Expert Decision Support System Research Articles

LOD Cloud Mining for Prognosis Model(Case Study: Native App for Drug Recommender System)

The goal of this project is to use the Semantic Web Technologies and Data Mining for disease diagnosis to assist health care professionals regarding the possible medication and drug to prescribe (Drug recommendation) according to the features of the patient. Numerous Decision Support Systems (DSS) and Expert Systems allow medical collaboration, like in the differential diagnosis specific or general. But, a medical recommendation system using both Semantic Web technologies and Data mining has not yet been developed which initiated this work. However, it should be mentioned that there are several system references about medicine or active ingredient interactions, but their final goal is not the Drug recommendation which uses above technologies. With this project we try to provide an assistant to the doctor for better recommendations. The patient will also able to use this system for explanation of drugs, food interaction and side effects of corresponding drugs.

A review of precision fertilization research

Precision agriculture plays an important role in sustainable development. Precision fertilization is the core of this field. Three methods of precision fertilization are introduced in this paper. They are: testing soil for formulated fertilization technology, decision support system and expert decision support system. Their development situations are also examined. Some suggestions in the agriculture sustainable development are also provided. The review summarized that 3S technology will become the main data source in the decision support system and in development process of expert decision support system. The MIII technology can raise the soil testing efficiency. The development of precision fertilization has great utility in sustainable development of agriculture.

Development and application of an innovative expert decision support system to manage sediments and to assess environmental risk in freshwater ecosystems

With the aim of supporting decision makers to manage contamination in freshwater environments, an innovative expert decision support system (EDSS) was developed. The EDSS was applied in a sediment quality assessment along the Bormida river (NW, Italy) which has been heavily contaminated by an upstream industrial site for more than a century. Sampling sites were classified by means of comparing chemical concentrations with effect-based target values (threshold and probable effect concentrations). The level of each contaminant and the combined toxic pressure were used to rank sites into three categories: (i) uncontaminated (8 sites), (ii) mildly contaminated (4) and (iii) heavily contaminated (19). In heavily contaminated sediments, an environmental risk index (EnvRI) was determined by means of integrating chemical data with ecotoxicological and ecological parameters (triad approach). In addition a sediment risk index (SedRI) was computed from combining chemical and ecotoxicological data. Eight sites exhibited EnvRI values ≥0.25, the safety threshold level (range of EnvRI values: 0.14–0.31) whereas SedRI exceeded the safety threshold level at 6 sites (range of SedRI values: 0.16–0.36). At sites classified as mildly contaminated, sublethal biomarkers were integrated with chemical data into a biological vulnerability index (BVI), which exceeded the safety threshold level at one site (BVI value: 0.28). Finally, potential human risk was assessed in selected stations (11 sites) by integrating genotoxicity biomarkers (GTI index falling in the range 0.00–0.53). General conclusions drawn from the EDSS data include: (i) in sites classified as heavily contaminated, only a few exhibited some significant, yet limited, effects on biodiversity; (ii) restrictions in re-using sediments from heavily contaminated sites found little support in ecotoxicological data; (iii) in the majority of the sites classified as mildly contaminated, tested organisms exhibited low response levels; (iv) preliminary results on genotoxicity biomarkers indicate possible negative consequences for humans if exposed to river sediments from target areas.

Application of Expert Decision Support System in Demonstration Engineering Project of Housing

The selection and the evaluation of demonstration engineering project of housing are a complex analysis process, many projects are involved, evaluation index system are complicated, the requirements of scientific, advanced, efficiency and fairness are failed to meet with the traditional decision method. Multi-dimensional network decision support system are constructed in this paper, the construction scheme of knowledge base, model base and data warehouse are made a detailed description, the technical method of system construction are made clearly. The new decision services support is provided to select and evaluate to the demonstration project.

Research on Reginal Agricultural Information Technology System Construction - Take Shandong Province as Example

Agricultural information technology, with the core of wide usage of information and information technology, is the important feature of modern agriculture, and has a strong infiltrating and leading role. The construction of regional agricultural information technology, has a positive meaning to optimize allocation of regional agricultural resources, and form regional agricultural information technology with regional characteristics and full functions. Based on analyzing the status quo of agricultural information technology in Shandong Province, this thesis constructed the regional agricultural information technology system from the view of cluster network, which mainly included agricultural Information technology Network System, Information technology Resources, agricultural expert decision-support system, and agricultural information technology service system. Upon constructing and analyzing these systems, it proposed the policy recommendations for promoting regional agricultural information technology development.

Development of a decision support system to manage contamination in marine ecosystems

In recent years, contamination and its interaction with climate-change variables have been recognized as critical stressors in coastal areas, emphasizing the need for a standardized framework encompassing chemical and biological data into risk indices to support decision-making. We therefore developed an innovative, expert decision support system (Exp-DSS) for the management of contamination in marine coastal ecosystems. The Exp-DSS has two main applications: (i) to determine environmental risk and biological vulnerability in contaminated sites; and (ii) to support the management of waters and sediments by assessing the risk due to the exposure of biota to these matrices. The Exp-DSS evaluates chemical data, both as single compounds and as total toxic pressure of the mixture, to compare concentrations to effect-based thresholds (TELs and PELs). Sites are then placed into three categories of contamination: uncontaminated, mildly contaminated, and highly contaminated. In highly contaminated sites, effects on high-level ecotoxicological endpoints (i.e. survival and reproduction) are used to determine risk at the organism-population level, while ecological parameters (i.e. alterations in community structure and ecosystem functions) are considered for assessing effects on biodiversity. Changes in sublethal biomarkers are utilized to assess the stress level of the organisms in mildly contaminated sites. In Triad studies, chemical concentrations, ecotoxicological high-level effects, and ecological data are combined to determine the level of environmental risk in highly contaminated sites; chemical concentration and ecotoxicological sublethal effects are evaluated to determine biological vulnerability in mildly contaminated sites. The Exp-DSS was applied to data from the literature about sediment quality in estuarine areas of Spain, and ranked risks related to exposure to contaminated sediments from high risk (Huelva estuary) to mild risk (Guadalquivir estuary and Bay of Cadiz). A spreadsheet-based version of the Exp-DSS is available at the MEECE and DiSIT web sites (www.meece.eu and www.disit.unipmn.it).

Estimating nutrient uptake requirements for wheat in China

Estimating balanced nutrient requirement for wheat (Triticum aestivum L.) in China is essential to manage nutrient application more effectively for increasing crop yields and reducing risk of negative environmental impact. Datasets from 2000 to 2011 dealing with nitrogen (N), phosphorus (P) and potassium (K) treatments across the winter and spring wheat growing regions in China were collected to assess the relationship between grain yield and nutrient uptake, and to estimate N, P and K optimal nutrient requirements for a target yield using the QUEFTS (Quantitative Evaluation of the Fertility of Tropical Soils) model. In the QUEFTS model, two boundary lines described the minimum and maximum internal efficiencies (IEs, kg grain per kg nutrient in above-ground plant dry matter) of N, P and K. The minimum and maximum IEs for wheat were 28.8 and 62.6kg grain per kg N, 98.9 and 487.4kg grain per kg P, and 23.0 and 112.9kg grain per kg K. The QUEFTS model predicted a linear–parabolic–plateau curve for balanced nutrient uptake with target yield increasing. The linear part continued until the yield was approximately at 60–70% of the potential yield, and 22.8kg N, 4.4kg P and 19.0kg K were required to produce 1000kg grain. The corresponding N:P:K ratio was 5.18:1:4.32, and the corresponding IEs were 43.9, 227.0 and 52.7kg grain per kg N, P and K, respectively. The QUEFTS model simulated balanced N, P and K removal by 1000kg grain were 18.3, 3.6 and 3.5kg, respectively, with a N:P:K ratio of 5.08:1:0.97. Approximately 80%, 82% and 18% of N, P and K in total above-ground plant material were presented in the grain and removed from the field. The relationship between grain yield and nutrient uptake was also estimated to suggest fertilizer application avoiding excess or deficient nutrient supply. Field experiment validation confirmed that the QUEFTS model could be used as a practical tool for the Nutrient Expert decision support system to make fertilizer recommendation.

Web-based Expert Decision Support System for Tourism Destination Management in Nigeria

The use of Information Technologies have played and currently playing prominent roles in many organizations, such as business, education, commerce. The tourism industry has witnessed the use and application of various computer-based systems in carrying out one or more activities or operation. But currently there is no computer-based system tourist destination to integrate the tourists (from outside Nigeria) and tourists center within Nigeria, so that tourists can make a pre destination plan and decision before venturing into tourism journey to the country Nigeria. The authors of this paper proposed the design of web-based Expert Decision System (WEDSS), to provide tourist to Nigeria and its environ essential data and tools to managing their tours and to base all the decisions concerning to queries on the, tourist centers and hotels based on the following issue; climate, road conditions, cultural aspects, lodging, health facilities, banking, etc. of the location to be visited on sound and rational bases. Web-Based Tourist Decision Support System (WEDSS) for Nigeria will be developed to allow the tourist to find their route in Nigeria and ask for information about sights, accommodations and other places of interest which are nearby to him to improve the convenience, safety, efficiency of travel and enhance tourism attraction of tourists.

MULTIPLE CRITERIA DECISION SUPPORT SYSTEM FOR THE ASSESSMENT OF ENERGY GENERATION TECHNOLOGIES CONSIDERING THE DIMENSION OF VALUES

Comprehension of the effect of energy generation technologies on the natural environment, human health and safety leads to a new and responsible approach to the choice and development of technologies. When it comes to preparing energy growth scenarios and handling issues related to the choice and assessment of technologies, environmental studies must be in a particular spotlight. One way to make quantitative and qualitative assessment of the effect of technologies on the environment is through a thorough integrated analysis, which, in addition to economic and technical solutions, also considers other aspects of concern to the public. A changed environment demands for systems of criteria which help consider its changes, the attitudes of the general public, public sentiments toward the effect of technologies, public values and community involvement in the process of important decision-making. The article examines how the dimension of values affects the analysis of the impact of environmental factors on the value of energy generation technologies. It presents a set of criteria for the assessment of energy generation technologies; the set, in addition to technological, economic and environmental criteria, includes criteria which reflect the values. The article also introduces the expert decision support system EGTAV-SPS, which helped assess the effect of environment on energy production technologies.

An ontological-based knowledge organization for bioinformatics workflow management system

Motivation and Objectives In the field of Computer Science, ontologies represent formal structures to define and organize knowledge of a specific application domain (Chandrasekaran et al., 1999). An ontology is composed of entities, called classes, and relationships among them. Classes are characterized by features, called attributes, and they can be arranged into a hierarchical organization. Ontologies are a fundamental instrument in Artificial Intelligence for the development of Knowledge-Based Systems (KBS). With its formal and well defined structure, in fact, an ontology provides a machine-understandable language that allows automatic reasoning for problems resolution. Typical KBS are Expert Systems (ES) and Decision Support Systems (DSS). ESs gather and formalize the knowledge of a human expert of a domain in order to produce inferences and recommendations given an initial query. DSSs are more interactive KBS, in the sense they offer support, rather than replacement, for the decision making process during the execution of a task, suggesting one possible strategy or tool given a set of initial conditions. DSSs are mainly adopted in the clinical field, where they are called Clinical DSS (CDSS). Ontology specification, structure and organization are then of fundamental importance for the development of a KBS. In this paper we present an improvement of our ontological approach for knowledge organization in DSS design. In our previous publication (Fiannaca et al., 2012) we defined a paradigm for ontology specification named Data Problem Solver (DPS) and we showed how our approach can be applied to bioinformatics domain, modeling the Protein-Protein Interaction Network extraction scenario. In the proposed approach, we aim at integrating into our ontology the concept of Workflow as a set of processes. Our main objective is to provide a general schema in order to add the functionalities and capability of a DSS to the more recent Workflow Management Systems, that especially in bioinformatics, with the Taverna workbench (Hull et al., 2006), represent a powerful instrument for researchers. We called our extended ontological approach Data Problem Solver Workflow (DPSW).

An ontological-based knowledge organization for bioinformatics workflow management system

An ontological-based knowledge organization for bioinformatics workflow management system

Improving consistency in AHP decision-making processes

Decision making in engineering is becoming increasingly complex due to the large number of alternatives and multiple conflicting goals. Powerful decision-support expert systems powered by suitable software are increasingly necessary. In this paper, the multiple attribute decision method known as analytical hierarchy process (AHP), which uses pairwise comparisons with numerical judgments, is considered. Since judgments may lack a minimum level of consistency, mechanisms to improve consistency are necessary. A method to achieve consistency through optimisation is described in this paper. This method has the major advantage of depending on just n decision variables – the number of compared elements – and so is less computationally expensive than other optimisation methods, and can be easily implemented in virtually any existing computer environment. The proposed approach is exemplified by considering a simplified version of one of the most important problems faced by water supply managers, namely, the minimisation of water loss.

Application of GIS in urban utility mapping using image processing techniques

Growing cities are creating an alarming situation in all countries of the world. It has led to serious land use problems such as loss of agricultural land, unauthorized urban sprawl, high land values, speculation in land, and other related problems. In this emerging scenario, it is essential to have updated information on urban growth patterns and their impact on the living environment. Growth and development of these cities are likely to continue and therefore there will be a need for proper planning and managing or improving the existing infrastructure facilities. This study demonstrates image fusion of LISS-IV MX and Cartosat-1 satellite data to create detailed town planning and utility mapping for amenity patterns and facilities available in Karaikal city, India. Road patterns within the city are analyzed and a road network map is generated. A proximity analysis was carried out to understand the availability of institutions, hospitals, and industries for effective disaster management. Karaikal has grown rapidly in all directions especially in north, northwest and west parts. A big question for planners is the provision of proper amenities. Using geographic information system and remote sensing, city administrators can now evolve an expert decision support system aimed at various decision-making processes.

Ant colony optimization for RDF chain queries for decision support

Semantic Web technologies can be utilized in expert systems for decision support, allowing a user to explore in the decision making process numerous interconnected sources of data, commonly represented by means of the Resource Description Framework (RDF). In order to disclose the ever-growing amount of widely distributed RDF data to demanding users in real-time environments, fast RDF query engines are of paramount importance. A crucial task of such engines is to optimize the order in which partial results of a query are joined. Several soft computing techniques have already been proposed to address this problem, i.e., two-phase optimization (2PO) and a genetic algorithm (GA). We propose an alternative approach – an ant colony optimization (ACO) algorithm, which may be more suitable for a Semantic Web environment. Experimental results with respect to the optimization of RDF chain queries on a large RDF data source demonstrate that our approach outperforms both 2PO and a GA in terms of execution time and solution quality for queries consisting of up to 15 joins. For larger queries, both ACO and a GA may be preferable over 2PO, subject to a trade-off between execution time and solution quality. The GA yields relatively good solutions in a comparably short time frame, whereas ACO needs more time to converge to high-quality solutions.

Application of a dual foundation approach for construction of an intelligent system

This paper presents the development of a decision support system for monitoring and diagnosis of the amine-based post-combustion carbon dioxide (CO2) capture process system at the International Test Centre for CO2 Capture (ITC) at the University of Regina. The amine-based CO2 absorption capture process system consists of dozens of components and generates more than a hundred different types of data. The vast amount of raw data produced by the system are measurements of the many reaction components, valves and pumps. The system operators often find it difficult to quickly detect, diagnose and correct any abnormal conditions that may arise during operation. Therefore, developing a decision support system for monitoring and diagnosis of the CO2 capture process system which aids the operator in monitoring and diagnosis of the system is a desirable objective. This paper describes development of the system based on the dual foundation of a domain ontology and an intelligent system framework in the domain of carbon dioxide capture process. The developed ontology provides the semantic knowledge foundation; it was implemented in the Knowledge Modeling System (KMS), and the knowledge was stored in the XML format. The intelligent system framework consists of system functions which can use the XML schema provided by the ontology and support the development process. A decision support expert system for process monitoring is a sample system developed on the dual foundation.

Aerial forest herbicide application: Comparative assessment of risk mitigation strategies in Canada

Herbicide use in forest management is subject to controversy due to potential risks to human and environmental health. Provinces with substantial forest herbicide use are the focus of this comparative assessment of risk mitigation strategies for aerial application of forestry herbicides. This paper explores risk mitigation procedures surrounding treatment prescriptions, herbicide planning and permitting, and operational treatment, against a background of legislative and regulatory requirements. The three major-use provinces have similarly high levels of risk mitigation, including detailed herbicide application plan requirements, use of electronic guidance systems, buffering of environmental sensitivities, pre-spray reconnaissance flights and post-spray auditing. Notable differences include standardizing use of rotary-wing aircraft, use of low-drift nozzles, the rigor applied to aircraft calibration and use of block monitors for detailed meteorological monitoring. These techniques are generally unique to Alberta and are considered best management practices. The routine use of validated aerial dispersal and expert decision support systems (e.g., AgDisp, SprayAdvisor) is recommended, as it could provide significant added value to generic and spatially explicit risk mitigation with multiple applications. It is the opinion of the authors that aerial herbicide applications as performed in all three major-use jurisdictions are highly protective of human and environmental health.

Integrating the Carbon and Water Footprints’ Costs in the Water Framework Directive 2000/60/EC Full Water Cost Recovery Concept: Basic Principles Towards Their Reliable Calculation and Socially Just Allocation

This paper presents the basic principles for the integration of the water and carbon footprints cost into the resource and environmental costs respectively, taking the suggestions set by the Water Framework Directive (WFD) 2000/60/EC one step forward. WFD states that full water cost recovery (FWCR) should be based on the estimation of the three sub-costs related: direct; environmental; and resource cost. It also strongly suggests the EU Member States develop and apply effective water pricing policies to achieve FWCR. These policies must be socially just to avoid any social injustice phenomena. This is a very delicate task to handle, especially within the fragile economic conditions that the EU is facing today. Water losses play a crucial role for the FWC estimation. Water losses should not be neglected since they are one of the major “water uses” in any water supply network. A methodology is suggested to reduce water losses and the related Non Revenue Water (NRW) index. An Expert Decision Support System is proposed to assess the FWC incorporating the Water and Carbon Footprint costs.

An exploratory analysis of hotel selection factors: A comprehensive survey of Tehran hotels

The selection of residence location in different countries is of high priority and significance for tourists. The selection of the most appropriate hotel entails a rather complicated decision-making process. A comprehensive hotel selection model can empower the hotel managers, the tourists, and the tourism industry to make decisions based on more effective indicators of high quality services for a higher rate of satisfaction. The purpose of this research is to deeply explore the broad literature and to identify the most significant hotel selection indicators and factors in Tehran hotels and to present a comprehensive model through an exploratory factor analysis of the extracted indicators so as to provide the managers and tourists with a firm ground for making better decisions regarding the indicators of hotel selection. Promenade and comfort, security and protection, network services, pleasure, staff and their services, news and recreational information, cleanliness and room comfort, expenditure, room facilities and car parking were identified as the main hotel selection factors of Tehran hotels. Afterwards, another factor analysis has been done in order to extract the next hidden set of factors within the aforementioned factors which return two main factors of “Hotel Comfort Factors” and “Hotel Compensatory Factors”. Following the creation of the final model and based on the intrinsic vagueness of decision making in the process of selection, a set of fuzzy membership functions for the extracted factors has been provided. The intention has been to provide the expert system and decision support system developers and users with a set of practical indicators in order to help them design and implement realistic systems based on the deeply studied indicators and factors of hotel selection. Such supportive systems can be directly presented to the tourists requesting a mechanism for selecting the most appropriate hotel but lacking enough information about the important indicators and factors and also to the managers of hotels who are trying to make strategic decisions regarding the most optimized investments on the indicators of selecting a hotel. Considering the priorities of tourists, hotel managers, entrepreneurs and investors in the hotel industry require deep investigations and studies for which this paper provides a firm basis.

The Theory and Method of Agricultural Expert Decision Support System

The Theory and Method of Agricultural Expert Decision Support System

Hybrid analytic/rule-based expert system for channel covering decision support

Expert systems are intelligent tools that serve as support in decision‐making processes. This study presents a new expert system for channel covering decision support with the aid of high‐level computer language, which combines knowledge‐ and rule‐based programming techniques. The proposed expert system has been called the “Channel Covering Decision Support Expert System” and abbreviated as “CCES”. CCES helps the user when deciding whether covering (lining) is necessary in rivers or open drainage channels, and it finds out whether or not the properties of the covering material types offered by the user are sufficient in case coverage is required. Furthermore, CCES offers the most appropriate covering type from the covering type database built by the user by taking technical and economical considerations into account. In the paper, the applicability of CCES has also been validated by a case study related to an irrigation project carried out in Turkey.