Search results for: design decision support system

Authors: Paulo Mendonca, Nzar Faiq Naqeshbandi

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The objective of this study is to propose an interactive design environment that outlines the underlying computational framework to reach self-supporting overhangs. The research demonstrates the digital printability of overhangs taking into consideration factors related to the geometry design, the material used, the applied support, and the printing set-up of slicing and the extruder inclination. Parametric design tools can contribute to the design phase, form-finding, and stability optimization of self-supporting structures while printing in order to hold the components in place until they are sufficiently advanced to support themselves. The challenge is to ensure the stability of the printed parts in the critical inclinations during the whole fabrication process. Facilitating the identification of parameterization will allow to predict and optimize the process. Later, in the light of the previous findings, some guidelines of simulations and physical tests are given to be conducted for estimating the structural and functional performance.

Keywords: additive manufacturing, overhangs, self-support overhangs, printability, parametric tools

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Authors: Cristian Matti, Valerie Fowles, Eva Enyedi, Piotr Pogorzelski

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The system mapping process can be defined as a knowledge service where a team of facilitators, experts and practitioners facilitate a guided conversation, enable the exchange of information and support an iterative curation process. System mapping processes rely on science-based tools to introduce and simplify a variety of components and concepts of socio-technical systems through metaphors while facilitating an interactive dialogue process to enable the design of co-created maps. System maps work then as “artifacts” to provide information and focus the conversation into specific areas around the defined challenge and related decision-making process. Knowledge management facilitates the curation of that data gathered during the system mapping sessions through practices of documentation and subsequent knowledge co-production for which common practices from data science are applied to identify new patterns, hidden insights, recurrent loops and unexpected elements. This study presents empirical evidence on the application of these techniques to explore mechanisms by which visual tools provide guiding principles to portray system components, key variables and types of data through the lens of climate change. In addition, data science facilitates the structuring of elements that allow the analysis of layers of information through affinity and clustering analysis and, therefore, develop simple indicators for supporting the decision-making process. This paper addresses methodological and empirical elements on the horizontal learning process that integrate system mapping through visual tools, interpretation, cognitive transformation and analysis. The process is designed to introduce practitioners to simple iterative and inclusive processes that create actionable knowledge and enable a shared understanding of the system in which they are embedded.

Keywords: indicators, knowledge management, system mapping, visual tools

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Authors: Shafiq ur Rehman, Zubair Ahmed Shaikh

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This research provides the comparative study of different mobile payment system and proposes an efficient solution of mobile payment system. The research involves discovering how the mobile payment methods can be used and implemented keeping user and system interaction under consideration. The implementation of Nielsen’s heuristic and universal design principles enhanced the user’s interaction design and made the system more appropriate, understandable and visible to the end user. The design of application is greatly affected by the user driven factors. These factors help in the efficiency of the application usage.

Keywords: mobile payment system, m-commerce, usability, near field communication

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Authors: Tulio Sulbaran, Sandeep Langar

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Architects are an integral part of the construction industry and are continuously incorporating decisions that influence projects during their life cycle. These decisions aim at selecting best alternative from the ones available. Unfortunately, this decision making process is mainly unexplored in the construction industry. No instrument to measure construction decision, based on knowledgebase of decision-makers, has existed. Additionally, limited literature is available on the topic. Recently, an instrument to gain an understanding of the construction decision-making process was developed by Dr. Tulio Sulbaran from the University of Texas, San Antonio. The instrument’s name is 'Construction Decision Making Inventory (CDMI)'. The CDMI is an innovative idea to measure the 'What? When? How? Moreover, Who?' of the construction decision-making process. As an innovative idea, its statistical validity (accuracy of the assessment) is yet to be assessed. Thus, the purpose of this paper is to describe the results of a case study with architects in the south-east of the United States aimed to determine the CDMI validity. The results of the case study are important because they assess the validity of the tool. Furthermore, as the architects evaluated each question within the measurements, this study is also guiding the enhancement of the CDMI.

Keywords: decision, support, inventory, architect

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Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

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The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

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Authors: Szilvia Halmos

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Hungary was one of the first countries to sign and ratify the UN Convention on the Rights of Persons with Disabilities (hereinafter: CRPD). Consequently, Hungary assumed an obligation under international law to review the national law in the light of the Article 12 of the CRPD requiring the States parties to guarantee the equality of persons with disabilities in terms of legal capacity, and to replace the regimes of substitute decision-making by the instruments of supported decision-making. This article is often characterized as one of the key norms of the CRPD, since the legal autonomy of the persons with disabilities is an essential precondition of their participation in the social life on an equal basis with others, envisaged by the social paradigm of disability. This paper examines the impact of the CRPD on the relevant Hungarian national legal norms, with special focus on the relevant rules of the recently codified Civil Code. The employed research methodologies include (1) the specification of the implementation requirements imposed by the Article 12 of the CRPD, (2) the determination of the indicators of the appropriate implementation, (3) the critical analysis of compliance of the relevant Hungarian legal regulation with the indicators, (4) with respect to the relevant case law of the Hungarian Constitutional Court and ordinary courts, the European Court of Human Rights and the Committee of Rights of Persons with Disabilities and (5) to the available empirical figures on the functioning of substitute and supported decision-making regimes. It will be established that the new Civil Code has made large steps toward the equality of persons with disabilities in terms of legal capacity and the support model of decision-making by the introduction of some specific instruments of supported decision-making and the restriction of the application of guardianship. Nevertheless, the regulation currently in effect fails to represent some crucial principles of the Article 12 of the CRPD, such as the non-discrimination of persons with psycho-social disabilities, the support of the articulation of the will and preferences of the individual instead of his/her best interest in the course of decision-making. The changes in the practice of the substitute and the support model brought about by the new legal norms can also be assessed as significant, however, so far unsatisfactory. The number of registered supporters is rather low, and the preconditions of the effective functioning of the support (e.g. the proper training of the supporters) are not ensured.

Keywords: Article 12 of the UN CRPD, Hungarian law on legal capacity, persons with intellectual and psycho-social disabilities, supported decision-making

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Authors: Avinash S. Jagtap, Sharad D. Gore, Rajendra G. Gurao

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Decision rules become more and more complex as the number of conditions increase. As a consequence, the complexity of the decision rule also influences the time complexity of computer implementation of such a rule. Consider, for example, a decision that depends on four conditions A, B, C and D. For simplicity, suppose each of these four conditions is binary. Even then the decision rule will consist of 16 lines, where each line will be of the form: If A and B and C and D, then action 1. If A and B and C but not D, then action 2 and so on. While executing this decision rule, each of the four conditions will be checked every time until all the four conditions in a line are satisfied. The minimum number of logical comparisons is 4 whereas the maximum number is 64. This paper proposes to present a complex decision rule in the form of a decision tree. A decision tree divides the cases into branches every time a condition is checked. In the form of a decision tree, every branching eliminates half of the cases that do not satisfy the related conditions. As a result, every branch of the decision tree involves only four logical comparisons and hence is significantly simpler than the corresponding complex decision rule. The conclusion of this paper is that every complex decision rule can be represented as a decision tree and the decision tree is mathematically equivalent but computationally much simpler than the original complex decision rule

Keywords: strategic, tactical, operational, adaptive, innovative

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Authors: A. Luft, S. Bremen, N. Balc

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The task of flexibility planning and design, just like factory planning, for example, is to create the long-term systemic framework that constitutes the restriction for short-term operational management. This is a strategic challenge since, due to the decision defect character of the underlying flexibility problem, multiple types of flexibility need to be considered over the course of various scenarios, production programs, and production system configurations. In this context, an evaluation model has been developed that integrates both conventional and additive resources on a basic task level and allows the quantification of flexibility enhancement in terms of mix and volume flexibility, complexity reduction, and machine capacity. The model helps companies to decide in early decision-making processes about the potential gains of implementing additive manufacturing technologies on a strategic level. For companies, it is essential to consider both additive and conventional manufacturing beyond pure unit costs. It is necessary to achieve an integrative view of manufacturing that incorporates both additive and conventional manufacturing resources and quantifies their potential with regard to flexibility and manufacturing complexity. This also requires a structured process for the strategic production systems design that spans the design of various scenarios and allows for multi-dimensional and comparative analysis. A respective guideline for the planning of additive resources on a strategic level is being laid out in this paper.

Keywords: additive manufacturing, production system design, flexibility enhancement, strategic guideline

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Authors: Ananda Perera

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Computer-Assisted Medical Evaluation of Symptoms (CAMEOS) is a medical expert system designed to help General Practices (GPs) make an accurate diagnosis. CAMEOS comprises a knowledge base, user input, inference engine, reasoning module, and output statement. The knowledge base was developed by the author. User input is an Html file. The physician user collects data in the consultation. Data is sent to the inference engine at servers. CAMEOS uses set theory to simulate diagnostic reasoning. The program output is a list of differential diagnoses, the most probable diagnosis, and the diagnostic reasoning.

Keywords: CDSS, computerized decision support systems, expert systems, general practice, diagnosis, diagnostic systems, primary care diagnostic system, artificial intelligence in medicine

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Authors: D. Tedesco, G. Feletti, P. Trucco

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The present study aims to develop a Decision Support System (DSS) to support the operational decision of the Emergency Medical Service (EMS) regarding the assignment of medical emergency requests to Emergency Departments (ED). In the literature, this problem is also known as “hospital selection” and concerns the definition of policies for the selection of the ED to which patients who require further treatment are transported by ambulance. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning DSSs to support the EMS management and, in particular, the hospital selection decision. From the literature analysis, it emerged that current studies are mainly focused on the EMS phases related to the ambulance service and consider a process that ends when the ambulance is available after completing a request. Therefore, all the ED-related issues are excluded and considered as part of a separate process. Indeed, the most studied hospital selection policy turned out to be proximity, thus allowing to minimize the transport time and release the ambulance in the shortest possible time. The purpose of the present study consists in developing an optimization model for assigning medical emergency requests to the EDs, considering information relating to the subsequent phases of the process, such as the case-mix, the expected service throughput times, and the operational capacity of different EDs in hospitals. To this end, a Discrete Event Simulation (DES) model was created to evaluate different hospital selection policies. Therefore, the next steps of the research consisted of the development of a general simulation architecture, its implementation in the AnyLogic software and its validation on a realistic dataset. The hospital selection policy that produced the best results was the minimization of the Time To Provider (TTP), considered as the time from the beginning of the ambulance journey to the ED at the beginning of the clinical evaluation by the doctor. Finally, two approaches were further compared: a static approach, which is based on a retrospective estimate of the TTP, and a dynamic approach, which is based on a predictive estimate of the TTP determined with a constantly updated Winters model. Findings reveal that considering the minimization of TTP as a hospital selection policy raises several benefits. It allows to significantly reduce service throughput times in the ED with a minimum increase in travel time. Furthermore, an immediate view of the saturation state of the ED is produced and the case-mix present in the ED structures (i.e., the different triage codes) is considered, as different severity codes correspond to different service throughput times. Besides, the use of a predictive approach is certainly more reliable in terms of TTP estimation than a retrospective approach but entails a more difficult application. These considerations can support decision-makers in introducing different hospital selection policies to enhance EMSs performance.

Keywords: discrete event simulation, emergency medical services, forecast model, hospital selection

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Authors: Ayedh Alqahtani, Andrew Whyte

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Life Cycle Cost (LCC) is one of the goals and key pillars of the construction management science because it comprises many of the functions and processes necessary, which assist organisations and agencies to achieve their goals. It has therefore become important to design and control assets during their whole life cycle, from the design and planning phase through to disposal phase. LCCA is aimed to improve the decision making system in the ownership of assets by taking into account all the cost elements including to the asset throughout its life. Current application of LCC approach is impractical during misunderstanding of the advantages of LCC. This main objective of this research is to show a different relationship between capital cost and long-term running costs. One hundred and thirty eight actual building projects in United Kingdom (UK) were used in order to achieve and measure the above-mentioned objective of the study. The result shown that LCC is one of the most significant tools should be considered on the decision making process.

Keywords: building projects, capital cost, life cycle cost, maintenance costs, operation costs

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Authors: Elke Meex, Elke Knapen, Griet Verbeeck

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The focus of sustainable building is gradually shifting from energy efficiency towards the more global environmental impact of building design during all life-cycle stages. In this context, many tools have been developed that use a LCA-approach to assess the environmental impact on a whole building level. Since the building design strongly influences the final environmental performance and the architect plays a key role in the design process, it is important that these tools are adapted to his work method and support the decision making from the early design phase on. Therefore, a comparative evaluation of the degree of architect-friendliness of some LCA tools on building level is made, based on an evaluation framework specifically developed for the architect’s viewpoint. In order to allow comparison of the results, a reference building has been designed, documented for different design phases and entered in all software tools. The evaluation according to the framework shows that the existing tools are not very architect-friendly. Suggestions for improvement are formulated.

Keywords: architect-friendliness, design supportive value, evaluation framework, tool comparison

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Authors: Muhammad Faheem Khakhi, Jian Yu Wang, Salman Muhammad, Muhammad Faisal Shabir

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Population growth and Chinese two-child policy will boost pharmaceutical market, and it will continue to maintain the growth for a period of time in the future, the traditional pharmacy dispensary has been unable to meet the growing medical needs of the peoples. Under the strong support of the national policy, the automatic transformation of traditional pharmacies is the inclination of the Times, the new type of intelligent pharmacy system will continue to promote the development of the pharmaceutical industry. Under this background, based on PLC control, the paper proposed an intelligent storage and automatic drug delivery system; complete design of the lower computer's control system and the host computer's software system has been present. The system can be applied to dispensing work for Chinese herbal medicinal and Western medicines. Firstly, the essential of intelligent control system for pharmacy is discussed. After the analysis of the requirements, the overall scheme of the system design is presented. Secondly, introduces the software and hardware design of the lower computer's control system, including the selection of PLC and the selection of motion control system, the problem of the human-computer interaction module and the communication between PC and PLC solves, the program design and development of the PLC control system is completed. The design of the upper computer software management system is described in detail. By analyzing of E-R diagram, built the establish data, the communication protocol between systems is customize, C++ Builder is adopted to realize interface module, supply module, main control module, etc. The paper also gives the implementations of the multi-threaded system and communication method. Lastly, each module of the lower computer control system is tested. Then, after building a test environment, the function test of the upper computer software management system is completed. On this basis, the entire control system accepts the overall test.

Keywords: automatic pharmacy, PLC, control system, management system, communication

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Authors: Masood Karamoozian, Zhang Hong

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The necessity and complexity of the decision-making process and the interference of the various factors to make decisions and consider all the relevant factors in a problem are very obvious nowadays. Hence, researchers show their interest in multi-criteria decision-making methods. In this research, the Analytical Hierarchy Process (AHP), Simple Additive Weighting (SAW), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods of multi-criteria decision-making have been used to solve the problem of optimal construction systems. Systems being evaluated in this problem include; Light Steel Frames (LSF), a case study of designs by Zhang Hong studio in the Southeast University of Nanjing, Insulating Concrete Form (ICF), Ordinary Construction System (OCS), and Prefabricated Concrete System (PRCS) as another case study designs in Zhang Hong studio in the Southeast University of Nanjing. Crowdsourcing was done by using a questionnaire at the sample level (200 people). Questionnaires were distributed among experts, university centers, and conferences. According to the results of the research, the use of different methods of decision-making led to relatively the same results. In this way, with the use of all three multi-criteria decision-making methods mentioned above, the Prefabricated Concrete System (PRCS) was in the first rank, and the Light Steel Frame (LSF) system ranked second. Also, the Prefabricated Concrete System (PRCS), in terms of performance standards and economics, was ranked first, and the Light Steel Frame (LSF) system was allocated the first rank in terms of environmental standards.

Keywords: multi-criteria decision making, AHP, SAW, TOPSIS

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Authors: Yuekun Chen, Yousef Sardahi, Salam Hajjar, Christopher Greer

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This paper presents a multi-objective optimal design of a cascade control system for an underactuated mechanical system. Cascade control structures usually include two control algorithms (inner and outer). To design such a control system properly, the following conflicting objectives should be considered at the same time: 1) the inner closed-loop control must be faster than the outer one, 2) the inner loop should fast reject any disturbance and prevent it from propagating to the outer loop, 3) the controlled system should be insensitive to measurement noise, and 4) the controlled system should be driven by optimal energy. Such a control problem can be formulated as a multi-objective optimization problem such that the optimal trade-offs among these design goals are found. To authors best knowledge, such a problem has not been studied in multi-objective settings so far. In this work, an underactuated mechanical system consisting of a rotary servo motor and a ball and beam is used for the computer simulations, the setup parameters of the inner and outer control systems are tuned by NSGA-II (Non-dominated Sorting Genetic Algorithm), and the dominancy concept is used to find the optimal design points. The solution of this problem is not a single optimal cascade control, but rather a set of optimal cascade controllers (called Pareto set) which represent the optimal trade-offs among the selected design criteria. The function evaluation of the Pareto set is called the Pareto front. The solution set is introduced to the decision-maker who can choose any point to implement. The simulation results in terms of Pareto front and time responses to external signals show the competing nature among the design objectives. The presented study may become the basis for multi-objective optimal design of multi-loop control systems.

Keywords: cascade control, multi-Loop control systems, multiobjective optimization, optimal control

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Authors: Haji Ali Haji, Hussein Suleman, Ulrike Rivett

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This paper presents the design, development and evaluation of an application prototype developed to support tuberculosis (TB) patients’ treatment adherence. The system makes use of graphics and voice reminders as opposed to text messaging to encourage patients to follow their medication routine. To evaluate the effect of the prototype applications, participants were given mobile phones on which the reminder system was installed. Thirty-eight people, including TB health workers and patients from Zanzibar, Tanzania, participated in the evaluation exercises. The results indicate that the participants found the mobile graphic-based application is useful to support TB treatment. All participants understood and interpreted the intended meaning of every image correctly. The study findings revealed that the use of a mobile visual-based application may have potential benefit to support TB patients (both literate and illiterate) in their treatment processes.

Keywords: ICT4D, mobile technology, tuberculosis, visual-based reminder

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Authors: Stephen A. Akinlabi, Esther T. Akinlabi

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The drip irrigation system is one of the important areas that affect the livelihood of farmers directly. The use of drip irrigation system has been the most efficient system compared to the other types of irrigations systems because the drip irrigation helps to save water and increase the productivity of crops. But like any other system, it can be considered inefficient when the filters and the emitters get clogged while in operation. The efficiency of the entire system is reduced when the emitters are clogged and blocked. This consequently impact and affect the farm operations which may result in scarcity of farm products and increase the demand. This design work focuses on how to overcome some of the challenges affecting drip irrigation system through the design of an efficient filtration and flushing system.

Keywords: drip irrigation system, filters, soil texture, mechanical engineering design, analysis

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Authors: S. Niamkaeo, O. Robert, O. Chaowalit

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In this investigation, we focus on discovering spatial relationship of drug smuggling along the northern border of Thailand. Thailand is no longer a drug production site, but Thailand is still one of the major drug trafficking hubs due to its topographic characteristics facilitating drug smuggling from neighboring countries. Our study areas cover three districts (Mae-jan, Mae-fahluang, and Mae-sai) in Chiangrai city and four districts (Chiangdao, Mae-eye, Chaiprakarn, and Wienghang) in Chiangmai city where drug smuggling of methamphetamine crystal and amphetamine occurs mostly. The data on drug smuggling incidents from 2011 to 2017 was collected from several national and local published news. Geo-spatial drug smuggling database was prepared. Decision tree algorithm was applied in order to discover the spatial relationship of factors related to drug smuggling, which was converted into rules using rule-based system. The factors including land use type, smuggling route, season and distance within 500 meters from check points were found that they were related to drug smuggling in terms of rules-based relationship. It was illustrated that drug smuggling was occurred mostly in forest area in winter. Drug smuggling exhibited was discovered mainly along topographic road where check points were not reachable. This spatial relationship of drug smuggling could support the Thai Office of Narcotics Control Board in surveillance drug smuggling.

Keywords: decision tree, drug smuggling, Geographic Information System, GIS knowledge discovery, rule-based system

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Authors: Manita Ale, Ganesh P. Shivakoti, Ram C. Bastakoti

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Irrigation system, a system for enhancing agricultural productivity, requires regular maintenance in order to avoid irregular allocation of water. For maintenance of the system in long run, farmers’ participation plays a key role increasing the performance of system. The performance of any irrigation system mainly relies on various factors which affect collective action plus decision making, as well as their shared impacts. The paper consists of system level information that were collected from 12 Irrigation Systems (IS) from three-sampled districts of Nepal and the household information that were collected from 160 irrigation water users. The results reveal that, out of 12 sampled irrigation systems, only 4 systems shows high performance levels. The high performance level of those systems was characterized on the basis of adequate availability of water, good maintenance of system infrastructure, and conformance to existing rules followed. In addition, the paper compares different irrigation systems based on trust, reciprocity, cropping intensity, command area and yield as tools to indicate the importance of collective action in performance of irrigation system.

Keywords: collective action, decision-making, farmers’ participation, performance

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Authors: Yujie Chen , Zhen Li

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In the context of planning transformation, how to promote public participation in the formulation and implementation of collaborative planning has been the focused issue of discussion. However, existing studies have often been case-specific or focused on a specific design field, leaving the role of participatory social media (PSM) in urban collaborative planning generally questioned. A systematic database search was conducted in December 2019. Articles and projects were eligible if they reported a quantitative empirical study applying participatory social media in the collaborative planning process (a prospective, retrospective, experimental, longitudinal research, or collective actions in planning practices). Twenty studies and seven projects were included in the review. Findings showed that social media are generally applied in public spatial behavior, transportation behavior, and community planning fields, with new technologies and new datasets. PSM has provided a new platform for participatory design, decision analysis, and collaborative negotiation most widely used in participatory design. Findings extracted several existing forms of PSM. PSM mainly act as three roles: the language of decision-making for communication, study mode for spatial evaluation, and decision agenda for interactive decision support. Three optimization content of PSM were recognized, including improving participatory scale, improvement of the grass-root organization, and promotion of politics. However, basically, participants only could provide information and comment through PSM in the future collaborative planning process, therefore the issues of low data response rate, poor spatial data quality, and participation sustainability issues worth more attention and solutions.

Keywords: participatory social media, collaborative planning, planning workshop, application mode

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Authors: Mansour N. Jadid

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This paper describes the implementation of a GIS to provide decision support for successfully monitoring the movements and storage of materials, hence ensuring that finished products travel from the point of origin to the destination construction site through the supply-chain management (SCM) system. This system ensures the efficient operation of suppliers, manufacturers, and distributors by determining the shortest path from the point of origin to the final destination to reduce construction costs, minimize time, and enhance productivity. These systems are essential to the construction industry because they reduce costs and save time, thereby improve productivity and effectiveness. This study describes a typical supply-chain model and a geographical information system (GIS)-based SCM that focuses on implementing an electronic document management system, which maps the application framework to integrate geodetic support with the supply-chain system. This process provides guidance for locating the nearest suppliers to fill the information needs of project members in different locations. Moreover, this study illustrates the use of a GIS-based SCM as a collaborative tool in innovative methods for implementing Web mapping services, as well as aspects of their integration by generating an interactive GIS for the construction industry platform.

Keywords: construction, coordinate, engineering, GIS, management, map

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Authors: Abdur Rosyid, Mohamed El-Madany, Mohanad Alata

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Due to simplicity and low cost, rotordynamic system is often modeled by using lumped parameters. Recently, finite elements have been used to model rotordynamic system as it offers higher accuracy. However, it involves high degrees of freedom. In some applications such as control design, this requires higher cost. For this reason, various model reduction methods have been proposed. This work demonstrates the quality of model reduction of rotor-bearing-support system through substructuring. The quality of the model reduction is evaluated by comparing some first natural frequencies, modal damping ratio, critical speeds and response of both the full system and the reduced system. The simulation shows that the substructuring is proven adequate to reduce finite element rotor model in the frequency range of interest as long as the numbers and the locations of master nodes are determined appropriately. However, the reduction is less accurate in an unstable or nearly-unstable system.

Keywords: rotordynamic, finite element model, timoshenko beam, 3D solid elements, Guyan reduction method

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Authors: Ali Farzan

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Classification of data objects or patterns is a major part in most of Decision making systems. One of the popular and commonly used classification methods is Decision Tree (DT). It is a hierarchical decision making system by which a binary tree is constructed and starting from root, at each node some of the classes is rejected until reaching the leaf nods. Each leaf node is a representative of one specific class. Finding the splitting criteria in each node for constructing or training the tree is a major problem. Particle Swarm Optimization (PSO) has been adopted as a metaheuristic searching method for finding the best splitting criteria. Result of evaluating the proposed method over benchmark datasets indicates the higher accuracy of the new PSO based decision tree.

Keywords: decision tree, particle swarm optimization, splitting criteria, metaheuristic

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Authors: Ru-Yu Lien, Shih-Hsin Hung, Shu-Fen Lu, Ju-Jen Shie, Wen-Ju Yang, Yuann-Meei Tzeng, Chien-Ying Wang

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Background: The quality of care in intensive care units (ICUs) is crucial, especially for terminally ill patients. Shared decision-making (SDM) with families is essential to ensure appropriate care and reduce suffering. Aim: This study explores the effectiveness of an end-of-life decision support Patient Decision Aid (PDA) in an ICU setting. Methods: This study employed a cross-sectional research design conducted in an ICU from August 2020 to June 2023. Participants included family members of end-of-life patients aged 20 or older. A total of 319 participants. Family members of end-of-life patients received the PDA, and data were collected after they made medical decisions. Data collection involved providing family members with a PDA during family meetings. A post-PDA questionnaire with 17 questions assessed PDA effectiveness and anxiety levels. Statistical analysis was performed using SPSS 22.0. Results: The PDA significantly reduced anxiety levels among family members (p < 0.001). It helped them organize their thoughts, prepare for discussions with doctors, and understand critical decision factors. Most importantly, it influenced decision outcomes, with a shift towards palliative care and withdrawal of life-sustaining treatment. Conclusion: This study highlights the importance of family-centered end-of-life care in ICUs. PDAs promote informed decision-making, reduce conflicts, and enhance patient and family involvement. These tools align patient values and goals with medical recommendations, ultimately leading to decisions that prioritize comfort and quality of life. Implementing PDAs in healthcare systems can ensure that patients' care aligns with their values.

Keywords: shared decision-making, patient decision aid, end-of-life care, intensive care unit, family-centered care

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Authors: Chinlun Lai, Yu-Mei Chang

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In this paper, an augmented reality learning support system is proposed to replace the traditional teaching tool thus to help students improve their learning motivation, effectiveness, and efficiency. The system can not only reduce the exhaust of educational hardware and realistic material, but also provide an eco-friendly and self-learning practical environment in any time and anywhere with immediate practical experiences feedback. To achieve this, an interactive self-training methodology which containing step by step operation directions is designed using virtual 3D scenario and wearable device platforms. The course of nasogastric tube care of nursing skills is selected as the test example for self-learning and online test. From the experimental results, it is observed that the support system can not only increase the student’s learning interest but also improve the learning performance than the traditional teaching methods. Thus, it fulfills the strategy of learning by practice while reducing the related cost and effort significantly and is practical in various fields.

Keywords: augmented reality technology, learning support system, self-learning, simulation learning method

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Authors: Mohamed H. Khalil

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Water is one of the most crucial elements which influence human lives and development. Noteworthy, over the last few years, GIS plays a significant role in optimizing water management systems, especially after exponential developing in this sector. In this context, the Egyptian government initiated an advanced ‘GIS-Web Based System’. This system is efficiently designed to tangibly assist and optimize the complement and integration of data between departments of Call Center, Operation and Maintenance, and laboratory. The core of this system is a unified ‘Data Model’ for all the spatial and tabular data of the corresponding departments. The system is professionally built to provide advanced functionalities such as interactive data collection, dynamic monitoring, multi-user editing capabilities, enhancing data retrieval, integrated work-flow, different access levels, and correlative information record/track. Noteworthy, this cost-effective system contributes significantly not only in the completeness of the base-map (93%), the water network (87%) in high level of details GIS format, enhancement of the performance of the customer service, but also in reducing the operating costs/day-to-day operations (~ 5-10 %). In addition, the proposed system facilitates data exchange between different departments (Call Center, Operation and Maintenance, and laboratory), which allowed a better understanding/analyzing of complex situations. Furthermore, this system reflected tangibly on: (i) dynamic environmental monitor/water quality indicators (ammonia, turbidity, TDS, sulfate, iron, pH, etc.), (ii) improved effectiveness of the different water departments, (iii) efficient deep advanced analysis, (iv) advanced web-reporting tools (daily, weekly, monthly, quarterly, and annually), (v) tangible planning synthesizing spatial and tabular data; and finally, (vi) scalable decision support system. It is worth to highlight that the proposed future plan (second phase) of this system encompasses scalability will extend to include integration with departments of Billing and SCADA. This scalability will comprise advanced functionalities in association with the existing one to allow further sustainable contributions.

Keywords: GIS Web-Based, base-map, water network, decision support system

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Wu Defu, Kiefer Chiam, Yang Kin Seng

Abstract:

The planning of geological survey works is an iterative process which involves planner, geologist, civil engineer and other stakeholders, who perform different roles and have different points of view. Traditionally, the team used paper maps or CAD drawings to present the proposal which is not an efficient way to present and share idea on the site investigation proposal such as sitting of borehole location or seismic survey lines. This paper focuses on how a GIS approach can be utilised to develop a web-based system to support decision making process in the planning of geological survey works and also to plan site activities carried out by Singapore Geological Office (SGO). The authors design a framework of building an interactive web-based GIS system, and develop a prototype, which enables the users to obtain rapidly existing geological information and also to plan interactively borehole locations and seismic survey lines via a web browser. This prototype system is used daily by SGO and has shown to be effective in increasing efficiency and productivity as the time taken in the planning of geological survey works is shortened. The prototype system has been developed using the ESRI ArcGIS API 3.7 for Flex which is based on the ArcGIS 10.2.1 platform.

Keywords: engineering geology, flex, geological survey planning, geoscience, GIS, site investigation, WebGIS

Procedia PDF Downloads 280

Authors: Anli Du Preez, James Bekker

Abstract:

Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

Procedia PDF Downloads 142

Authors: Abadi Berhane, Walelign Worku, Berhanu Abrha, Gebre Hadgu, Tigray

Abstract:

Sesame is an important oilseed crop in Ethiopia; which is the second most exported agricultural commodity next to coffee. However, there is poor soil fertility management and a research-led farming system for the crop. The AquaCrop model was applied as a decision-support tool; which performs a semi-quantitative approach to simulate the yield of crops under different soil fertility levels. The objective of this experiment was to calibrate and validated the AquaCrop model for simulating the growth and yield of sesame under different nitrogen fertilizer levels and to test the performance of the model as a decision-support tool for improved sesame cultivation in the study area. The experiment was laid out as a randomized complete block design (RCBD) in a factorial arrangement in the 2016, 2017, and 2018 main cropping seasons. In this experiment, four nitrogen fertilizer rates; 0, 23, 46, and 69 Kg/ha nitrogen, and three improved varieties (Setit-1, Setit-2, and Humera-1). In the meantime, growth, yield, and yield components of sesame were collected from each treatment. Coefficient of determination (R2), Root mean square error (RMSE), Normalized root mean square error (N-RMSE), Model efficiency (E), and Degree of agreement (D) were used to test the performance of the model. The results indicated that the AquaCrop model successfully simulated soil water content with R2 varying from 0.92 to 0.98, RMSE 6.5 to 13.9 mm, E 0.78 to 0.94, and D 0.95 to 0.99; and the corresponding values for AB also varied from 0.92 to 0.98, 0.33 to 0.54 tons/ha, 0.74 to 0.93, and 0.9 to 0.98, respectively. The results on the canopy cover of sesame also showed that the model acceptably simulated canopy cover with R2 varying from 0.95 to 0.99, and a RMSE of 5.3 to 8.6%. The AquaCrop model was appropriately calibrated to simulate soil water content, canopy cover, aboveground biomass, and sesame yield; the results indicated that the model adequately simulated the growth and yield of sesame under the different nitrogen fertilizer levels. The AquaCrop model might be an important tool for improved soil fertility management and yield enhancement strategies of sesame. Hence, the model might be applied as a decision-support tool in soil fertility management in sesame production.

Keywords: aquacrop model, sesame, normalized water productivity, nitrogen fertilizer

Procedia PDF Downloads 40