Pub Date : 2023-06-29DOI: 10.1109/SCSE59836.2023.10214990
H.A. Dimuthu Maduranga Arachchi, G. Samarasinghe
This study focused on explaining the influence of fashion retail autonomy avatar on consumers’ acceptance of fashion retail service; this study also examined the moderating impact of precision toward avatar acceptancy. Based on the extensive literature review, this study formulated five hypotheses to support the arguments. Quantitative methodology with a survey strategy was undertaken, which had an effective sample size of 278 young consumers. Furthermore, analysis was carried out using Smart partial least squares (PLS)-structural equation modelling. The study finds a significant direct relationship between the autonomy characters of avatar (sensing, thought, action) and consumer novel experience. Other than that, it also finds significant relationships between consumers’ novel experience and avatar acceptance. It was further revealed that precision toward avatar significantly moderates impact on fashion retail avatar acceptance. The findings shed the light on improving fashion retail service with avatar based applications.
{"title":"Impact of artificial autonomy avatar on consumer acceptance of fashion retail services","authors":"H.A. Dimuthu Maduranga Arachchi, G. Samarasinghe","doi":"10.1109/SCSE59836.2023.10214990","DOIUrl":"https://doi.org/10.1109/SCSE59836.2023.10214990","url":null,"abstract":"This study focused on explaining the influence of fashion retail autonomy avatar on consumers’ acceptance of fashion retail service; this study also examined the moderating impact of precision toward avatar acceptancy. Based on the extensive literature review, this study formulated five hypotheses to support the arguments. Quantitative methodology with a survey strategy was undertaken, which had an effective sample size of 278 young consumers. Furthermore, analysis was carried out using Smart partial least squares (PLS)-structural equation modelling. The study finds a significant direct relationship between the autonomy characters of avatar (sensing, thought, action) and consumer novel experience. Other than that, it also finds significant relationships between consumers’ novel experience and avatar acceptance. It was further revealed that precision toward avatar significantly moderates impact on fashion retail avatar acceptance. The findings shed the light on improving fashion retail service with avatar based applications.","PeriodicalId":429228,"journal":{"name":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130241645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-29DOI: 10.1109/SCSE59836.2023.10214986
Bhagya N. Wickramasinghe, P. Asanka
The world is shifting towards the higher utilization of renewable energy sources in the road to greener energy which conserves an environmentally friendly atmosphere. The generation of sustainable energy via adopting solar photovoltaic is common worldwide. The objectives of the research study are to identify the salient factors contributing to the energy generation of photovoltaic systems, to utilize a gamut of machine learning algorithms to build the predictive model and to identify the best machine learning algorithm to predict the energy generation based on accuracy and precision metrices. These objectives aid to achieve the aim of this study, which is to build a predictive model to determine the medium-term energy generated from on-grid rooftop solar systems. The study has unveiled a new piece of knowledge on how the photovoltaic system dynamics and location specific data has contributed to the prediction of the power output of the system. Further the findings are of paramount importance to the industry experts as well as the current and prospective solar panel users. The data of all solar panel sites of the installer was utilized and it was extracted from the source information systems. The necessary transformations and validations were applied and a detailed analysis was performed. The feature engineering, feature scaling, outlier-handling, multi-collinearity and feature selection was performed on data. The intended forecasting model based on fourteen supervised machine learning algorithms was built. The KNN Regression algorithm in the factor analysis of all features after principal component analysis has outperformed all other built models. Moreover, a strong positive co-relation was observed in the principal component analysis towards the solar panel energy output prediction. As part of future work, it’s imperative to build models utilizing a wider sample of on-grid roof top solar plants.
{"title":"Forecasting of Medium-Term Energy Output of On-Grid Rooftop Photovoltaic Arrays -Case Study for a Sri Lankan Solar Panel Installer","authors":"Bhagya N. Wickramasinghe, P. Asanka","doi":"10.1109/SCSE59836.2023.10214986","DOIUrl":"https://doi.org/10.1109/SCSE59836.2023.10214986","url":null,"abstract":"The world is shifting towards the higher utilization of renewable energy sources in the road to greener energy which conserves an environmentally friendly atmosphere. The generation of sustainable energy via adopting solar photovoltaic is common worldwide. The objectives of the research study are to identify the salient factors contributing to the energy generation of photovoltaic systems, to utilize a gamut of machine learning algorithms to build the predictive model and to identify the best machine learning algorithm to predict the energy generation based on accuracy and precision metrices. These objectives aid to achieve the aim of this study, which is to build a predictive model to determine the medium-term energy generated from on-grid rooftop solar systems. The study has unveiled a new piece of knowledge on how the photovoltaic system dynamics and location specific data has contributed to the prediction of the power output of the system. Further the findings are of paramount importance to the industry experts as well as the current and prospective solar panel users. The data of all solar panel sites of the installer was utilized and it was extracted from the source information systems. The necessary transformations and validations were applied and a detailed analysis was performed. The feature engineering, feature scaling, outlier-handling, multi-collinearity and feature selection was performed on data. The intended forecasting model based on fourteen supervised machine learning algorithms was built. The KNN Regression algorithm in the factor analysis of all features after principal component analysis has outperformed all other built models. Moreover, a strong positive co-relation was observed in the principal component analysis towards the solar panel energy output prediction. As part of future work, it’s imperative to build models utilizing a wider sample of on-grid roof top solar plants.","PeriodicalId":429228,"journal":{"name":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","volume":"430 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127942909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-29DOI: 10.1109/SCSE59836.2023.10214987
A. Withanaarachchi, A.M. Himashi Silva
The Sri Lankan apparel manufacturing business, a major contributor to the country’s export revenue, has been attempting to adopt industry 4.0. Only a few developing nations have been able to capture the maximum benefits of the fourth industrial revolution. The purpose of this study is to identify the critical factors that must be considered for the successful implementation of industry 4.0 in the Sri Lankan apparel manufacturing sector. Throughout the research, a quantitative approach was used. Initially, the six most significant critical factors and two moderating variables were determined by a review of prior research and the opinions of industry professionals. Partial Least Square – Structural Equation Modelling (PLS-SEM) was used to analyze the relationship between the factors. Greater financial investments, organizational strategy, workforce, a dynamic organizational culture, the involvement of top management, and the availability of IT infrastructure have a significant positive impact on the successful implementation of industry 4.0 in the Sri Lankan apparel manufacturing sector, as determined by the final findings of the data analysis. In addition, the availability and accessibility of support services have a significant positive moderating effect on financial investments, when successfully implementing industry 4.0 in the Sri Lankan apparel industry. In addition, the advancement of digital technologies has a significant positive moderating effect on financial investments and, a significant negative effect on organizational strategy and the involvement of top management when successfully implementing industry 4.0 in the Sri Lankan apparel industry. The outcomes of this study assist the managers of the Sri Lankan clothing manufacturing sector in comprehending the critical factors that must be considered when successfully implementing industry 4.0 technologies.
{"title":"Critical Success Factors Affecting the Successful Implementation of Industry 4.0 in The Sri Lankan Apparel Manufacturing Industry","authors":"A. Withanaarachchi, A.M. Himashi Silva","doi":"10.1109/SCSE59836.2023.10214987","DOIUrl":"https://doi.org/10.1109/SCSE59836.2023.10214987","url":null,"abstract":"The Sri Lankan apparel manufacturing business, a major contributor to the country’s export revenue, has been attempting to adopt industry 4.0. Only a few developing nations have been able to capture the maximum benefits of the fourth industrial revolution. The purpose of this study is to identify the critical factors that must be considered for the successful implementation of industry 4.0 in the Sri Lankan apparel manufacturing sector. Throughout the research, a quantitative approach was used. Initially, the six most significant critical factors and two moderating variables were determined by a review of prior research and the opinions of industry professionals. Partial Least Square – Structural Equation Modelling (PLS-SEM) was used to analyze the relationship between the factors. Greater financial investments, organizational strategy, workforce, a dynamic organizational culture, the involvement of top management, and the availability of IT infrastructure have a significant positive impact on the successful implementation of industry 4.0 in the Sri Lankan apparel manufacturing sector, as determined by the final findings of the data analysis. In addition, the availability and accessibility of support services have a significant positive moderating effect on financial investments, when successfully implementing industry 4.0 in the Sri Lankan apparel industry. In addition, the advancement of digital technologies has a significant positive moderating effect on financial investments and, a significant negative effect on organizational strategy and the involvement of top management when successfully implementing industry 4.0 in the Sri Lankan apparel industry. The outcomes of this study assist the managers of the Sri Lankan clothing manufacturing sector in comprehending the critical factors that must be considered when successfully implementing industry 4.0 technologies.","PeriodicalId":429228,"journal":{"name":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121442093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-29DOI: 10.1109/SCSE59836.2023.10215016
T.I. Attygalle, A. Withanaarachchi, S. Jayalal
IT industry is one of the fast-growing industries in Sri Lanka. In that industry the software development sector plays a massive role. Out of these software development firms, a considerable number of companies are startups. But compared to other countries, the contribution from software startups to the country’s economy is very low in Sri Lanka. Further with the current economic crisis Sri Lanka faces it is even harder for startups to continue their businesses and also it is challenging for an entrepreneur-minded person who wants to establish a software startup in Sri Lanka. This study focuses on the factors influencing the success of software startups in Sri Lanka and how those factors will be affected by the current economic crisis in Sri Lanka. The study has been conducted using a systematic literature review to discover and validate influential factors from past studies. Then the conceptual framework was formed to assess the variables. To validate the model, data was collected through an online questionnaire survey. Testing and validation of collected data were done using a comparative analysis between Smart PLS and SEMinR. The results of both studies show that the availability of finance is the only factor that has a significant relationship with the success of software startups in Sri Lanka. With that the study also recommends taking necessary actions to improve the availability of funds for software startup companies.
{"title":"Factors Influencing the Success of Software Startups in Sri Lanka: A Comparative Analysis using SmartPLS & SEMinR","authors":"T.I. Attygalle, A. Withanaarachchi, S. Jayalal","doi":"10.1109/SCSE59836.2023.10215016","DOIUrl":"https://doi.org/10.1109/SCSE59836.2023.10215016","url":null,"abstract":"IT industry is one of the fast-growing industries in Sri Lanka. In that industry the software development sector plays a massive role. Out of these software development firms, a considerable number of companies are startups. But compared to other countries, the contribution from software startups to the country’s economy is very low in Sri Lanka. Further with the current economic crisis Sri Lanka faces it is even harder for startups to continue their businesses and also it is challenging for an entrepreneur-minded person who wants to establish a software startup in Sri Lanka. This study focuses on the factors influencing the success of software startups in Sri Lanka and how those factors will be affected by the current economic crisis in Sri Lanka. The study has been conducted using a systematic literature review to discover and validate influential factors from past studies. Then the conceptual framework was formed to assess the variables. To validate the model, data was collected through an online questionnaire survey. Testing and validation of collected data were done using a comparative analysis between Smart PLS and SEMinR. The results of both studies show that the availability of finance is the only factor that has a significant relationship with the success of software startups in Sri Lanka. With that the study also recommends taking necessary actions to improve the availability of funds for software startup companies.","PeriodicalId":429228,"journal":{"name":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132366010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-29DOI: 10.1109/SCSE59836.2023.10215030
Achini Nisansala, Rukshani Puvnendran
The ability to recognize different postures of any living creature is a prerequisite for getting an accurate idea about their mental and physical well-being. Dogs are the most friendly and social canine breeds that provide love and security for human companions being their best friend at all times. The present study aimed at paying the initiatives at exploring important information about the wellbeing of the dogs with their sleeping postures. The paper studies and compared the classification performance of three deep transfer learning algorithms: VGG16, Xception, and ResNet50, and Convolutional Neural Network on a manually collected and augmented dataset of nearly 4000 images consisting of four different sleeping postures of dogs. Our model reveals that ResNet50 outperforms all other algorithms and achieved the highest accuracy of S7.35%. Overall, our finding would help disabled and special requirement dogs and their owners to identify canine’s health conditions and requirements using the sleeping postures and provide a more comfortable and better life for them.
{"title":"Canine Sleeping Posture Identification using Transfer Learning","authors":"Achini Nisansala, Rukshani Puvnendran","doi":"10.1109/SCSE59836.2023.10215030","DOIUrl":"https://doi.org/10.1109/SCSE59836.2023.10215030","url":null,"abstract":"The ability to recognize different postures of any living creature is a prerequisite for getting an accurate idea about their mental and physical well-being. Dogs are the most friendly and social canine breeds that provide love and security for human companions being their best friend at all times. The present study aimed at paying the initiatives at exploring important information about the wellbeing of the dogs with their sleeping postures. The paper studies and compared the classification performance of three deep transfer learning algorithms: VGG16, Xception, and ResNet50, and Convolutional Neural Network on a manually collected and augmented dataset of nearly 4000 images consisting of four different sleeping postures of dogs. Our model reveals that ResNet50 outperforms all other algorithms and achieved the highest accuracy of S7.35%. Overall, our finding would help disabled and special requirement dogs and their owners to identify canine’s health conditions and requirements using the sleeping postures and provide a more comfortable and better life for them.","PeriodicalId":429228,"journal":{"name":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129004842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-29DOI: 10.1109/SCSE59836.2023.10215001
Vithushigan Jayatharan, Dileeka Alwis
The recent advancements in deep learning techniques and computational power have promoted the development of novel approaches for music generation. In this study, generating alapana, an improvisational form of Carnatic music was proposed, by leveraging Generative Adversarial Networks (GANs) and Finite State Machines (FSM). The goal is to create melodious alapana sequences that follow a given input Raga, ensuring continuity and coherence throughout the generated musical piece. The proposed approach incorporates Carnatic music theory rules into the generation process to enhance the structural coherence of the generated alapana. Additionally, various hyperparameter settings were explored to achieve the best performance. The Fréchet Audio Distance, Percentage of Correct Pitches and the Subjective evaluation through human listeners are the evaluation metrics of this approach. The result of this study demonstrates the potential of using GANs and FSM for generating continuous and pleasing alapana sequences in Carnatic music, contributing to the growing body of research in computational music generation.
{"title":"Alapana Generation using Finite State Machines and Generative Adversarial Networks","authors":"Vithushigan Jayatharan, Dileeka Alwis","doi":"10.1109/SCSE59836.2023.10215001","DOIUrl":"https://doi.org/10.1109/SCSE59836.2023.10215001","url":null,"abstract":"The recent advancements in deep learning techniques and computational power have promoted the development of novel approaches for music generation. In this study, generating alapana, an improvisational form of Carnatic music was proposed, by leveraging Generative Adversarial Networks (GANs) and Finite State Machines (FSM). The goal is to create melodious alapana sequences that follow a given input Raga, ensuring continuity and coherence throughout the generated musical piece. The proposed approach incorporates Carnatic music theory rules into the generation process to enhance the structural coherence of the generated alapana. Additionally, various hyperparameter settings were explored to achieve the best performance. The Fréchet Audio Distance, Percentage of Correct Pitches and the Subjective evaluation through human listeners are the evaluation metrics of this approach. The result of this study demonstrates the potential of using GANs and FSM for generating continuous and pleasing alapana sequences in Carnatic music, contributing to the growing body of research in computational music generation.","PeriodicalId":429228,"journal":{"name":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125204440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-29DOI: 10.1109/SCSE59836.2023.10215009
S. De Silva, A. Withanaarachchi
ERP implementation failure can be one of the most expensive errors a business can make. It is critical to understand the success factors behind the effective usage of an ERP system in order to reduce the risk of failure. A large quantity of literature and research are available on factors behind a successful ERP initial implementation, but it lacks studies on post implementation. Moreover, there’s no such work has been done concerning the moderation implication of organizational culture and economic uncertainty over the association between the identified factors and the effective usage of ERP system making it a new addition to literature. Therefore, this research aims to study the success factors behind the effective usage of the ERP system in the post-implementation period and how the above moderators can moderate these factors on the effective usage of ERP system. A survey questionnaire was used to collect data from the users who are using an ERP system in a matured company in Sri Lanka. A preliminary data analysis was done using SPSS software and hypothesis were evaluated using Partial Least Squares Structural Equation Modelling approach as it enables researchers to estimate complex models with many constructs, indicator variables, and structural paths without imposing distributional assumptions on the data. The results of the study suggest that all the independent variables namely top management support, complexity of the ERP used, business IT infrastructure, hidden costs in ERP changes and training on ERP were influencing drivers for the effective usage of ERP system. In addition, concerning the moderator effect of organizational culture, top management support, ERP complexity and IT infrastructure showed a significant impact while the moderator effect of economic uncertainty, top management support, ERP complexity and training showed significant but negative relationship on the effective usage of the ERP system.
{"title":"Success Factors for the Effective Usage of an ERP System in the Post Implementation Period; Case of Sri Lankan Firms","authors":"S. De Silva, A. Withanaarachchi","doi":"10.1109/SCSE59836.2023.10215009","DOIUrl":"https://doi.org/10.1109/SCSE59836.2023.10215009","url":null,"abstract":"ERP implementation failure can be one of the most expensive errors a business can make. It is critical to understand the success factors behind the effective usage of an ERP system in order to reduce the risk of failure. A large quantity of literature and research are available on factors behind a successful ERP initial implementation, but it lacks studies on post implementation. Moreover, there’s no such work has been done concerning the moderation implication of organizational culture and economic uncertainty over the association between the identified factors and the effective usage of ERP system making it a new addition to literature. Therefore, this research aims to study the success factors behind the effective usage of the ERP system in the post-implementation period and how the above moderators can moderate these factors on the effective usage of ERP system. A survey questionnaire was used to collect data from the users who are using an ERP system in a matured company in Sri Lanka. A preliminary data analysis was done using SPSS software and hypothesis were evaluated using Partial Least Squares Structural Equation Modelling approach as it enables researchers to estimate complex models with many constructs, indicator variables, and structural paths without imposing distributional assumptions on the data. The results of the study suggest that all the independent variables namely top management support, complexity of the ERP used, business IT infrastructure, hidden costs in ERP changes and training on ERP were influencing drivers for the effective usage of ERP system. In addition, concerning the moderator effect of organizational culture, top management support, ERP complexity and IT infrastructure showed a significant impact while the moderator effect of economic uncertainty, top management support, ERP complexity and training showed significant but negative relationship on the effective usage of the ERP system.","PeriodicalId":429228,"journal":{"name":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122599210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-29DOI: 10.1109/scse59836.2023.10214998
{"title":"Technical Programme Committee","authors":"","doi":"10.1109/scse59836.2023.10214998","DOIUrl":"https://doi.org/10.1109/scse59836.2023.10214998","url":null,"abstract":"","PeriodicalId":429228,"journal":{"name":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122114611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-29DOI: 10.1109/SCSE59836.2023.10214996
Thamara Damayanthi, S. Ahangama
Due to globalization, Sri Lanka’s education system is experiencing major difficulty in maintaining educational quality. It is imperative to adopt the latest educational technology to meet global education standards. Information Technology (IT) tools can be used as creative teaching aids to increase the quality of teaching and learning. Computer laboratory in-charge teachers will have to share scarce IT resources among the school community. This study proposes a new methodology for sharing IT resources and it will facilitate the implementation of a computer laboratory management system (CLMS). The study was conducted using the Information System (IS) Design Science approach to create a usable IT artifact to solve this foreseen problem in government schools. The pre and post-evaluations were done with research rigor based on Delone and McLean’s IS success model in multiple iterations to allow users to determine whether their expectations are achieved by the system. 59 computer laboratory in-charge teachers participated in the evaluation process of the existing system and the new system. The result shows that the new CLMS will benefit the target community with some improvements to increase the service quality of the IS.
{"title":"Computer Laboratory Management System for Government Schools in Sri Lanka: Design Science Approach","authors":"Thamara Damayanthi, S. Ahangama","doi":"10.1109/SCSE59836.2023.10214996","DOIUrl":"https://doi.org/10.1109/SCSE59836.2023.10214996","url":null,"abstract":"Due to globalization, Sri Lanka’s education system is experiencing major difficulty in maintaining educational quality. It is imperative to adopt the latest educational technology to meet global education standards. Information Technology (IT) tools can be used as creative teaching aids to increase the quality of teaching and learning. Computer laboratory in-charge teachers will have to share scarce IT resources among the school community. This study proposes a new methodology for sharing IT resources and it will facilitate the implementation of a computer laboratory management system (CLMS). The study was conducted using the Information System (IS) Design Science approach to create a usable IT artifact to solve this foreseen problem in government schools. The pre and post-evaluations were done with research rigor based on Delone and McLean’s IS success model in multiple iterations to allow users to determine whether their expectations are achieved by the system. 59 computer laboratory in-charge teachers participated in the evaluation process of the existing system and the new system. The result shows that the new CLMS will benefit the target community with some improvements to increase the service quality of the IS.","PeriodicalId":429228,"journal":{"name":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123573947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-29DOI: 10.1109/SCSE59836.2023.10215015
Bhimaja Goonatillaka, C. Kodithuwakku, Amila Sandaruwan, Thamalsha Wijayarathne, J. Wickramarathne
Apps for mobile health (mHealth) have proliferated and offer a variety of features to help users achieve better health outcomes. Thousands of mHealth apps are giving many great options for end users and they also introduce different options for different requirements. In this study the focus is specifically on the fitness mobile health apps. There are a variety of UX evaluation frameworks that are being used for the UX evaluation of those apps. However, not much research work is available in evaluating the UX frameworks relevant to mHealth mobile apps. The three frameworks evaluated in this study are the hook model, the mental model, and the double diamond model as those models have shown considerable success in this context. Five main user case studies are used in the user testing relevant to the UX of the selected mHealth app. At least three casual interviews together with three observation sessions are conducted per respondent to gather feedback on the usability, accessibility, and the effectiveness of the three frameworks. Thereby, the three frameworks are compared for their suitability and recommendations are tendered in suggesting a better suited framework for the UX evaluation purposes for mHealth apps. The Double Diamond Hook Mental (DDHM) hybrid model is proposed as the main outcome of this study to overcome the inherent drawbacks of each framework if used individually. After usability testing, it has proven that this proposed model enables to guide improved UX of mHealth apps.
{"title":"A Comparative Study of Three User Experience Frameworks for Enhancing Health Mobile Applications","authors":"Bhimaja Goonatillaka, C. Kodithuwakku, Amila Sandaruwan, Thamalsha Wijayarathne, J. Wickramarathne","doi":"10.1109/SCSE59836.2023.10215015","DOIUrl":"https://doi.org/10.1109/SCSE59836.2023.10215015","url":null,"abstract":"Apps for mobile health (mHealth) have proliferated and offer a variety of features to help users achieve better health outcomes. Thousands of mHealth apps are giving many great options for end users and they also introduce different options for different requirements. In this study the focus is specifically on the fitness mobile health apps. There are a variety of UX evaluation frameworks that are being used for the UX evaluation of those apps. However, not much research work is available in evaluating the UX frameworks relevant to mHealth mobile apps. The three frameworks evaluated in this study are the hook model, the mental model, and the double diamond model as those models have shown considerable success in this context. Five main user case studies are used in the user testing relevant to the UX of the selected mHealth app. At least three casual interviews together with three observation sessions are conducted per respondent to gather feedback on the usability, accessibility, and the effectiveness of the three frameworks. Thereby, the three frameworks are compared for their suitability and recommendations are tendered in suggesting a better suited framework for the UX evaluation purposes for mHealth apps. The Double Diamond Hook Mental (DDHM) hybrid model is proposed as the main outcome of this study to overcome the inherent drawbacks of each framework if used individually. After usability testing, it has proven that this proposed model enables to guide improved UX of mHealth apps.","PeriodicalId":429228,"journal":{"name":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129023853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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