Search results for: military decision making process (MDMP)

Authors: Irfan Khan

Abstract:

Both the analytical methods used to understand the phenomena of peacebuilding and the ensuing viewpoints on achieving and sustaining "sustainable peace" are broad and diverse. This new field of study draws from sociology, anthropology, political theory, and political economy, psychology, international relations, and more recently, the development sciences to examine the wide range of 'conflicts' it describes. This paper emphasizes the significance of investigating the causes of juvenile disputes. It explains how police corruption encourages youth crime and why it's so important to address this issue head-on. It also examines the historical foundations and external pressures that have increased religious extremism and sectarian strife in Pakistan. The primary argument is that peace is not only a desirable 'goal' in itself but also that it may be a means to achieve political stability and long-term prosperity. Strategies for constructing peace may take many shapes, each tailored to the specifics of a given conflict, its scope, and the individuals involved. By drawing on some existing literature and applying it to the situation in Pakistan, this article proposes a viewpoint that centers on the participation of young people in the peacebuilding process. Due to their enhanced susceptibility and penchant for demanding change, young people are more likely to get involved in a conflict when economic failure and unemployment are present. The piece also emphasizes the marginalization young people experience as a result of their absence from decision-making processes and the political system. The article claims that Pakistan's rapidly growing young population presents a significant chance for a long-term "demographic dividend" in the form of improvements in peacebuilding processes. This benefit will only materialize if serious steps are taken to increase young people's voice and agency in political decision-making.

Keywords: peacebuilding, youth-led initiatives, empowerment, conflict & violence, religious extremism, political involvement, decision-making

Procedia PDF Downloads 48

Authors: Boukrida Rafiq

Abstract:

Democracy is based on the notion that all citizens have the right to participate in the managing of political affairs and that every citizens input is of equal importance. This basic assumption clearly places emphasis on public participation in maintaining a stable democracy. The level of public participation, however is highly contested with many theorists arguing that too much public participation would overwhelm and ultimately cripple democratic systems. On the other hand, others who favor high levels of participation argue that more citizen involvement leads to greater representation. Regardless of these disagreements over the utopian level of participation, there is widespread agreement amongst scholars that, at the very least, some participation is necessary to maintain democratic systems. The ways in which citizens participate vary greatly and depending on the method used, influence political decision making at varying levels. The method of political participation is a key in controlling public influence over political affairs and therefore is also an integral part of maintaining democracy, whether it be "thin" (low levels of participation) or "Robust" (high levels of participation). High levels of participation or "robust" democracy are argued by some theorists to enhance democracy through providing the opportunity for more issues to be represented during decision making. The notion of widespread participation was first advanced by classical theorists.

Keywords: assumption clearly places emphasis, ultimately cripple, influence political decision making at varying, classical theorists

Procedia PDF Downloads 438

Authors: Y. Kourd, D. Lefebvre, N. Guersi

Abstract:

This paper presents a new idea for fault detection and isolation (FDI) technique which is applied to industrial system. This technique is based on Neural Networks fault-free and Faulty behaviors Models (NNFM's). NNFM's are used for residual generation, while decision tree architecture is used for residual evaluation. The decision tree is realized with data collected from the NNFM’s outputs and is used to isolate detectable faults depending on computed threshold. Each part of the tree corresponds to specific residual. With the decision tree, it becomes possible to take the appropriate decision regarding the actual process behavior by evaluating few numbers of residuals. In comparison to usual systematic evaluation of all residuals, the proposed technique requires less computational effort and can be used for on line diagnosis. An application example is presented to illustrate and confirm the effectiveness and the accuracy of the proposed approach.

Keywords: neural networks, decision trees, diagnosis, behaviors

Procedia PDF Downloads 469

Authors: A. Senthil Kumar, V. Murali Bhaskaran

Abstract:

In the information technology ground, people are using various tools and software for their official use and personal reasons. Nowadays, people are worrying to choose data accessing and extraction tools at the time of buying and selling their products. In addition, worry about various quality factors such as price, durability, color, size, and availability of the product. The main purpose of the research study is to find solutions to these unsolved existing problems. The proposed algorithm is a Multidirectional Rank Prediction (MDRP) decision making algorithm in order to take an effective strategic decision at all the levels of data extraction, uses a real time textile dataset and analyzes the results. Finally, the results are obtained and compared with the existing measurement methods such as PCC, SLCF, and VSS. The result accuracy is higher than the existing rank prediction methods.

Keywords: Knowledge Discovery in Database (KDD), Multidirectional Rank Prediction (MDRP), Pearson’s Correlation Coefficient (PCC), VSS (Vector Space Similarity)

Procedia PDF Downloads 262

Authors: Faruk Aras, Melih Inal, Tansel Cinar

Abstract:

The coordination of airport staff especially in the operations and maintenance departments is important for the airport operation. As a result, this coordination will increase the efficiency in all operation. Therefore, a Collaborative Decision-Making (CDM) system targets on improving the overall productivity of all operations by optimizing the use of resources and improving the predictability of actions. Enlarged productivity can be of major benefit for all airport operations. It also increases cost-efficiency. This study explains how predictive maintenance using IoT (Internet of Things), predictive operations and the statistical data such as Mean Time To Failure (MTTF) improves airport terminal operations and utilize airport terminal equipment in collaboration with collaborative decision making system/Airport Operation Control Center (AOCC). Data generated by the predictive maintenance methods is retrieved and analyzed by maintenance managers to predict when a problem is about to occur. With that information, maintenance can be scheduled when needed. As an example, AOCC operator would have chance to assign a new gate that towards to this gate all the equipment such as travellator, elevator, escalator etc. are operational if the maintenance team is in collaboration with AOCC since maintenance team is aware of the health of the equipment because of predictive maintenance methods. Applying predictive maintenance methods based on analyzing the health of airport terminal equipment dramatically reduces the risk of downtime by on time repairs. We can classify the categories as high priority calls for urgent repair action, as medium priority requires repair at the earliest opportunity, and low priority allows maintenance to be scheduled when convenient. In all cases, identifying potential problems early resulted in better allocation airport terminal resources by AOCC.

Keywords: airport, predictive maintenance, collaborative decision-making system, Airport Operation Control Center (AOCC)

Procedia PDF Downloads 342

Authors: Romain Ben Taleb, Aurélie Montarnal, Matthieu Lauras, Mathieu Dahan, Romain Miclo

Abstract:

To be competitive and sustainable, any company has to maximize its value. However, unlike listed companies that can assess their values based on market shares, most Small and Medium Enterprises (SMEs) which are non-listed cannot have direct and live access to this critical information. Traditional accounting reports only give limited insights to SME decision-makers about the real impact of their day-to-day decisions on the company’s performance and value. Most of the time, an SME’s financial valuation is made one time a year as the associated process is time and resource-consuming, requiring several months and external expertise to be completed. To solve this issue, we propose in this paper a value-oriented metamodel that enables real-time and dynamic assessment of the SME’s value based on the large definition of their assets. These assets cover a wider scope of resources of the company and better account for immaterial assets. The proposal, which is illustrated in a case study, discusses the benefits of incorporating assets in the SME valuation.

Keywords: SME, metamodel, decision support system, financial valuation, assets

Procedia PDF Downloads 73

Authors: B. Güney, Ç. Teke

Abstract:

In recent years, rapid and correct decision making is crucial for both people and enterprises. However, uncertainty makes decision-making difficult. Fuzzy logic is used for coping with this situation. Thus, fuzzy linear programming models are developed in order to handle uncertainty in objective function and the constraints. In this study, a problem of a factory in food industry is investigated, required data is obtained and the problem is figured out as a fuzzy linear programming model. The model is solved using Zimmerman approach which is one of the approaches for fuzzy linear programming. As a result, the solution gives the amount of production for each product type in order to gain maximum profit.

Keywords: food industry, fuzzy linear programming, fuzzy logic, linear programming

Procedia PDF Downloads 622

Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

Abstract:

Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, decision support system, TOPSIS, FAHP, PROMETHEE

Procedia PDF Downloads 136

Authors: Nsimbe Allan

Abstract:

The study examines the impact of Building Information Modeling (BIM) on the cost management of engineering projects, focusing specifically on the Mombasa Port Area Development Project. The objective of this research venture is to determine the mechanisms through which Building Information Modeling (BIM) facilitates stakeholder collaboration, reduces construction-related expenses, and enhances the precision of cost estimation. Furthermore, the study investigates barriers to execution, assesses the impact on the project's transparency, and suggests approaches to maximize resource utilization. The study, selected for its practical significance and intricate nature, conducted a Systematic Literature Review (SLR) using credible databases, including ScienceDirect and IEEE Xplore. To constitute the diverse sample, 69 individuals, including project managers, cost estimators, and BIM administrators, were selected via stratified random sampling. The data were obtained using a mixed-methods approach, which prioritized ethical considerations. SPSS and Microsoft Excel were applied to the analysis. The research emphasizes the crucial role that project managers, architects, and engineers play in the decision-making process (47% of respondents). Furthermore, a significant improvement in cost estimation accuracy was reported by 70% of the participants. It was found that the implementation of BIM resulted in enhanced project visibility, which in turn optimized resource allocation and facilitated the process of budgeting. In brief, the study highlights the positive impacts of Building Information Modeling (BIM) on collaborative decision-making and cost estimation, addresses challenges related to implementation, and provides solutions for the efficient assimilation and understanding of BIM principles.

Keywords: cost management, resource utilization, stakeholder collaboration, project transparency

Procedia PDF Downloads 35

Authors: Murat Sözen

Abstract:

It is not at all difficult to estimate which level today’s technology reaches considering that humankinds space-faring in early 1950s. Technology is a means to help achieve goals and people can produce systems on their physical and mental abilities. Needed and used as tools in all areas of life and became a necessity and dependency, technology, widely used in the military field. To be a revolutionary change in the military matters, opportunities offered by technology should be put into practice. Tech makes weapons, sensors, platforms and soldiers carrying them more effective. To increase this efficiency in the battlefield defense industry is seeking every advantage of technology. In this study, the applicability of existing and on-going augmented reality applications for Armed Forces will be evaluated.

Keywords: augmented reality, battlefield, military, virtual reality

Procedia PDF Downloads 241

Authors: Dhiraj Neupane

Abstract:

Decentralized policy and practices have largely concentrated on the transformation of decision-making authorities from central to local institutions (or people) in the developing world. Such policy and practices always aimed for the equitable and efficient management of resources in the line of poverty reduction. The transformation of forest decision-making autonomy has also glorified as the best forest management alternatives to maximize the forest benefits and improve the livelihood of local people living nearby the forests. However, social heterogeneity and poor decision-making capacity of local institutions (or people) pose a nexus while managing the resources and sharing the forest benefits among the user households despite the policy objectives. The situation is severe in the lowland of Nepal, where forest resources have higher economic potential and user households have heterogeneous socio-economic conditions. The study discovered that utilizing the power of decision-making autonomy, user households were putting low values of timber considering the equitable access of timber to all user households as it is the most valuable product of community forest. Being the society is heterogeneous by socio-economic conditions, households of better economic conditions were always taking higher amount of forest benefits. The low valuation of timber has negative consequences on equitable benefit sharing and poor support to livelihood improvement of user households. Moreover, low valuation has possibility to increase the local demands of timber and increase the human pressure on forests.

Keywords: decentralized forest policy, Nepal, poverty, social heterogeneity, Terai

Procedia PDF Downloads 264

Authors: Mona Isazad Mashinchi, Davood Roshan Sangachin, Francis J. Sullivan, Dietrich Rebholz-Schuhmann

Abstract:

Background: Decision-making processes are nowadays driven by data, data analytics and Business Intelligence (BI). BI as a software platform can provide a wide variety of capabilities such as organization memory, information integration, insight creation and presentation capabilities. Visualizing data through dashboards is one of the BI solutions (for a variety of areas) which helps managers in the decision making processes to expose the most informative information at a glance. In the healthcare domain to date, dashboard presentations are more frequently used to track performance related metrics and less frequently used to monitor those quality parameters which relate directly to patient outcomes. Providing effective and timely care for patients and improving the health outcome are highly dependent on presenting and visualizing data and information. Objective: In this research, the focus is on the presentation capabilities of BI to design a dashboard for prostate cancer (PC) data that allows better decision making for the patients, the hospital and the healthcare system related to a cancer dataset. The aim of this research is to customize a retrospective PC dataset in a dashboard interface to give a better understanding of data in the categories (risk factors, treatment approaches, disease control and side effects) which matter most to patients as well as other stakeholders. By presenting the outcome in the dashboard we address one of the major targets of a value-based health care (VBHC) delivery model which is measuring the value and presenting the outcome to different actors in HC industry (such as patients and doctors) for a better decision making. Method: For visualizing the stored data to users, three interactive dashboards based on the PC dataset have been developed (using the Tableau Software) to provide better views to the risk factors, treatment approaches, and side effects. Results: Many benefits derived from interactive graphs and tables in dashboards which helped to easily visualize and see the patients at risk, better understanding the relationship between patient's status after treatment and their initial status before treatment, or to choose better decision about treatments with fewer side effects regarding patient status and etc. Conclusions: Building a well-designed and informative dashboard is related to three important factors including; the users, goals and the data types. Dashboard's hierarchies, drilling, and graphical features can guide doctors to better navigate through information. The features of the interactive PC dashboard not only let doctors ask specific questions and filter the results based on the key performance indicators (KPI) such as: Gleason Grade, Patient's Age and Status, but may also help patients to better understand different treatment outcomes, such as side effects during the time, and have an active role in their treatment decisions. Currently, we are extending the results to the real-time interactive dashboard that users (either patients and doctors) can easily explore the data by choosing preferred attribute and data to make better near real-time decisions.

Keywords: business intelligence, dashboard, decision making, healthcare, prostate cancer, value-based healthcare

Procedia PDF Downloads 125

Authors: Rebecca K. Blais, Lindsey Monteith, Hallie Tannahill

Abstract:

Military sexual trauma (MST) includes sexual harassment or assault that occurred during military service. Studies conducted to date on the association of MST with mental health and suicide outcomes are generally circumscribed to either active duty or veteran samples, precluding a thorough analysis of developmental trajectories of distress following MST within the context of ongoing (vs. discharged from) military service. The Military Social Science Laboratory has collected data on mixed service samples of men and women service members, addressing this important literature gap. The purpose of this study was to examine the association of MST, suicide risk, PTSD, depression, alcohol use, and posttraumatic cognitions using two separate samples, which collectively allow for a comprehensive examination of the development of distress following MST. The first sample consisted of 1389 men and women service members and veterans with varying levels of MST severity, including no MST, harassment-only MST, and assault MST. The second sample consisted of 400 men and women service members, all reporting the highest severity of MST, assault MST. In both samples, roughly half reported being discharged from service. Participants completed self-report measures of MST exposure severity, suicide ideation, suicide risk, PTSD, depression, alcohol misuse, and posttraumatic cognitions, as well as perceptions of how the military responded to their MST. Relative to those still serving in the US military, veterans were more likely to endorse suicidal ideation, higher PTSD symptoms, and higher depression symptoms if they felt the military mishandled their experience of MST (referred to as perceived institutional betrayal). However, among those reporting the most severe MST, veterans reported lower alcohol misuse and more adaptive posttraumatic cognitions. These findings suggest that those separated from the military experience different posttraumatic aftermath following MST relative to those who are currently serving in the military. Such findings suggest critical differences in the developmental trajectory of distress, necessitating different interventions to successfully reduce distress and dysfunction. Additional analyses will explore the impact of gender on these associations and explore full mechanistic models of distress grouped by discharged status.

Keywords: military sexual trauma, PTSD, suicide, developmental trajectories, depression

Procedia PDF Downloads 109

Authors: M. Pushparani, A. Sagaya

Abstract:

Embedded systems have emerged as important elements in various domains with extensive applications in automotive, commercial, consumer, healthcare and transportation markets, as there is emphasis on intelligent devices. On the other hand, Business Intelligence (BI) has also been extensively used in a range of applications, especially in the agriculture domain which is the area of this research. The aim of this research is to create a framework for Embedded Weight Comparison Algorithm with Business Intelligence (EWCA-BI). The weight comparison algorithm will be embedded within the plantation management system and the weighbridge system. This algorithm will be used to estimate the weight at the site and will be compared with the actual weight at the plantation. The algorithm will be used to build the necessary alerts when there is a discrepancy in the weight, thus enabling better decision making. In the current practice, data are collected from various locations in various forms. It is a challenge to consolidate data to obtain timely and accurate information for effective decision making. Adding to this, the unstable network connection leads to difficulty in getting timely accurate information. To overcome the challenges embedding is done on a portable device that will have the embedded weight comparison algorithm to also assist in data capture and synchronize data at various locations overcoming the network short comings at collection points. The EWCA-BI will provide real-time information at any given point of time, thus enabling non-latent BI reports that will provide crucial information to enable efficient operational decision making. This research has a high potential in bringing embedded system into the agriculture industry. EWCA-BI will provide BI reports with accurate information with uncompromised data using an embedded system and provide alerts, therefore, enabling effective operation management decision-making at the site.

Keywords: embedded business intelligence, weight comparison algorithm, oil palm plantation, embedded systems

Procedia PDF Downloads 265

Authors: Mariam Shah

Abstract:

The way the human mind interprets and comprehends the world it occupies has long been a topic of discussion amongst philosophers and phenomenologists. This paper will focus predominantly on the ideologies espoused by the phenomenologist Alfred Schutz and will investigate how we attribute meaning to an event through the process of typification, and the production and usage of ‘types' and ‘stereotypes.' This paper will then discuss how subjective ideologies innate within us result in unique and subjective decision outcomes, based on a phenomenologically influenced theoretical framework which will illustrate how we form ‘types’ in order to ‘typecast’ and form judgements of everything and everyone we experience. The framework used will be founded in theory espoused by Alfred Schutz, and will review the different types of knowledge we rely on innately to inform our judgements, the relevance we attribute to the information which we acquire, and how we consciously and unconsciously apply this framework to everyday situations. An assessment will then be made of the potential impact that these subjective meaning structures can present when dispensing justice in criminal courts. This paper will investigate how these subjective meaning structures can influence our consciousness on both a conscious and unconscious level, and how this could potentially result in bias judicial outcomes due to negative ‘types’ or ‘stereotypes.' This paper will ultimately illustrate that we unconsciously and unreflexively use pre-formed types and stereotypes to inform our judgements and give meaning to what we have just experienced.

Keywords: Alfred Schutz, criminal courts, decision making, judicial decision making, phenomenology, Schutzian stereotypes, types, typification

Procedia PDF Downloads 207

Authors: Ana Fouto

Abstract:

Background: Continuing Personal Development (CPD) enables professionals to keep up to date with the professional requirements, broadening their knowledge and expertise. However, much of the research explores the registered professionals’ experiences and the factors that influence their choice of engaging, despite the unregistered staff providing the majority of the direct patient care. Aim: To explore the Nursing/Midwifery Assistants’ (NAs) perception of the concept of CPD, as well as explore the factors that influence the NAs to engage (or not) with CPD experiences. Methodology: This pilot study used a qualitative approach through a case study, where a semi-structured interview was applied to three NAs to explore the factors that influence the decision-making of process of CPD engagement. Thematic analysis was used to analyse their answers and interpret patterns and associations. Findings: All the participants agreed that CPD is important and relevant to their practice and personal lives. Five main categories were identified: NAs’ scope of practice, the impact of CPD; decision-making process; challenges; changes required. Although similar findings to the registered nurses were identified, the lack of CPD regulation for NAs and the rapid evolution of their role make the CPD engagement more problematic. Conclusion: Engagement with CPD is influenced by a wide range of professional (organisational and national) and personal factors. NAs perceive lack of management support at different stages of the CPD activities as a main influence. Organisations should be more flexible in the recruitment, offer of CPD choices, content, delivery, and contractual arrangements of NAs, which may increase engagement.

Keywords: nursing assistants, engagement, factors, pilot, continuing professional development (CPD)

Procedia PDF Downloads 130

Authors: Kingkan Pongsiri

Abstract:

The study of marketing mix influencing on hotel booking decision making: Japanese senior traveler case aims to study the individual factors that are involved in the decision-making reservation for Japanese elderly travelers. Then, it aims to study other factors that influence the decision of tourists booking elderly Japanese people. This is a quantitative research methods, total of 420 completed questionnaires were collect via a Non-Probability sampling techniques. The study found that the majority of samples were female, 53.3 percent of 224 people aged between 66-70 years were 197, representing a 46.9 percent majority, the marital status of marriage is 212 per cent.50.5. Majority of samples have a bachelor degree of education with number of 326 persons (77.6 percentages) 50 percentages of samples (210 people) have monthly income in between 1,501-2,000 USD. The Samples mostly have a length of stay in a short period between 1-14 days counted as 299 people which representing 71.2 percentages of samples. The senior Japanese tourists apparently sensitive to the factors of products/services the most. Then they seem to be sensitive to the price, the marketing promotion and people, respectively. There are two factors identified as moderately influence to the Japanese senior tourists are places or distribution channels and physical evidences.

Keywords: Japanese senior traveler, marketing mix, senior tourist, hotel booking

Procedia PDF Downloads 273

Authors: Wai Ho Darrell Kwok

Abstract:

Building entities are valuable assets of a society, however, all of them are suffered from the ravages of weather and time. Facilitating onerous maintenance activities is the only way to either maintain or enhance the value and contemporary standard of the premises. By the way, maintenance budget is always bounded by the corresponding threshold limit. In order to optimize the limited resources allocation in carrying out maintenance, there is a substantial need to prioritize maintenance work. This paper reveals the application of Fuzzy AHP in a Facilities Management Company determining the maintenance priorities on the basis of predetermined criteria, viz., Building Status (BS), Effects on Fabrics (EF), Effects on Sustainability (ES), Effects on Users (EU), Importance of Usage (IU) and Physical Condition (PC) in dealing with categorized 8 predominant building components maintenance aspects for building premises. From the case study, it is found that ‘building exterior repainting or re-tiling’, ‘spalling concrete repair works among exterior area’ and ‘lobby renovation’ are the top three maintenance priorities from facilities manager and maintenance expertise personnel. Through the application of the Fuzzy AHP for maintenance priorities decision algorithm, a more systemic and easier comparing scalar linearity factors being explored even in considering other multiple criteria decision scenarios of building maintenance issue.

Keywords: building maintenance, fuzzy AHP, maintenance priority, multi-criteria decision making

Procedia PDF Downloads 218

Authors: Alice Brites, Gerd Sparovek, Jean Paul Metzger, Ricardo Rodrigues

Abstract:

The segregation between science and policy in decision making process hinders nature conservation efforts worldwide. Scientists have been criticized for not producing information that leads to effective solutions for environmental problems. In an attempt to bridge this gap between science and practice, we conducted a project aimed at supporting the implementation of the Brazilian Native Vegetation Protection Law (NVPL) implementation in São Paulo State (SP), Brazil. To do so, we conducted multiple open meetings with the stakeholders involved in this discussion. Throughout this process, we raised stakeholders' demands for scientific information and brought feedbacks about our findings. However, our main scientific advice was not taken into account during the NVPL implementation in SP. The NVPL has a mechanism that exempts landholders who converted native vegetation without offending the legislation in place at the time of the conversion from restoration requirements. We found out that there were no accurate spatialized data for native vegetation cover before the 1960s. Thus, the initial benchmark for the mechanism application should be the 1965 Brazilian Forest Act. Even so, SP kept the 1934 Brazilian Forest Act as the initial legal benchmark for the law application. This decision implies the use of a probabilistic native vegetation map that has uncertainty and subjectivity as its intrinsic characteristics, thus its use can lead to legal queries, corruption, and an unfair benefit application. But why this decision was made even after the scientific advice was vastly divulgated? We raised some possible reasons to explain it. First, the decision was made during a government transition, showing that circumstantial political events can overshadow scientific arguments. Second, the debate about the NVPL in SP was not pacified and powerful stakeholders could benefit from the confusion created by this decision. Finally, the native vegetation protection mechanism is a complex issue, with many technical aspects that can be hard to understand for a non-specialized courtroom, such as the one that made the final decision at SP. This example shows that science and decision-makers still have a long way ahead to improve their way to interact and that science needs to find its way to be heard above the political buzz.

Keywords: Brazil, forest act, science-based dialogue, science-policy interface

Procedia PDF Downloads 103

Authors: Peng Liu, Chyng Wen Tee, Xiaofei Xu

Abstract:

This paper integrates machine learning forecasting techniques into the multi-period portfolio optimization framework, enabling dynamic asset allocation based on multiple future periods. We explore both theoretical foundations and practical applications, employing diverse machine learning models for return forecasting. This comprehensive guide demonstrates the superiority of multi-period optimization over single-period approaches, particularly in risk mitigation through strategic rebalancing and enhanced market trend forecasting. Our goal is to promote wider adoption of multi-period optimization, providing insights that can significantly enhance the decision-making capabilities of practitioners and researchers alike.

Keywords: multi-period portfolio optimization, look-ahead constrained optimization, machine learning, sequential decision making

Procedia PDF Downloads 17

Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

Abstract:

In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

Procedia PDF Downloads 60

Authors: Ian McCulloh, Andrew Placona, Darren Stewart, Daniel Gause, Kevin Kiernan, Morgan Stuart, Christopher Zinner, Laura Cartwright

Abstract:

An estimated 22-25% of viable deceased donor kidneys are discarded every year in the US, while waitlisted candidates are dying every day. As many as 85% of transplanted organs are refused at least once for a patient that scored higher on the match list. There are hundreds of clinical variables involved in making a clinical transplant decision and there is rarely an ideal match. Decision makers exhibit an optimism bias where they may refuse an organ offer assuming a better match is imminent. We propose a semi-parametric Cox proportional hazard model, augmented by an accelerated failure time model based on patient specific suitable organ supply and demand to estimate a time-to-next-offer. Performance is assessed with Cox-Snell residuals and decision curve analysis, demonstrating improved decision support for up to a 5-year outlook. Providing clinical decision makers with quantitative evidence of likely patient outcomes (e.g., time to next offer and the mortality associated with waiting) may improve decisions and reduce optimism bias, thus reducing discarded organs and matching more patients on the waitlist.

Keywords: decision science, KDPI, optimism bias, organ transplant

Procedia PDF Downloads 83

Authors: A. Aguezzoul

Abstract:

The Logistics Services Providers (LSPs) selection and performance is a strategic decision that affects the overall performance of any company as well as its supply chain. It is a complex process, which takes into account various conflicting quantitative and qualitative factors, as well as outsourced logistics activities. This article focuses on the evolution of the weights associated to these factors over the last years in order to better understand the change in the importance that logistics professionals place on them criteria when choosing their LSPs. For that, an analysis of 17 main studies published during 2014-2017 period was carried out and the results are compared to those of a previous literature review on this subject. Our analysis allowed us to deduce the following observations: 1) the LSPs selection is a multi-criteria process; 2) the empirical character of the majority of studies, conducted particularly in Asian countries; 3) the criteria importance has undergone significant changes following the emergence of information technologies that have favored the work in close collaboration and in partnership between the LSPs and their customers, even on a worldwide scale; 4) the cost criterion is relatively less important than in the past; and finally 5) with the development of sustainable supply chains, the factors associated with the logistic activities of return and waste processing (reverse logistics) are becoming increasingly important in this multi-criteria process of selection and evaluation of LSPs performance.

Keywords: logistics outsourcing, logistics providers, multi-criteria decision making, performance

Procedia PDF Downloads 133

Authors: Almas Athif Fathin Wiyantoro, Fransiskus Xaverius Ivan Budiman, Fithra Faisal Hastiadi

Abstract:

The growth of clothing and technology as a marketing tool has a great influence on online business owners to know how much the characteristics and psychology of consumers in influencing purchasing decisions made by Indonesian women consumers. One of the most important issues faced by Indonesian women consumers is the suitability of clothing. The suitability of clothing can affect the body cathexis, identity, and confidence. So the thematic analysis of clothing fitness and body cathexis of women consumers when and after using virtual fitting room technology to purchase decision is important to do. This research using group method of pre-post treatment and considers how the recruitment technique of snowball sampling, which uses interpersonal relations and connections between people, both includes and excludes individuals into 39 participants' social networks to access specific populations. The results obtained from the study that the results of body scans and photos of virtual fitting room results can be made an intervention in women consumers in assessing their body cathexis objectively in the process of making purchasing decisions. The study also obtained a regression equation Y = 0.830 + 0.290X1 + 0.292X2, showing a positive relationship between suitability of clothing and body cathexis which influenced purchasing decisions on women consumers and after (personal and psychological factors) using virtual fitting room, meaning that all independent variables influence Positive towards the purchasing decision of the women consumers.

Keywords: body cathexis, clothing fitness, purchasing decision making and virtual fitting room

Procedia PDF Downloads 189

Authors: U. S. Putro, L. Mayangsari, M. Siallagan, N. P. Tjahyani

Abstract:

National Collective Management Institute (LKMN) in Indonesia stated that legal music products were about 77.552.008 unit while illegal music products were about 22.0688.225 unit in 1996 and this number keeps getting worse every year. Consequently, Indonesia named as one of the countries with high piracy levels in 2005. This study models people decision toward unlawful behavior, music content piracy in particular, using agent-based modeling and simulation (ABMS). The classification of actors in the model constructed in this study are legal consumer, illegal consumer, and neutral consumer. The decision toward piracy among the actors is a manifestation of the social norm which attributes are social pressure, peer pressure, social approval, and perceived prevalence of piracy. The influencing attributes fluctuate depending on the majority of surrounding behavior called social network. There are two main interventions undertaken in the model, campaign and peer influence, which leads to scenarios in the simulation: positively-framed descriptive norm message, negatively-framed descriptive norm message, positively-framed injunctive norm with benefits message, and negatively-framed injunctive norm with costs message. Using NetLogo, the model is simulated in 30 runs with 10.000 iteration for each run. The initial number of agent was set 100 proportion of 95:5 for illegal consumption. The assumption of proportion is based on the data stated that 95% sales of music industry are pirated. The finding of this study is that negatively-framed descriptive norm message has a worse reversed effect toward music piracy. The study discovers that selecting the context-based campaign is the key process to reduce the level of intention toward music piracy as unlawful behavior by increasing the compliance awareness. The context of Indonesia reveals that that majority of people has actively engaged in music piracy as unlawful behavior, so that people think that this illegal act is common behavior. Therefore, providing the information about how widespread and big this problem is could make people do the illegal consumption behavior instead. The positively-framed descriptive norm message scenario works best to reduce music piracy numbers as it focuses on supporting positive behavior and subject to the right perception on this phenomenon. Music piracy is not merely economical, but rather social phenomenon due to the underlying motivation of the actors which has shifted toward community sharing. The indication of misconception of value co-creation in the context of music piracy in Indonesia is also discussed. This study contributes theoretically that understanding how social norm configures the behavior of decision-making process is essential to breakdown the phenomenon of unlawful behavior in music industry. In practice, this study proposes that reward-based and context-based strategy is the most relevant strategy for stakeholders in music industry. Furthermore, this study provides an opportunity that findings may generalize well beyond music piracy context. As an emerging body of work that systematically constructs the backstage of law and social affect decision-making process, it is interesting to see how the model is implemented in other decision-behavior related situation.

Keywords: music piracy, social norm, behavioral decision-making, agent-based model, value co-creation

Procedia PDF Downloads 172

Authors: Assem El-Ansary

Abstract:

This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach using the Healthcare Multi-Agent System. The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are: The Behavioral Pattern Analysis (BPA) modeling methodology. The development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases, Healthcare Multi-Agent System

Procedia PDF Downloads 526

Authors: Zahid Ullah, Atlas Khan

Abstract:

The rapid growth of data in various domains has created a pressing need for effective methods to transform this data into meaningful knowledge. In this era of big data, mathematical and statistical innovations play a crucial role in unlocking insights and facilitating informed decision-making in data analytics. This abstract aims to explore the transformative potential of these innovations and their impact on converting raw data into actionable knowledge. Drawing upon a comprehensive review of existing literature, this research investigates the cutting-edge mathematical and statistical techniques that enable the conversion of data into knowledge. By evaluating their underlying principles, strengths, and limitations, we aim to identify the most promising innovations in data analytics. To demonstrate the practical applications of these innovations, real-world datasets will be utilized through case studies or simulations. This empirical approach will showcase how mathematical and statistical innovations can extract patterns, trends, and insights from complex data, enabling evidence-based decision-making across diverse domains. Furthermore, a comparative analysis will be conducted to assess the performance, scalability, interpretability, and adaptability of different innovations. By benchmarking against established techniques, we aim to validate the effectiveness and superiority of the proposed mathematical and statistical innovations in data analytics. Ethical considerations surrounding data analytics, such as privacy, security, bias, and fairness, will be addressed throughout the research. Guidelines and best practices will be developed to ensure the responsible and ethical use of mathematical and statistical innovations in data analytics. The expected contributions of this research include advancements in mathematical and statistical sciences, improved data analysis techniques, enhanced decision-making processes, and practical implications for industries and policymakers. The outcomes will guide the adoption and implementation of mathematical and statistical innovations, empowering stakeholders to transform data into actionable knowledge and drive meaningful outcomes.

Keywords: data analytics, mathematical innovations, knowledge extraction, decision-making

Procedia PDF Downloads 52

Authors: S. Malisuwan, J. Sivaraks, N. Madan, N. Suriyakrai

Abstract:

The ever going evolution of advanced wireless technologies makes it financially impossible for military operations to completely manufacture their own equipment. Therefore, Commercial-Off-The-Shelf (COTS) and Modified-Off-The-Shelf (MOTS) are being considered in military mission with low-cost modifications. In this paper, we focus on the LTE multicast systems for military communication systems under tactical environments with jamming condition. We examine the influence of the colored noise jamming on the performance of the LTE multicast systems in terms of the average throughput. The simulation results demonstrate the degradation of the average throughput for different dynamic ranges of the colored noise jamming versus average SNR.

Keywords: performance, LTE, multicast, jamming, throughput

Procedia PDF Downloads 400

Authors: Assem El-Ansary

Abstract:

This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Intelligent Agent Reservation System (IARS). The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are developing the Behavioral Pattern Analysis (BPA) modeling methodology, and developing an interactive software tool (DECISION) which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, intelligent agent, reservation system, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

Procedia PDF Downloads 460

Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

Abstract:

Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

Procedia PDF Downloads 104