow injection analysis which is tiresome and time consuming job. The approach for this system relies on the fast operation of PCS which operates under sub threshold conditions and reduced computation time. The system is more user friendly and the outcomes of simulation are fairly in agreement with the theoretical estimations. The system is highly favourable for water quality monitoring applications due to reduced response time.

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Smart virtual expert system to assist psychiatrists (SVESTAP)

Smart virtual expert system to assist psychiatrists (SVESTAP)

Udara Srimath S. Samaratunge Arachchillage

Статья научная

Psychological issues in the world are exponentially growing and the treatment gap is also comparatively high. The main reason would be the shortage of expertise and time-consuming in conventional diagnose process. The main objective of this research is to lower the mental issues treatment gap of professionals or apprentices in the field by creating a virtual expert system to assist psychiatrists. This system diagnoses most common mental disorders such as Depression Disorder, Anxiety Disorder, and Dementia. The proposed expert system can communicate with patients, to identify the current state of the illness. During the conversation, a standard questionnaire is given for the disease verification purpose. The experienced mental health professionals can use this expert system to assist in diagnosing process and the apprentices of the psychology can use this expert system as a training asset.

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Smartphone-based Biometric Authentication Scheme for Access Control Management in Client-server Environment

Smartphone-based Biometric Authentication Scheme for Access Control Management in Client-server Environment

Sajaad Ahmed Lone, A.H. Mir

Статья научная

As the information put together by the blend of smartphones, the cloud, the IOT, and ubiquitous computing continue to expand at an alarming rate, a data breach increases. Today, users' strong authentication and authorization approaches are increasingly important to secure sensitive, confidential, secret information. Possession and knowledge-based authentication techniques for computers, the internet, email accounts, etc., are commonly used to access vital information; they do not link a user to an established identity, resulting in most security vulnerabilities. Biometric authentication, on the other hand, has the privilege of being more reliable than traditional authentication as biometric characteristics of a person can’t be lost; they are tough to distribute, exchange or duplicate; and it requires the user to be present during the authentication process, thereby relating the users to established identities. Biometrics provides a higher level of assurance that the individual attempting to ascertain is the individual in question. Thus, resulting in a more reliable, usable, and cost-effective model with a higher level of protection to deter an attacker from obtaining entry to a computer or network and gaining access to confidential data. This paper introduces a novel fingerprint-based authentication scheme for mobile environments, enabling user authentication based on fingerprint features using a challenge-response-based authentication process. In this study, the proposed authentication system has been developed on a real Android-based smartphone, tested on actual users, and performance analysis has been carried out; empirical results reveal that the proposed authentication scheme achieves increased performance. Moreover, a usability analysis has been done to determine efficiency, effectiveness, and user satisfaction. The evaluation results indicate its feasibility to use it as an effective authentication mechanism for mobile phone environments.

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Social Network Clustering

Social Network Clustering

Narges Azizifard

Статья научная

As we know, the datasets related to social networks are increasing. There are different procedures to analyze these types of datasets; one of these procedures is clustering which makes communities of social data. Random walk is a process which can find communities in a network, in other words when a random walk is used, it scans the nodes in some steps; it begins with an initial node and based on a random process progresses to neighboring nodes. In this paper an algorithm is proposed which aims to finding communities in a way that modularity factor increases, for this goal, random walks with random local search agent are combined. Experimental results show that the proposed method gives better modularity in comparison with other algorithms.

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Software Effort Estimation Using Grey Relational Analysis

Software Effort Estimation Using Grey Relational Analysis

M.Padmaja, D. Haritha

Статья научная

Software effort estimation is the process of predicting the number of persons required to build a software system. Effort estimation is calculated in terms of person per month for the completion of a project. If any new project is launched into a market or in industry, then cost and effort of a new project will be estimated. In this context, a number of models have been proposed to construct the effort and cost estimation. Accurate software effort estimation is a challenge within the software industry. In this paper we propose a novel method, Grey Relational Analysis (GRA) to estimate the effort of a particular project. To estimate the effort of a project, traditional methods have been used as algorithmic models to evaluate the parameters of the basic model i.e. basic COCOMO model. In this paper, to show the minimum error rate we have used Grey Relational Analysis (GRA) to predict the effort estimation on Kemerer dataset. When compared to the traditional techniques for estimation, the proposed method proved better results. The efficiency of the proposed system is illustrated through experimental results.

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Software Implementation of Modular Reduction by Pseudo-mersenne Primes

Software Implementation of Modular Reduction by Pseudo-mersenne Primes

Mariia Kovtun, Vladyslav Kovtun, Oleksandr Stokipnyi, Andrew Okhrimenko

Статья научная

Modern cryptosystems allow the use of operation in prime fields with special kind of modules that can speed up the prime field operation: multiplication, squaring, exponentiation. The authors took into account in the optimizations: the CPU architecture and the multiplicity of the degree of the modulus in relation to the machine word width. As example, shown adopted module reduction algorithms hard-coded for modern CPU in special form of pseudo-Mersenne prime used in MAC algorithm Poly1305, - in electronic signature algorithm EdDSA and - in short message encryption algorithm DSTU 9041. These algorithms have been software implemented on both 32-bit and 64-bit platforms and compared with Barrett modular reduction algorithm for different pseudo-Mersenne and generalized-Mersenne modules. Timings for proposed and Barrett algorithms for different modules are presented and discussed.

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Software Product Lines Composition through Partial Derivation

Software Product Lines Composition through Partial Derivation

Amina Guendouz, Djamal Bennouar

Статья научная

Software product line approach has been successfully adopted in various software domains. In some fields, single SPLs are no longer sufficient to fulfill their requirements due to the large variability amount they include. Consequently, a set of separated SPLs is built to handle this issue and construct what is known by Multi Product Lines (MPL). However, the emergence of MPLs results in several challenges, namely: managing the reuse between SPLs, structuring the MPL model and distributed derivation. In this paper, we propose a new approach for SPLs composition. Our approach relies on two main concepts: the separation of concerns and the partial derivation. It is validated in the context of an e-Learning MPL and an illustration is explained throughout the paper. The results show that our approach helps systemizing reuse within MPLs and structuring the MPL model. Moreover, SPLs are integrated early in the development process avoiding thus the distributed derivation challenges.

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Software Quality Attributes in Requirements Engineering

Software Quality Attributes in Requirements Engineering

Denys Gobov, Oleksandra Zuieva

Статья научная

As software systems continue to grow more complex, evaluating software quality becomes increasingly critical. This study analyzes existing software quality models, including McCall, Boehm, FURPS, and ISO Systems and Software Engineering – Systems and Software Quality Requirements and Evaluation (SQuaRE), with a specific focus on the ISO/IEC 25010:2023 standard. The research aims to assess the completeness of these models and explore interdependencies among key quality attributes relevant to software requirements engineering. The paper identifies key characteristics and associated metrics based on ISO/IEC standards using comparative analysis and a literature review. Findings show that ISO/IEC 25010:2023 provides the most comprehensive structure, with Functional Suitability and Compatibility identified as essential due to their universally recommended metrics. Survey data from 328 practicing analysts in Ukraine and internationally demonstrate a gap between theoretical models and real-world requirements documentation practices, particularly for non-functional requirements. The identified dependencies between quality attributes enable a more integrated and structured approach to identifying and analyzing non-functional requirements in IT projects. The study emphasizes that software quality models must be tailored to project-specific goals and constraints, with attention to trade-offs and stakeholder needs during the requirements specification, prioritization, and validation processes. The findings support the adaptation of quality models to specific project constraints and emphasize the business analyst’s role in tailoring quality criteria for practical use in software development.

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Software Reliability Modeling using Soft Computing Techniques: Critical Review

Software Reliability Modeling using Soft Computing Techniques: Critical Review

Kuldeep Singh Kaswan, Sunita Choudhary, Kapil Sharma

Статья научная

Software reliability models assess the reliability by predicting faults for the software. Reliability is a real world phenomenon with many associated real-time problems. To obtain solutions to problems quickly, accurately and acceptably, a large number of soft computing techniques have been developed, but it is very difficult to find out which one is the most suitable and can be used globally. In this paper, we have provided an overview of existing soft computing techniques, and then critically analyzed the work done by the various researchers in the field of software reliability. Further to this, we have also compared soft computing techniques in terms of software reliability modeling capabilities.

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Solving Web-based Applications Architectural Problems in the Cloud: The Way Forward

Solving Web-based Applications Architectural Problems in the Cloud: The Way Forward

Philip Achimugu, Oluwatolani Oluwagbemi, Ishaya Gambo

Статья научная

Highly-available and scalable software systems can be a complex and expensive proposition. Traditional scalable software architectures have not only needed to implement complex solutions to ensure high levels of reliability, but have also required an accurate forecast of traffic to provide a high level of customer service. This traditional software architecture is built around a common three-tier web application model that separates the architecture into presentation, business logic and database layers. This architecture has already been designed to scale out by adding additional hosts at these layers and has built-in performance, failover and availability features. Even with all these developments in architectural designs, some software still lacks in scalability, reliability and efficiency. This paper therefore examines the shortfalls of traditional software architectural problems with a view to addressing them using the cloud computing approach.

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Some Algebraic Properties of Multigranulations and an Analysis of Multigranular Approximations of Classifications

Some Algebraic Properties of Multigranulations and an Analysis of Multigranular Approximations of Classifications

B.K.Tripathy, R.Raghavan

Статья научная

Ever since the introduction of rough sets by Pawlak as a model to capture uncertainty, it has drawn much attention from both theoretical and application point of view. Classifications of universes play very important roles in several fields of study. The study of rough definability of classifications was initiated by Busse. The properties of approximations of classifications were established in the form of four theorems and were used to define the types of classifications. These results were generalised to develop two theorems of necessary and sufficient type were established by Tripathy et al , from which several results including the four theorems of Busse could be derived as corollaries. Recently, rough sets based on Multigranulation were introduced and studied by Qian et al. Also, it has been extended to include incomplete information systems. Many of these results are extended to the multigranular cases. In this paper, we extend the properties of types of classifications to the multigranular context. Also, we introduce some parameters like the accuracy of approximation and the quality of approximation of classifications with respect to Multigranulations. We have obtained interesting criteria under which both types of Multigranulations reduce to single granulation. Also, some algebraic properties of Multigranulations are derived.

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Some Observations on Dependency Analysis of SOA Based Systems

Some Observations on Dependency Analysis of SOA Based Systems

Pawan Kumar, Ratneshwer

Статья научная

This paper presents some observations on Dependency Analysis of Service Oriented Architecture (SOA) based systems. In general, dependency analysis is based on the internal properties of artifacts (objects/components/services) and inter-relationship between the artifacts in the system. In order to make a dependency analysis for SOA based systems, one have to consider the special features of SOA that make them different with other approaches. This paper surveys the previous works taken on dependency analysis of service oriented systems. The present work provides insights about definitions related to service dependency, the modeling and analysis techniques of service dependency analysis, failure results to service dependence and some research challenges of the topic.The contribution of this paper is for novice researchers working on this topic as they can get an overview of dependency analysis of SOA based systems for their further research.

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Spatial co-location patterns on weather and forest fire data

Spatial co-location patterns on weather and forest fire data

Imas S. Sitanggang, Sergi Roseli, Lailan Syaufina

Статья научная

One of problems that can increase the risk of forest fire occurrences in Indonesia is drought which is affected by weather conditions. Therefore, weather conditions and forest fire are strongly related. Spatial co-location pattern can be applied to identify the weather conditions that are vulnerable to fires based on the distance between weather observation points and hotspot occurrences. The purpose of this study is to apply the co-location miner algorithm on the weather and hotspot data in Rokan Hilir Riau Indonesia and to analyze the generated co-location patterns. Experimental results show that precipitation which co-located with hotspot occurrences are 0.08–6.69 mm/day. In addition, the temperature which co-located with hotspot occurrences are 22°C–29.17°C. Inside the intervals, hotspots will occur in the radius of 9.724 km from the precipitation and temperature observation points. In 2008, many hotspots were found on the three areas in the study area with the average of precipitation around 3.65–3.71 mm/day and temperature around 24.44°C–25.23°C.

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Spectrogram-based Deep Learning Approach for Anomaly Detection from Cough Sounds

Spectrogram-based Deep Learning Approach for Anomaly Detection from Cough Sounds

Tugce Keles, Sengul Dogan, Abdul-Hafeez Baig, Turker Tuncer

Статья научная

Artificial intelligence is now applied in many fields beyond computer science. In healthcare, it enables early disease detection and improves patient outcomes. This study develops a model that uses AI to find abnormal patterns in cough sounds. A cough is a key symptom of asthma and other respiratory diseases. Previous research has focused on raw audio signals of coughs. In contrast, we analyze spectrogram images derived from these sounds to improve accuracy. We designed a new convolutional neural network (CNN) for this purpose and the recommended CNN is termed as TwoConvNeXt. To showcase the classification performance of the recommended TwoConvNeXt model, a cough sound dataset has been utilized and the recommended TwoConvNeXt achieved 99.66% classification test accuracy. These results illustrate that the presented TwoConvNeXt CNN architecture can be useful in both research and clinical settings. This CNN model can be utilized for other image classification problems. It may aid in the early diagnosis of respiratory conditions. Future work will expand the dataset and test the model on larger, more diverse samples.

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Speech Quality Assessment of VoIP: G.711 VS G.722 Based on Interview Tests with Thai Users

Speech Quality Assessment of VoIP: G.711 VS G.722 Based on Interview Tests with Thai Users

Therdpong Daengsi, Chai Wutiwiwatchai, Apiruck Preechayasomboon, Saowanit Sukparungsee

Статья научная

This paper presents the comparison between two codecs, G.711 and G.722 at 64 kbps, referring to speech quality perception using a subjective method called interview tests. These subjective tests have been conducted with 201 subjects, who are Thai native speakers that use Thai which is a tonal language, for accuracy and reliability of results. The results from testing with both codecs are almost the same; the scores are 4.17 for G.722 and 4.14 for G.711. After analyzing the results, it has been confirmed that G.722 does not provide better speech quality than G.711 to the Thai subjects significantly, which is consistent with previous information. However, these results could be used as the benchmark of G.711 and G.722 for speech quality assessment within Thai environments.

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Stable Fuzzy PD Control with Parallel Sliding Mode Compensation with Application to Rigid Manipulator

Stable Fuzzy PD Control with Parallel Sliding Mode Compensation with Application to Rigid Manipulator

Farzin Piltan, Mohammad A. Bairami, Farid Aghayari, Mohammad Reza Rashidian

Статья научная

Both fuzzy logic and sliding mode can compensate the steady-state error of proportional-derivative (PD) control. This paper presents parallel sliding mode compensations for fuzzy PD controllers. The asymptotic stability of fuzzy PD control with first-order sliding mode compensation in the parallel structure is proven. For the parallel structure, the finite time convergence with a super-twisting second-order sliding-mode is guaranteed.

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