scholarly journals Designing an Information System that Supports Decision Making for Passengers of Autonomous Vehicles

2021 ◽  
Vol 34 (4) ◽  
pp. 121-139
Author(s):  
Sooyeon Kwon ◽  
Sooyeon Kwon ◽  
Dongwhan Kim ◽  
Dongwhan Kim
Author(s):  
Nguyen Viet Hung ◽  
Phan Van Hung ◽  
Be Trung Anh

Data mode “good governance” developed in the last century for process of sustainable base system, providing basic information and on-line services, supports the development, challenges and opportunities in the context of globalization and integration. In this paper I discuss a framework for the design of e-Local Governance (eLG) that integrates Information System (IS), Geographical Information System (GIS) and Atlas with focus on ethnic minorities in Vietnam. The design framework is based on various classifications such categories as sex, age, ethnic group, education background and income. The database system is built to enhance the Committee for Ethnic Minority Affairs (CEMA) capabilities in the planning and decision making process by providing the authorities with data, internet GIS, internet communication and some ecological economic models to disseminate results to the ethnic minorities. The unique feature of the CEMADATA using GIS is that it helps users not only to improve the public services and to provide information and encourage ethnic minorities to participate in decision making processes, but also to support the competency-based training for IT staff


2017 ◽  
Vol 5 (1) ◽  
pp. 122
Author(s):  
Assist. Prof. Dr. Demokaan DEMİREL

The distinctive quality of the new social structure is that information becomes the only factor of production. In today's organizations, public administrators are directly responsible for applying information to administrative processes. In addition to his managerial responsibilities, a knowledge based organization requires every employee to take responsibility for achieving efficiency. This has increased the importance of information systems in the decision-making process. Information systems consist of computer and communication technology, data base management and model management and include activity processing system, management information system, decision support systems, senior management information system, expert systems and office automation systems. Information systems in the health sector aim at the management and provision of preventive and curative health services. The use of information systems in healthcare has the benefits of increasing service quality, shortening treatment processes, maximizing efficiency of the time, labour and medical devices. The use of information systems for clinical decision making and reducing medical errors in the healthcare industry dates back to the 1960s. Clinical information systems involve processing, storing and re-accessing information that supports patient care in a hospital. Clinical information systems are systems that are directly or indirectly related to patient care. These systems include electronic health/patient records, clinical decision support systems, nurse information systems, patient tracking systems, tele-medicine, case mix and smart card applications. Diagnosis-treatment systems are information-based systems used in the diagnosis and treatment of diseases. It consists of laboratory information systems, picture archiving and communication system, pharmacy information system, radiology information system, nuclear medicine information system. This study aims to evaluate the effectiveness of health information system applications in Turkey. The first part of the study focuses on the concept of information systems and the types of information systems in organization structures. In the second part, clinical information systems and applications for diagnosis-treatment systems in Turkey are examined. Finally, the study evaluates applications in the health sector qualitatively from the new organizational structure, which is formed by information systems.


Author(s):  
I. М. Mikhaylenko ◽  
V. N. Timoshin

The transition to "intellectual" agriculture is the main vector of modernization of the agricultural sector of the economy. It is based on integrated automation and robotization of production, the use of automated decision-making systems. This is inevitably accompanied by a significant increase in data flow from sensors, monitoring systems, meteorological stations, drones, satellites and other external systems. Farm management has the opportunity to use various online applications for accurate recommendations and making various kinds of management decisions. In this regard, the most effective use of cloud information technologies, allowing implementing the most complex information and technical level of automation systems for management of agricultural technologies. The purpose of this work is to test the approach to creating expert management decision support systems (DSS) through the knowledge base (KB), formed in the cloud information system. For this, we consider an example of constructing a DSS for choosing the optimal date for preparing forage from perennial grasses. A complete theoretical and algorithmic database of the analytical DSS implemented in the data processing center of the cloud information system is given. On its basis, a KB is formed for a variety of different decision-making conditions. This knowledge base is transmitted to the local DSS. To make decisions about the optimal dates for the preparation of the local DSS, two variants of algorithms are used. The first option is based on management models, and the second uses the pattern recognition method. The approbation of the algorithms was carried out according to the BZ from 50 cases. According to the results of testing, the method of pattern recognition proved to be more accurate, which provides a more flexible adjustment of the situation on the local DSS to a similar situation in the KB. The considered technique can be extended to other crops.


2019 ◽  
Author(s):  
Weichao Wang ◽  
Quang A Nguyen ◽  
Paul Wai Hing Chung ◽  
Qinggang Meng

2020 ◽  
pp. 31-34
Author(s):  
CHUNMEI JI

The study considers the problem of decision-making in the actvites of agricultural enterprises in conditons of environmental uncertainty. The problem is formalized as a multcriteria conditonal optmizaton problem. The novelty of the work is that the factors are considered as dynamic fuzzy quanttes. The choice of the best alternatve is made between the elements of a predetermined fnite set of alternatves. Based on this formalizaton of the decision-making task, six requirements to the informaton system of decision support in the conditons of ecological uncertainty are formulated.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1523
Author(s):  
Nikita Smirnov ◽  
Yuzhou Liu ◽  
Aso Validi ◽  
Walter Morales-Alvarez ◽  
Cristina Olaverri-Monreal

Autonomous vehicles are expected to display human-like behavior, at least to the extent that their decisions can be intuitively understood by other road users. If this is not the case, the coexistence of manual and autonomous vehicles in a mixed environment might affect road user interactions negatively and might jeopardize road safety. To this end, it is highly important to design algorithms that are capable of analyzing human decision-making processes and of reproducing them. In this context, lane-change maneuvers have been studied extensively. However, not all potential scenarios have been considered, since most works have focused on highway rather than urban scenarios. We contribute to the field of research by investigating a particular urban traffic scenario in which an autonomous vehicle needs to determine the level of cooperation of the vehicles in the adjacent lane in order to proceed with a lane change. To this end, we present a game theory-based decision-making model for lane changing in congested urban intersections. The model takes as input driving-related parameters related to vehicles in the intersection before they come to a complete stop. We validated the model by relying on the Co-AutoSim simulator. We compared the prediction model outcomes with actual participant decisions, i.e., whether they allowed the autonomous vehicle to drive in front of them. The results are promising, with the prediction accuracy being 100% in all of the cases in which the participants allowed the lane change and 83.3% in the other cases. The false predictions were due to delays in resuming driving after the traffic light turned green.


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