Search results for: expert premiums

Authors: Olivia Rybak-Karkosz

Abstract:

This paper's purpose was to present a case study on a questioned Claude Monet's signature forensic handwriting analysis. It is an example taken from the author’s experience as a court handwriting expert. A comparative study was conducted to determine whether the signature resembles similarities (and if so, to what measure) with the features representing the writing patterns and their natural variability typical for Claude Monet. It was conducted to check whether all writing features are within the writer's normal range of variation. The paper emphasizes the difficulties and challenges encountered by the forensic handwriting expert while analysing the questioned signature.

Keywords: artist’s signatures, authenticity of an artwork, forensic handwriting analysis, graphic-comparative method

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Authors: E. Rama Devi Jothilingam

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Diabetes mellitus is now one of the most common non communicable diseases globally. India leads the world with largest number of diabetic subjects earning the title "diabetes capital of the world". In order to reduce the mortality rate, a fuzzy expert system is designed to predict the severity of cardiac and renal problems of diabetic patients using fuzzy logic. Since uncertainty is inherent in medicine, fuzzy logic is used in this research work to remove the inherent fuzziness of linguistic concepts and uncertain status in diabetes mellitus which is the prime cause for the cardiac arrest and renal failure. In this work, the controllable risk factors "blood sugar, insulin, ketones, lipids, obesity, blood pressure and protein/creatinine ratio" are considered as input parameters and the "the stages of cardiac" (SOC)" and the stages of renal" (SORD) are considered as the output parameters. The triangular membership functions are used to model the input and output parameters. The rule base is constructed for the proposed expert system based on the knowledge from the medical experts. Mamdani inference engine is used to infer the information based on the rule base to take major decision in diagnosis. Mean of maximum is used to get a non fuzzy control action that best represent possibility distribution of an inferred fuzzy control action. The proposed system also classifies the patients with high risk and low risk using fuzzy c means clustering techniques so that the patients with high risk are treated immediately. The system is validated with Matlab and is used as a tracking system with accuracy and robustness.

Keywords: Diabetes mellitus, fuzzy expert system, Mamdani, MATLAB

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Authors: Ashfaq M. Naikwadi

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Decided cases of medical negligence, mostly are not settled in the lower courts. Majority of them reach up to the apex courts. This is mostly due to different interpretations of the term medical negligence. After studying various cases of medical negligence it is found that in most of the cases the doctors/hospitals are not held liable. There are different interpretations of law concerning medical services. Globally the principles deciding medical negligence are same, viz. Legal duty of care - breach of that duty - direct causation resulting in damages. Since ordinary negligence is not punishable by law, doctors/hospitals have defenses to save themselves from liability. Complaints of negligence come to the courts whose judges mostly are not oriented with medical services or health sciences. Matters of medical negligence are decided on the basic principles of reasonableness and prudence or by relying on the expert’s opinion. Deciding reasonableness or prudence is a complex issue in case of medical services. Again expert opinion is also questionable as an expert in case of medical negligence is appointed from the same field and same faculty. There is a chance of favoritism to the doctor/hospital. The concept of vicarious liability is not widely applied to in many of the medical negligence cases. Established cases used as precedents were studied to understand the basic principles in deciding medical negligence. This paper evaluates the present criteria in interpreting medical negligence and concludes with suggesting reforms required to be made in deciding matters of medical negligence under the consumer laws.

Keywords: consumer, doctors, laws, medical negligence

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Authors: Sri Rejeki Dwi Astuti, Suyanta

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The demanding of the asessment in learning process was impact by policy changes. Nowadays, the assessment not only emphasizes knowledge, but also skills and attitude. However, in reality there are many obstacles in measuring them. This paper aimed to describe how to develop instrument of integrated assessment as alternative assessment to measure critical thinking skills and science process skills in electrolyte solution and to describe instrument’s characteristic such as logic validity and construct validity. This instrument development used test development model by McIntire. Development process data was acquired based on development test step and was analyzed by qualitative analysis. Initial product was observed by three peer reviewer and six expert judgment (two subject matter expert, two evaluation expert and two chemistry teacher) to acquire logic validity test. Logic validity test was analyzed using Aiken’s formula. The estimation of construct validity was analyzed by exploratory factor analysis. Result showed that integrated assessment instrument has 0,90 of Aiken’s Value and all item in integrated assessment asserted valid according to construct validity.

Keywords: construct validity, critical thinking skills, integrated assessment instrument, logic validity, science process skills

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Authors: Rachel Goh, Alexander McNab, Brent Alsop, David O'Hare

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In a busy airport, the decision whether to take passengers aside and search their luggage for dangerous items can have important consequences. If an officer fails to search and stop a bag containing a dangerous object, a life-threatening incident might occur. But stopping a bag unnecessarily means that the officer might lose time searching the bag and face an angry passenger. Passengers’ bags, however, are often cluttered with personal belongings of varying shapes and sizes. It can be difficult to determine what is dangerous or not, especially if the decisions must be made quickly in cases of busy flight schedules. Additionally, the decision to search bags is often made with input from the surrounding officers on duty. This scenario raises several questions: 1) Past findings suggest that humans are more reliant on an automated aid when under time pressure in a visual search task, but does this translate to human-human reliance? 2) Are humans more likely to agree with another person if the person is assumed to be an expert or a novice in these ambiguous situations? In the present study, forty-one participants performed a simulated luggage-screening task. They were partnered with an advisor of two different statuses (expert vs. novice), but of equal accuracy (90% correct). Participants made two choices each trial: their first choice with no advisor input, and their second choice after advisor input. The second choice was made within either 2 seconds or 8 seconds; failure to do so resulted in a long time-out period. Under the 2-second time pressure, participants were more likely to disagree with their own first choice and agree with the expert advisor, regardless of whether the expert was right or wrong, but especially when the expert suggested that the bag was safe. The findings indicate a tendency for people to assume less responsibility for their decisions and defer to their partner, especially when a quick decision is required. This over-reliance on others’ opinions might have negative consequences in real life, particularly when relying on fallible human judgments. More awareness is needed regarding how a stressful environment may influence reliance on other’s opinions, and how better techniques are needed to make the best decisions under high stress and time pressure.

Keywords: advisors, decision-making, time pressure, trust

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Authors: C. U. Om Kumar, S. Kishore, A. Geetha

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An Operating system (OS) is software that manages computer hardware and software resources by providing services to computer programs. One of the important user expectations of the operating system is to provide the practice of defending information from unauthorized access, disclosure, modification, inspection, recording or destruction. Operating system is always vulnerable to the attacks of malwares such as computer virus, worm, Trojan horse, backdoors, ransomware, spyware, adware, scareware and more. And so the anti-virus software were created for ensuring security against the prominent computer viruses by applying a dictionary based approach. The anti-virus programs are not always guaranteed to provide security against the new viruses proliferating every day. To clarify this issue and to secure the computer system, our proposed expert system concentrates on authorizing the processes as wanted and unwanted by the administrator for execution. The Expert system maintains a database which consists of hash code of the processes which are to be allowed. These hash codes are generated using MD5 message-digest algorithm which is a widely used cryptographic hash function. The administrator approves the wanted processes that are to be executed in the client in a Local Area Network by implementing Client-Server architecture and only the processes that match with the processes in the database table will be executed by which many malicious processes are restricted from infecting the operating system. The add-on advantage of this proposed Expert system is that it limits CPU usage and minimizes resource utilization. Thus data and information security is ensured by our system along with increased performance of the operating system.

Keywords: virus, worm, Trojan horse, back doors, Ransomware, Spyware, Adware, Scareware, sticky software, process table, MD5, CPU usage and resource utilization

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining

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Authors: Masoumeh Mofarrah, Amir NahanMoghadam

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Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise, and improve EOR methods and their application. Recently, Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic, and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization infeasible and effective way.

Keywords: artificial intelligence, EOR, neural networks, expert systems

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Authors: Saleh Hayat

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Efficiency, productivity and sustainability are important factors for structure and the application of processes in green building. Various previous studies have addressed efficiency, productivity and sustainability separately. This research study aims to investigate the implications of these three factors taking together. Frequency analysis and the ranking techniques are carried out to explore the connection between these factors. The interconnection matrix has been developed and functional grouping is made based upon data from expert opinion and field professionals. The existence of a relationship, the type of relationship and the scaled impact have been drawn. Additionally, a system diagram has been developed to show the variable correlation. The results of expert opinion show that efficiency, productivity and sustainability have a stronger impact on green buildings.

Keywords: efficiency, green building, productivity, sustainability

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Authors: Nicole Bandow, Peter Emmermacher, Oliver Wienert, Steffen Masik, Kerstin Witte

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Karate-kumite is a fast sport where a good perception and anticipation of movements is needed in order to respond appropriately. Perception and anticipation are therefore essential for an efficient and precise movement control and a limiting factor in karate kumite. Previous studies only used 2D video technologies combined with the occlusion technique to study anticipation in sports. These studies showed limitations in the usage of 2D video footage in regards to realism and the presentation of depth information. To overcome these issues a virtual 3D environment was developed to create a similar to real life environment. The aim of this study was to compare the differences in responses of intermediate and expert karate athletes towards temporally and spatially occluded virtual karate attacks from two attackers. Five male expert and five intermediate karate athletes responded physically to nine (3 temporal combined with 3 spatial) occluded attacks of the Gyaku-Zuki of each attacker in the 3D virtual environment. The responses were evaluated in regards to correct point of time and appropriate response technique. Significant differences between the expertises’ responses for the attackers were found. Experts respond more often correct to early information of attacks than novices.

Keywords: anticipation, karate, occlusion, virtual reality

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Authors: Dennis Otieno, Lilian Kirimi Nicholas Odhiambo, Hillary Bii

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Kenya is considered to be a middle level income country and usuaaly does not meet household food security needs especially in North and South eastern parts. Approximately half of the population is living under the poverty line (www, CIA 1, 2012). Agriculture is the largest sector in the country, employing 80% of the population. These are thereby directly dependent on the sufficiency of outputs received. This makes efficient, easy-accessible and cheap agricultural practices an important matter in order to improve food security. Maize is the prime staple food commodity in Kenya and represents a substantial share of people’s nutritional intake. This study is the result of questionnaire based interviews, Key informant and focus group discussion involving 220 small scale maize farmers Kenyan. The study was located to two separated areas; Lower Kuja, Bunyala, Nandi, Lower Nzoia, Perkerra, Mwea Bura, Hola and Galana Kulalu in Kenya. The questionnaire captured the farmers’ use and perceived importance of the use irrigation services and irrigated maize production. Viability was evaluated using the four indices which were all positive with NPV giving positive cash flows in less than 21 years at most for one season output. The mean willingness to pay was found to be KES 3082 and willingness to pay increased with increase in irrigation premiums. The economic value of water was found to be greater than the willingness to pay implying that irrigated maize production is sustainable. Farmers stated that viability was influenced by high output levels, good produce quality, crop of choice, availability of sufficient water and enforcement the last two factors had a positive influence while the other had negative effect on the viability of irrigated maize. A regression was made over the correlation between the willingness to pay for irrigated maize production using scheme and plot level factors. Farmers that already use other inputs such as animal manure, hired labor and chemical fertilizer should also have a demand for improved seeds according to Liebig's law of minimum and expansion path theory. The regression showed that premiums, and high yields have a positive effect on willingness to pay while produce quality, efficient fertilizer use, and crop season have a negative effect.

Keywords: maize, food security, profits, sustainability, willingness to pay

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Authors: Masoumeh Mofarrah, Amir NahanMoghadam

Abstract:

Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise and improve EOR methods and their application. Recently Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization in feasible and effective way.

Keywords: artificial intelligence, EOR, neural networks, expert systems

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Authors: Lina Feng

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The study aimed at establishing quality evaluation indicators of an early education center for 0~3 years old, and defining the weight system of it. Expert questionnaire and Fuzzy Delphi method were applied. Firstly, in order to ensure the indicators in accordance with the practice of early education, 16 experts were invited as respondents to a preliminary Expert Questionnaire about Quality Evaluation Indicators of Early Education Center for 0~3 Years Old. The indicators were based on relevant studies on quality evaluation indicators of early education centers in China and abroad. Secondly, 20 scholars, kindergarten principals, and educational administrators were invited to form a fuzzy Delphi expert team. The experts’ opinions on the importance of indicators were calculated through triangle fuzzy numbers in order to select appropriate indicators and calculate indicator weights. This procedure resulted in the final Quality Evaluation Indicators of Early education Center for 0~3 Years Old. The Indicators contained three major levels, including 6 first-level indicators, 30 second-level indicators, and 147 third-level indicators. The 6 first-level indicators were health and safety; educational and cultivating activities; development of babies; conditions of the center; management of the center; and collaboration between family and the community. The indicators established by this study could provide suggestions for the high-quality environment for promoting the development of early year children.

Keywords: early education center for 0~3 years old, educational management, fuzzy delphi method, quality evaluation indicator

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Authors: Sinead Impey, Gaye Stephens, Declan O’Sullivan

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Mitigating organisational knowledge loss presents challenges for knowledge managers. Expert knowledge is embodied in people and captured in ‘routines, processes, practices and norms’ as well as in the paper system. These knowledge stores have limitations in so far as they make knowledge diffusion beyond geography or over time difficult. However, technology could present a potential solution by facilitating the capture and management of expert knowledge in a codified and sharable format. Before it can be digitised, however, the knowledge of healthcare experts must be captured. Methods: As a first step in a larger project on this topic, a scoping review was conducted to identify how expert healthcare knowledge is captured digitally. The aim of the review was to identify current healthcare knowledge capture practices, identify gaps in the literature, and justify future research. The review followed a scoping review framework. From an initial 3,430 papers retrieved, 22 were deemed relevant and included in the review. Findings: Two broad approaches –direct and indirect- with themes and subthemes emerged. ‘Direct’ describes a process whereby knowledge is taken directly from subject experts. The themes identified were: ‘Researcher mediated capture’ and ‘Digital mediated capture’. The latter was further distilled into two sub-themes: ‘Captured in specified purpose platforms (SPP)’ and ‘Captured in a virtual community of practice (vCoP)’. ‘Indirect’ processes rely on extracting new knowledge using artificial intelligence techniques from previously captured data. Using this approach, the theme ‘Generated using artificial intelligence methods’ was identified. Although presented as distinct themes, some papers retrieved discuss combining more than one approach to capture knowledge. While no approach emerged as superior, two points arose from the literature. Firstly, human input was evident across themes, even with indirect approaches. Secondly, a range of challenges common among approaches was highlighted. These were (i) ‘Capturing an expert’s knowledge’- Difficulties surrounding capturing an expert’s knowledge related to identifying the ‘expert’ say from the very experienced and how to capture their tacit or difficult to articulate knowledge. (ii) ‘Confirming quality of knowledge’- Once captured, challenges noted surrounded how to validate knowledge captured and, therefore, quality. (iii) ‘Continual knowledge capture’- Once knowledge is captured, validated, and used in a system; however, the process is not complete. Healthcare is a knowledge-rich environment with new evidence emerging frequently. As such, knowledge needs to be reviewed, updated, or removed (redundancy) as appropriate. Although some methods were proposed to address this, such as plausible reasoning or case-based reasoning, conclusions could not be drawn from the papers retrieved. It was, therefore, highlighted as an area for future research. Conclusion: The results described two broad approaches – direct and indirect. Three themes were identified: ‘Researcher mediated capture (Direct)’; ‘Digital mediated capture (Direct)’ and ‘Generated using artificial intelligence methods (Indirect)’. While no single approach was deemed superior, common challenges noted among approaches were: ‘capturing an expert’s knowledge’, ‘confirming quality of knowledge’, and ‘continual knowledge capture’. However, continual knowledge capture was not fully explored in the papers retrieved and was highlighted as an important area for future research. Acknowledgments: This research is partially funded by the ADAPT Centre under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund.

Keywords: expert knowledge, healthcare, knowledge capture and knowledge management

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Authors: Abubakar Sa’adatu Mohammed

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This paper reports on a study of problem solving differences between expert and novice Problem solvers for effective physics teaching. Significant differences were found both at the conceptual level and at the level of critical thinking, creative thinking and reasoning. It is suggested for a successful solution of a problem, conceptual knowledge alone may not be sufficient. There is the need of the knowledge of how the conceptual knowledge should be applied (problem solving skills). It is hoped that this research might contribute to efforts of exploring ways for students to acquire a powerful conceptual toolkit based on experts like problem solvers approach for effective teaching delivery.

Keywords: conceptual knowledge, procedural knowledge, critical thinking, creative thinking, reasoning ability

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Authors: Luis Javier Serrano Tamayo

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This research on technology makes a first approach to the selection of an amphibious landing ship with strategic capabilities, through the implementation of a multi-criteria model using Analytical Hierarchical Process (AHP), in which a significant group of alternatives of latest technology has been considered. The variables were grouped at different levels to match design and performance characteristics, which affect the lifecycle as well as the acquisition, maintenance and operational costs. The model yielded an overall measure of effectiveness and an overall measure of cost of each kind of ship that was compared each other inside the model and showed in a Pareto chart. The modeling was developed using the Expert Choice software, based on AHP method.

Keywords: analytic hierarchy process, multi-criteria decision-making, Pareto analysis, Colombian Marine Corps, projection operations, expert choice, amphibious landing ship

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Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

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Recently, an increasing number of researchers have been focusing on working out realistic solutions to sustainability problems. As sustainability issues gain higher importance for organisations, the management of such decisions becomes critical. Knowledge representation is a fundamental issue of complex knowledge based systems. Many types of sustainability problems would benefit from models based on experts’ knowledge. Cognitive maps have been used for analyzing and aiding decision making. A cognitive map can be made of almost any system or problem. A fuzzy cognitive map (FCM) can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behavior of any system. Integrated waste management systems (IWMS) are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall decision process of the system. The goal of the present paper is to construct an efficient IWMS which considers various factors. The authors’ intention is to propose an expert based system design approach for implementing expert decision support in the area of IWMSs and introduces an appropriate methodology for the development and analysis of group FCM. A framework for such a methodology consisting of the development and application phases is presented.

Keywords: factors, fuzzy cognitive map, group decision, integrated waste management system

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Authors: Marianna Nigra, Maicol Negrello

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Efficiency, productivity, and sustainability are important factors for structure and the application of processes in green building. Various previous studies have addressed efficiency, productivity, and sustainability separately. This research study aims to investigate the implications of these three factors taking together. Frequency analysis and the ranking techniques are carried out to explore the connection between these factors. The interconnection matrix has been developed and functional grouping is made based upon data from expert opinion and field professionals. The existence of a relationship, the type of relationship and the scaled impact have been drawn. Additionally, a system diagram has been developed to show the variable correlation. The results of expert opinion show that efficiency, productivity, and sustainability have a stronger impact on green buildings.

Keywords: green roof regulation, architecture, climate adaptation, resilience, innovation management

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

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This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

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Authors: Zina Benouaret, Djamil Aissani

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In this work, we introduce the qualitative and quantitative concept of the strong stability method in the risk process modeling two lines of business of the same insurance company or an insurance and re-insurance companies that divide between them both claims and premiums with a certain proportion. The approach proposed is based on the identification of the ruin probability associate to the model considered, with a stationary distribution of a Markov random process called a reversed process. Our objective, after clarifying the condition and the perturbation domain of parameters, is to obtain the stability inequality of the ruin probability which is applied to estimate the approximation error of a model with disturbance parameters by the considered model. In the stability bound obtained, all constants are explicitly written.

Keywords: Markov chain, risk models, ruin probabilities, strong stability analysis

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for the classification of an unstructured format description for identification of file formats. The main contribution of this work is the employment of data mining techniques to support file format selection with just the unstructured text description that comprises the most important format features for a particular organisation. Subsequently, the file format indentification method employs file format classifier and associated configurations to support digital preservation experts with an estimation of required file format. Our goal is to make use of a format specification knowledge base aggregated from a different Web sources in order to select file format for a particular institution. Using the naive Bayes method, the decision support system recommends to an expert, the file format for his institution. The proposed methods facilitate the selection of file format and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and specifications of file formats. To facilitate decision-making, the aggregated information about the file formats is presented as a file format vocabulary that comprises most common terms that are characteristic for all researched formats. The goal is to suggest a particular file format based on this vocabulary for analysis by an expert. The sample file format calculation and the calculation results including probabilities are presented in the evaluation section.

Keywords: data mining, digital libraries, digital preservation, file format

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Authors: Belén Vinaixa Kinnear, Arturo Hidalgo López, Bernardo Elembo Wilasi, Pablo Fernández Pérez, Cecilia Hernández Fuentealba

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The expanded use of risk assessment in legislative and corporate decision-making has increased the role of expert judgement in giving data for security-related decision-making. Expert judgements are required in most steps of risk assessment: danger recognizable proof, hazard estimation, risk evaluation, and examination of choices. This paper presents a fault tree analysis (FTA), which implies a probabilistic failure analysis applied to leakage of oil in a subsea production system. In standard FTA, the failure probabilities of items of a framework are treated as exact values while evaluating the failure probability of the top event. There is continuously insufficiency of data for calculating the failure estimation of components within the drilling industry. Therefore, fuzzy hypothesis can be used as a solution to solve the issue. The aim of this paper is to examine the leaks from the Zafiro West subsea oil facility by using fuzzy fault tree analysis (FFTA). As a result, the research has given theoretical and practical contributions to maritime safety and environmental protection. It has been also an effective strategy used traditionally in identifying hazards in nuclear installations and power industries.

Keywords: expert judgment, probability assessment, fault tree analysis, risk analysis, oil pipelines, subsea production system, drilling, quantitative risk analysis, leakage failure, top event, off-shore industry

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Authors: Mohit Tyagi, Pradeep Kumar

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The objective of this research work is to identify and analyze the significant corporate social responsibility (CSR) practices with an aim to improve the supply chain performance of automobile industry located at National Capital Region (NCR) of India. To achieve the objective, 6 CSR practices have been considered and analyzed using expert’s preference rating (EPR) approach. The considered CSR practices are namely, Top management and employee awareness about CSR (P₁), Employee involvement in social and environmental problems (P₂), Protection of human rights (P₃), Waste reduction, energy saving and water conservation (P₄), Proper visibility of CSR guidelines (P₅) and Broad perception towards CSR initiatives (P₆). The outcomes of this research may help mangers in decision making processes and framing polices for SCP implementation under CSR context.

Keywords: supply chain performance, corporate social responsibility, CSR practices, expert’s preference rating approach

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Authors: Zaid Almahmoud, Rana Mahmoud

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To mitigate the environmental impacts of throwing away plastic waste, there has been a recent interest in manufacturing and producing biodegradable plastics. Here, we study a new class of biodegradable plastics which are mixed with external natural additives, including catalytic additives that lead to a successful degradation of the resulting material. To recommend the best alternative among multiple materials, we propose a multi-objective AI model that evaluates the material against multiple objectives given the material properties. As a proof of concept, the AI model was implemented in an expert system and evaluated using multiple materials. Our findings showed that Polyethylene Terephalate is potentially the best biodegradable plastic substitute based on its material properties. Therefore, it is recommended that governments shift the attention to the use of Polyethylene Terephalate in the manufacturing of bottles to gain a great environmental and sustainable benefits.

Keywords: plastic bottles, expert systems, multi-objective model, biodegradable substitutes

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Authors: T. Penkova, A. Korobko, V. Nicheporchuk, L. Nozhenkova, A. Metus

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This paper presents an approach of on-line control of the state of technosphere and environment objects based on the integration of Data Warehouse, OLAP and Expert systems technologies. It looks at the structure and content of data warehouse that provides consolidation and storage of monitoring data. There is a description of OLAP-models that provide a multidimensional analysis of monitoring data and dynamic analysis of principal parameters of controlled objects. The authors suggest some criteria of emergency risk assessment using expert knowledge about danger levels. It is demonstrated now some of the proposed solutions could be adopted in territorial decision making support systems. Operational control allows authorities to detect threat, prevent natural and anthropogenic emergencies and ensure a comprehensive safety of territory.

Keywords: decision making support systems, emergency risk assessment, natural and anthropogenic safety, on-line control, territory

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Authors: Sudhir K. Gupta

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Introduction: When a forensic doctor determines that a suspicious death is a suicide, homicide, or accident, the decision virtually becomes incontestable by the investigating police officer, and it becomes an issue whether the medical opinion was created with necessary checks and balances on the other probabilities of the case. It is suggested that the opinion of Forensic Medical experts is conventional, mutable, and shifting from one expert to another. The determination of suicide, accident, or homicide is mandatorily required, which is the Gold Standard for conducting death investigations. Forensic investigations serve many audiences, but the court is by far the most critical. The likely questions on direct and cross-examination determine how forensic doctors gather and handle evidence and what conclusions they reach. Methodology: The author interacted with the investigative authority, and a crime scene visit was also done along with the perusal of the Postmortem report, subsequent opinion, and crime scene photographs and statements of the witness and accused. Further analysis of all relevant scientific documents and opinions of other forensic doctors, forensic scientists, and ballistic experts involved in these cases was done to arrive at an opinion with scientific justification. Findings: The opinions arrived at by the author and how they helped the judiciary in delivering justice in these cases have been discussed in this article. This can help the readers to understand the process involved in formulating a credible forensic medical expert opinion for investigators and the judiciary. Conclusion: A criminal case might be won or lost over doubt cast on the chain of custody. Medically trained forensic doctors, therefore, learn to practice their profession in legally appropriate ways, and opinions must be based on medical justifications with credible references.

Keywords: forensic doctor, professional credibility, investigation, expert opinion

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

Abstract:

This paper presents an approach for the easy creation of an institutional risk profile for endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support risk factors set up with just the most important values that are important for a particular organisation. Subsequently, the risk profile employs fuzzy models and associated configurations for the file format metadata aggregator to support digital preservation experts with a semi-automatic estimation of endangerment level for file formats. Our goal is to make use of a domain expert knowledge base aggregated from a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation and analysis of risk factors for a requried dimension. The proposed methods improve the visibility of risk factor information and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and automatically aggregated file format metadata from linked open data sources. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: digital information management, file format, endangerment analysis, fuzzy models

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Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

Abstract:

For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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Authors: Jonida Hasanaj

Abstract:

Abstract: Four years after the pandemic, numerous studies discuss the long-term effects of COVID-19 on patients, with chronic fatigue syndrome being a prominent concern. Understanding the mechanisms behind this syndrome is crucial for developing prevention, treatment, and rehabilitation strategies. The appropriateness of physiotherapeutic treatment in covid 19 and post-COVID-19 patients has remained uncertain due to inconsistent diagnostic criteria, highlighting the need for further research. This paper intends to offer guidelines and specific suggestions for hospital-based physical therapists managing COVID-19 hospitalized patients at ‘’Expert Physiotherapy’ and ’American Hospital’ in Albania using a national approach in accordance with worldwide initiatives. Several studies indicate that chronic tiredness syndrome and high intracranial pressure could result from failure of the post-Covid-19 lymphatic system. Enabling the patient to intensify their physical activity and enhance their ability to move, exercise, and even resume a regular life cycle is the aim of physiotherapy treatment.

Keywords: mobility, physiotherapy, post-covid 19, rehabilitation, results

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Authors: Mohammadreza Bakhtiari, Mehrdad Maghsoudi, Hamidreza Bakhtiari

Abstract:

This study investigates consumer behavior in the notebook computer market by integrating social media sentiment analysis with expert evaluations. The rapid evolution of the notebook industry has intensified competition among manufacturers, necessitating a deeper understanding of consumer priorities. Social media platforms, particularly Twitter, have become valuable sources for capturing real-time user feedback. In this research, sentiment analysis was performed on Twitter data gathered in the last two years, focusing on seven major notebook brands. The PyABSA framework was utilized to extract sentiments associated with various notebook components, including performance, design, battery life, and price. Expert evaluations, conducted using fuzzy logic, were incorporated to assess the impact of these sentiments on purchase behavior. To provide actionable insights, the TOPSIS method was employed to prioritize notebook features based on a combination of consumer sentiments and expert opinions. The findings consistently highlight price, display quality, and core performance components, such as RAM and CPU, as top priorities across brands. However, lower-priority features, such as webcams and cooling fans, present opportunities for manufacturers to innovate and differentiate their products. The analysis also reveals subtle but significant brand-specific variations, offering targeted insights for marketing and product development strategies. For example, Lenovo's strong performance in display quality points to a competitive edge, while Microsoft's lower ranking in battery life indicates a potential area for R&D investment. This hybrid methodology demonstrates the value of combining big data analytics with expert evaluations, offering a comprehensive framework for understanding consumer behavior in the notebook market. The study emphasizes the importance of aligning product development and marketing strategies with evolving consumer preferences, ensuring competitiveness in a dynamic market. It also underscores the potential for innovation in seemingly less important features, providing companies with opportunities to create unique selling points. By bridging the gap between consumer expectations and product offerings, this research equips manufacturers with the tools needed to remain agile in responding to market trends and enhancing customer satisfaction.

Keywords: consumer behavior, customer preferences, laptop industry, notebook computers, social media analytics, TOPSIS

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