Support System Model Research Articles

Designing a model of a decision support system based on a multi-aspect factographic search

A theoretical-multiple model, describing the composition and structure of a decision support system was proposed. The system operates based on a multi-aspect factographic search using simple methods of precedents detection, concerning different aspects of the problem to be solved. The information technology of a multi-aspect factographic search was proposed. The technology allows us, on the basis of a primary query, to generate a query group in accordance with the aspects of the solved problem. In this case, subsets of aspect-relevant documents are separated. In each document, aspect-relevant precedents are found. Then, the redundancy in search results is eliminated. Effectiveness of the technology is ensured by two factors. This is the generation of a package of secondary queries on certain aspects, as well as sufficient completeness of a sample of documents for analysis. In addition, filtering of the content of each document on particular aspects allows guaranteed and even redundant detection of precedents, containing the facts that are required by the user. Redundancy of the search results is eliminated by the threshold processing of found textual fragments and by using importance weight factors of aspects. The system minimizes actions of the user who does not need to generate multiple queries and take care of solving multi-aspect problems. The information technology was tested on the example of a marketing task. Satisfactory assessment of completeness of search results was obtained both by aspects and, on average, by a task.

Mathematical Modeling of Hemolysis in Pulsatile Blood Pumps

The paper presents the results of calculation of the normalized index of hemolysis using three different approaches based on mathematical modeling of a pulsatile circulatory support system with a stroke volume of 30 cm3. The suggested approaches are shown to be useful for estimating the hemolysis level in pulsatile circulatory support systems at various stages of the design process.

The Seattle spine score: Predicting 30-day complication risk in adult spinal deformity surgery

BackgroundComplication rates in complex spine surgery range from 25% to 80% in published studies. Numerous studies have shown that surgeons are not able to accurately predict whether patients are likely to face post-operative complications, in part due to biases based on individual experience. The purpose of this study was to develop and evaluate a predictive risk model and decision support system that could accurately predict the likelihood of 30-day postoperative complications in complex spine surgery based on routinely measured preoperative variables. MethodsPreoperative and postoperative data were collected for 136 patients by reviewing medical records. Logistic regression analysis (LRA) was applied to develop the predictive algorithm based on patient demographic parameters, including age, gender, and co-morbidities, including obesity, diabetes, hypertension and anemia. We additionally compared the performance of the predictive model to a spine surgeon’s ability to predict patient complications using signal detection theory statistics representing sensitivity and response bias (A′ and B″ respectively). We developed a decision support system tool, based on the LRA predictive algorithm, that was able to provide a numeric probabilistic likelihood statistic representing an individual patient’s risk of developing a complication within the first 30days after surgery. ResultsThe predictive model was significant (χ2=16.242, p<0.05), showed good fit, and was calibrated by using area under the receiver operating characteristics curve analysis (AUROC=0.712, p<0.01). The model yielded a predictive accuracy of 75.0%. It was validated by splitting the data set, comparing subset models, and testing them with unknown data. Validation also involved comparing the classification of cases by experts with the classification of cases by the model. The model significantly improved the classification accuracy of physicians involved in the delivery of complex spine surgical care. ConclusionsThe application of technology and data-driven tools to advanced surgical practice has the potential to improve decision making quality, service quality and patient safety.

A geospatial decision support system for supporting quality viticulture at the landscape scale

The world of viticulture connected to wine making has become a very important activity in many inland areas permitting both the generation of important income and the sustaining of agriculture systems.Recent progress in both crop modeling and Decision Support Systems (DSS) applied to viticulture promises important changes that combine both high quality production and environmental sustainability. However, most of this progress is only addressed at the farm level and does not challenge the viticulture landscape, which is a key issue when facing DOC, DOCG areas, wine growers' cooperatives and consortiums and strategic viticulture planning.Thus, this paper aims to demonstrate that a new type of DSS, which is developed on a Geospatial Cyberinfrastructure (GCI) platform, may provide an important web-based operational tool for high quality viticulture as it connects farm and landscape levels better.The GCI platform supports acquisition, management, processing of both static and dynamic data (e.g. pedological, daily climatic, and vineyard distribution), data visualization, and on-the-fly computer applications in order to perform simulation modeling (e.g. grapevine water stress, evaluation of ecosystem services, etc.). These are all potentially accessible via the Web.This is possible thanks to the implementation of a set of modeling clusters that is strongly rooted in soil-plant-atmosphere and physically based simulation modeling.The DSS tool, applied to an area of 20,000ha in Southern Italy, is designed to address viticulture planning and management by providing operational support for farmers, farmer associations and decision makers involved in the viticulture landscape.Output of the system includes viticulture planning and management scenario analysis, maps and evaluation of potential and current plant water stress.The tool will also be demonstrated through a short selection of practical case studies.

Forecasting model for Pea seed-borne mosaic virus epidemics in field pea crops in a Mediterranean-type environment

An empirical model was developed to forecast Pea seed-borne mosaic virus (PSbMV) incidence at a critical phase of the annual growing season to predict yield loss in field pea crops sown under Mediterranean-type conditions. The model uses pre-growing season rainfall to calculate an index of aphid abundance in early-August which, in combination with PSbMV infection level in seed sown, is used to forecast virus crop incidence. Using predicted PSbMV crop incidence in early-August and day of sowing, PSbMV transmission from harvested seed was also predicted, albeit less accurately. The model was developed so it provides forecasts before sowing to allow sufficient time to implement control recommendations, such as having representative seed samples tested for PSbMV transmission rate to seedlings, obtaining seed with minimal PSbMV infection or of a PSbMV-resistant cultivar, and implementation of cultural management strategies. The model provides a disease forecast risk indication, taking into account predicted percentage yield loss to PSbMV infection and economic factors involved in field pea production. This disease risk forecast delivers location-specific recommendations regarding PSbMV management to end-users. These recommendations will be delivered directly to end-users via SMS alerts with links to web support that provide information on PSbMV management options. This modelling and decision support system approach would likely be suitable for use in other world regions where field pea is grown in similar Mediterranean-type environments.

The Research of Concrete Floor Stress under Construction Process in Main Structure

The construction process of each floor is the same. It’s inevitable to appear the inter-related load phenomenon. Construction loads are acted on concrete slab which transfer loads to multi-storey formwork support system model. Concrete slabs have different stress on different layers. This article uses the finite element software to simulate the multi-story formwork system to study the stress of different floors and locations.

Highway and Life Cycle Costing as Decision-Making Support System Model

Objective: This paper presents the measurable variables in Malaysia Green Highway Index (MyGHI). Methods/Statistical Analysis: Mean result were determined showed respondents level of agreement towards LCC component and Green Highway Index (GHI) measureable criteria. Findings: This paper also highlights the expected findings which lead to identifying important factors in developing real-time decision making application using LCC. The outcome of the paper will inspire the Malaysian highway builders to respond to green highway development and make LCC as a tool of decision making. Applications/Improvements: Thus the later, correlation between MyGHI measurable variables and LCC can be carried out to determine the significant elements that influence the decision-making to achieve targeted score of MyGHI.

Emission Characteristics of Vehicle Exhaust in Artery and Collector Roads in Nanjing Based on Real-time Traffic Data

The vehicle emissions were estimated by the Urban High Temporal-Spatial Resolution Vehicle Emission Inventory Model and Decision Support System (hereinafter referred to as the HTSVE system) with the real-time data including traffic flow, average speed and fleet compositions obtained from Radio Frequency Identification (RFID) and emission factors based on COPERT. The study focused on the characteristics of vehicle emissions by means of non-parametric test and cluster analysis with ArcGIS in artery roads and collector roads in Nanjing, 2014. The result showed that the proportion of passenger cars reached up to 80%, and China 3 and China 4 accounted for over 90% while China 3 contributed most. The daily average emissions in special periods including morning, noon and evening were affected by both road types and weekend effect. The artery and collector roads were classified as 5 clusters. Each type had similar emission rates distribution and was affected by spatial position to support traffic management.

Development and Application of Urban High Temporal-Spatial Resolution Vehicle Emission Inventory Model and Decision Support System

This paper reports on the development and application of an urban high temporal-spatial resolution vehicle emission inventory model and decision support system based on the current situation in China and actual vehicle emission control requirements. The system incorporates a user-friendly modular architecture that integrates a vehicle emission model and a decision support platform and includes scenario analysis and visualisation capabilities. A bottom-up approach based on localised emission factors and actual on-road driving condition has been adopted to develop the system. As a case study of application and evaluation, an emission reduction effect analysis of the supposed low-emission zone (LEZ) policy in Beijing (2012) was conducted. According to the simulated results in the forms of tables, histograms and grid maps, the establishment of this LEZ had a definite effect on the emission reduction of various types of air pollutants, especially carbon monoxide and hydrocarbon. In the system, the simulation methodology for identifying environmental benefits brought by the LEZ policy could be used to assess other similar environmental policies. Through flexible modification of configuration values or input data variables, the efficacy of separate or joint policies could be quantifiably evaluated and graphically displayed.

Clinical Decision Support System for Assessment Coronary Heart Disease Based on Risk Factor

Objectives: This study aims to propose a model of coronary heart disease assessment system based on risk factors. Methods/Statistical Analysis: To achieve these objectives, the model proposed system comprises several processes. First, the dimension reduction using principle component analysis (PCA). Second, classification using support vector machine. Third, validate using 10-fold cross validation in the process of training and testing. Training and testing using patient data from the Hospital Dr. Moewardi Solo Indonesia, which amounted to 120 with 12 attributes. Fourth, the system performance is measured using several parameters, namely sensitivity, specificity, area under the curve, positive prediction value, negative prediction value and accuracy. Findings: Tests on the proposed system, to process the dimensional reduction by PCA, which is followed by the method of orthogonal rotation with verimax, resulting nine attributes of the 12 attributes of risk factors. Attribute are obtained by using the variance of data from the PCA process of 71.1908%. Attribute risk factors rotation outcome is age, gender, occupation rate, total cholesterol, low-density lipoprotein, triglycerides, systolic and diastolic blood pressure and smooking. System performance prediction is generated for parameter sensitivity 84.20%, specificity 69.09%, accuracy 78.61%, positive prediction value 82.53%, negative prediction value 71.70% and the area under the curve 76.64%. Applications/Improvements: System model of clinical decision support system for the assessmen of coronary heart disease based on risk factors can be used by clinicians, as support in making clinical decisions. The proposed system provides the performance of the medium category.

Supporting system interference on aerodynamic characteristics of an aircraft model in a low-speed wind tunnel

Many kinds of support system, such as tail support system, external/balance support system, side wall support system and wing tip support system are used for wind tunnel testing. The difference between the flow around the test model and the flow around the real aircraft is caused by the support system and results in a difference between aerodynamic characteristics of the test article and the actual one and is referred to as support interference. Support interference is one of the important topics of aerodynamic testing since it can have significant influence on the accuracy of the test data. The support system and support interference become one of the main investigation areas of experiment aerodynamics. The results of experimental investigation of the influence of model support on the determination of aerodynamic coefficients of a wind tunnel model are presented. A discussion is given of the forms of interference occurring in the low speed wind tunnel of the Military Technical Institute due to the model support system. Two types of model attachments, bent sting and external/balance model support are considered. The magnitude of interference on the test results is given. The main interference is on the pitching moment coefficient Cm. The computational results of the interference-free aerodynamic coefficients of a Training Aircraft Model are also given and compared to experimental data. A procedure for eliminating the undesired effect of interference of the model support system on the test results is presented.

Forming Local Support System (LSS) Model as Agent of Change Behavior of Clean and Healthy Household in Riverbanks of Banjar Regency

PHBS is currently the theme of an important strategy in improving public health status. PHBS development program is a program that has been running since 1996. However, its success is still far from expectations. In South Kalimantan in 2015, the percentage of households with PHBS is 60.09%. The coverage of PHBS households in the work area of the District Health Office of Banjar in 2015 amounted to 52.1%.Based on the success of the previous cadre program, the alternative solution that can be done in the field is the formation of Local Support System (LSS) model as an agent of change of clean and healthy life behavior in the household order. This research uses analytic design, with Cross Sectional approach. Subjects were 90 peoples. Based on the results of the activity it was found that there was no significant correlation between knowledge, support of community leaders, and support of health officers and household PHBS strata shown with p-values of 0.337, 1, 000 and 0.059, respectively. However, there is a correlation between education level and household PHBS stratum with p-value= 0, 014, and there is significant difference before counseling and after counseling p-value equal to 0.0001. Suggestion from this research is LSS modeling is expected to become a model which can be one way to increase PHBS coverage of household order and to maintain positive behavior of community in applying PHBS of household order.

A Monitoring, Modeling and Decision Support System (DSS) for a Microalgae Production Plant based on Internet of Things Structure

Microalgae cultivation is an emerging and interesting field with an increasing market and with Great prospects for the future both in the food, pharmaceutical, cosmetic and energetic field as well as for other new applications. Microalgae are photosynthetic aquatic microorganism which growth is regulated in-primis by light, temperature, pH and nutrients availability. The monitoring and control of these parameters is crucial in Microalgae cultivation plants because it allows to increase the production and the quality of microalgae biomass feedstock and to prevent the critical conditions for the culture which can compromise the cultivation.In the present work, we present an affordable and easy to use application of Internet of Things (IoT) for the monitoring and control of a microalgae cultivation coupled with a biological modeling for Decision Support System (DSS) to the operator for managing a plant sited in Southern Italy.

BOUNDARIES OF THE ONTOLOGY OF DESIGNING

The ongoing research in the field of computer ontologies, ontological engineering, decision-making systems as well as an emerging mutual interest for philosophic, physiological and linguistic aspects of ontology of designing among humanitarian and technical scientific communities have stipulated the need for further distinction of the boundaries of the researched scientific discipline. This paper continues and develops the ideas, presented by the author in the article titled "Scientific basis of ontology of designing", published in the first issue of the journal in 2013. This work attempts to further outline the research area of the journal by elaborating the scientific problematic of the journal, making focuses and placing accents, relevant at the current stage of the discipline’s development, to distinguish the place of the ontology of designing amongst the current well-established but ever-changing differentiation of sciences. The article presents the results of analysis performed on the key concepts of ontology of designing based on the scientometric resources of network origin. It is shown, that the conventional segregation of scientific disciplines was largely determined by their development, accumulated experience, traditions, cultural features of their genesis, linguistic and conceptual content. Ontology of designing is still considered to be an integrative scientific discipline based on methods of system and ontological analysis, information technologies, computer modeling, artificial intelligence, descriptive logic, CAD systems and decision-making support systems, data and knowledge bases.

Transfer Model and Decision Support System of Smart Microgrids Multiple Distributed Power

Transfer Model and Decision Support System of Smart Microgrids Multiple Distributed Power

MODEL SISTEM PENUNJANG KEPUTUSAN PENENTUAN JURUSAN BAGI SISWA SMA MENGGUNAKAN METODE TOPSIS (STUDI KASUS YADIKA NATAR)

Natar Yadika SMA is one of the senior high school in Bandar Lampung which is located on Jl. Sitara No. 84 Muara Putih Natar, South Lampung. SMA Yadika Natar has two courses, namely science and social studies. At each new admissions SMA Yadika Natar has determined the majors for students done by the student in the student section which process refers to the value of report cards, results of written tests, and the interests of students who then recapitulated and calculation . A process which has been running at high school Natar Yadika can cause several problems including, the selection is not objective (results of calculations which are not in accordance with the interests of students), there can be errors in the calculation(HumanError). In order to improve objectivity in determining the majors in high school Yadika Natar. the research build a Decision Support System (DSS) model in the determination of the majors for students / high school Yadika Natar. The system uses a method (TOPSIS) Technique for Order Preference by Similarity to Ideal Solution to the stages of the intelligence phase, the design phase, the selection phase and the implementation phase.Decision support systems in school Yadika Natar which includes determining the majors for students / student is expected to increase the objective assessment and provide the right decisions with the best results in the establishment of a department Keywords — Decision Support System, TOPSIS method, determination of the Department.

Leaving Educating Women In Its WAKE: Amplifying the work of those leading global change [Amperes: Current Affairs from Around the World

When asked, many women credit a former teacher, mentor, relative, or friend with giving them the confidence to pursue a career in engineering despite a hesitation of some kind. Whether it be that the way forward would require being one of few females in science, technology, engineering, and math (STEM) classes, community pressure to take a different path with one?s career and family life, or other concerns, challenges arise. Nevertheless, they followed their passions into rewarding, fulfilling careers. Perhaps this sounds familiar to some of you reading right now. Now, how often have you considered becoming that support system or role model for someone else?

Modeling the cost-effectiveness of stormwater best management practices in an urban watershed in Las Vegas Valley

The Las Vegas Valley is one of the fastest growing urban areas in the United States. Any future urbanization and climate change, especially if the climate becomes wetter and there are more intense and frequent storm events, will undoubtedly cause excessive urban stormwater runoff and exacerbate flooding in the Valley. Stormwater management is therefore one of the key challenges to the local government. The main goal of this study was to ascertain the utility of Best management Practices (BMPs) in mitigating stormwater runoff in the Duck Creek watershed in the Las Vegas Valley. The cost-effectiveness of different BMPs were also compared so as to determine the best BMP arrangement under the current and future climate and land use change conditions. By applying SUSTAIN (System for Urban Stormwater Treatment and Analysis INtegration) as a comprehensive GIS-based modeling and decision support system in the BMP analyses, modeling results show that although the installation of the existing three detention basins in the watershed can provide a 9% flow reduction, these three detention basins alone will not be adequate in the future with the impending changes in climate and land use. To alleviate the potential problems of water resources, SUSTAIN was further used to determine the number of additional BMPs required, the optimal types of BMPs (such as, detention and infiltration BMPs), and their locations in reducing storm runoff in the watershed under the future land-use and climate regimes. By comparing the performances of five potential BMP implementation scenarios, it was found that a mixed implementation of one additional detention BMP and one infiltration BMP to the existing detention BMPs in the downstream area of the watershed would be the most cost-effective stormwater runoff control solution in face of future urbanization and climate change. Depending on the locations of the new detention and infiltration BMPs, surface flow, even without BMP retrofit options, could be reduced by 27–31%. The cost for such installations would range from $1,141,000 to $1,319,000. This information may be useful to local planners and water resource managers in their efforts to develop alternative stormwater management plans in the arid Southwest.

A performance measurement decision support system method applied for technology-based firms’ suppliers

The present article proposes a mathematical decision support system model to measure the performance of incubated technology-based firms (TBFs) suppliers. The research was conducted based on three steps: (1) a literature review, in order to parameterise the research in relation to the theme; (2) the construction of a measuring system, based on the presumptions permeated by the analytic hierarchy process (AHP); and (3) the application of the system at three companies. The findings demonstrated the mathematical modelling developed is capable of providing satisfactory results to the reality of the sector studied, presenting the situation of the suppliers evaluated, independent of the nature of the indicated critical success factors (CSFs). Also, this tool supports companies by providing a strong foundation to organise the information regarding the service level delivered by each supplier, according to previous research on the theme.

An adaptive stock index trading decision support system

Predicting the direction and movement of stock index prices is difficult, often leading to excessive trading, transaction costs, and missed opportunities. Often traders need a systematic method to not only spot trading opportunities, but to also provide a consistent approach, thereby minimizing trading errors and costs. While mechanical trading systems exist, they are usually designed for a specific stock, stock index, or other financial asset, and are often highly dependent on preselected inputs and model parameters that are expected to continue providing trading information well after the initial training or back-tested model development period. The following research leads to a detailed trading model that provides a more effective and intelligent way for recognizing trading signals and assisting investors with trading decisions by utilizing a system that adapts both the inputs and the prediction model based on the desired output. To illustrate the adaptive approach, multiple inputs and modeling techniques are utilized, including neural networks, particle swarm optimization, and denoising. Simulations with stock indexes illustrate how traders can generate higher returns using the developed adaptive decision support system model. The benefits of adding adaptive and intelligent decision making to forecasts are also discussed.