Search results for: data-driven decision making

Authors: Norezzine Abdelaziz, Rebouh Nazih Yacer, Kezimana Parfait, Parpura D. I., Gadzhikurbanov A., Anastasios Dranidis

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The genetic variation of Shvicezebuvides cattle from three different farms in the Tajikistan Republic was studied using 10 microsatellite markers (SSR). The trials were laid out using a multi- locus analysis system for the analysis of cattle microsatellite locus. An estimated genetic variability of the examined livestock is given in the article. The results of our SSR analysis as well as the numbers and frequencies of common alleles in studied samples, we established a high genetic similarity of studied samples. These results can also be furthermore useful in the decision making for preservation and rational genetic resources usage of the Tajik Shvicezebuvides cattle.

Keywords: genetic characteristic, frequencies of the occurrence alleles, microsatellite markers, Swiss cattle

Procedia PDF Downloads 307

Authors: Bronwen Wade

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Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

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Authors: Parisa Moghaddam

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The significance of this study lies in its comprehensive exploration of renewable energy integration in poultry farming, a highly energy-intensive sector, to address pressing global food and energy crisis. As population growth amplifies these issues, innovative solutions are crucial for sustainable food production and energy security. This research investigated the potential of renewable energy sources, particularly anaerobic digestion and solar photovoltaics, to reduce energy consumption, mitigate greenhouse gas emissions, promote circular economy principles in agriculture, and reduce reliance on fossil fuels. By examining case studies from various countries and analyzing the economic and environmental benefits of these technologies, the study aimed to provide practical insights for farmers, stakeholders, and policymakers. Ultimately, this research developed a conceptual tool and framework to facilitate the transition towards more sustainable and circular agricultural practices, addressing critical gaps in renewable energy integration within agricultural systems, and aiming to attract potential investors and gain traction for sustainable practices. The study employed a mixed-methods approach, combining quantitative and qualitative analyses to provide a comprehensive evaluation framework for renewable energy integration in agriculture. Key components included a case study analysis utilizing data from a poultry operation in Armenia, an anaerobic digestion plant in Pakistan, and a solar photovoltaic project in Lebanon. A comprehensive literature review was conducted to understand the current state of renewable energy adoption, challenges, and opportunities in poultry farming. For quantitative analysis, the study used Cost-Benefit Analysis (CBA) to assign monetary values to costs and benefits of renewable energy investment projects, including economic valuation, financial budgeting, and cash flow considerations to compare two modes of renewable energy sources. The qualitative approach utilized Multi-Criteria Decision-Making (MCDM) to evaluate and prioritize alternatives based on multiple criteria, incorporating both objective and subjective factors beyond economic viability. Additionally, sensitivity analysis was conducted for more accurate modeling. Key findings revealed that on-farm anaerobic digester plants focusing on biogas and digestate production, rather than electricity generation, demonstrated economic viability with a Net Present Value of $621,386.3 and an Internal Rate of Return of 149%. Solar PV implementation showed moderate economic potential. The Multi-Criteria Decision-Making analysis, incorporating economic, technical, environmental, and social criteria, ranked anaerobic digesters (0.91) higher than solar PV (0.64) for agricultural applications. The findings suggest that small-scale anaerobic digesters offer the most promising pathway for agricultural waste valorization and renewable energy generation. However, successful implementation requires addressing limitations such as financial uncertainties, lack of accurate data, industry collaboration, and policy support. This research contributes to the growing body of knowledge on circular economy implementation in agriculture, offering practical insights for sustainable development in similar economic contexts.

Keywords: circular economy, renewable energy integration, sustainable poultry farming, anaerobic digestion, solar photovoltaics, sustainability, cost-benefit analysis, multi-criteria decision making, economic modeling

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Authors: Najam U. Saqib

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Self-construal or an individual’s view of him or herself is an important variable by which culture affects the way people think and act. This notion of self-construal is identified with two distinct perspectives on the self. Within the independent construal, the self is seen as different from others, a way of defining the self, prominent in Western societies. The interdependent perspective which is typical for Eastern cultures emphasizes the connectedness of the self to others. The degree of independence-interdependence in one’s self-construal is thought to affect behavior, acceptance of social values, and decision making. This paper manipulates self-construal of Qatari consumers and investigates its effects on accepting incongruent changes in culture as a result of adopting market offerings and behavior that may be perceived as inconsistent with their self-construal. The research recommends strategies for policy makers in Qatar for successful advocacy of initiatives of national importance such as reducing diabetes and obesity by applying self-construal theory.

Keywords: cross-cultural, consumer behavior, self-construal, GCC (Gulf Cooperation Council)

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Authors: Nawaporn Thongnut

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The objective was to study the process and how to prepare the accounting of the Thai temples and to study the performance and quality in the accounting preparation of the temples in accordance with the regulation. The population was the accountants and individuals involved in the accounting preparation of 17 temples in the suburban Bangkok. The measurement used in this study was questionnaire. The statistics used in the analysis are the descriptive statistic. The data was presented in the form of percentage tables to describe the data on the demographic characteristics. The study found that temple wardens were responsible for the accounting and reporting of the temples. Abbots were to check the accuracy of the accounts in the monasteries. Mostly, there was no account auditing of the monasteries from the outside. The practice when receiving income for most of the monasteries had been keeping financial document in an orderly manner.

Keywords: corporate social responsibility, creating shared value, management accountant’s roles, stock exchange of Thailand

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Authors: Somayeh Nezami

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The management of financial and human resources of police in metropolitans requires many information and exact plans to reduce a rate of crime and increase the safety of the society. Geographical Information Systems have an important role in providing crime maps and their analysis. By using them and identification of crime hot spots along with spatial presentation of the results, it is possible to allocate optimum resources while presenting effective methods for decision making and preventive solutions. In this paper, we try to explain and compare between some of the methods of hot spots analysis such as Mode, Fuzzy Mode and Nearest Neighbour Hierarchical spatial clustering (NNH). Then the spots with the highest crime rates of drug smuggling for one province in Iran with borderline with Afghanistan are obtained. We will show that among these three methods NNH leads to the best result.

Keywords: GIS, Hot spots, nearest neighbor hierarchical spatial clustering, NNH, spatial analysis of crime

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Authors: S. Khakurel, R. P. Dhakal, T. Z. Yeow

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Downtime is one of the major sources (alongside damage and injury/death) of financial loss incurred by a structure in an earthquake. The length of downtime associated with a building after an earthquake varies depending on the time taken for the reaction (to the earthquake), decision (on the future course of action) and execution (of the decided course of action) phases. Post-earthquake assessment of buildings is a key step in the decision making process to decide the appropriate safety placarding as well as to decide whether a damaged building is to be repaired or demolished. The aim of the present study is to develop a model to quantify downtime associated with the post-earthquake building-assessment phase in terms of two parameters; i) duration of the different assessment phase; and ii) probability of different colour tagging. Post-earthquake assessment of buildings includes three stages; Level 1 Rapid Assessment including a fast external inspection shortly after the earthquake, Level 2 Rapid Assessment including a visit inside the building and Detailed Engineering Evaluation (if needed). In this study, the durations of all three assessment phases are first estimated from the total number of damaged buildings, total number of available engineers and the average time needed for assessing each building. Then, probability of different tag colours is computed from the 2010-11 Canterbury earthquake Sequence database. Finally, a downtime model for the post-earthquake building inspection phase is proposed based on the estimated phase length and probability of tag colours. This model is expected to be used for rapid estimation of seismic downtime within the Loss Optimisation Seismic Design (LOSD) framework.

Keywords: assessment, downtime, LOSD, Loss Optimisation Seismic Design, phase length, tag color

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Authors: Demet Ozgur-Unluakin, Busenur Turkali, Ayse Karacaorenli

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Maintenance strategies can be classified into two types, which are reactive and proactive, with respect to the time of the failure and maintenance. If the maintenance activity is done after a breakdown, it is called reactive maintenance. On the other hand, proactive maintenance, which is further divided as preventive and predictive, focuses on maintaining components before a failure occurs to prevent expensive halts. Recently, the number of interacting components in a system has increased rapidly and therefore, the structure of the systems have become more complex. This situation has made it difficult to provide the right maintenance decisions. Herewith, determining effective decisions has played a significant role. In multi-component systems, many methodologies and strategies can be applied when a component or a system has already broken down or when it is desired to identify and avoid proactively defects that could lead to future failure. This study focuses on the comparison of various maintenance strategies on a multi-component dynamic system. Components in the system are hidden, although there exists partial observability to the decision maker and they deteriorate in time. Several predefined policies under corrective, preventive and predictive maintenance strategies are considered to minimize the total maintenance cost in a planning horizon. The policies are simulated via Dynamic Bayesian Networks on a multi-component system with different policy parameters and cost scenarios, and their performances are evaluated. Results show that when the difference between the corrective and proactive maintenance cost is low, none of the proactive maintenance policies is significantly better than the corrective maintenance. However, when the difference is increased, at least one policy parameter for each proactive maintenance strategy gives significantly lower cost than the corrective maintenance.

Keywords: decision making, dynamic Bayesian networks, maintenance, multi-component systems, reliability

Procedia PDF Downloads 134

Authors: D. Pinto, L. Castro, M. L. Cruzat, S. Barros, J. Gironás, C. Oberli, M. Torres, C. Escauriaza, A. Cipriano

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Flash floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work, we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations.

Keywords: decision support systems, early warning systems, flash flood, natural hazard

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Authors: Mohammad Rahmani Rezaiyeh, Mojtaba Rahmani Rezaiyeh, Mehrdad Rahmani Rezaiyeh

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Smart speed bump is a new invention and I am invented it. Smart speed bump is a system that can change the position of speed bumps either active or passive in necessary situations. The basic system of smart speed bumps is based on a robotic system which includes mechanic, electronic and artificial intelligence. The smart speed bump is capable of smart decision making and can change its position by anticipating the peak of terrific hours. It can be noted to the advantages of this system such as preventing the waste of petrol while crossing speed bumps, traffic management, accelerating, flowing and securing traffic, reducing accidents and judicial records.

Keywords: invention, smart, robotic system, speed bump, traffic, management

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Authors: Udeh Nneka Evelyn

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The shortcomings of traditional costing system, in terms of validity, accuracy, consistency and relevance increased the need for modern management accounting system. ABC (Activity-Based Costing) can be used as a modern tool for planning, control and decision making for management. Past studies on activity-based costing (ABC) system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing techniques in service oriented business organisations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on activity-based costing (ABC). Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry, and government organizations. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: Identification of the most profitable customers; more accurate product and service pricing; increase product profitability; well-organized process costs.

Keywords: profitability, activity-based costing (ABC), management accounting, manufacture

Procedia PDF Downloads 582

Authors: Mehak Masood

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Education is critical for promoting sustainable development and improving the capacity of people to address environment and development issues. It is also critical for achieving environmental and ethical awareness, values and attitudes, skills and behaviour consistent with sustainable development and for effective public participation in decision-making. In this regard, The British Council Pakistan have conducted a need assessment study conducted during the training sessions with three different groups of educationists belonging to both government and public sectors on the topic of Climate Change and Environmental Education (CCEE). This study aims to review perceptions about climate change and environmental education and analyze its need and importance according to educationists of Pakistan.

Keywords: environmental education, climate change, resilience development, awareness

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Authors: Mohammad Safaeipour, Yousef Amer

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This study directs its focus on developing a conceptual model to offer a systematic and integrated method to weigh the related measures and evaluate a competence of hospitals and rank of the selected hospitals that involve and consider the stakeholders’ key performance indicators (KPI’s). The Analytical Hierarchy Process (AHP) approach will use to weigh the dimensions and related sub- components. The weights and performance scores will combine by using the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) and rank the selected hospitals. The results of this study provide interesting insight into the necessity of process improvement implementation in which hospital that received the lowest ranking score.

Keywords: performance measurement system, PMS, hospitals, AHP, TOPSIS

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Authors: Susmita Ghosh, Bhaskar Bhowmick

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Market is an important factor for start-ups to look into during decision-making in product development and related areas. Emerging country markets are more uncertain in terms of information availability and institutional supports. The literature review of market uncertainty reveals the need for identifying factors representing the market uncertainty. This paper identifies factors for market uncertainty using Exploratory Factor Analysis (EFA) and confirms the number of factor retention using an alternative factor retention criterion, ‘Parallel Analysis’. 500 entrepreneurs, engaged in start-ups from all over India participated in the study. This paper concludes with the factor structure of ‘market uncertainty’ having dimensions of uncertainty in industry orientation, uncertainty in customer orientation and uncertainty in marketing orientation.

Keywords: uncertainty, market, orientation, competitor, demand

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Authors: Yurii Bloshko, Oksana Olar

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This paper presents the analysis of 6 different classes of Petri nets: fuzzy Petri nets (FPN), generalized fuzzy Petri nets (GFPN), parameterized fuzzy Petri nets (PFPN), T2GFPN, flexible generalized fuzzy Petri nets (FGFPN), binary Petri nets (BPN). These classes were simulated in the special software PNeS® for the analysis of its pros and cons on the example of models which are dedicated to the decision-making process of passenger transport logistics. The paper includes the analysis of two approaches: when input values are filled with the experts’ knowledge; when fuzzy expectations represented by output values are added to the point. These approaches fulfill the possibilities of triples of functions which are replaced with different combinations of t-/s-norms.

Keywords: fuzzy petri net, intelligent computational techniques, knowledge representation, triangular norms

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Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

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Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: big data, social networks, sentiment analysis, twitter

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Authors: K. Allaw, J. Adjizian Gerard, M. Chehayeb, A. Raad, W. Fahs, A. Badran, A. Fakherdin, H. Madi, N. Badaro Saliba

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Population estimation using Geographic Information System (GIS) and remote sensing faces many obstacles such as the determination of permanent residents. A permanent resident is an individual who stays and works during all four seasons in his village. So, all those who move towards other cities or villages are excluded from this category. The aim of this study is to identify the factors affecting the percentage of permanent residents in a village and to determine the attributed weight to each factor. To do so, six factors have been chosen (slope, precipitation, temperature, number of services, time to Central Business District (CBD) and the proximity to conflict zones) and each one of those factors has been evaluated using one of the following data: the contour lines map of 50 m, the precipitation map, four temperature maps and data collected through surveys. The weighting procedure has been done using decision tree method. As a result of this procedure, temperature (50.8%) and percentage of precipitation (46.5%) are the most influencing factors.

Keywords: remote sensing, GIS, permanent residence, decision tree, Lebanon

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Authors: Ernesto A. Lagarda-Leyva, Manuel A. Valenzuela L., José G. Oshima C., Arnulfo A. Naranjo-Flores

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From August to December of 2016, a diagnostic and strategic planning study was carried out on the supply chain of the company Agropecuaria GABO S.A. de C.V. The final product of the study was the development of the strategic plan and a project portfolio to meet the demands of the three links in the supply chain of the Roma tomato exported annually to the United States of America. In this project, the strategic objective of ensuring the proper handling of the product was selected and one of the goals associated with this was the employment of quantitative methods to support decision making. Considering the antecedents, the objective of this case study was to develop a model to analyze the behavioral dynamics in the distribution chain, from the logistics of storage and shipment of Roma tomato in 81-case pallets (11.5 kg per case), to the two pre-cooling rooms and eventual loading onto transports, seeking to reduce the bottleneck and the associated costs by means of a dynamic interface. The methodology used was that of system dynamics, considering four phases that were adapted to the purpose of the study: 1) the conceptualization phase; 2) the formulation phase; 3) the evaluation phase; and 4) the communication phase. The main practical conclusions lead to the possibility of reducing both the bottlenecks in the cooling rooms and the costs by simulating scenarios and modifying certain policies. Furthermore, the creation of the dynamic interface between the model and the stakeholders was achieved by generating interaction with buttons and simple instructions that allow making modifications and observing diverse behaviors.

Keywords: agrilogistics, distribution, scenarios, system dynamics

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Authors: Yingxiao Ye, Christopher Doehring, Angelos Georghiou, Hugh Robinson, Phebe Vayanos

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Human development is a threat to biodiversity, and conservation organizations (COs) are purchasing land to protect areas for biodiversity preservation. However, COs have limited budgets and thus face hard prioritization decisions that are confounded by uncertainty in future human land use. This research proposes a data-driven sequential planning model to help COs choose land parcels that minimize the uncertain human impact on biodiversity. The proposed model is robust to uncertain development, and the sequential decision-making process is adaptive, allowing land purchase decisions to adapt to human land use as it unfolds. The cellular automata model is leveraged to simulate land use development based on climate data, land characteristics, and development threat index from NASA Socioeconomic Data and Applications Center. This simulation is used to model uncertainty in the problem. This research leverages state-of-the-art techniques in the robust optimization literature to propose a computationally tractable reformulation of the model, which can be solved routinely by off-the-shelf solvers like Gurobi or CPLEX. Numerical results based on real data from the Jaguar in Central and South America show that the proposed method reduces conservation loss by 19.46% on average compared to standard approaches such as MARXAN used in practice for biodiversity conservation. Our method may better help guide the decision process in land acquisition and thereby allow conservation organizations to maximize the impact of limited resources.

Keywords: data-driven robust optimization, biodiversity conservation, uncertainty simulation, adaptive sequential planning

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Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

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In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

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Authors: M. Shoukath Ali, Rajendra Prasad Singh

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Game Theory approaches and their application in improving the performance of Wireless Sensor Networks (WSNs) are discussed in this paper. The mathematical modeling and analysis of WSNs may have low success rate due to the complexity of topology, modeling, link quality, etc. However, Game Theory is a field, which can efficiently use to analyze the WSNs. Game Theory is related to applied mathematics that describes and analyzes interactive decision situations. Game theory has the ability to model independent, individual decision makers whose actions affect the surrounding decision makers. The outcome of complex interactions among rational entities can be predicted by a set of analytical tools. However, the rationality demands a stringent observance to a strategy based on measured of perceived results. Researchers are adopting game theory approaches to model and analyze leading wireless communication networking issues, which includes QoS, power control, resource sharing, etc.

Keywords: wireless sensor network, game theory, cooperative game theory, non-cooperative game theory

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Authors: Supunmali Ahangama, Danny Chiang Choon Poo

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Health analytics (HA) is used in healthcare systems for effective decision-making, management, and planning of healthcare and related activities. However, user resistance, the unique position of medical data content, and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. The success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose an HA process model with features from the rational unified process (RUP) model and agile methodology.

Keywords: agile methodology, health analytics, unified process model, UML

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Authors: Sithandazile Masuku

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Introduction: Public health approaches to offender mental health are driven by international policies and frameworks in response to the disproportionately large representation of people with mental health problems within the offender pathway compared to the general population. Public health service innovations include mental health courts in the US, restorative models in Singapore and, liaison and diversion services in Australia, the UK, and some other European countries. Mental health nurses are at the forefront of offender health service innovations. In the U.K. context, police custody has been identified as an early point within the offender pathway where nurses can improve outcomes by offering assessments and share information with criminal justice partners. This scope of nursing practice has introduced challenges related to skills and support required for nurses working at the interface of health and the criminal justice system. Parallel literature exploring experiences of nurses working in forensic settings suggests the presence of compassion fatigue, burnout and vicarious trauma that may impede risk harm to the nurses in these settings. Published research explores mainly service-level outcomes including monitoring of figures indicative of a reduction in offending behavior. There is minimal research exploring the experiences of liaison and diversion nurses who are situated away from a supportive clinical environment and engaged in complex autonomous decision-making. Aim: This paper will share qualitative findings (in progress) from a PhD study that aims to explore the experiences of liaison and diversion nurses in one service in the U.K. Methodology: This is a qualitative interview study conducted using an Interpretative Phenomenological Analysis to gain an in-depth analysis of lived experiences. Methods: A purposive sampling technique was used to recruit n=8 mental health nurses registered with the UK professional body, Nursing and Midwifery Council, from one UK Liaison and Diversion service. All participants were interviewed online via video call using semi-structured interview topic guide. Data were recorded and transcribed verbatim. Data were analysed using the seven steps of the Interpretative Phenomenological Analysis data analysis method. Emerging Findings Analysis to date has identified pertinent themes: • Difficulties of meaning-making for nurses because of the complexity of their boundary spanning role. • Emotional burden experienced in a highly emotive and fast-changing environment. • Stress and difficulties with role identity impacting on individual nurses’ ability to be resilient. • Challenges to wellbeing related to a sense of isolation when making complex decisions. Conclusion Emerging findings have highlighted the lived experiences of nurses working in liaison and diversion as challenging. The nature of the custody environment has an impact on role identity and decision making. Nurses left feeling isolated and unsupported are less resilient and may go on to experience compassion fatigue. The findings from this study thus far point to a need to connect nurses working in these boundary spanning roles with a supportive infrastructure where the complexity of their role is acknowledged, and they can be connected with a health agenda. In doing this, the nurses would be protected from harm and the likelihood of sustained positive outcomes for service users is optimised.

Keywords: liaison and diversion, nurse experiences, offender health, staff wellbeing

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Authors: Umugwaneza Francoise, Ntamazeze Janviere, Donghong Ding

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Entrepreneurship has been considered by majority people from developing world as “no other option” kind of career. Consequently, for a long time entrepreneurship in developing countries has been mainly practiced by people who have low or not at all formal education. Even today, to some extent, much of the actions taken by governments, donors and some societies have tendency to consider entrepreneurship as an instrument to lift up the most vulnerable population including uneducated women, school drop outers, people with disabilities and other groups who live with some sort of vulnerability. However, there is a shortage of knowledge based and know-how entrepreneurship in developing countries. Although, the entrepreneurship done with formal educated people would contribute indispensably and sustain the development, the low numbers of formal educated people become entrepreneurs in developing countries. Empirically, this paper investigated the influential factors affecting the entrepreneurial motivation, intentions and decision among African scientists and engineers postgraduate from china universities since 1995 to 2014. Results revealed that 39% are entrepreneurs, 43% work for private sectors and 18% work for governments. Only 6% of respondents are in technological entrepreneurship related to their field of graduation. Study location, mentors or research supervisors and life style are the major factors influenced their decisions to become entrepreneurs whereas complex financial systems and political instability pushed some to employments. Interestingly, significant number of entrepreneurs did not have any entrepreneurial intentions. This paper concludes with suggestions to policy makers and investors in order to encouraging technological entrepreneurs which will provide more opportunities, create jobs and improve people’s quality of life.

Keywords: technological entrepreneurship, entrepreneurial motivation, entrepreneurship decision making, entrepreneurship intentions, formal education

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Authors: Vishnu Pratap Singh Kirar

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The main aim of the communication system is to achieve maximum performance. In cognitive radio, any user or transceiver have the ability to sense best suitable channel, while the channel is not in use. It means an unlicensed user can share the spectrum of licensed user without any interference. Though the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper, we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision-making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: artificial neural network, cognitive radio, cognitive radio networks, back propagation, spectrum sensing

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Authors: Anil Anand

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Despite enormous strides made during the past decade, particularly with the adoption and expansion of community policing, there remains much that police leaders can do to improve police-public relations. The urgency is particularly evident in cities across the United States and Europe where an increasing number of police interactions over the past few years have ignited large, sometimes even national, protests against police policy and strategy, highlighting a gap between what police leaders feel they have archived in terms of public satisfaction, support, and legitimacy and the perception of bias among many marginalized communities. The decision on which one policing strategy is chosen over another, how many resources are allocated, and how strenuously the policy is applied resides primarily with the police and the units and subunits tasked with its enforcement. The scope and opportunity for police officers in impacting social attitudes and social policy are important elements that cannot be overstated. How do police leaders, for instance, decide when to apply one strategy—say community-based policing—over another, like intelligence-led policing? How do police leaders measure performance and success? Should these measures be based on quantitative preferences over qualitative, or should the preference be based on some other criteria? And how do police leaders define, allow, and control discretionary decision-making? Mending Broken Fences Policing provides police and security services leaders with a model based on social cohesion, that incorporates intelligence-led and community policing (IP-CP), supplemented by a quality/quantity/crime (QQC) framework to provide a four-step process for the articulable application of police intervention, performance measurement, and application of discretion.

Keywords: social cohesion, quantitative performance measurement, qualitative performance measurement, sustainable leadership

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Authors: Gospel Iyioku, Jana Mazancova, Jiri Hejkrlik

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The “Agricultural Promotion Policy (2016–2020)” represents a strategic initiative by the Nigerian government to address domestic food shortages and the challenges in exporting products at the required quality standards. Hindered by an inefficient system for setting and enforcing food quality standards, coupled with a lack of market knowledge, the Federal Ministry of Agriculture and Rural Development (FMARD) aims to enhance support for the production and activities of key crops like cashew. By collaborating with farmers, processors, investors, and stakeholders in the cashew sector, the policy seeks to define and uphold high-quality standards across the cashew value chain. Given the challenges and opportunities faced by Nigerian cashew farmers, active participation in cashew marketing groups becomes imperative. These groups serve as essential platforms for farmers to collectively navigate market intricacies, access resources, share knowledge, improve output quality, and bolster their overall bargaining power. Through engagement in these cooperative initiatives, farmers not only boost their economic prospects but can also contribute significantly to the sustainable growth of the cashew industry, fostering resilience and community development. This study explores the perceptions and intentions of farmers regarding their involvement in cashew marketing cooperatives, utilizing an expanded version of the Theory of Planned Behaviour. Drawing insights from a diverse sample of 321 cashew farmers in Southwest Nigeria, the research sheds light on the factors influencing decision-making in cooperative participation. The demographic analysis reveals a diverse landscape, with a substantial presence of middle-aged individuals contributing significantly to the agricultural sector and cashew-related activities emerging as a primary income source for a substantial proportion (23.99%). Employing Structural Equation Modelling (SEM) with Maximum Likelihood Robust (MLR) estimation in R, the research elucidates the associations among latent variables. Despite the model’s complexity, the goodness-of-fit indices attest to the validity of the structural model, explaining approximately 40% of the variance in the intention to join cooperatives. Moral norms emerge as a pivotal construct, highlighting the profound influence of ethical considerations in decision-making processes, while perceived behavioural control presents potential challenges in active participation. Attitudes toward joining cooperatives reveal nuanced perspectives, with strong beliefs in enhanced connections with other farmers but varying perceptions on improved access to essential information. The SEM analysis establishes positive and significant effects of moral norms, perceived behavioural control, subjective norms, and attitudes on farmers’ intention to join cooperatives. The knowledge construct positively affects key factors influencing intention, emphasizing the importance of informed decision-making. A supplementary analysis using partial least squares (PLS) SEM corroborates the robustness of our findings, aligning with covariance-based SEM results. This research unveils the determinants of cooperative participation and provides valuable insights for policymakers and practitioners aiming to empower and support this vital demographic in the cashew industry.

Keywords: marketing cooperatives, theory of planned behaviour, structural equation modelling, cashew farmers

Procedia PDF Downloads 92

Authors: Toshiki Ito

Abstract:

Mutual squiggle story making (MSSM ) is the development of Winnicott’s squiggle method in Japan. In the MSSM Method, a therapist has the client freely divide a piece of drawing paper into six spaces, and both the therapist and client do squiggle in each space. All six pictures finished, the therapist then asks the client to create a story using all the pictures. Making a story has the effect of reintegrating what is projected by consciousness. In this paper, the author presented a case with a junior high school girl using MSSM. And it is considered that the advantage of this technique is that (1) it enables non-verbal communication with children and adults who cannot express their feelings verbally. (2) Through this communication, the psychological content of the client and the characteristics of the client's mind can be understood, and (3) It can be said that mutual rapport is deepened by the supportive reaction of the therapist.

Keywords: MSSM, squiggle, Winnicott, drawing method

Procedia PDF Downloads 206

Authors: Fouad M. Bendimerad, Jerome B. Zayas, Michael Adrian T. Padilla

Abstract:

With the increasing scale of severity and frequency of disasters worldwide, the performance of governance systems for disaster risk reduction and management in many countries are being put to the test. In the Philippines, the Disaster Risk Reduction and Management (DRRM) Act of 2010 (Republic Act 10121 or RA 10121) as the framework for disaster risk reduction and management was tested when Super Typhoon Haiyan hit the eastern provinces of the Philippines in November 2013. Typhoon Haiyan is considered to be the strongest recorded typhoon in history to make landfall with winds exceeding 252 km/hr. In assessing the performance of RA 10121 the authors conducted document reviews of related policies, plans, programs, and key interviews and focus groups with representatives of 21 national government departments, two (2) local government units, six (6) private sector and civil society organizations, and five (5) development agencies. Our analysis will argue that enhancements are needed in RA 10121 in order to meet the challenges of large-scale disasters. The current structure where government agencies and departments organize along DRRM thematic areas such response and relief, preparedness, prevention and mitigation, and recovery and response proved to be inefficient in coordinating response and recovery and in mobilizing resources on the ground. However, experience from various disasters has shown the Philippine government’s tendency to organize major recovery programs along development sectors such as infrastructure, livelihood, shelter, and social services, which is consistent with the concept of DRM mainstreaming. We will argue that this sectoral approach is more effective than the thematic approach to DRRM. The council-type arrangement for coordination has also been rendered inoperable by Typhoon Haiyan because the agency responsible for coordination does not have decision-making authority to mobilize action and resources of other agencies which are members of the council. Resources have been devolved to agencies responsible for each thematic area and there is no clear command and direction structure for decision-making. However, experience also shows that the Philippine government has appointed ad-hoc bodies with authority over other agencies to coordinate and mobilize action and resources in recovering from large-scale disasters. We will argue that this approach be institutionalized within the government structure to enable a more efficient and effective disaster risk reduction and management system.

Keywords: risk reduction and management, recovery, governance, typhoon haiyan response and recovery

Procedia PDF Downloads 289

Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

Abstract:

Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

Procedia PDF Downloads 450