Статьи журнала - International Journal of Information Technology and Computer Science

Все статьи: 1235

Pronunciation Proficiency Evaluation based on Discriminatively Refined Acoustic Models

Pronunciation Proficiency Evaluation based on Discriminatively Refined Acoustic Models

Ke Yan, Shu Gong

Статья научная

The popular MLE (Maximum Likelihood Estimation) is a generative approach for acoustic modeling and ignores the information of other phones during training stage. Therefore, the MLE-trained acoustic models are confusable and unable to distinguish confusing phones well. This paper introduces discriminative measures of minimum phone/word error (MPE/MWE) to refine acoustic models to deal with the problem. Experiments on the database of 498 people’s live Putonghua test indicate that: 1) Refined acoustic models are more distinguishable than conventional MLE ones; 2) Even though training and test are mismatch, they still perform significantly better than MLE ones in pronunciation proficiency evaluation. The final performance has approximately 4.5% relative improvement.

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Proposal of Implicit Coordination Model for Performance Enhancement Using Sprint Zero

Proposal of Implicit Coordination Model for Performance Enhancement Using Sprint Zero

M. Rizwan Jameel Qureshi, Ahmed Barnawi, Aiesha Ahmad

Статья научная

Scrum model always welcome the new requirements from customer at any stage of software development. This situation creates problem for development team to meet estimated timelines. The Scrum development team is always under heavy workload and stress because of this situation. A high level of coordination among team members is required in order to overcome this work pressure and meet quality demands within estimated time and cost. Scrum model emphasis to coordinate through communication to cope with changing requirements. Scrum development is facing new challenges to meet high quality demands with critical timeline environment. The ability of a team to act intelligently in such situation is gaining key position for the survival and success of an organization. The goal of this paper is to highlight the role of implicit coordination helping the software development team members to act intelligently in time demand environment to achieve common goals. Implicit coordination among team members during sprint zero development can show significant improvement in team performance. This will help to achieve high quality product under heavy workload within estimated time period. A survey is conducted to validate the research i.e., implicit coordination has strong impact for successful implementation of Scrum methodology.

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Proposal of New PRORISK Model for GSD Projects

Proposal of New PRORISK Model for GSD Projects

M. Rizwan Jameel Qureshi, Aysha Albarqi

Статья научная

The level of complexity and risks associated with software are increasing exponentially because of competing environment especially in geographically distributed projects. Global software development (GSD) face challenges like distance, communication and coordination challenges. The coordination and communication challenges are the main causes of failure in GSD. Project Oriented Risk Management (PRORISK) is one of the models to address the importance of risk management and project management processes in standard software projects. However, existing model is not proposed to handle GSD associated risks. This warrants the proposal of new PRORISK model to manage the risks of GSD. Survey is used as a research design to validate the proposed solution. We anticipate that the proposed solution will help the software companies to cater the risks associated with GSD.

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Provisioning quality of service for multimedia applications in cloud computing

Provisioning quality of service for multimedia applications in cloud computing

Muhammad Usman Ashraf, Sabah Arif, Abdul Basit, Malik Sheraaz Khan

Статья научная

Since the last decade, many new trends have been introduced to access network technologies and services through internet. Cloud computing is one of those significant technologies that reduce the cost and increase the productivity by providing a variety of services. Recently, cloud computing based system is primarily used for multimedia applications. Over the cloud computing, multimedia applications has some significant quality of service (QoS) requirements such as bandwidth, jitter, latency etc. But due to some limitations in services providing, it is constantly complex to make selection for an appropriate service. Keeping in view the provision of multimedia services through cloud computing, many different concepts and approaches that provide better cloud services under the constraints of QoS attributes have been described in the literature. The goal of this paper is to assess the applicability and provision of multimedia applications over cloud computing through enhanced quality of service. We have identified the primary quality of service msetrics evaluation of multimedia services over cloud computing. Furthermore, under these metrics we evaluated the existing approaches that provide multimedia related services with their strengths and limitations. This evaluation approach could provide the service that can provide better QoS in multimedia applications over cloud computing.

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Pseudo-Spectrum Time Domain and Time Reversal Mirror technique using in Microwave-induced Thermo-Acoustic Tomography System

Pseudo-Spectrum Time Domain and Time Reversal Mirror technique using in Microwave-induced Thermo-Acoustic Tomography System

Guoping Chen, Zhiqin Zhao, Qing.H. Liu

Статья научная

Microwave-Induced Thermo-Acoustic Tomograp- phy (MITAT) has attracted more concerns in recent years in biomedical imaging field. It has both the high contrast of the microwave imaging and the high resolution of ultrasound imaging. As compared to optoacoustics, which uses instead a pulsed light for evoking optoacoustic response, thermo-aco- ustic imaging has the advantage of deeper tissue penetration, attaining the potential for wider clinical dissemination, especially for malignant tumors. In this paper, the induced thermo-acoustic wave propagating in a mimic biologic tissue is simulated by numeric method Pseudo-Spectrum Time Domain (PSTD). Due to the excellent performance in noise- depress and the stability for the fluctuation of the model parameters, Time Reversal Mirror (TRM) imaging technique is studied computationally for the simulative received therm- o-acoustic signals. Some thermo-acoustic objects with differ- ent initial pressure distribution are designed and imaged by TRM technique to represent the complex biologic tissue case in a random media. The quality of images generated by TRM technique based on PSTD method hints the potential of the MITAT technique.

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Psychological Status Monitoring with Cerebral Blood Flow, Electroencephalogram and Electro-oculogram Measurements

Psychological Status Monitoring with Cerebral Blood Flow, Electroencephalogram and Electro-oculogram Measurements

Kohei Arai

Статья научная

Psychological status monitoring with Cerebral Blood Fflow: CBF, Electroencephalogram: EEG and Electro-oculogram: EOG measurements are attempted. Through experiments, it is confirmed that the proposed method for psychological status monitoring is valid. It is also found correlations among the amplitudes of peak alpha and beta as well as gamma frequency of EEG signals and EOG as well as cerebral blood flow. Therefore, psychological status can be monitored with either EEG measurements or cerebral blood flow and EOG measurements.

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Psychosocial Features for Hate Speech Detection in Code-switched Texts

Psychosocial Features for Hate Speech Detection in Code-switched Texts

Edward Ombui, Lawrence Muchemi, Peter Wagacha

Статья научная

This study examines the problem of hate speech identification in codeswitched text from social media using a natural language processing approach. It explores different features in training nine models and empirically evaluates their predictiveness in identifying hate speech in a ~50k human-annotated dataset. The study espouses a novel approach to handle this challenge by introducing a hierarchical approach that employs Latent Dirichlet Analysis to generate topic models that help build a high-level Psychosocial feature set that we acronym PDC. PDC groups similar meaning words in word families, which is significant in capturing codeswitching during the preprocessing stage for supervised learning models. The high-level PDC features generated are based on a hate speech annotation framework [1] that is largely informed by the duplex theory of hate [2]. Results obtained from frequency-based models using the PDC feature on the dataset comprising of tweets generated during the 2012 and 2017 presidential elections in Kenya indicate an f-score of 83% (precision: 81%, recall: 85%) in identifying hate speech. The study is significant in that it publicly shares a unique codeswitched dataset for hate speech that is valuable for comparative studies. Secondly, it provides a methodology for building a novel PDC feature set to identify nuanced forms of hate speech, camouflaged in codeswitched data, which conventional methods could not adequately identify.

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Python Data Analysis and Visualization in Java GUI Applications Through TCP Socket Programming

Python Data Analysis and Visualization in Java GUI Applications Through TCP Socket Programming

Bala Dhandayuthapani V.

Статья научная

Python is popular in artificial intelligence (AI) and machine learning (ML) due to its versatility, adaptability, rich libraries, and active community. The existing Python interoperability in Java was investigated using socket programming on a non-graphical user interface (GUI). Python's data analysis library modules such as numpy, pandas, and scipy, together with visualization library modules such as Matplotlib and Seaborn, and Scikit-learn for machine-learning, aim to integrate into Java graphical user interface (GUI) applications such as Java applets, Java Swing, and Java FX. The substantial method used in the integration process is TCP socket programming, which makes instruction and data transfers to provide interoperability between Python and Java GUIs. This empirical research integrates Python data analysis and visualization graphs into Java applications and does not require any additional libraries or third-party libraries. The experimentation confirmed the advantages and challenges of this integration with a concrete solution. The intended audience for this research extends to software developers, data analysts, and scientists, recognizing Python's broad applicability to artificial intelligence (AI) and machine learning (ML). The integration of data analysis and visualization and machine-learning functionalities within the Java GUI. It emphasizes the self-sufficiency of the integration process and suggests future research directions, including comparative analysis with Java's native capabilities, interactive data visualization using libraries like Altair, Bokeh, Plotly, and Pygal, performance and security considerations, and no-code and low-code implementations.

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QoS Aware Logical Channel Prioritization under Burst Resource Allocation for Uplink in LTE

QoS Aware Logical Channel Prioritization under Burst Resource Allocation for Uplink in LTE

Mannu Kumar, Neeti Kashyap

Статья научная

Long Term Evolution (LTE) is the latest 3GPP (3rd Generation Partnership Project) standard of the Mobile communication system. LTE has been proposed to achieve higher data throughput, lower latency and better quality of service (QoS). In LTE network (n/w), the resource (resource referred to frequency and time domain on the air interface) sharing is one of the major challenging issues and it is one of the key functions to achieve the desired QoS for the different configured data stream. In this context of QoS for LTE n/w, Multiplexing & Logical Channel Prioritization (LCP) is referred. In this paper, we present a brief survey on LCP techniques for the uplink (UL) direction. UL direction referred mobile to n/w communication. A strategy has been proposed for LCP to achieve QoS under burst resource allocation environment. Proposed approach considers the priority of each logical channel configured by evolved NodeB (eNB) during radio bearer (RB) setup/re-configuration.

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Quality of Service Enhancement of Wireless Sensor Network Using Symmetric Key Cryptographic Schemes

Quality of Service Enhancement of Wireless Sensor Network Using Symmetric Key Cryptographic Schemes

Er. Gurjot Singh, Er. Sandeep Kaur Dhanda

Статья научная

A Wireless Sensor Network is a combination of spatially distributed independent nodes deployed in dense environment, communicating wirelessly over limited bandwidth and frequency. Security and Qos is the major concern in wireless sensor network due to its wireless communication nature and constraints like low computation capability, less memory, bounded energy resources, susceptibility to physical capture or damages and the use of insecure wireless communication channels. These constraints make security along with the QoS, a challenge in wireless sensor network. The cryptographic schemes increases the level of security and make it secure against critical attacks but also has a significant impact on the QoS of wireless sensor network. In this paper, the different cryptographic schemes based on asymmetric key and symmetric key cryptography are evaluated. The symmetric key cryptography schemes require less time for processing, less power and also require less storage space as compared to asymmetric key cryptographic schemes, results in less impact on the QoS of wireless sensor network. In this paper, the QoS of wireless sensor network along with cryptographic schemes will be evaluated on the basis of metrics like throughput, jitter, end-to-end delay, total packet received and energy consumption.

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Quantitative Analysis of RFID based Vehicle Toll Collection System using UML and SPN

Quantitative Analysis of RFID based Vehicle Toll Collection System using UML and SPN

Razib Hayat Khan

Статья научная

This paper focuses on the quantitative analysis of RFID based vehicle toll collection system. Since we conduct the quantitative analysis long before the implementation of the infrastructure, the approach is realized by the UML and SPN to capture the system dynamics and carry out multiple performance tests of the possible infrastructure. Thus, the performance tests ensure the installation of correct number of RFID vehicle toll collection booth in the entrance of a bridge or a highway so that the traffic congestion can be kept as minimal as possible as well as financial viability can be confirmed. We analyze the response time and throughput to know the maximum limit for the diverse number of arrival vehicles that is served by the different number of toll booths. This finally gives us a better understanding of the number of units necessary for toll collection to decrease the traffic congestion in a budget constraint manner.

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Quantum-dot Controlled Electronic Block Triggering a Quantum Computation Procedure

Quantum-dot Controlled Electronic Block Triggering a Quantum Computation Procedure

Vladimir К. Voronov

Статья научная

The works devoted to an issue of quantum computer design have been analyzed. The main problems related to creation of the quantum computer are discussed. A fundamentally new approach to solving the problem of creating a truly quantum computer based on the “up to bottom” strategy has been proposed and justified. The strategy can be implemented by preliminary visualization of the quantum states of qubits using nanotriggers formed from two-dimensional material, in particular, graphene. This refers to the visualization (materialization) of all, including entangled, states, which mainly determine the theoretically possible large mathematical resource of a quantum computer. A block-diagram of the electronic device based on “a priory” quantum states of q-bits is proposed. It is shown that for implementation of quantum computation procedure, each materialized (visualized) Shor's cell should correspond to an element of the electronic scheme. The device includes a block containing at least 1010 nanotriggers that perform a role of q-bits of quantum computation, which are created using graphene nanoribbons and controlled by a special element. The latter represents a self-organizing quantum dot having two essentially different states in terms of magnetic properties. This quantum dot is prepared on the basis of a compound, the molecules of which are characterized by the intramolular rearrangement. The nanotriggers are employed to form reversible logic blocks or gates. Each gate contains three triggers to perform logical operations. The offered device is an additional electronic unit that is embedded in a digital computer, which makes it possible to implement the computational process in accordance with the requirements of the provisions of quantum physics.

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Quantum-dot cellular automata based fragile watermarking method for tamper detection using chaos

Quantum-dot cellular automata based fragile watermarking method for tamper detection using chaos

Turker Tuncer, Sengul Dogan

Статья научная

Fragile watermarking techniques have been widely used in the literature for tampered areas localization and image authentication. In this study, a novel quantum-dot cellular automata based fragile watermarking method for tampered area localization using chaotic piecewise map is proposed. Watermark generation, embedding, extraction and tampered area localization phases are consisted of the proposed quantum dot cellular automata and chaos based fragile watermarking method. In the watermark generation phase, quantum dot cellular automata and piecewise map which is a chaotic map are utilized. A block based method is utilized as authentication values embedding and extraction phases. To detect tampered areas, generated watermark and extracted watermark are compared. Also, block counters are used to tamper detection. In order to evaluate this method, capacity, imperceptibility and image authentication ability were utilized as performance metrics and the results of these metrics clearly illustrated that the presented method is suitable for image authentication and tamper detection.

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Query Recommendation by Coupling Personalization with Clustering for Search Engine

Query Recommendation by Coupling Personalization with Clustering for Search Engine

Dhiliphanrajkumar.Thambidurai, Suruliandi. Aandavar, Selvaperumal.Prakasam

Статья научная

In the present world internet and web search engines have become an important part in one's day-to-day life. For a user query, more than few thousand web pages are retrieved but most of them are irrelevant. A major problem in search engine is that the user queries are usually short and ambiguous, and they are not sufficient to satisfy the precise user needs. Also listing more number of results according to user make them worry about searching the desired results and it takes large amount of time to search from the huge list of results. To overcome all the problems, an effective approach is developed by capturing the users' click through and bookmarking data to provide personalized query recommendation. For retrieving the results, Google API is used. Experimental results show that the proposed method is providing better query recommendation results than the existing query suggestion methods.

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RBNS Encoded Energy Efficient Routing Protocol for Wireless Sensor Network

RBNS Encoded Energy Efficient Routing Protocol for Wireless Sensor Network

Indrajit Bhattcharya, Prasun Sarkar, Priyasha Basu

Статья научная

Self Organizing Wireless Sensor Networks (WSN) is an emergent and challenging technology that is applicable to various real life scenarios. Different routing protocols in the WSN have been proposed over the years. In this type of network the major concern is the energy constraint sensor nodes that operate on limited battery power. Hence energy efficient routing algorithm in WSN need to be developed in order to address the battery power constraint of the sensor nodes. Minimizing the communication overhead during the data transmission and reception can considerably reduce the energy requirement of the sensor nodes. Redundant Binary Number System (RBNS) is one of the energy efficient techniques that can reduce the communication overhead by reducing the number of 1’s required to communicate in a data packet. In our proposed work the RBNS communication technique is applied with an existing popular routing protocol in WSN to achieve an energy efficient routing protocol. The algorithm has been successfully implemented in a simulated environment and the result that has obtained demonstrates the significant enhancement of network lifetime of the sensor network.

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RDF link generation by exploring related links on the web of data

RDF link generation by exploring related links on the web of data

Kumar Sharma, Ujjal Marjit, Utpal Biswas

Статья научная

Interlinking RDF resources is a vital aspect of the Semantic Web technology. It is the basis of Linked Data that provides interlinked datasets on the web. One of the principles of Linked Data is interlinking resources from different data sources on the web. Data interlinking is a critical and challenging problem that every Linked Data generation applications face. Various approaches have been evolved for resolving this problem, but, for more massive datasets, it becomes almost indefinite time while linking similar or related resources. Linking RDF resources is like the problem of entity matching, record matching or duplicate resource detection. More or less they attempt to point to the same problem, but the RDF link generation is the task of finding related resources on the web. In this article, we present an approach for generating RDF links using the similarity measure between two RDF resources and by exploring associated relationships of the matched resources. The idea is to find related resources and link them with an RDF resource that is being generated.

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RFID Based Toll Deduction System

RFID Based Toll Deduction System

Asif Ali Laghari, M. Sulleman Memon, Agha Sheraz Pathan

Статья научная

In this research paper we examine RFID based toll deduction system and how to make more efficient and perfect. The vehicle will be equipped with a radio frequency (RF) tag which will detect RF Reader located in on toll plaza. The amount will then automatically deduct from the bank account. This research paper can be considered scalable to implement in motor vehicles used today.

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RLS Wiener Smoother for Colored Observation Noise with Relation to Innovation Theory in Linear Discrete-Time Stochastic Systems

RLS Wiener Smoother for Colored Observation Noise with Relation to Innovation Theory in Linear Discrete-Time Stochastic Systems

Seiichi Nakamori

Статья научная

Almost estimators are designed for the white observation noise. In the estimation problems, rather than the white observation noise, there might be actual cases where the observation noise is colored. This paper, from the viewpoint of the innovation theory, based on the recursive least-squares (RLS) Wiener fixed-point smoother and filter for the colored observation noise, newly proposes the RLS Wiener fixed-interval smoothing algorithm in linear discrete-time wide-sense stationary stochastic systems. The observation y(k) is given as the sum of the signal z(k)=Hx(k) and the colored observation noise (v_c)(k). The RLS Wiener fixed-interval smoother uses the following information: (a) the system matrix for the state vector x(k); (b) the observation matrix H; (c) the variance of the state vector; (d) the system matrix for the colored observation noise (v_c)(k); (e) the variance of the colored observation noise; (f) the input noise variance in the state equation for the colored observation noise.

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RS-CBAODV: An Enhanced Reactive Routing Algorithm for VANET to Reduce Connection Breakage using Remote Storage Concepts

RS-CBAODV: An Enhanced Reactive Routing Algorithm for VANET to Reduce Connection Breakage using Remote Storage Concepts

N. Arul Kumar, E. George Dharma Prakash Raj

Статья научная

Vehicular Ad hoc Network (VANET) is formed to share information on a temporary basis between the vehicular nodes in a wireless medium. The routing information is used to discover the vehicles and the route has to be maintained to transfer the data. It may lead to link failure or breakage in the communication, if there is high network mobility and constrained topology arrangement. In case of failure, it may cause loss of data and delay in the network. So, to avoid breakage, the routing information is stored in traditional protocols like CBAODV and CS-CBAODV. Instead of storing routing information in client side, the idea of storing data in the remote side is taken into consideration to backup permanently. This remote server manages the data in client server which is to be delivered to vehicular node. After analyzing related protocols and simulators, a new reactive based routing protocol is designed in this research work and it is named as RS-CBAODV is used to handle routing information between vehicular node, Client side node (RST i.e. Road Side Terminals) and also in Remote side storage node. To analysis the performance of the proposed protocol, MOVE and NS2 simulator is used to compare both CS-CBAODV and RS-CBAODV protocols.

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RSKD Ensemble Classifier with Stable Ensemble Feature Selection for High Dimensional Low Sample Size Cancer Datasets

RSKD Ensemble Classifier with Stable Ensemble Feature Selection for High Dimensional Low Sample Size Cancer Datasets

Archana Suhas Vaidya, Dipak V. Patil

Статья научная

This study presents the RSKD ensemble classifier, developed with ensemble feature selection techniques, to address high-dimensional, low-sample-size cancer datasets. Ensemble classifiers are advantageous in such scenarios, offering better classification accuracy than traditional methods by combining multiple models. This combination enhances predictive performance on high-dimensional datasets. However, stability—a key factor for consistent performance on unseen data—often involves a tradeoff with accuracy. Ensemble methods, due to their generalization capabilities, exhibit higher stability, with feature selection stability measured using a consistency index, averaging 65–70%. The RSKD classifier integrates ensemble feature selection methods SU-R and ChS-R, which enhance feature selection stability and classification accuracy. Its performance was evaluated on seven high-dimensional, low-sample-size datasets and compared against state-of-the-art classifiers, including Adaboost, GradientBoost, REPTree, asBagging_FSS, SRKNN, MF-GE, and eAdaBoost with DSC. The RSKD ensemble classifier achieved an accuracy improvement of 7.69% to 12.35% over these methods. Among the feature selection approaches, SU-R combined with RSKD outperformed ChS-R, demonstrating superior results in cancer prediction tasks. The findings of this study underscore the potential of RSKD for achieving generalized, robust performance on challenging datasets. By leveraging ensemble classifiers and ensemble feature selection techniques, researchers can address the inherent difficulties of high-dimensional, low-sample-size datasets, enhancing both accuracy and stability. This work provides a valuable foundation for developing diverse, heterogeneous ensemble approaches for cancer prediction and similar applications.

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