Search results for: decision rules

Authors: Mohammad Besharatloo

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Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context.

Keywords: intrusion detection system, differential evolution, firefly algorithm, support vector machine, decision tree

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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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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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Authors: Thea Freese, Michael Gille, Andrew Hursthouse, John Struthers

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Ship operators on the North and Baltic Sea have been experiencing increased political interest in marine environmental protection and cleaner vessel operations. Stricter legislation on SO2 and NOx emissions, ballast water management and other measures of protection are currently being phased in or will come into force in the coming years. These measures benefit the health of the marine environment, while increasing company’s operational costs. In times of excess shipping capacity and linked consolidation in the industry non-compliance with environmental rules is one way companies might hope to stay competitive with both intra- and inter-modal trade. Around 5-15% of industry participants are believed to neglect laws on vessel-source pollution willingly or unwillingly. Exploratory in-depth interviews conducted with 12 experts from various stakeholder groups informed the researchers about variables influencing compliance levels, including awareness and apprehension, willingness to comply, ability to comply and effectiveness of controls. Semi-structured expert interviews were evaluated using qualitative content analysis. A model of determinants of compliance was developed and is presented here. While most vessel operators endeavour to achieve full compliance with environmental rules, a lack of availability of technical solutions, expediency of implementation and operation and economic feasibility might prove a hindrance. Ineffective control systems on the other hand foster willing non-compliance. With respect to motivations, lacking time, lacking financials and the absence of commercial advantages decrease compliance levels. These and other variables were inductively developed from qualitative data and integrated into a model on environmental compliance. The outcomes presented here form part of a wider research project on economic effects of maritime environmental legislation. Research on determinants of compliance might inform policy-makers about actual behavioural effects of shipping companies and might further the development of a comprehensive legal system for environmental protection.

Keywords: compliance, marine environmental protection, exploratory qualitative research study, clean vessel operations, North and Baltic Sea area

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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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Authors: Carlos Tadeu Santana Tatum, Suzana Leitão Russo

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This paper aims to show comparative studies of different types of innovation applied to lighting, along with a theoretical review by means of a bibliographic method. We demonstrate that it is possible to understand the impacts of industries with a conventional innovation that uses natural resources to manufacture lights, and the opposite, when a frugal innovation solves the problems of a society at the bottom of the pyramid, helping people without access to electricity to get home lighting. The frugal innovation is simply the use of recycled PET bottles. We achieved the objective of our study by gathering data from environment, electrical engineering, international rules, and innovation, which gave us the best results. With all these variables, we can characterize this work as an interdisciplinary study.

Keywords: frugal, innovation, PET bottle, light

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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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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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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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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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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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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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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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Authors: Ipenyi Peter

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Discipline is an issue that tends to undermine the provision of quality education in tertiary institutions in Nigeria. This is because the overall goals of tertiary institutions, as enunciated in the National Policy of Education, can hardly be achieved by all the stakeholders without strict conformity and adherence to the rules and regulations and the ideals of the entire society. The adherence is essential for the general welfare of the society. This paper critically X-rayed the causes of indiscipline in tertiary institutions in Nigeria. Such courses include laxity in home control and parental supervision, school, teacher and societal factors as well as government influence. The paper recommended among others such strategies as enculturation, acculturation as well as the acquisition of a certain number of generic skills for dealing with discipline and ethical issues in tertiary institutions in Nigeria.

Keywords: discipline, education, tertiary institutions, society

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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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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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Authors: Dolapo Adeyemo

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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

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Authors: Shameka Stanford

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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

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Authors: Alexander Denzler, Marcel Wehrle, Andreas Meier

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A knowledge base stores facts and rules about the world that applications can use for the purpose of reasoning. By applying the concept of granular computing to a knowledge base, several advantages emerge. These can be harnessed by applications to improve their capabilities and performance. In this paper, the concept behind such a construct, called a granular knowledge cube, is defined, and its intended use as an instrument that manages to cope with different data types and detect knowledge domains is elaborated. Furthermore, the underlying architecture, consisting of the three layers of the storing, representing, and structuring of knowledge, is described. Finally, benefits as well as challenges of deploying it are listed alongside application types that could profit from having such an enhanced knowledge base.

Keywords: granular computing, granular knowledge, hierarchical structuring, knowledge bases

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Authors: Qamar Raza

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This paper deals with the human concern and onus which every person should provide to his/her society. Especially the rules and regulations described in constitution or traditions which we have inherited from ancestors should be followed, and also our lives should be led in accordance with them. The main concern of paper would be personal behavior with others in a good manner especially what he/she should exercise for society’s welfare. As human beings are the fundamental organ of society, who play a crucial role in reforming the society, they should try their best to develop it as well as maintain harmony, peace, we-feeling and mutual contact in the society. Focusing on how the modern society and its elements keep society successful. Regulations of our constitution and tradition are essential for reforming the society. In a nutshell, a human has to mingle in his society and keep mutual respect and understand the value of others as well as for himself.

Keywords: constitution, human beings, society, traditions

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Authors: Mishak Rahul, Naveen Kumar, Bharath Kumar

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

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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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Authors: Abdullah Ali Salamai

Abstract:

Smart healthcare management systems (SHMS) play a vital role in medical centers. SHMS has various risks and threats that affect patient care. So, risk management is the best choice to identify and mitigate these risks. This study proposed a multi-criteria decision-making (MCDM) framework for identifying risks in SHMS and selecting the best project in SHMS to reduce risks. This study used the MCDM method to deal with conflict criteria. There are two MCDM methods: CRiteria Importance Through Intercriteria Correlation (CRITIC) and Additive Ration Assessment (ARAS). The CRITIC approach is used to compute the criteria weights, and the ARAS algorithm is used to select the appropriate projects in SHMS. The neutrosophic set (NS) was applied with MCDM methods to deal with inconsistent data in the evaluation process. The results show the Health Data Informational System project is the best. Sensitivity analysis was conducted to show the stability of the rank. The comparative study was conducted to show the effectiveness of the proposed methodology. The outcomes demonstrate the rank of projects is stable through all scenarios, and the proposed methodology is effective compared with other MCDM methods.

Keywords: risk management, portfolio management, smart healthcare, neutrosophic set, MCDM

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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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Authors: Raymond Feng, Shadi Ghiasi

Abstract:

An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

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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

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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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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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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

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Authors: Elisabetta Cianfanelli, Paolo Pupparo, Maria Claudia Coppola

Abstract:

The recent evolutions in the innovation processes and in the intrinsic tendencies of the product development process, lead to new considerations on the design flow. The instability and complexity that contemporary life describes, defines new problems in the production of products, stimulating at the same time the adoption of new solutions across the entire design process. The advent of Additive Manufacturing, but also of IOT and AI technologies, continuously puts us in front of new paradigms regarding design as a social activity. The totality of these technologies from the point of view of application describes a whole series of problems and considerations immanent to design thinking. Addressing these problems may require some initial intuition and the use of some provisional set of rules or plausible strategies, i.e., heuristic reasoning. At the same time, however, the evolution of digital technology and the computational speed of new design tools describe a new and contrary design framework in which to operate. It is therefore interesting to understand the opportunities and boundaries of the new man-algorithm relationship. The contribution investigates the man-algorithm relationship starting from the state of the art of the Made in Italy model, the most known fields of application are described and then focus on specific cases in which the mutual relationship between man and AI becomes a new driving force of innovation for entire production chains. On the other hand, the use of algorithms could engulf many design phases, such as the definition of shape, dimensions, proportions, materials, static verifications, and simulations. Operating in this context, therefore, becomes a strategic action, capable of defining fundamental choices for the design of product systems in the near future. If there is a human-algorithm combination within a new integrated system, quantitative values can be controlled in relation to qualitative and material values. The trajectory that is described therefore becomes a new design horizon in which to operate, where it is interesting to highlight the good practices that already exist. In this context, the designer developing new forms can experiment with ways still unexpressed in the project and can define a new synthesis and simplification of algorithms, so that each artifact has a signature in order to define in all its parts, emotional and structural. This signature of the designer, a combination of values and design culture, will be internal to the algorithms and able to relate to digital technologies, creating a generative dialogue for design purposes. The result that is envisaged indicates a new vision of digital technologies, no longer understood only as of the custodians of vast quantities of information, but also as a valid integrated tool in close relationship with the design culture.

Keywords: decision making, design euristics, product design, product design process, design paradigms

Procedia PDF Downloads 107