Fátima C. C. Dargam, E. Perz, S. Bergmann, E. Rodionova, Pedro Sousa, Francisco Alexandre A. Souza, Tiago Matias, J. M. Ortiz, A. Estéve-Núñez, Pau Rodenas, Patricia Zamora Bonachela
This paper describes some of the work carried out within the Horizon 2020 project MIDES (MIcrobial DESalination for low energy drinking water), which is developing the world's largest demonstration of a low-energy sys-tem to produce safe drinking water. The work in focus concerns the support for operational decisions on desalination plants, specifically applied to a mi-crobial-powered approach for water treatment and desalination, starting from the stages of process modelling, process simulation, optimization and lab-validation, through the stages of plant monitoring and automated control. The work is based on the application of the environment IPSEpro for the stage of process modelling and simulation; and on the system DataBridge for auto-mated control, which employs techniques of Machine Learning.
{"title":"Operational Decision-Making on Desalination Plants: From Process Modelling and Simulation to Monitoring and Automated Control With Machine Learning","authors":"Fátima C. C. Dargam, E. Perz, S. Bergmann, E. Rodionova, Pedro Sousa, Francisco Alexandre A. Souza, Tiago Matias, J. M. Ortiz, A. Estéve-Núñez, Pau Rodenas, Patricia Zamora Bonachela","doi":"10.4018/ijdsst.315639","DOIUrl":"https://doi.org/10.4018/ijdsst.315639","url":null,"abstract":"This paper describes some of the work carried out within the Horizon 2020 project MIDES (MIcrobial DESalination for low energy drinking water), which is developing the world's largest demonstration of a low-energy sys-tem to produce safe drinking water. The work in focus concerns the support for operational decisions on desalination plants, specifically applied to a mi-crobial-powered approach for water treatment and desalination, starting from the stages of process modelling, process simulation, optimization and lab-validation, through the stages of plant monitoring and automated control. The work is based on the application of the environment IPSEpro for the stage of process modelling and simulation; and on the system DataBridge for auto-mated control, which employs techniques of Machine Learning.","PeriodicalId":42414,"journal":{"name":"International Journal of Decision Support System Technology","volume":"10 1","pages":"1-20"},"PeriodicalIF":1.1,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75216933","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}
Cities are complex and dynamic systems in which a network of actors interact, creating value through different activities. Cities can, therefore, be viewed as service ecosystems. Municipalities take advantage of digitalization to implement a service-dominant logic in urban and mobility planning and management, developing strategies with which citizens, local authorities, and other actors can create value together. While citizens are offered a better service experience, local authorities use citizens' input to improve decision-making processes. This research considers that designing an integrated service supported by an integrated information system can respond to current challenges in decision-making and information access for transport and mobility. Through a multidisciplinary methodological approach, this work proposes some guidelines to design an integrated information system to improve citizens' participation in urban planning and mobility services.
{"title":"Rethinking Technology-Based Services to Promote Citizen Participation in Urban Mobility","authors":"S. Duarte, J. P. Sousa, Jorge Freire de Sousa","doi":"10.4018/ijdsst.315642","DOIUrl":"https://doi.org/10.4018/ijdsst.315642","url":null,"abstract":"Cities are complex and dynamic systems in which a network of actors interact, creating value through different activities. Cities can, therefore, be viewed as service ecosystems. Municipalities take advantage of digitalization to implement a service-dominant logic in urban and mobility planning and management, developing strategies with which citizens, local authorities, and other actors can create value together. While citizens are offered a better service experience, local authorities use citizens' input to improve decision-making processes. This research considers that designing an integrated service supported by an integrated information system can respond to current challenges in decision-making and information access for transport and mobility. Through a multidisciplinary methodological approach, this work proposes some guidelines to design an integrated information system to improve citizens' participation in urban planning and mobility services.","PeriodicalId":42414,"journal":{"name":"International Journal of Decision Support System Technology","volume":"19 1","pages":"1-20"},"PeriodicalIF":1.1,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90039564","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}
M. T. Escobar, J. Aguarón, J. Moreno‐Jiménez, Alberto Turón
This paper presents a DSS aimed at helping decision makers reduce and improve their inconsistency in eliciting their judgements when using the analytic hierarchy process (AHP). The DSS is designed for revising the judgements of a pairwise comparison matrix when the row geometric mean (RGM) is used as the prioritisation procedure and the geometric consistency index (GCI) as the inconsistency measure. The procedure employed guarantees that both the judgements and the derived priority vector will be close to the initial values. The DSS allows different degrees of participation of the decision maker in the review/modification of the judgements: no participation (automatic mode); prior participation (semi-automatic mode); and ongoing participation (interactive mode). The DSS also includes options to incorporate other requirements of the decision maker, such as limiting the modified values to an interval or improving inconsistency by modifying the lowest number of judgements, among others.
{"title":"A Decision Support System for Improving the Inconsistency in AHP","authors":"M. T. Escobar, J. Aguarón, J. Moreno‐Jiménez, Alberto Turón","doi":"10.4018/ijdsst.315644","DOIUrl":"https://doi.org/10.4018/ijdsst.315644","url":null,"abstract":"This paper presents a DSS aimed at helping decision makers reduce and improve their inconsistency in eliciting their judgements when using the analytic hierarchy process (AHP). The DSS is designed for revising the judgements of a pairwise comparison matrix when the row geometric mean (RGM) is used as the prioritisation procedure and the geometric consistency index (GCI) as the inconsistency measure. The procedure employed guarantees that both the judgements and the derived priority vector will be close to the initial values. The DSS allows different degrees of participation of the decision maker in the review/modification of the judgements: no participation (automatic mode); prior participation (semi-automatic mode); and ongoing participation (interactive mode). The DSS also includes options to incorporate other requirements of the decision maker, such as limiting the modified values to an interval or improving inconsistency by modifying the lowest number of judgements, among others.","PeriodicalId":42414,"journal":{"name":"International Journal of Decision Support System Technology","volume":"20 1","pages":"1-16"},"PeriodicalIF":1.1,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86105701","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}
Guoqing Zhao, Shaofeng Liu, S. Elgueta, J. Manzur, Carmen Lopez, Huilan Chen
The current world business environment is characterized by increasing uncertainties, complexities, and risks, which require agri-food supply chain (AFSC) managers to respond and act quickly in a context full of instability and unpredictability. Increasing pressure placed on AFSC managers intensifies the need to combine knowledge management (KM) and decision support that rapidly overcome knowledge boundaries. It has been recognized that the research issue related to the knowledge mobilization crossing boundaries in the AFSC needs to be addressed. This paper investigates knowledge boundaries and boundary-spanning mechanisms by collecting data from experienced AFSC practitioners. Empirical results verify that knowledge boundaries such as syntactic boundaries, semantic boundaries, and pragmatic boundaries could be effectively tackled by four specific boundary-spanning mechanisms: boundary spanners, boundary objects, boundary practices, and boundary discourses.
{"title":"Knowledge Mobilization for Agri-Food Supply Chain Decisions: Identification of Knowledge Boundaries and Categorization of Boundary-Spanning Mechanisms","authors":"Guoqing Zhao, Shaofeng Liu, S. Elgueta, J. Manzur, Carmen Lopez, Huilan Chen","doi":"10.4018/ijdsst.315640","DOIUrl":"https://doi.org/10.4018/ijdsst.315640","url":null,"abstract":"The current world business environment is characterized by increasing uncertainties, complexities, and risks, which require agri-food supply chain (AFSC) managers to respond and act quickly in a context full of instability and unpredictability. Increasing pressure placed on AFSC managers intensifies the need to combine knowledge management (KM) and decision support that rapidly overcome knowledge boundaries. It has been recognized that the research issue related to the knowledge mobilization crossing boundaries in the AFSC needs to be addressed. This paper investigates knowledge boundaries and boundary-spanning mechanisms by collecting data from experienced AFSC practitioners. Empirical results verify that knowledge boundaries such as syntactic boundaries, semantic boundaries, and pragmatic boundaries could be effectively tackled by four specific boundary-spanning mechanisms: boundary spanners, boundary objects, boundary practices, and boundary discourses.","PeriodicalId":42414,"journal":{"name":"International Journal of Decision Support System Technology","volume":"26 1","pages":"1-25"},"PeriodicalIF":1.1,"publicationDate":"2022-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86920938","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}
In the present scenario, it is inevitable for organizations to use the services offered through the cloud. As there are numerous cloud service providers, the users have a vast number of choices to get the desired service. For the long term success of any organization, it is important to choose the right cloud service provider. This paper focuses on proposing a new framework to select the best cloud service provider. While selecting the best service provider, using an appropriate method for finding out the weight of each criterion is very important as it directly impacts the ranking of candidate service providers. In this work, the Full Consistency Method (FUCOM) is employed for finding the weight of each criterion and Multi-Objective Optimization by Ratio Analysis (MOORA) is proposed for ranking the service provider. The integration of FUCOM with MOORA results in computing the reliable values of criteria weight and a simpler procedure for computing the overall score of the service provider. Hence a rational decision making is possible in selecting the best cloud service provider.
{"title":"An Integrated Multi-Criteria Decision-Making Model for Cloud Service Provider Selection","authors":"S. Uma, D. Geetha","doi":"10.4018/ijdsst.286692","DOIUrl":"https://doi.org/10.4018/ijdsst.286692","url":null,"abstract":"In the present scenario, it is inevitable for organizations to use the services offered through the cloud. As there are numerous cloud service providers, the users have a vast number of choices to get the desired service. For the long term success of any organization, it is important to choose the right cloud service provider. This paper focuses on proposing a new framework to select the best cloud service provider. While selecting the best service provider, using an appropriate method for finding out the weight of each criterion is very important as it directly impacts the ranking of candidate service providers. In this work, the Full Consistency Method (FUCOM) is employed for finding the weight of each criterion and Multi-Objective Optimization by Ratio Analysis (MOORA) is proposed for ranking the service provider. The integration of FUCOM with MOORA results in computing the reliable values of criteria weight and a simpler procedure for computing the overall score of the service provider. Hence a rational decision making is possible in selecting the best cloud service provider.","PeriodicalId":42414,"journal":{"name":"International Journal of Decision Support System Technology","volume":"88 1","pages":"1-18"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86867981","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}
This article has developed specifications for a new model-driven decision support system (DSS) that aids the key stakeholders of public hospitals in estimating and tracking a set of crucial performance indicators pertaining to the patients flow. The developed specifications have considered several requirements for ensuring an effective system, including tracking the performance indicator on the level of the entire patients flow system, paying attention to the dynamic change of the values of the indicator’s parameters, and considering the heterogeneity of the patients. According to these requirements, the major components of the proposed system, which include a comprehensive object-based queuing model and an object-oriented database, have been specified. In addition to these components, the system comprises the equations that produce the required predictions. From the system output perspective, these predictions act as a foundation for evaluating the performance indicators as well as developing policies for managing the patients flow in the public hospitals.
{"title":"Specifications of a Queuing Model-Driven Decision Support System for Predicting the Healthcare Performance Indicators Pertaining to the Patient Flow","authors":"A. A. Fadelelmoula","doi":"10.4018/ijdsst.286676","DOIUrl":"https://doi.org/10.4018/ijdsst.286676","url":null,"abstract":"This article has developed specifications for a new model-driven decision support system (DSS) that aids the key stakeholders of public hospitals in estimating and tracking a set of crucial performance indicators pertaining to the patients flow. The developed specifications have considered several requirements for ensuring an effective system, including tracking the performance indicator on the level of the entire patients flow system, paying attention to the dynamic change of the values of the indicator’s parameters, and considering the heterogeneity of the patients. According to these requirements, the major components of the proposed system, which include a comprehensive object-based queuing model and an object-oriented database, have been specified. In addition to these components, the system comprises the equations that produce the required predictions. From the system output perspective, these predictions act as a foundation for evaluating the performance indicators as well as developing policies for managing the patients flow in the public hospitals.","PeriodicalId":42414,"journal":{"name":"International Journal of Decision Support System Technology","volume":"6 1","pages":"1-24"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86557068","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}
POS (Parts of Speech) tagging, a vital step in diverse Natural Language Processing (NLP) tasks has not drawn much attention in case of Odia a computationally under-developed language. The proposed hybrid method suggests a robust POS tagger for Odia. Observing the rich morphology of the language and unavailability of sufficient annotated text corpus a combination of machine learning and linguistic rules is adopted in the building of the tagger. The tagger is trained on tagged text corpus from the domain of tourism and is capable of obtaining a perceptible improvement in the result. Also an appreciable performance is observed for news articles texts of varied domains. The performance of proposed algorithm experimenting on Odia language shows its manifestation in dominating over existing methods like rule based, hidden Markov model (HMM), maximum entropy (ME) and conditional random field (CRF).
{"title":"A Modified Markov-Based Maximum-Entropy Model for POS Tagging of Odia Text","authors":"Sagarika Pattnaik, Ajit Kumar Nayak","doi":"10.4018/ijdsst.286690","DOIUrl":"https://doi.org/10.4018/ijdsst.286690","url":null,"abstract":"POS (Parts of Speech) tagging, a vital step in diverse Natural Language Processing (NLP) tasks has not drawn much attention in case of Odia a computationally under-developed language. The proposed hybrid method suggests a robust POS tagger for Odia. Observing the rich morphology of the language and unavailability of sufficient annotated text corpus a combination of machine learning and linguistic rules is adopted in the building of the tagger. The tagger is trained on tagged text corpus from the domain of tourism and is capable of obtaining a perceptible improvement in the result. Also an appreciable performance is observed for news articles texts of varied domains. The performance of proposed algorithm experimenting on Odia language shows its manifestation in dominating over existing methods like rule based, hidden Markov model (HMM), maximum entropy (ME) and conditional random field (CRF).","PeriodicalId":42414,"journal":{"name":"International Journal of Decision Support System Technology","volume":"69 1","pages":"1-24"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86137125","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}
Nana Yaw Asabere, Elikem Fiamavle, Joseph Agyiri, W. Torgby, Joseph Eyram Dzata, N. Doe
In the domain of cyber security, the defence mechanisms of networks has traditionally been placed in a reactionary role. Cyber security professionals are therefore disadvantaged in a cyber-attack situation due to the fact that it is vital that they maneuver such attacks before the network is totally compromised. In this paper, we utilize the Betweenness Centrality network measure (social property) to discover possible cyber-attack paths and then employ computation of similar personality of nodes/users to generate predictions about possible attacks within the network. Our method proposes a social recommender algorithm called socially-aware recommendation of cyber-attack paths (SARCP), as an attack predictor in the cyber security defence domain. In a social network, SARCP exploits and delivers all possible paths which can result in cyber-attacks. Using a real-world dataset and relevant evaluation metrics, experimental results in the paper show that our proposed method is favorable and effective.
{"title":"SARCP: Exploiting Cyber-Attack Prediction Through Socially-Aware Recommendation","authors":"Nana Yaw Asabere, Elikem Fiamavle, Joseph Agyiri, W. Torgby, Joseph Eyram Dzata, N. Doe","doi":"10.4018/ijdsst.286691","DOIUrl":"https://doi.org/10.4018/ijdsst.286691","url":null,"abstract":"In the domain of cyber security, the defence mechanisms of networks has traditionally been placed in a reactionary role. Cyber security professionals are therefore disadvantaged in a cyber-attack situation due to the fact that it is vital that they maneuver such attacks before the network is totally compromised. In this paper, we utilize the Betweenness Centrality network measure (social property) to discover possible cyber-attack paths and then employ computation of similar personality of nodes/users to generate predictions about possible attacks within the network. Our method proposes a social recommender algorithm called socially-aware recommendation of cyber-attack paths (SARCP), as an attack predictor in the cyber security defence domain. In a social network, SARCP exploits and delivers all possible paths which can result in cyber-attacks. Using a real-world dataset and relevant evaluation metrics, experimental results in the paper show that our proposed method is favorable and effective.","PeriodicalId":42414,"journal":{"name":"International Journal of Decision Support System Technology","volume":"27 1 1","pages":"1-21"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85479145","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}
Utility mining with negative item values has recently received interest in the data mining field due to its practical considerations. Previously, the values of utility item-sets have been taken into consideration as positive. However, in real-world applications an item-set may be related to negative item values. This paper presents a method for redesigning the ordering policy by including high utility item-sets with negative items. Initially, utility mining algorithm is used to find high utility item-sets. Then, ordering policy is estimated for high utility items considering defective and non-defective items. A numerical example is illustrated to validate the results
{"title":"Ordering Policy Estimation for High Utility Item-Sets Considering Negative Item Values in Large Databases","authors":"R. Agarwal","doi":"10.4018/ijdsst.286682","DOIUrl":"https://doi.org/10.4018/ijdsst.286682","url":null,"abstract":"Utility mining with negative item values has recently received interest in the data mining field due to its practical considerations. Previously, the values of utility item-sets have been taken into consideration as positive. However, in real-world applications an item-set may be related to negative item values. This paper presents a method for redesigning the ordering policy by including high utility item-sets with negative items. Initially, utility mining algorithm is used to find high utility item-sets. Then, ordering policy is estimated for high utility items considering defective and non-defective items. A numerical example is illustrated to validate the results","PeriodicalId":42414,"journal":{"name":"International Journal of Decision Support System Technology","volume":"25 1","pages":"1-16"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85841508","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}
Plant detection forms an integral part of the life of the forest guards, researchers, and students in the field of Botany and for common people also who are curious about knowing a plant. But detecting plants suffer a major drawback that the true identifier is only the flower and in certain species flowering occurs at major time period gaps spanning from few months to over 100 years (in certain types of bamboos). Machine Learning-based systems could be used in developing models where the experience of researchers in the field of plant sciences can be incorporated into the model. In this paper, we present a machine learning-based approach based upon other quantifiable parameters for the detection of the plant presented. The system takes plant parameters as the inputs and will detect the plant family as the output.
{"title":"Parametric Model for Flora Detection in Middle Himalayas","authors":"Aviral Sharma, S. Nigam","doi":"10.4018/ijdsst.286698","DOIUrl":"https://doi.org/10.4018/ijdsst.286698","url":null,"abstract":"Plant detection forms an integral part of the life of the forest guards, researchers, and students in the field of Botany and for common people also who are curious about knowing a plant. But detecting plants suffer a major drawback that the true identifier is only the flower and in certain species flowering occurs at major time period gaps spanning from few months to over 100 years (in certain types of bamboos). Machine Learning-based systems could be used in developing models where the experience of researchers in the field of plant sciences can be incorporated into the model. In this paper, we present a machine learning-based approach based upon other quantifiable parameters for the detection of the plant presented. The system takes plant parameters as the inputs and will detect the plant family as the output.","PeriodicalId":42414,"journal":{"name":"International Journal of Decision Support System Technology","volume":"78 1","pages":"1-11"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82583082","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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