Pub Date : 2022-12-02DOI: 10.1109/SKIMA57145.2022.10029532
Seanghort Born, Dona Valy, Phutphalla Kong
Correcting spelling errors in texts extracted from Khmer palm leaf manuscripts by handwritten text recognition (HTR) systems can be very challenging. A Khmer Language Model developed in this study aims to facilitate the task mentioned above. The proposed model utilizes long short-term memory (LSTM) modules applicable for improving the performance of text recognition which is to predict a sequence of characters as output. The architecture of the language model is based on an encoder-decoder mechanism which is composed of two parts: an encoder to capture the context of the input erroneous word and a decoder to decode and predict the correctly spelt output word. Experimental evaluations are conducted on a text corpus consisting of Khmer words extracted from Sleuk-Rith set.
{"title":"Encoder-Decoder Language Model for Khmer Handwritten Text Recognition in Historical Documents","authors":"Seanghort Born, Dona Valy, Phutphalla Kong","doi":"10.1109/SKIMA57145.2022.10029532","DOIUrl":"https://doi.org/10.1109/SKIMA57145.2022.10029532","url":null,"abstract":"Correcting spelling errors in texts extracted from Khmer palm leaf manuscripts by handwritten text recognition (HTR) systems can be very challenging. A Khmer Language Model developed in this study aims to facilitate the task mentioned above. The proposed model utilizes long short-term memory (LSTM) modules applicable for improving the performance of text recognition which is to predict a sequence of characters as output. The architecture of the language model is based on an encoder-decoder mechanism which is composed of two parts: an encoder to capture the context of the input erroneous word and a decoder to decode and predict the correctly spelt output word. Experimental evaluations are conducted on a text corpus consisting of Khmer words extracted from Sleuk-Rith set.","PeriodicalId":277436,"journal":{"name":"2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114434865","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 : 2022-12-02DOI: 10.1109/SKIMA57145.2022.10029650
C. Csáki, Z. Szabó, A. Gábor
Teaching Business Information Systems programs faces increased pressure from several sources. On the one hand the underlying field of IT and technologies change rapidly, on the other future employers of BIS graduates have diverging expectation (which has also been changing). Furthermore, digital savviness of students and their expectations towards highly technological teaching solutions is increasing, while new pedagogical methods gaining ground as well. To meet these challenges - further complicated with the demand for blended learning solution by the recent pandemic - require higher education institutions to find new ways of delivering BIS degree programs. The approach reported in this paper proposes the redesign of the full curriculum (instead of just ‘fixing’ individual courses). Such redesign is organized around the TOGAF framework and utilizes problem-based learning and online education pushed to the extreme. Elements of the proposal (called BIPER) has been tested in the context of a Summer School using VR technology and online collaboration tools.
{"title":"Problem-based Redesign of the BIS Curriculum","authors":"C. Csáki, Z. Szabó, A. Gábor","doi":"10.1109/SKIMA57145.2022.10029650","DOIUrl":"https://doi.org/10.1109/SKIMA57145.2022.10029650","url":null,"abstract":"Teaching Business Information Systems programs faces increased pressure from several sources. On the one hand the underlying field of IT and technologies change rapidly, on the other future employers of BIS graduates have diverging expectation (which has also been changing). Furthermore, digital savviness of students and their expectations towards highly technological teaching solutions is increasing, while new pedagogical methods gaining ground as well. To meet these challenges - further complicated with the demand for blended learning solution by the recent pandemic - require higher education institutions to find new ways of delivering BIS degree programs. The approach reported in this paper proposes the redesign of the full curriculum (instead of just ‘fixing’ individual courses). Such redesign is organized around the TOGAF framework and utilizes problem-based learning and online education pushed to the extreme. Elements of the proposal (called BIPER) has been tested in the context of a Summer School using VR technology and online collaboration tools.","PeriodicalId":277436,"journal":{"name":"2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132930600","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 : 2022-12-02DOI: 10.1109/SKIMA57145.2022.10029603
R. Chea
Women run 65% of businesses in Cambodia, and 96% are micro-sized and participate in the informal economy. These women face barriers of a lack of education, digital literacy, technology, access to finance, and legal and regulatory challenges. This paper presents an investigation into the development of a high-quality All-in-one eCommerce technology platform to overcome these barriers. These include access to the market by providing digital literacy and marketing support for vendors to create a storefront on our platform for their handmade and local goods. To achieve this goal, this research has investigated the development of an All-in-one eCommerce platform called Khmum eShop for various activities including financial tools for sales reports and Financial Statements. With banking partners, AMK Microfinance Institution Plc., Acleda, and SMEs Bank, the platform offers vendors to use their inventory stock report and financial statement as collateral for loan application prep to clear pathways to finance. The proposed platform has been co-created with multiple stakeholders based on the needs of the community vendors and has been tested, validated, and deployed to community vendors. It was found that the proposed innovative framework has a significant impact on growing the community vendors.
{"title":"Women Entrepreneur Capacity Building toward Digital Economy Using an All-in-One eCommerce Platform","authors":"R. Chea","doi":"10.1109/SKIMA57145.2022.10029603","DOIUrl":"https://doi.org/10.1109/SKIMA57145.2022.10029603","url":null,"abstract":"Women run 65% of businesses in Cambodia, and 96% are micro-sized and participate in the informal economy. These women face barriers of a lack of education, digital literacy, technology, access to finance, and legal and regulatory challenges. This paper presents an investigation into the development of a high-quality All-in-one eCommerce technology platform to overcome these barriers. These include access to the market by providing digital literacy and marketing support for vendors to create a storefront on our platform for their handmade and local goods. To achieve this goal, this research has investigated the development of an All-in-one eCommerce platform called Khmum eShop for various activities including financial tools for sales reports and Financial Statements. With banking partners, AMK Microfinance Institution Plc., Acleda, and SMEs Bank, the platform offers vendors to use their inventory stock report and financial statement as collateral for loan application prep to clear pathways to finance. The proposed platform has been co-created with multiple stakeholders based on the needs of the community vendors and has been tested, validated, and deployed to community vendors. It was found that the proposed innovative framework has a significant impact on growing the community vendors.","PeriodicalId":277436,"journal":{"name":"2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133022155","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 : 2022-12-02DOI: 10.1109/SKIMA57145.2022.10029570
Afsana Airin, Rezab Ud Dawla, Ahmed Shabab Noor, Muhib Al Hasan, Ahmed Rafi Hasan, Akib Zaman, D. Farid
The automated creation of a semantic structural scene graph from an image or video is known as scene graph generation (SGG), which includes accurate labeling of all objects that are identified and the interconnections between them. Several SGG methods have been proposed employing deep learning techniques nowadays to achieve good results but most of the approaches failed to integrate the contextual information of pair of objects. Apart from the existing state of the arts of SGG, the attention mechanism is creating a new horizon in this field. This paper offers a thorough analysis of the most recent Attention-Based Scene Graph Generation techniques. In this paper, we have compared and tested five existing Attention-Based Scene Graph Generation methods. We have summarised the results of existing methods to understand progress in this field of Scene Graph Generation. Moreover, we have discussed the strengths of existing techniques and future directions of attention-based models in Scene Graph Generation.
{"title":"Attention-Based Scene Graph Generation: A Review","authors":"Afsana Airin, Rezab Ud Dawla, Ahmed Shabab Noor, Muhib Al Hasan, Ahmed Rafi Hasan, Akib Zaman, D. Farid","doi":"10.1109/SKIMA57145.2022.10029570","DOIUrl":"https://doi.org/10.1109/SKIMA57145.2022.10029570","url":null,"abstract":"The automated creation of a semantic structural scene graph from an image or video is known as scene graph generation (SGG), which includes accurate labeling of all objects that are identified and the interconnections between them. Several SGG methods have been proposed employing deep learning techniques nowadays to achieve good results but most of the approaches failed to integrate the contextual information of pair of objects. Apart from the existing state of the arts of SGG, the attention mechanism is creating a new horizon in this field. This paper offers a thorough analysis of the most recent Attention-Based Scene Graph Generation techniques. In this paper, we have compared and tested five existing Attention-Based Scene Graph Generation methods. We have summarised the results of existing methods to understand progress in this field of Scene Graph Generation. Moreover, we have discussed the strengths of existing techniques and future directions of attention-based models in Scene Graph Generation.","PeriodicalId":277436,"journal":{"name":"2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114500062","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 : 2022-12-02DOI: 10.1109/SKIMA57145.2022.10029463
Dongyang Huo, Sri Devi Ravana, A. Malik, A. U. Rahman, I. Ahmedy
Traditional agriculture is highly dependent on human participation and experience. Therefore, it is not possible to guarantee crop yield and quality while expanding the production scale. In recent years, based on the continuous development and innovation of IoT and ICT technologies, the concept of smart farming has started to receive the attention of researchers and farmers. However, many existing smart agriculture applications and research are conducted under controlled environments such as greenhouse farming, vertical farming, and hydroponic farming, etc. Few studies have shifted attention to large-scale arable agriculture, thus neglecting the scalability of the system. This work presents a simulation stack (digital mapping) in which the results of running the simulation model in a large-scale class of real-world scenarios are used to enhance the further performance of the proposed farming system in large-scale scenarios.
{"title":"Towards Smart Farming: Simulation Framework to Exploit Network Connectivity for End-to-End Data Transmission","authors":"Dongyang Huo, Sri Devi Ravana, A. Malik, A. U. Rahman, I. Ahmedy","doi":"10.1109/SKIMA57145.2022.10029463","DOIUrl":"https://doi.org/10.1109/SKIMA57145.2022.10029463","url":null,"abstract":"Traditional agriculture is highly dependent on human participation and experience. Therefore, it is not possible to guarantee crop yield and quality while expanding the production scale. In recent years, based on the continuous development and innovation of IoT and ICT technologies, the concept of smart farming has started to receive the attention of researchers and farmers. However, many existing smart agriculture applications and research are conducted under controlled environments such as greenhouse farming, vertical farming, and hydroponic farming, etc. Few studies have shifted attention to large-scale arable agriculture, thus neglecting the scalability of the system. This work presents a simulation stack (digital mapping) in which the results of running the simulation model in a large-scale class of real-world scenarios are used to enhance the further performance of the proposed farming system in large-scale scenarios.","PeriodicalId":277436,"journal":{"name":"2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124842640","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 : 2022-12-02DOI: 10.1109/SKIMA57145.2022.10029487
Chayada Kanokphanvanich, W. Rattanawong, V. Vongmanee
The coronavirus (COVID-19) pandemic has had a huge impact all over the world. Healthcare industry is one that has been greatly affected by Global supply chain disruption, including shortages of critical medical equipment and drugs, insufficiency of diagnostic, and inadequacy of medical personnel. The aforementioned problems directly affect human health in the dimension of “patient safety” which may cause life-threatening situations. Therefore, it is important to learn how to strengthen the healthcare supply chain (HSC) and increase safety, particularly for patients. There are various researchers who studied HSC performance in developed countries but the research in developing countries especially southeast Asia countries e.g., Cambodia is scarce. Therefore, this research aims to identify and synthesize HSC performance for patient safety and provide a novel model of HSC performance in developing countries' healthcare settings. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) was conducted using a patient safety definition from WHO, International Patient Safety Goals from Joint Commission International (JCI), and the Hospital Accreditation institute (HA) from Thailand. The HSC performances are categorized under the easily recognizable heading SIMPLE (stands for patient safety goals in 6 domains as follows: Safe surgery, Infection Prevention & Control, Medication safety, Patient care process, Laboratory & blood product safety, and Emergency preparedness and response). The novel model of HSC performance for patient safety is provided to demonstrate the factors that can enhance the performance of HSC management in developing countries. Moreover, this study contributes to the meta-analysis by analyzing existing research and proposing new future research opportunities in HSC performance for patient safety that leads to social sustainability.
{"title":"A Meta-Analysis of Health care Supply Chain Performance for Patient Safety","authors":"Chayada Kanokphanvanich, W. Rattanawong, V. Vongmanee","doi":"10.1109/SKIMA57145.2022.10029487","DOIUrl":"https://doi.org/10.1109/SKIMA57145.2022.10029487","url":null,"abstract":"The coronavirus (COVID-19) pandemic has had a huge impact all over the world. Healthcare industry is one that has been greatly affected by Global supply chain disruption, including shortages of critical medical equipment and drugs, insufficiency of diagnostic, and inadequacy of medical personnel. The aforementioned problems directly affect human health in the dimension of “patient safety” which may cause life-threatening situations. Therefore, it is important to learn how to strengthen the healthcare supply chain (HSC) and increase safety, particularly for patients. There are various researchers who studied HSC performance in developed countries but the research in developing countries especially southeast Asia countries e.g., Cambodia is scarce. Therefore, this research aims to identify and synthesize HSC performance for patient safety and provide a novel model of HSC performance in developing countries' healthcare settings. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) was conducted using a patient safety definition from WHO, International Patient Safety Goals from Joint Commission International (JCI), and the Hospital Accreditation institute (HA) from Thailand. The HSC performances are categorized under the easily recognizable heading SIMPLE (stands for patient safety goals in 6 domains as follows: Safe surgery, Infection Prevention & Control, Medication safety, Patient care process, Laboratory & blood product safety, and Emergency preparedness and response). The novel model of HSC performance for patient safety is provided to demonstrate the factors that can enhance the performance of HSC management in developing countries. Moreover, this study contributes to the meta-analysis by analyzing existing research and proposing new future research opportunities in HSC performance for patient safety that leads to social sustainability.","PeriodicalId":277436,"journal":{"name":"2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128675870","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 : 2022-12-02DOI: 10.1109/skima57145.2022.10029413
{"title":"Copyright and Reprint Permission","authors":"","doi":"10.1109/skima57145.2022.10029413","DOIUrl":"https://doi.org/10.1109/skima57145.2022.10029413","url":null,"abstract":"","PeriodicalId":277436,"journal":{"name":"2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125188316","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 : 2022-12-02DOI: 10.1109/SKIMA57145.2022.10029537
A. A. Masud, Sabbir Hossain, Muhsina Rifa, Farhana Akter, Akib Zaman, D. Farid
In the present digital era, a popular use of Machine learning is knowledge mining from big data. Machine learning is the sub-branch of Artificial Intelligence (AI) that extracts rules automatically from Big Data for decision-making to build expert systems. Meta-Learning is a sub-branch of machine learning, which uses machine learning classifiers that learns to map and combine predictions and information of data of other ML-models in the field of ensemble-learning. Meta-learning helps us to select the best/right learning algorithms to solve a particular problem. It maps from the meta-data of other machine learning algorithms by evaluating it on different datasets. In this paper, we have presented very recent state-of-the-art research works on meta-learning. We have categorized meta-learning on supervised learning data sets into three categories: (1) Task Independent Recommendation, (2) Configuration Space Design, and (3) Configuration Transfer, and reviewed the recent works on each category.
{"title":"Meta-Learning in Supervised Machine Learning","authors":"A. A. Masud, Sabbir Hossain, Muhsina Rifa, Farhana Akter, Akib Zaman, D. Farid","doi":"10.1109/SKIMA57145.2022.10029537","DOIUrl":"https://doi.org/10.1109/SKIMA57145.2022.10029537","url":null,"abstract":"In the present digital era, a popular use of Machine learning is knowledge mining from big data. Machine learning is the sub-branch of Artificial Intelligence (AI) that extracts rules automatically from Big Data for decision-making to build expert systems. Meta-Learning is a sub-branch of machine learning, which uses machine learning classifiers that learns to map and combine predictions and information of data of other ML-models in the field of ensemble-learning. Meta-learning helps us to select the best/right learning algorithms to solve a particular problem. It maps from the meta-data of other machine learning algorithms by evaluating it on different datasets. In this paper, we have presented very recent state-of-the-art research works on meta-learning. We have categorized meta-learning on supervised learning data sets into three categories: (1) Task Independent Recommendation, (2) Configuration Space Design, and (3) Configuration Transfer, and reviewed the recent works on each category.","PeriodicalId":277436,"journal":{"name":"2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127378892","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 : 2022-12-02DOI: 10.1109/SKIMA57145.2022.10029536
Chaowapark Srikasem, P. Sureepong, Ahmad Yahya Dawod, N. Chakpitak
The adaptation of halal food to Chinese food culture was investigated in a meta-analysis of this China e-commerce study. Indoctrination is a sociocultural transformation in the Coronavirus pandemic in which a community of people or an in-dividual integrates into a different culture or country by adopting the host culture's linguistic skills, social features, nutritional pat-terns, and the current growth of e-commerce consumption. We ap-ply a data-driven marketing approach and modify the STP model in marketing to analyze the product differentiation parameters ac-cording to the research. Consuming halal food prepared following Islamic standards is a religious dietary obligation imposed on all Muslims, regardless of where they reside or travel. In Arabic, the term “halal food” refers to food that is legal and allowed to ingest. Among many other dietary requirements, Islamic tenets ban the consumption of porcine food items, dead animal meat, animal blood, and any quantity of alcohol. Islam and halal eating prac-tices were introduced to China in the early seventh century by Cen-tral Asians and Muslim missionaries traveling through the peri-lous ancient desert. Throughout its history, China has been a non-Muslim country, but halal food practice has been successfully assimilated and even flourished as a key component of contemporary Chinese cuisine culture. This paper addresses the two most significant variables that have contributed to the successful cultural as-similation of halal food into the new Chinese food culture in the digital era through key Chinese e-commerce sites.
{"title":"Data-Driven Approach to Raise the Marketing and Trade Strategy based on Halal Food Product Transactions of China Market","authors":"Chaowapark Srikasem, P. Sureepong, Ahmad Yahya Dawod, N. Chakpitak","doi":"10.1109/SKIMA57145.2022.10029536","DOIUrl":"https://doi.org/10.1109/SKIMA57145.2022.10029536","url":null,"abstract":"The adaptation of halal food to Chinese food culture was investigated in a meta-analysis of this China e-commerce study. Indoctrination is a sociocultural transformation in the Coronavirus pandemic in which a community of people or an in-dividual integrates into a different culture or country by adopting the host culture's linguistic skills, social features, nutritional pat-terns, and the current growth of e-commerce consumption. We ap-ply a data-driven marketing approach and modify the STP model in marketing to analyze the product differentiation parameters ac-cording to the research. Consuming halal food prepared following Islamic standards is a religious dietary obligation imposed on all Muslims, regardless of where they reside or travel. In Arabic, the term “halal food” refers to food that is legal and allowed to ingest. Among many other dietary requirements, Islamic tenets ban the consumption of porcine food items, dead animal meat, animal blood, and any quantity of alcohol. Islam and halal eating prac-tices were introduced to China in the early seventh century by Cen-tral Asians and Muslim missionaries traveling through the peri-lous ancient desert. Throughout its history, China has been a non-Muslim country, but halal food practice has been successfully assimilated and even flourished as a key component of contemporary Chinese cuisine culture. This paper addresses the two most significant variables that have contributed to the successful cultural as-similation of halal food into the new Chinese food culture in the digital era through key Chinese e-commerce sites.","PeriodicalId":277436,"journal":{"name":"2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126064045","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 : 2022-12-02DOI: 10.1109/SKIMA57145.2022.10029649
Benbouzid Mohamed, S. Elkosantini, S. Darmoul
The exploitation and management of a public transportation system (PTS) is usually considered as a complex task, which is even more challenging when various types of disturbances are considered. Although many approaches were suggested to control disturbances, only a few of them addressed the modeling and analysis of their propagation, and the evaluation of their potential impacts on the PTS entities, performance, and behavior. Without such analysis, decision making would be misled and its effectiveness/efficiency hindered. Thus, this paper presents an integrated and multidimensional framework firstly for disturbance propagation. The framework includes a disturbance evaluation model that takes into account bus related data and resilience index and a multistep bus features and residual error prediction models.
{"title":"Multidimensional Disturbance Propagation Model for a Network of Bus Lines","authors":"Benbouzid Mohamed, S. Elkosantini, S. Darmoul","doi":"10.1109/SKIMA57145.2022.10029649","DOIUrl":"https://doi.org/10.1109/SKIMA57145.2022.10029649","url":null,"abstract":"The exploitation and management of a public transportation system (PTS) is usually considered as a complex task, which is even more challenging when various types of disturbances are considered. Although many approaches were suggested to control disturbances, only a few of them addressed the modeling and analysis of their propagation, and the evaluation of their potential impacts on the PTS entities, performance, and behavior. Without such analysis, decision making would be misled and its effectiveness/efficiency hindered. Thus, this paper presents an integrated and multidimensional framework firstly for disturbance propagation. The framework includes a disturbance evaluation model that takes into account bus related data and resilience index and a multistep bus features and residual error prediction models.","PeriodicalId":277436,"journal":{"name":"2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114300849","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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