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检索条件"任意字段=8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023"

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Crow Search Freeman Chain Code (CS-FCC) Feature Extraction Algorithm for Handwritten Character Recognition 8

Crow Search Freeman Chain Code (CS-FCC) Feature Extraction A...

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8th ieee international conference on software engineering and computer systems, icsecs 2023

作者： Mohamad, Muhammad Arif Musa, Zalili Ismail, Amelia Ritahani Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan Pahang26600 Malaysia Kulliyyah of Information and Communication Technology International Islamic University Malaysia Kuala Lumpur Malaysia

ISBN: (纸本)9798350310931

With so many algorithms developed to improve classification accuracy, interest in feature extraction in Handwritten Character Recognition (HCR) has increased. In this research, a Crow Search Algorithm (CSA)-based metaheuristic strategy for feature extraction in HCR was developed. the data representation method employed was Freeman Chain Code (FCC). the fundamental issue with using FCC to represent a character is that the outcomes of the extractions depend on the starting points that changed the chain code's route length. the shortest route length and least amount of computational time for HCR were found using the metaheuristic technique via CSA, which was suggested as a solution to this issue. the suggested CS-FCC extraction algorithm's computation durations and route lengths serve as performance indicators. the algorithm experiments are carried out using the chain code representation created from previous research of the Centre of Excellence for Document Analysis and Recognition (CEDAR) dataset, which consists of 126 upper-case letter characters. According to the results, the proposed CS-FCC has a route length of 1880.28 and only takes 1.10 seconds to solve the entire set of character images. © 2023 ieee.

关键词： Feature extraction

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Shaping the Digital Future of Civil Service: An Assessment of Digital Transformation and Data Science Competencies 8

Shaping the Digital Future of Civil Service: An Assessment o...

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8th ieee international conference on software engineering and computer systems, icsecs 2023

作者： Junaini, Syahrul Nizam Bujang, Sopian Basmawi, Nadri Aetis Fauzaman, Jusmawati Universiti Malaysia Sarawak Faculty of Computer Science and Information Technology Kota Samarahan Sarawak94300 Malaysia Universiti Malaysia Sarawak Faculty of Cognitive Science and Human Development Kota Samarahan Sarawak94300 Malaysia Leadership Institute of Sarawak Civil Service Kuching Sarawak93250 Malaysia Abdulhamid Abusulayman Kulliyyah of IRKHS International Islamic University Malaysia Kuala Lumpur50728 Malaysia

ISBN: (纸本)9798350310931

In the era of digital transformation and data proliferation, the need for effective digital competency assessment is increasingly critical. However, existing frameworks often lack comprehensive integration of key digital transformation and data science competencies necessary for roles within the civil service sector. this study introduces a robust instrument to profile competency domains critical to digital transformation and data science roles in the civil service. Leveraging a four-phase mixed-method methodology, including brainstorming, external validation, and a pilot study, the instrument was developed, validated, and tested among 30 state government servants. the reliability of the domains-Data Analytics, Data Science Management, Data and Digital Architecture, and Digital Transformation-was confirmed by excellent Cronbach's Alpha values ( 0.9). Content validity was evaluated using Lawshe's Content Validity Ratio (CVR) and Index (CVI), indicating strong validity for Digital Transformation and Data and Digital Architecture domains, while suggesting refinement for Data Analytics and Data Science Management. the proposed instrument, validated through self-evaluation scores, illustrates potential for career and organizational development within the civil service, emphasizing its practical value and feasibility. © 2023 ieee.

关键词： Data Analytics

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SDN Enabled Big Data Analytics and Framework for Sensor Data of Vehicle Health, Safety and Monitoring System 8

SDN Enabled Big Data Analytics and Framework for Sensor Data...

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8th ieee international conference on software engineering and computer systems, icsecs 2023

作者： Ahmad, Tanvir Ismail, Nor Syahidatul Nadiah Binti Safri, Abdullah Mat Rahman, Md. Arafatur Beg, Mohammad Sojon Bin Bakhtiar, M. Taher University Malaysia Pahang Al-Sultan Abdullah Faculty of Computing Pekan Malaysia Unversity of Wolverhampton Faculty of Science and Engineering Wolverhampton United Kingdom University Malaysia Pahang Al-Sultan Abdullah Faculty of Mechanical and Automotive Engineering Malaysia Kulliyyah of Pharmacy IIUM Kuantan Campus Kuantan Malaysia

ISBN: (纸本)9798350310931

Vehicular network enabled vehicle health, safety and monitoring system is gaining attention for its potential application while software defined network (SDN) is supporting vehicular communication for designing core of the network. Vehicular network emits enormous amount of data where most of them are sensor data and that amount of data required to undergo analyzed for productive output. there are two types of sensor data are used in vehicular network, vehicle sensor data (VSD) and infrastructure sensor data (ISD). Flow based SDN controller examines every packet of the network which is responsible of engagement of resources gravely. For vehicular health monitoring and safety applications, SDN doesn't required to check and analyze ISD. In this paper, a framework is proposed that promises to ignore ISD and only consider VSD for vehicle health, safety and monitoring applications. With this connections, this paper proposes big data module along with SDN controller and inside the big data module, a partitioner program is designed. the partitioner program categorize VSD and ISD on the basis of certain parameters like data payload, technology used, packet header and restrict RSD to be processed by SDN controller. A combiner program is designed that bind both VSD and ISD to fed to the application plane of system. Additionally, a big data analytics for vehicle health, safety and monitoring application is derived. © 2023 ieee.

关键词： Big data

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COVID-19 Analysis and Predictions Evaluation for KSA Using Machine Learning 7

COVID-19 Analysis and Predictions Evaluation for KSA Using M...

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7th international conference on software engineering and computer systems and 4th international conference on Computational Science and Information Management, icsecs-ICOCSIM 2021

作者： Elarabi, Rawia Alqahtani, Fatimah Balobaid, Awatef Zain, Halah Babiker, Najla Jazan University Computer Science Department Jazan Saudi Arabia Jazan University Information Technology Department Jazan Saudi Arabia

ISBN: (纸本)9781665414074

the unprecedented rise in the number of new coronavirus infections worldwide has prompted many researchers to use mathematical and machine-learning-based prediction models to predict future epidemic patterns that will help governments, health service providers, and society understand how to deal with this situation. Using different machine learning methodologies helps researchers to understand the trend curve clearly. these may lead to a better and more effective fight against the epidemic and reduce or end preventive measures, allowing people to return to their everyday lives. this study is based on an analysis of COVID-19 data of KSA. Also, it demonstrates the prediction of the new confirmed cases and death of COVID-19 in the next ten days from 8th July in KSA, which is considered the period of the performing Hajj in 2021. It uses machine learning models such as Support Vector Machine (SVM), Bayesian Edge (BR), Linear Regression (LR), and Moving Average (MA). Each model provides two types of predictions: the number of newly infected cases and deaths over the next 10 days. the results indicate that SVM and MA forecasts have high accuracy, followed by LR which performs well. the BR performs poorly in forecast scenarios when applied with the available data set in forecasting new confirmed cases. All models were accurate in predicting mortality, with the best performing model being SVM, followed by MA, LR, and BR. It also expects an increase in confirmed cases under the SVM model scenario to 511, 257 on 17th July from 496, 516 on 7th July in the actual daily cumulative cases. the number of deaths will rise to 8, 113 on 17th July from 7, 921 on 7th July in actual cumulative daily data. © 2021 ieee.

关键词： Coronavirus

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Effective Visualization Electrification System via PSCADA Event Log in Railway Industry 8

Effective Visualization Electrification System via PSCADA Ev...

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8th ieee international conference on software engineering and computer systems, icsecs 2023

作者： Bin Kamaruddin, Syamsul Azrin Hashim, Hairulazwan Bin Binti Mohamad, Elmy Johana Binti Mohamad, Nazwa Hidayah Mamat, Halim Bin Universiti Tun Hussein Onn Malaysia Centre for Diploma Studies Department of Mechanical Engineering Johor Malaysia Faculty of Engineering Technology Johor Malaysia Universiti Tun Hussein Onn Malaysia Faculty of Electrical and Electronic Engineering Department of Electrical Engineering Johor Malaysia Pestech Technology Sdn. Bhd. Department of Quality Health Safety Environment and System Assurance Selangor Malaysia Keretapi Tanah Melayu Berhad Department of Electrification Kuala Lumpur Malaysia

ISBN: (纸本)9798350310931

Rail transport has been one of the main intercity passenger train operators in Malaysia. the Electrification Department is the most important department to make sure the trains have enough power to operate and is responsible for the maintenance of the power supply infrastructure and SCADA system to ensure the Electrification System is accurately monitored and controlled and assure the Reliability, Availability, Maintainability and Safety of the system. the key issue faced by this department is related to reporting on maintenance. the report was very time-consuming to prepare because it was on a paper-based method, and information was presented badly due to the lack of a visualization tool and being vulnerable to data quality problems. To address this issue, the current study aims to propose a tool that provides screening and detecting of device fault status using a dashboard developed using Microsoft Power BI by extracting the raw data log from the Power SCADA server. We demonstrate the process of adopting the cloud-based dashboard using Power BI at the strategic management level. the development of the dashboard system is adopted from the previous research framework, consisting of four main stages which are designing, data analyzing process, visualizing, and validating. One of the findings is that the data cleansing process is the most important stage to produce the right information. this interactive tool made instant visibility of device status and assisted the maintenance team to capture the status trends. the study benefits to the organization are to reduce 86% of the time and cost to prepare the maintenance reporting and planning. © 2023 ieee.

关键词： Electric utilities

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Performance Evaluation of Completed Local Ternary Patterns (CLTP) for Medical, Scene and Event Image Categorisation 4

Performance Evaluation of Completed Local Ternary Patterns (...

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4th international conference on software engineering and computer systems (icsecs)

作者： Rassem, Taha H. Mohammed, Mohammed Falah Khoo, Bee Ee Makbol, Nasrin M. Univ Malaysia Pahang Fac Comp Syst & Software Engn Kuantan Malaysia Univ Sains Malaysia Sch Elect & Elect Engn George Town Malaysia

ISBN: (纸本)9781467367226

the Completed Local Ternary Pattern descriptor (CLTP) was proposed to overcome the drawbacks of the Local Binary Pattern (LBP). It used for rotation invariant texture classification and demonstrated superior classification accuracy with different types of texture datasets. In this paper, the performance of CLTP for image categorisation is studied and investigated. Different image datasets are used in the experiments such as the Oliva and Torralba datasets (OT8), Event sport datasets, and 2D HeLa medical images. the experimental results proved the superiority of the CLTP descriptor over the original LBP, and different new texture descriptors such as Completed Local Binary Pattern (CLBP) in the image categorisation task. In 2D HeLa medical images, the proposed CLTP achieved the highest state of the art classification rate reaching 95.62%.

关键词： Completed Local Ternary Pattern descriptor (CLTP) Local Binary Pattern (LBP) Completed Local Binary Pattern (CLBP) 2D HeLa image categorisation

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Managing software evolution with a formalized abstraction hierarchy 8

Managing software evolution with a formalized abstraction hi...

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8th ieee international conference on engineering of Complex computer systems

作者： Aaltonen, T Mikkonen, T Tampere Univ Technol FIN-33101 Tampere Finland

ISBN: (纸本)0769517579

Complex computer systems are seldom made from scratch but they, contain significant amounts of legacy code, which then is under continuous pressure for evolution. therefore, a need for a rigorous method for managing evolution in this setting is evident. In this paper we propose a management method for reactive and distributed systems. the method is based on creating a formal abstraction hierarchy to model the system with abstractions that exceed those that are used as implementation facilities. this hierarchy is then used to assess the cost of a modification by associating the modification to appropriate abstractions in the hierarchy and by determining the abstractions that need to be revisited to retain the hierarchy consistent.

关键词： computer architecture computer languages Costs Packaging Robustness software architecture software design software engineering software quality Switches

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A light-weight process for capturing and evolving defect reduction experience 8

A light-weight process for capturing and evolving defect red...

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8th ieee international conference on engineering of Complex computer systems

作者： Basili, VR Lindvall, M Shull, F Fraunhofer Center for Experimental Software Engineering MD United States

ISBN: (纸本)0769517579

Selecting technologies for developing software is a crucial activity in software projects. Defect reduction is an example of an area in which software developers have to decide what technologies to use. CeBASE is a NSF funded project that has the role of improving software development by providing decision support on the selection of techniques and tools. the decision support is based on empirical data organized in experience bases and refined into high-level models. Empirical data is collected through various activities, for example through eWorkshops in which experts discuss important issues, and formalized using the lightweight knowledge dust to knowledge pearl process.

关键词： Costs Fault detection Financial management Optical propagation Phase detection Programming software debugging software engineering software quality software systems

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Using aspects to design a secure system 8

Using aspects to design a secure system

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8th ieee international conference on engineering of Complex computer systems

作者： Georg, G Ray, I France, R Agilent Technol Ft Collins CO USA

ISBN: (纸本)0769517579

Developers of complex systems have to address concerns such as security, availability of services, and timeliness that often are non-orthogonal to traditional design structures, that is, the concerns cross-cut traditional design units. In this paper we illustrate how an aspect-oriented approach to modeling allows developers to encapsulate such design concerns so that they can be woven into a design in a systematic and consistent manner. the paper focuses on the use of aspects for modeling and weaving in security concerns.

关键词： Availability Information security Interference Internet Pattern analysis Programming software design software systems Unified modeling language Weaving

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An evolutionary lifecycle model with Agile practices for software development at ABB 8

An evolutionary lifecycle model with Agile practices for sof...

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8th ieee international conference on engineering of Complex computer systems

作者： Dagnino, A ABB US Corp Res Ctr Raleigh NC USA

ISBN: (纸本)0769517579

Current software environments face increased pressure to develop products under evolving requirements, changing technologies, scarce human, resources, and the need to develop high quality applications. ABB has similar pressures, especially as the organization embraces the Industrial (IT) initiative that aims at the development of interoperable and intelligent products. A new generation of software development lifecycle models has emerged lately called "Agile" and they embrace change, reduce development cycle time, and attempt a useful compromise between no process and too much process. the Agile Development in Evolutionary Prototyping Technique (ADEPT) presented in this paper, was developed at the ABB US Corporate Research Center, and incorporates "Agile" practices to streamline the technology development lifecycle of Industrial (IT) products.

关键词： Application software Collaboration Face Humans Predictive models Process control Programming Prototypes software prototyping software quality

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