Search results for: probabilistic decision tree
Commenced in January 2007
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Edition: International
Paper Count: 4804

Search results for: probabilistic decision tree

3334 Estimation of Transition and Emission Probabilities

Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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3333 Hybrid Structure Learning Approach for Assessing the Phosphate Laundries Impact

Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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3332 Enhancing Sustainable Stingless Beekeeping Production through Technology Transfer and Human Resource Development in Relationship with Extension Agents Work Performance among Malaysian Beekeepers

Authors: Ibrahim Aliyu Isah, Mohd Mansor Ismail, Salim Hassan, Norsida Man, Oluwatoyin Olagunju

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Stingless beekeeping is not only a profitable activity for Malaysian beekeepers but also for the Malaysian economy. However, natural honey has faced some difficulties, which resulted in low production due to a lack of information on improved technology as well as the capacity and potential building of stingless beekeeping farmers, which depend mostly on information received from the extension agents. Hence, it is the responsibility of the extension agents to give useful information on the available technology and develop the capacity of the farmers to make the right decision that will improve their level of production. This study assessed how technology transfer and human resource development skills influence the work performance of the extension agents toward sustainable beekeeping production among beekeepers. The study sought to establish the role of relevant technology transfer and human resource development skills in effective performance. The research design was a descriptive and quantitative survey of stingless beekeepers on technology transfer and human resource development by the extension agent. Data was obtained from 54 beekeeping farmers and was analyzed using descriptive and inferential statistics. The results revealed that technology skill, technology dissemination skill, technology evaluation skill, Decision-making process skill, Leadership development skill and work performance were rated moderate by stingless beekeeping farmers, while Social skill was rated high. A significant and positive correlation (P<0.01) existed between all variables and performance. Regression results showed that leadership development skills, Decision-making process skills, and social skills are significant (P=.05), while technology skills, technology dissemination skills, and technology evaluation skills are not significant. The highest contributing factor is social skill (β=.446). Beekeeping is a profitable project in Malaysia and can be sustained if the extension services and programs are well carried out by competent extension agents and relevant agricultural government agencies.

Keywords: beekeeping, extension agents, human resource development, sustainable, technology transfer, work performance

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3331 Physics of Decision for Polling Place Management: A Case Study from the 2020 USA Presidential Election

Authors: Nafe Moradkhani, Frederick Benaben, Benoit Montreuil, Ali Vatankhah Barenji, Dima Nazzal

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In the context of the global pandemic, the practical management of the 2020 presidential election in the USA was a strong concern. To anticipate and prepare for this election accurately, one of the main challenges was to confront (i) forecasts of voter turnout, (ii) capacities of the facilities and, (iii) potential configuration options of resources. The approach chosen to conduct this anticipative study consists of collecting data about forecasts and using simulation models to work simultaneously on resource allocation and facility configuration of polling places in Fulton County, Georgia’s largest county. A polling place is a dedicated facility where voters cast their ballots in elections using different devices. This article presents the results of the simulations of such places facing pre-identified potential risks. These results are oriented towards the efficiency of these places according to different criteria (health, trust, comfort). Then a dynamic framework is introduced to describe risks as physical forces perturbing the efficiency of the observed system. Finally, the main benefits and contributions resulting from this simulation campaign are presented.

Keywords: performance, decision support, simulation, artificial intelligence, risk management, election, pandemics, information system

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3330 Consumer Behavior and the Demand for Sustainable Buildings in an Emerging Market: The Example of Brazil

Authors: Vinícius L. L. Morrone, David Douek, Helder M. F. Pereira, Bernadete L. M. Grandolpho

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This work aimed to identify the relationships between the level of consumer environmental awareness and their search for sustainable properties, as well as to understand the main sustainability structures considered by these consumers during the decision process. Additionally, the paper looked up to the influence environmental awareness and financial status have over the disposition of buyers to pay more for sustainable properties. To achieve these objectives, 318 questionnaires were answered electronically, after being sent to the Green Building Brazil email basis, as to other Real Estate developers client basis. From all the questionnaires answered, 71 were discarded, leaving a total amount of 247 admitted questionnaires to be analyzed. The responses were evaluated based on the theory of consumer decision making, especially on the influence factors of this process. The data were processed using a PLS model, using the R software. The results have shown that the level of consumer environmental awareness effectively affects the consumer’s will of acquiring a sustainable property or, at least, a property with some environmental friendly structures. The consumer’s environmental awareness also positively impacts the importance consumers give to individual environmental friendly structures. Also, as a consumer value to those individual structures raises, it is also observed a raise in his will to buy a sustainable property. Additionally, the impact of consumer’s environmental awareness and financial status over the willingness to pay more for a property with those attributes. The results indicate that there was no relationship between consumers' environmental awareness and their willingness to pay more for a sustainable property. On the other hand, the financial status and the family income of the consumers showed a positive relation with the willingness to pay more for a sustainable property. This indicates that consumers with better financial conditions, which according to the analysis do not necessarily have a greater environmental awareness, are those who are willing to pay more for a sustainable property. Thus, this study indicates that, even if the environmental awareness impact positively the demand for sustainable structures and properties, this impact is not price reflected, due to the price elasticity of the consumption, especially for a category of lower income consumers. This paper adds to the literature in the way it projects some guidelines to the consumer’s decision process in the Real Estate market in emerging economies, as well as it presents some drivers to pricing decisions.

Keywords: consumer behavior, environmental awareness, real estate pricing, sustainable buildings

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3329 Conception of a Regulated, Dynamic and Intelligent Sewerage in Ostrevent

Authors: Rabaa Tlili Yaakoubi, Hind Nakouri, Olivier Blanpain

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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of the CARDIO project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 40 to 100%. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 60% of total volume rejected to the natural environment and of 80 % in the number of discharges.

Keywords: RTC, paradigm, optimization, automation

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3328 Life Cycle Assessment as a Decision Making for Window Performance Comparison in Green Building Design

Authors: Ghada Elshafei, Abdelazim Negm

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Life cycle assessment is a technique to assess the environmental aspects and potential impacts associated with a product, process, or service, by compiling an inventory of relevant energy and material inputs and environmental releases; evaluating the potential environmental impacts associated with identified inputs and releases; and interpreting the results to help you make a more informed decision. In this paper, the life cycle assessment of aluminum and beech wood as two commonly used materials in Egypt for window frames are heading, highlighting their benefits and weaknesses. Window frames of the two materials have been assessed on the basis of their production, energy consumption and environmental impacts. It has been found that the climate change of the windows made of aluminum and beech wood window, for a reference window (1.2m × 1.2m), are 81.7 mPt and - 52.5 mPt impacts respectively. Among the most important results are: fossil fuel consumption, potential contributions to the green building effect and quantities of solid waste tend to be minor for wood products compared to aluminum products; incineration of wood products can cause higher impacts of acidification and eutrophication than aluminum, whereas thermal energy can be recovered.

Keywords: aluminum window, beech wood window, green building, life cycle assessment, life cycle analysis, SimaPro software, window frame

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3327 Increasing of Resiliency by Using Gas Storage in Iranian Gas Network

Authors: Mohsen Dourandish

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Iran has a huge pipeline network in every state of country which is the longest and vastest pipeline network after Russia and USA (360,000 Km high pressure pipelines and 250,000 Km distribution networks). Furthermore in recent years National Iranian Gas Company is planning to develop natural gas network to cover all cities and villages above 20 families, in a way that 97 percent of Iran population will be gas consumer by 2020. In this condition, network resiliency will be the first priority of NIGC and due to that several planning for increasing resiliency of gas network is under construction. The most important strategy of NIGC is converting tree form pattern network to loop gas networks and developing underground gas storage near main gas consuming centers. In this regard NIGC is planning for construction of over 3500 km high-pressure pipeline and also 10 TCM gas storage capacities in UGSs.

Keywords: Iranian gas network, peak shaving, resiliency, underground gas storage

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3326 Suitable Site Selection of Small Dams Using Geo-Spatial Technique: A Case Study of Dadu Tehsil, Sindh

Authors: Zahid Khalil, Saad Ul Haque, Asif Khan

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Decision making about identifying suitable sites for any project by considering different parameters is difficult. Using GIS and Multi-Criteria Analysis (MCA) can make it easy for those projects. This technology has proved to be an efficient and adequate in acquiring the desired information. In this study, GIS and MCA were employed to identify the suitable sites for small dams in Dadu Tehsil, Sindh. The GIS software is used to create all the spatial parameters for the analysis. The parameters that derived are slope, drainage density, rainfall, land use / land cover, soil groups, Curve Number (CN) and runoff index with a spatial resolution of 30m. The data used for deriving above layers include 30-meter resolution SRTM DEM, Landsat 8 imagery, and rainfall from National Centre of Environment Prediction (NCEP) and soil data from World Harmonized Soil Data (WHSD). Land use/Land cover map is derived from Landsat 8 using supervised classification. Slope, drainage network and watershed are delineated by terrain processing of DEM. The Soil Conservation Services (SCS) method is implemented to estimate the surface runoff from the rainfall. Prior to this, SCS-CN grid is developed by integrating the soil and land use/land cover raster. These layers with some technical and ecological constraints are assigned weights on the basis of suitability criteria. The pairwise comparison method, also known as Analytical Hierarchy Process (AHP) is taken into account as MCA for assigning weights on each decision element. All the parameters and group of parameters are integrated using weighted overlay in GIS environment to produce suitable sites for the Dams. The resultant layer is then classified into four classes namely, best suitable, suitable, moderate and less suitable. This study reveals a contribution to decision-making about suitable sites analysis for small dams using geospatial data with minimal amount of ground data. This suitability maps can be helpful for water resource management organizations in determination of feasible rainwater harvesting structures (RWH).

Keywords: Remote sensing, GIS, AHP, RWH

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3325 Quality Function Deployment Application in Sewer Pipeline Assessment

Authors: Khalid Kaddoura, Tarek Zayed

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Infrastructure assets are essential in urban cities; their purpose is to facilitate the public needs. As a result, their conditions and states shall always be monitored to avoid any sudden malfunction. Sewer systems, one of the assets, are an essential part of the underground infrastructure as they transfer sewer medium to designated areas. However, their conditions are subject to deterioration due to ageing. Therefore, it is of great significance to assess the conditions of pipelines to avoid sudden collapses. Current practices of sewer pipeline assessment rely on industrial protocols that consider distinct defects and grades to conclude the limited average or peak score of the assessed assets. This research aims to enhance the evaluation by integrating the Quality Function Deployment (QFD) and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods in assessing the condition of sewer pipelines. The methodology shall study the cause and effect relationship of the systems’ defects to deduce the relative influence weights of each defect. Subsequently, the overall grade is calculated by aggregating the WHAT’s and HOW’s of the House of Quality (HOQ) using the computed relative weights. Thus, this study shall enhance the evaluation of the assets to conclude informative rehabilitation and maintenance plans for decision makers.

Keywords: condition assessment, DEMATEL, QFD, sewer pipelines

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3324 Financial Risk Tolerance and Its Impact on Terrorism-Tourism Relation in Pakistan

Authors: Sania Sana, Afnan Nasim, Usman Malik, Maroof Tahir

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The aim of this research is to scrutinize the interdependent relationship between terrorism and behavioral changes in the tourism activities in Pakistan with the moderating impact of a unique variable titled 'Financial Risk Tolerance'. The article looks at the inter-reliant relationship with the alleged political and economic aspects and behavioral changes in the tourists and the consumers by these variables over time. The researchers used many underlying theories like the catastrophe theory by (Svyantek, Deshon and Siler 1991), information integration theory (Anderson 1981, 1982) and prospect theory (Kahneman and Tversky 1979) to shape the study’s framework as per tourist decision making model. A sample of around 110 locals was used for this purpose and the data was gathered by convenience sampling. The responses were analyzed using regression analysis. The results exhibited how terrorism along with the influence of financial risk tolerance had inclined a behavioral shift in the travelling patterns and vacation destination choice of the local tourists. Lastly, the paper proposes a number of suggestive measures for the tourism industry and the legislative bodies to ensure the safety of travelers and to boost the tourist activities in the vacation industry of Pakistan.

Keywords: terrorism, tourism, financial risk tolerance, tourist decision-making, destination choice

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3323 Occurrence and Habitat Status of Osmoderma barnabita in Lithuania

Authors: D. Augutis, M. Balalaikins, D. Bastyte, R. Ferenca, A. Gintaras, R. Karpuska, G. Svitra, U. Valainis

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Osmoderma species complex (consisting of Osmoderma eremita, O. barnabita, O. lassallei and O. cristinae) is a scarab beetle serving as indicator species in nature conservation. Osmoderma inhabits cavities containing sufficient volume of wood mould usually caused by brown rot in veteran deciduous trees. As the species, having high demands for the habitat quality, they indicate the suitability of the habitat for a number of other specialized saproxylic species. Since typical habitat needed for Osmoderma and other species associated with hollow veteran trees is rapidly declining, the species complex is protected under various legislation, such as Bern Convention, EU Habitats Directive and the Red Lists of many European states. Natura 2000 sites are the main tool for conservation of O. barnabita in Lithuania, currently 17 Natura 2000 sites are designated for the species, where monitoring is implemented once in 3 years according to the approved methodologies. Despite these monitoring efforts in species reports, provided to EU according to the Article 17 of the Habitats Directive, it is defined on the national level, that overall assessment of O. barnabita is inadequate and future prospects are poor. Therefore, research on the distribution and habitat status of O. barnabita was launched on the national level in 2016, which was complemented by preparatory actions of LIFE OSMODERMA project. The research was implemented in the areas equally distributed in the whole area of Lithuania, where O. barnabita was previously not observed, or not observed in the last 10 years. 90 areas, such as Habitats of European importance (9070 Fennoscandian wooded pastures, 9180 Tilio-Acerion forests of slopes, screes, and ravines), Woodland key habitats (B1 broad-leaved forest, K1 single giant tree) and old manor parks, were chosen for the research after review of habitat data from the existing national databases. The first part of field inventory of the habitats was carried out in 2016 and 2017 autumn and winter seasons, when relative abundance of O. barnabita was estimated according to larval faecal pellets in the tree cavities or around the trees. The state of habitats was evaluated according to the density of suitable and potential trees, percentage of not overshadowed trees and amount of undergrowth. The second part of the field inventory was carried out in the summer with pheromone traps baited with (R)-(+)-γ –decalactone. Results of the research show not only occurrence and habitat status of O. barnabita, but also help to clarify O. barnabita habitat requirements in Lithuania, define habitat size, its structure and distribution. Also, it compares habitat needs between the regions in Lithuania and inside and outside Natura 2000 areas designated for the species.

Keywords: habitat status, insect conservation, Osmoderma barnabita, veteran trees

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3322 Collective Intelligence-Based Early Warning Management for Agriculture

Authors: Jarbas Lopes Cardoso Jr., Frederic Andres, Alexandre Guitton, Asanee Kawtrakul, Silvio E. Barbin

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The important objective of the CyberBrain Mass Agriculture Alarm Acquisition and Analysis (CBMa4) project is to minimize the impacts of diseases and disasters on rice cultivation. For example, early detection of insects will reduce the volume of insecticides that is applied to the rice fields through the use of CBMa4 platform. In order to reach this goal, two major factors need to be considered: (1) the social network of smart farmers; and (2) the warning data alarm acquisition and analysis component. This paper outlines the process for collecting the warning and improving the decision-making result to the warning. It involves two sub-processes: the warning collection and the understanding enrichment. Human sensors combine basic suitable data processing techniques in order to extract warning related semantic according to collective intelligence. We identify each warning by a semantic content called 'warncons' with multimedia metaphors and metadata related to these metaphors. It is important to describe the metric to measuring the relation among warncons. With this knowledge, a collective intelligence-based decision-making approach determines the action(s) to be launched regarding one or a set of warncons.

Keywords: agricultural engineering, warning systems, social network services, context awareness

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3321 Parents’ Perceptions of the Consent Arrangements for Dental Public Health Programmes in North London: A Qualitative Exploration

Authors: Charlotte Jeavons, Charitini Stavropoulous, Nicolas Drey

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Background: Over one-third of five-year-olds and almost half of all eight-year-olds in the UK have obvious caries experience that can be detected by visual screening techniques. School-based caries preventions programs to apply fluoride varnish to young children’s teeth operate in many areas in the UK. Their aim is to reduce dental caries in children. The Department of Health guidance (2009) on consent states information must be provided to parents to enable informed autonomous decision-making prior to any treatment involving their young children. Fluoride varnish schemes delivered in primary schools use letters for this purpose. Parents are expected to return these indicating their consent or refusal. A large proportion of parents do not respond. In the absence of positive consent, these children are excluded from the program. Non-response is more common in deprived areas creating inequality. The reason for this is unknown. The consent process used is underpinned by the ethical theory of deontology that is prevalent in clinical dentistry and widely accepted in bio-ethics. Objective: To investigate parents’ views, understanding and experience of the fluoride varnish program taking place in their child’s school, including their views about the practical consent arrangements. Method: Schools participating in the fluoride varnish scheme operating in Enfield, North London, were asked to take part. Parents with children in nursery, reception, or year one were invited to participate via semi-structured interviews and focus groups. Thematic analysis was conducted. Findings: 40 parents were recruited from eight schools. The global theme of ‘trust’ was identified as the strongest influence on parental responses. Six themes were identified; protecting children from harm is viewed by parents as their role, parents have the capability to decide but lack confidence, sharing responsibility for their child’s oral health with the State is welcomed by a parent, existing relationships within parents’ social networks strongly influences consent decisions, official dental information is not communicated effectively, sending a letter to parents’ and excluding them from meeting dental practitioners is ineffective. The information delivered via a letter was not strongly identified by parents as influencing their response. Conclusions: Personal contact with the person(s) providing information and requesting consent has a greater impact on parental consent responses than written information provided alone. This demonstrates that traditional bio-ethical ideas about rational decision-making where emotions are transcended and interference is not justified unless preventing harm to an unaware person are outdated. Parental decision-making is relational and the consent process should be adapted to reflect this. The current system that has a deontology view of decision making at its core impoverishes parental autonomy and may, ultimately, increase dental inequalities as a result.

Keywords: consent, decision, ethics, fluoride, parents

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3320 Dynamic Route Optimization in Vehicle Adhoc Networks: A Heuristics Routing Protocol

Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

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3319 Digital Transformation: The Effect of Artificial Intelligence on the Efficiency of Financial Administrative Workers in Peru in 2024

Authors: Thiago Fabrizio Gavilano Farje, Marcelo Patricio Herrera Malpartida

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This study examines the influence of artificial intelligence (AI) on the work efficiency of administrative employees in the financial sector of Metropolitan Lima, Peru, during the year 2024. Focusing on the relationship between AI implementation and work efficiency, it addresses specific variables such as decision-making, motivation, and employee productivity. To accomplish the analysis between AI and work efficiency within the financial sector of Metropolitan Lima, it is necessary to evaluate how AI optimizes time in administrative tasks, examine how AI impacts the agility of the process of making decisions, and investigate the influence of AI on the satisfaction and motivation of employees. The research adopts a correlational and explanatory approach, designed to establish and understand the connections between AI and work efficiency. A survey design adapted from an OECD study is used, applying questionnaires to a representative sample of administrative workers in the financial sector who incorporate AI into their functions. The target population includes administrative workers in the financial sector of Metropolitan Lima, estimated at 73,097 employees based on data from the Censo Nacional de Empresas y Establecimientos and studies by the BCRP. The sample, selected through simple random sampling, comprises 246 workers.

Keywords: business management, artificial intelligence, decision making, labor efficiency, financial sector

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3318 Characteristics of Patients Undergoing Subclavian Artery Revascularization in Latvia: A Retrospective Analysis

Authors: Majid Shahbazi

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Subclavian artery stenosis (SAS) is a common vascular disease that can cause a range of symptoms, from arm fatigue and weakness to ischemic stroke. Revascularization procedures, such as percutaneous transluminal angioplasty and stenting, are widely used to treat SAS and improve blood flow to the affected arm. However, the optimal management of patients with SAS is still unclear, and further research is needed to evaluate the safety and efficacy of different treatment options. This study aims to investigate the characteristics of patients with SAS who underwent revascularization procedures in Latvia (Specifically RAKUS). The research part of this paper aims to describe and analyze the demographics, comorbidities, diagnostic methods, types of revascularization procedures, and antiaggregant therapy used. The goal of this study is to provide insights into the current clinical practice in Latvia and help future treatment decision-makers. To achieve this aim, a retrospective study of 76 patients with SAS who underwent revascularization procedures was performed. After statistical analysis of the data, the study provided insights into the characteristics and management of patients with SAS in Latvia, highlighting the most observed comorbidities in these patients, the preferred diagnostic methods, and the most performed procedures. These findings can inform clinical decision-making and may have implications for the management of patients with subclavian artery stenosis in Latvia.

Keywords: subclavian artery stenosis, revascularization, characteristics of patients, comorbidities, retrospective analysis

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3317 Knowledge Management and Administrative Effectiveness of Non-teaching Staff in Federal Universities in the South-West, Nigeria

Authors: Nathaniel Oladimeji Dixon, Adekemi Dorcas Fadun

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Educational managers have observed a downward trend in the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. This is evident in the low-quality service delivery of administrators and unaccomplished institutional goals and missions of higher education. Scholars have thus indicated the need for the deployment and adoption of a practice that encourages information collection and sharing among stakeholders with a view to improving service delivery and outcomes. This study examined the extent to which knowledge management correlated with the administrative effectiveness of non-teaching staff in federal universities in South-west Nigeria. The study adopted the survey design. Three federal universities (the University of Ibadan, Federal University of Agriculture, Abeokuta, and Obafemi Awolowo University) were purposively selected because administrative ineffectiveness was more pronounced among non-teaching staff in government-owned universities, and these federal universities were long established. The proportional and stratified random sampling was adopted to select 1156 non-teaching staff across the three universities along the three existing layers of the non-teaching staff: secretarial (senior=311; junior=224), non-secretarial (senior=147; junior=241) and technicians (senior=130; junior=103). Knowledge Management Practices Questionnaire with four sub-scales: knowledge creation (α=0.72), knowledge utilization (α=0.76), knowledge sharing (α=0.79) and knowledge transfer (α=0.83); and Administrative Effectiveness Questionnaire with four sub-scales: communication (α=0.84), decision implementation (α=0.75), service delivery (α=0.81) and interpersonal relationship (α=0.78) were used for data collection. Data were analyzed using descriptive statistics, Pearson product-moment correlation and multiple regression at 0.05 level of significance, while qualitative data were content analyzed. About 59.8% of the non-teaching staff exhibited a low level of knowledge management. The indices of administrative effectiveness of non-teaching staff were rated as follows: service delivery (82.0%), communication (78.0%), decision implementation (71.0%) and interpersonal relationship (68.0%). Knowledge management had significant relationships with the indices of administrative effectiveness: service delivery (r=0.82), communication (r=0.81), decision implementation (r=0.80) and interpersonal relationship (r=0.47). Knowledge management had a significant joint prediction on administrative effectiveness (F (4;1151)= 0.79, R=0.86), accounting for 73.0% of its variance. Knowledge sharing (β=0.38), knowledge transfer (β=0.26), knowledge utilization (β=0.22), and knowledge creation (β=0.06) had relatively significant contributions to administrative effectiveness. Lack of team spirit and withdrawal syndrome is the major perceived constraints to knowledge management practices among the non-teaching staff. Knowledge management positively influenced the administrative effectiveness of the non-teaching staff in federal universities in South-west Nigeria. There is a need to ensure that the non-teaching staff imbibe team spirit and embrace teamwork with a view to eliminating their withdrawal syndromes. Besides, knowledge management practices should be deployed into the administrative procedures of the university system.

Keywords: knowledge management, administrative effectiveness of non-teaching staff, federal universities in the south-west of nigeria., knowledge creation, knowledge utilization, effective communication, decision implementation

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3316 Hardware Implementation on Field Programmable Gate Array of Two-Stage Algorithm for Rough Set Reduct Generation

Authors: Tomasz Grzes, Maciej Kopczynski, Jaroslaw Stepaniuk

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The rough sets theory developed by Prof. Z. Pawlak is one of the tools that can be used in the intelligent systems for data analysis and processing. Banking, medicine, image recognition and security are among the possible fields of utilization. In all these fields, the amount of the collected data is increasing quickly, but with the increase of the data, the computation speed becomes the critical factor. Data reduction is one of the solutions to this problem. Removing the redundancy in the rough sets can be achieved with the reduct. A lot of algorithms of generating the reduct were developed, but most of them are only software implementations, therefore have many limitations. Microprocessor uses the fixed word length, consumes a lot of time for either fetching as well as processing of the instruction and data; consequently, the software based implementations are relatively slow. Hardware systems don’t have these limitations and can process the data faster than a software. Reduct is the subset of the decision attributes that provides the discernibility of the objects. For the given decision table there can be more than one reduct. Core is the set of all indispensable condition attributes. None of its elements can be removed without affecting the classification power of all condition attributes. Moreover, every reduct consists of all the attributes from the core. In this paper, the hardware implementation of the two-stage greedy algorithm to find the one reduct is presented. The decision table is used as an input. Output of the algorithm is the superreduct which is the reduct with some additional removable attributes. First stage of the algorithm is calculating the core using the discernibility matrix. Second stage is generating the superreduct by enriching the core with the most common attributes, i.e., attributes that are more frequent in the decision table. Described above algorithm has two disadvantages: i) generating the superreduct instead of reduct, ii) additional first stage may be unnecessary if the core is empty. But for the systems focused on the fast computation of the reduct the first disadvantage is not the key problem. The core calculation can be achieved with a combinational logic block, and thus add respectively little time to the whole process. Algorithm presented in this paper was implemented in Field Programmable Gate Array (FPGA) as a digital device consisting of blocks that process the data in a single step. Calculating the core is done by the comparators connected to the block called 'singleton detector', which detects if the input word contains only single 'one'. Calculating the number of occurrences of the attribute is performed in the combinational block made up of the cascade of the adders. The superreduct generation process is iterative and thus needs the sequential circuit for controlling the calculations. For the research purpose, the algorithm was also implemented in C language and run on a PC. The times of execution of the reduct calculation in a hardware and software were considered. Results show increase in the speed of data processing.

Keywords: data reduction, digital systems design, field programmable gate array (FPGA), reduct, rough set

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3315 Recent Developments in Artificial Intelligence and Information Communications Technology

Authors: Dolapo Adeyemo

Abstract:

Technology can be designed specifically for geriatrics and persons with disabilities or ICT accessibility solutions. Both solutions stand to benefit from advances in Artificial intelligence, which are computer systems that perform tasks that require human intelligence. Tasks such as decision making, visual perception, speech recognition, and even language translation are useful in both situation and will provide significant benefits to people with temporarily or permanent disabilities. This research’s goal is to review innovations focused on the use of artificial intelligence that bridges the accessibility gap in technology from a user-centered perspective. A mixed method approach that utilized a comprehensive review of academic literature on the subject combined with semi structure interviews of users, developers, and technology product owners. The internet of things and artificial intelligence technology is creating new opportunities in the assistive technology space and proving accessibility to existing technology. Device now more adaptable to the needs of the user by learning the behavior of users as they interact with the internet. Accessibility to devices have witnessed significant enhancements that continue to benefit people with disabilities. Examples of other advances identified are prosthetic limbs like robotic arms supported by artificial intelligence, route planning software for the visually impaired, and decision support tools for people with disabilities and even clinicians that provide care.

Keywords: ICT, IOT, accessibility solutions, universal design

Procedia PDF Downloads 72
3314 Quantifying the Effects of Canopy Cover and Cover Crop Species on Water Use Partitioning in Micro-Sprinkler Irrigated Orchards in South Africa

Authors: Zanele Ntshidi, Sebinasi Dzikiti, Dominic Mazvimavi

Abstract:

South Africa is a dry country and yet it is ranked as the 8th largest exporter of fresh apples (Malus Domestica) globally. Prime apple producing regions are in the Eastern and Western Cape Provinces of the country where all the fruit is grown under irrigation. Climate change models predict increasingly drier future conditions in these regions and the frequency and severity of droughts is expected to increase. For the sustainability and growth of the fruit industry it is important to minimize non-beneficial water losses from the orchard floor. The aims of this study were firstly to compare the water use of cover crop species used in South African orchards for which there is currently no information. The second aim was to investigate how orchard water use (evapotranspiration) was partitioned into beneficial (tree transpiration) and non-beneficial (orchard floor evaporation) water uses for micro-sprinkler irrigated orchards with different canopy covers. This information is important in order to explore opportunities to minimize non-beneficial water losses. Six cover crop species (four exotic and two indigenous) were grown in 2 L pots in a greenhouse. Cover crop transpiration was measured using the gravimetric method on clear days. To establish how water use was partitioned in orchards, evapotranspiration (ET) was measured using an open path eddy covariance system, while tree transpiration was measured hourly throughout the season (October to June) on six trees per orchard using the heat ratio sap flow method. On selected clear days, soil evaporation was measured hourly from sunrise to sunset using six micro-lysimeters situated at different wet/dry and sun/shade positions on the orchard floor. Transpiration of cover crops was measured using miniature (2 mm Ø) stem heat balance sap flow gauges. The greenhouse study showed that exotic cover crops had significantly higher (p < 0.01) average transpiration rates (~3.7 L/m2/d) than the indigenous species (~ 2.2 L/m²/d). In young non-bearing orchards, orchard floor evaporative fluxes accounted for more than 60% of orchard ET while this ranged from 10 to 30% in mature orchards with a high canopy cover. While exotic cover crops are preferred by most farmers, this study shows that they use larger quantities of water than indigenous species. This in turn contributes to a larger orchard floor evaporation flux. In young orchards non-beneficial losses can be minimized by adopting drip or short range micro-sprinkler methods that reduce the wetted soil fraction thereby conserving water.

Keywords: evapotranspiration, sap flow, soil evaporation, transpiration

Procedia PDF Downloads 374
3313 Cognition and Communication Disorders Effect on Death Penalty Cases

Authors: Shameka Stanford

Abstract:

This presentation will discuss how cognitive and communication disorders in the areas of executive functioning, receptive and expressive language can impact the problem-solving and decision making of individuals with such impairments. More specifically, this presentation will discuss approaches the legal defense team of capital case lawyers can add to their experience when servicing individuals who have a history of educational decline, special education, and limited intervention and treatment. The objective of the research is to explore and identify the correlations between impaired executive function skills and decision making and competency for individuals facing death penalty charges. To conduct this research, experimental design, randomized sampling, qualitative analysis was employed. This research contributes to the legal and criminal justice system related to how they view, defend, and characterize, and judge individuals with documented cognitive and communication disorders who are eligible for capital case charges. More importantly, this research contributes to the increased ability of death penalty lawyers to successfully defend clients with a history of academic difficulty, special education, and documented disorders that impact educational progress and academic success.

Keywords: cognitive impairments, communication disorders, death penalty, executive function

Procedia PDF Downloads 141
3312 Intelligent Crop Circle: A Blockchain-Driven, IoT-Based, AI-Powered Sustainable Agriculture System

Authors: Mishak Rahul, Naveen Kumar, Bharath Kumar

Abstract:

Conceived as a high-end engine to revolutionise sustainable agri-food production, the intelligent crop circle (ICC) aims to incorporate the Internet of Things (IoT), blockchain technology and artificial intelligence (AI) to bolster resource efficiency and prevent waste, increase the volume of production and bring about sustainable solutions with long-term ecosystem conservation as the guiding principle. The operating principle of the ICC relies on bringing together multidisciplinary bottom-up collaborations between producers, researchers and consumers. Key elements of the framework include IoT-based smart sensors for sensing soil moisture, temperature, humidity, nutrient and air quality, which provide short-interval and timely data; blockchain technology for data storage on a private chain, which maintains data integrity, traceability and transparency; and AI-based predictive analysis, which actively predicts resource utilisation, plant growth and environment. This data and AI insights are built into the ICC platform, which uses the resulting DSS (Decision Support System) outlined as help in decision making, delivered through an easy-touse mobile app or web-based interface. Farmers are assumed to use such a decision-making aid behind the power of the logic informed by the data pool. Building on existing data available in the farm management systems, the ICC platform is easily interoperable with other IoT devices. ICC facilitates connections and information sharing in real-time between users, including farmers, researchers and industrial partners, enabling them to cooperate in farming innovation and knowledge exchange. Moreover, ICC supports sustainable practice in agriculture by integrating gamification techniques to stimulate farm adopters, deploying VR technologies to model and visualise 3D farm environments and farm conditions, framing the field scenarios using VR headsets and Real-Time 3D engines, and leveraging edge technologies to facilitate secure and fast communication and collaboration between users involved. And through allowing blockchain-based marketplaces, ICC offers traceability from farm to fork – that is: from producer to consumer. It empowers informed decision-making through tailor-made recommendations generated by means of AI-driven analysis and technology democratisation, enabling small-scale and resource-limited farmers to get their voice heard. It connects with traditional knowledge, brings together multi-stakeholder interactions as well as establishes a participatory ecosystem to incentivise continuous growth and development towards more sustainable agro-ecological food systems. This integrated approach leverages the power of emerging technologies to provide sustainable solutions for a resilient food system, ensuring sustainable agriculture worldwide.

Keywords: blockchain, internet of things, artificial intelligence, decision support system, virtual reality, gamification, traceability, sustainable agriculture

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3311 Flood Planning Based on Risk Optimization: A Case Study in Phan-Calo River Basin in Vinh Phuc Province, Vietnam

Authors: Nguyen Quang Kim, Nguyen Thu Hien, Nguyen Thien Dung

Abstract:

Flood disasters are increasing worldwide in both frequency and magnitude. Every year in Vietnam, flood causes great damage to people, property, and environmental degradation. The flood risk management policy in Vietnam is currently updated. The planning of flood mitigation strategies is reviewed to make a decision how to reach sustainable flood risk reduction. This paper discusses the basic approach where the measures of flood protection are chosen based on minimizing the present value of expected monetary expenses, total residual risk and costs of flood control measures. This approach will be proposed and demonstrated in a case study for flood risk management in Vinh Phuc province of Vietnam. Research also proposed the framework to find a solution of optimal protection level and optimal measures of the flood. It provides an explicit economic basis for flood risk management plans and interactive effects of options for flood damage reduction. The results of the case study are demonstrated and discussed which would provide the processing of actions helped decision makers to choose flood risk reduction investment options.

Keywords: drainage plan, flood planning, flood risk, residual risk, risk optimization

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3310 Seismic Hazard Analysis for a Multi Layer Fault System: Antalya (SW Turkey) Example

Authors: Nihat Dipova, Bulent Cangir

Abstract:

This article presents the results of probabilistic seismic hazard analysis (PSHA) for Antalya (SW Turkey). South west of Turkey is characterized by large earthquakes resulting from the continental collision between the African, Arabian and Eurasian plates and crustal faults. Earthquakes around the study area are grouped into two; crustal earthquakes (D=0-50 km) and subduction zone earthquakes (50-140 km). Maximum observed magnitude of subduction earthquakes is Mw=6.0. Maximum magnitude of crustal earthquakes is Mw=6.6. Sources for crustal earthquakes are faults which are related with Isparta Angle and Cyprus Arc tectonic structures. A new earthquake catalogue for Antalya, with unified moment magnitude scale has been prepared and seismicity of the area around Antalya city has been evaluated by defining ‘a’ and ‘b’ parameters of the Gutenberg-Richter recurrence relationship. The Standard Cornell-McGuire method has been used for hazard computation utilizing CRISIS2007 software. Attenuation relationships proposed by Chiou and Youngs (2008) has been used for 0-50 km earthquakes and Youngs et. al (1997) for deep subduction earthquakes. Finally, Seismic hazard map for peak horizontal acceleration on a uniform site condition of firm rock (average shear wave velocity of about 1130 m/s) at a hazard level of 10% probability of exceedance in 50 years has been prepared.

Keywords: Antalya, peak ground acceleration, seismic hazard assessment, subduction

Procedia PDF Downloads 359
3309 Breast Cancer Risk is Predicted Using Fuzzy Logic in MATLAB Environment

Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

Abstract:

Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

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3308 Wireless Sensor Network for Forest Fire Detection and Localization

Authors: Tarek Dandashi

Abstract:

WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

Procedia PDF Downloads 247
3307 Autonomic Sonar Sensor Fault Manager for Mobile Robots

Authors: Martin Doran, Roy Sterritt, George Wilkie

Abstract:

NASA, ESA, and NSSC space agencies have plans to put planetary rovers on Mars in 2020. For these future planetary rovers to succeed, they will heavily depend on sensors to detect obstacles. This will also become of vital importance in the future, if rovers become less dependent on commands received from earth-based control and more dependent on self-configuration and self-decision making. These planetary rovers will face harsh environments and the possibility of hardware failure is high, as seen in missions from the past. In this paper, we focus on using Autonomic principles where self-healing, self-optimization, and self-adaption are explored using the MAPE-K model and expanding this model to encapsulate the attributes such as Awareness, Analysis, and Adjustment (AAA-3). In the experimentation, a Pioneer P3-DX research robot is used to simulate a planetary rover. The sonar sensors on the P3-DX robot are used to simulate the sensors on a planetary rover (even though in reality, sonar sensors cannot operate in a vacuum). Experiments using the P3-DX robot focus on how our software system can be adapted with the loss of sonar sensor functionality. The autonomic manager system is responsible for the decision making on how to make use of remaining ‘enabled’ sonars sensors to compensate for those sonar sensors that are ‘disabled’. The key to this research is that the robot can still detect objects even with reduced sonar sensor capability.

Keywords: autonomic, self-adaption, self-healing, self-optimization

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3306 Probing Environmental Sustainability via Brownfield Remediation: A Framework to Manage Brownfields in Ethiopia Lesson to Africa

Authors: Mikiale Gebreslase Gebremariam, Chai Huaqi, Tesfay Gebretsdkan Gebremichael, Dawit Nega Bekele

Abstract:

In recent years, brownfield redevelopment projects (BRPs) have contributed to the overarching paradigm of the United Nations 2030 agendas. In the present circumstance, most developed nations adopted BRPs, an efficacious urban policy tool. However, in developing and some advanced countries, BRPs are lacking due to limitations of awareness, policy tools, and financial capability for cleaning up brownfield sites. For example, the growth and development of Ethiopian cities were achieved at the cost of poor urban planning, including no community consultations and excessive urbanization for future growth. The demand for land resources is more and more urgent as the result of an intermigration to major cities and towns for socio-economic reasons and population growth. In the past, the development mode of spreading major cities has made horizontal urbanizations stretching outwards. Expansion in search of more land resources, while the outer cities are growing, the inner cities are polluted by environmental pollution. It is noteworthy that the rapid development of cities has not brought about an increase in people's happiness index. Thus, the proposed management framework for managing brownfields in Ethiopia as a lesson to the developing nation facing similar challenges and growth will add immense value in solving the problems and give insights into brownfield land utilization. Under the umbrella of the grey incidence decision-making model and with the consideration of multiple stakeholders and tight environmental and economic constraints, the proposed management framework integrates different criteria from economic, social, environmental, technical, and risk aspects into the grey incidence decision-making model and gives useful guidance to manage brownfields in Ethiopia. Furthermore, it will contribute to the future development of the social economy and the missions of the 2030 UN sustainable development goals.

Keywords: Brownfields, environmental sustainability, Ethiopia, grey-incidence decision-making, sustainable urban development

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3305 Integrating of Multi-Criteria Decision Making and Spatial Data Warehouse in Geographic Information System

Authors: Zohra Mekranfar, Ahmed Saidi, Abdellah Mebrek

Abstract:

This work aims to develop multi-criteria decision making (MCDM) and spatial data warehouse (SDW) methods, which will be integrated into a GIS according to a ‘GIS dominant’ approach. The GIS operating tools will be operational to operate the SDW. The MCDM methods can provide many solutions to a set of problems with various and multiple criteria. When the problem is so complex, integrating spatial dimension, it makes sense to combine the MCDM process with other approaches like data mining, ascending analyses, we present in this paper an experiment showing a geo-decisional methodology of SWD construction, On-line analytical processing (OLAP) technology which combines both basic multidimensional analysis and the concepts of data mining provides powerful tools to highlight inductions and information not obvious by traditional tools. However, these OLAP tools become more complex in the presence of the spatial dimension. The integration of OLAP with a GIS is the future geographic and spatial information solution. GIS offers advanced functions for the acquisition, storage, analysis, and display of geographic information. However, their effectiveness for complex spatial analysis is questionable due to their determinism and their decisional rigor. A prerequisite for the implementation of any analysis or exploration of spatial data requires the construction and structuring of a spatial data warehouse (SDW). This SDW must be easily usable by the GIS and by the tools offered by an OLAP system.

Keywords: data warehouse, GIS, MCDM, SOLAP

Procedia PDF Downloads 156