Search results for: PU decision

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: Nadia Arikat, Katharine Blain

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During the worst of the COVID pandemic, only essential treatment was provided for patients needing urgent care. With the prolonged extent of the pandemic, there has been a return to more routine referrals for paediatric dentistry advice and treatment for specialist conditions. However, some of these patients and/or their carers may have significant medical issues meaning that attending in-person appointments carries additional risks. This poses an ethical dilemma for clinicians. This project looks at how a secure video conferencing platform (“Near Me”) has been used to assess the need and urgency for in-person new patient visits, particularly for patients and families with additional risks. “Near Me” is a secure online video consulting service used by NHS Scotland. In deciding whether to bring a new patient to the hospital for an appointment, the clinical condition of the teeth together with the urgency for treatment need to be assessed. This is not always apparent from the referral letter. In addition, it is important to judge the risks to the patients and carers of such visits, particularly if they have medical issues. The use and effectiveness of “Near Me” consultations to help decide whether vulnerable paediatric patients should have in-person appointments will be illustrated and discussed using two families: one where the child is medically compromised (Alagille syndrome with previous liver transplant), and the other where there is a medically compromised parent (undergoing chemotherapy and a bone marrow transplant). In both cases, it was necessary to take into consideration the risks and moral implications of requesting that they attend the dental hospital during a pandemic. The option of remote consultation allowed further clinical information to be evaluated and the families take part in the decision-making process about whether and when such visits should be scheduled. These cases will demonstrate how medically compromised patients (or patients with vulnerable carers), could have their dental needs assessed in a socially distanced manner by video consultation. Together, the clinician and the patient’s family can weigh up the risks, with regards to COVID-19, of attending for in-person appointments against the benefit of having treatment. This is particularly important for new paediatric patients who have not yet had a formal assessment. The limitations of this technology will also be discussed. It is limited by internet availability, the strength of the connection, the video quality and families owning a device which allows video calls. For those from a lower socio-economic background or living in some rural areas, this may not be possible or limit its usefulness. For the two patients discussed in this project, where the urgency of their dental condition was unclear, video consultation proved beneficial in deciding an appropriate outcome and preventing unnecessary exposure of vulnerable people to a hospital environment during a pandemic, demonstrating the usefulness of such technology when it is used appropriately.

Keywords: COVID-19, paediatrics, triage, video consultations

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Authors: Khaled M. Alhawiti

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This paper aims to analyze the role of natural language processing (NLP). The paper will discuss the role in the context of automated data retrieval, automated question answer, and text structuring. NLP techniques are gaining wider acceptance in real life applications and industrial concerns. There are various complexities involved in processing the text of natural language that could satisfy the need of decision makers. This paper begins with the description of the qualities of NLP practices. The paper then focuses on the challenges in natural language processing. The paper also discusses major techniques of NLP. The last section describes opportunities and challenges for future research.

Keywords: data retrieval, information retrieval, natural language processing, text structuring

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Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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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: Nugzar Todua, Charita Jashi

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This paper is focusing on the attitude of Georgian consumers toward social media, influence of social media on consumer buying behavior. The purpose of this paper is to explore the impact and usage of social media marketing strategies for Georgian companies and consumers in the new reality of Georgia. There is a lack of research on social media marketing in Georgia, especially the topic which analyzes the possible purchase influence of consumers. The result of marketing research has revealed that social webs are mostly used by Georgian consumers, but they have little impact on the buying decision. The research method was exploratory in nature in the sense that there is no previous academic research about consumers’ attitude towards social media marketing.

Keywords: marketing research, purchasing behavior, social media marketing, social networking sites

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Authors: Luay Jum'a

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Many challenges are facing third-party logistics (3PL) providers in the domestic and global markets which create a volatile decision making environment. All these challenges such as managing changes in consumer behaviour, demanding expectations from customers and time compressions have turned into complex problems for 3PL providers. Since the movement towards increased outsourcing outpaces movement towards insourcing, the need to achieve a competitive advantage over competitors in 3PL market increases. This trend continues to grow over the years and as a result, areas of strengths and improvements are highlighted through the analysis of the LSQ factors that lead to B2B customers’ satisfaction which become a priority for 3PL companies. Consequently, 3PL companies are increasingly focusing on the most important issues from the perspective of their customers and relying more on this value of information in making their managerial decisions. Therefore, this study is concerned with providing guidance for improving logistics service quality (LSQ) levels in the context of 3PL industry in Jordan. The study focused on the most important factors in LSQ and used a managerial tool that guides 3PL companies in making LSQ improvements based on a quadrant analysis of two main dimensions: LSQ declared importance and LSQ inferred importance. Although, a considerable amount of research has been conducted to investigate the relationship between logistics service quality (LSQ) and customer satisfaction, there remains a lack of developing managerial tools to aid in the process of LSQ improvement decision-making. Moreover, the main advantage for the companies to use 3PL service providers as a trend is due to the realised percentage of cost reduction on the total cost of logistics operations and the incremental improvement in customer service. In this regard, having a managerial tool that help 3PL service providers in managing the LSQ factors portfolio effectively and efficiently would be a great investment for service providers. One way of suggesting LSQ improvement actions for 3PL service providers is via the adoption of analysis tools that perform attribute categorisation such as Importance–Performance matrix. In mind of the above, it can be stated that the use of quadrant analysis will provide a valuable opportunity for 3PL service providers to identify improvement opportunities as customer service attributes or factors importance are identified in two different techniques that complete each other. Moreover, the data were collected through conducting a survey and 293 questionnaires were returned from business-to-business (B2B) customers of 3PL companies in Jordan. The results showed that the LSQ factors vary in their importance and 3PL companies should focus on some LSQ factors more than other factors. Moreover, ordering procedures, timeliness/responsiveness LSQ factors considered being crucial in 3PL businesses and therefore they need to have more focus and development by 3PL service providers in the Jordanian market.

Keywords: logistics service quality, managerial decisions, quadrant analysis, third party logistics service provider

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Authors: Samar Mousa, Ryan Kerstein, Mohanad Adam

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Regional anaesthesia has been associated with favourable outcomes in patients undergoing a wide range of surgeries. Beneficial effects have been demonstrated in terms of postoperative respiratory and cardiovascular endpoints, 7-day survival, time to ambulation and hospital discharge, and postoperative analgesia. Our project aimed at assessing the regional anaesthesia practice in the plastic surgery department of Buckinghamshire trust and finding out ways to improve the service in collaboration with the anaesthesia team. It is a retrospective study associated with a questionnaire filled out by plastic surgeons and anaesthetists to get the full picture behind the numbers. The study period was between 1/3/2022 and 23/5/2022 (12 weeks). The operative notes of all patients who had an operation under plastic surgery, whether emergency or elective, were reviewed. The criteria of suitable candidates for the regional block were put by the consultant anaesthetists as follows: age above 16, single surgical site (arm, forearm, leg, foot), no drug allergy, no pre-existing neuropathy, no bleeding disorders, not on ant-coagulation, no infection to the site of the block. For 12 weeks, 1061 operations were performed by plastic surgeons. Local cases were excluded leaving 319 cases. Of the 319, 102 patients were suitable candidates for regional block after applying the previously mentioned criteria. However, only seven patients had their operations under the regional block, and the rest had general anaesthesia that could have been easily avoided. An online questionnaire was filled out by both plastic surgeons and anaesthetists of different training levels to find out the reasons behind the obvious preference for general over regional anaesthesia, even if this was against the patients’ interest. The questionnaire included the following points: training level, time taken to give GA or RA, factors that influence the decision, percentage of RA candidates that had GA, reasons behind this percentage, recommendations. Forty-four clinicians filled out the questionnaire, among which were 23 plastic surgeons and 21 anaesthetists. As regards the training level, there were 21 consultants, 4 associate specialists, 9 registrars, and 10 senior house officers. The actual percentage of patients who were good candidates for RA but had GA instead is 93%. The replies estimated this percentage as between 10-30%. 29% of the respondents thought that this percentage is because of surgeons’ preference to have GA rather than RA for their operations without medical support for the decision. 37% of the replies thought that anaesthetists prefer giving GA even if the patient is a suitable candidate for RA. 22.6% of the replies thought that patients refused to have RA, and 11.3% had other causes. The recommendations were in 5 main accesses, which are protocols and pathways for regional blocks, more training opportunities for anaesthetists on regional blocks, providing a separate block room in the hospital, better communication between surgeons and anaesthetists, patient education about the benefits of regional blocks.

Keywords: regional anaesthesia, regional block, plastic surgery, general anaesthesia

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Authors: Niina Meriläinen

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Digital platforms are arenas for dialogue, various kinds of political debates, information and news gathering, policymaking, and social change processes. Human rights serve as examples of social and political issues that are universally noted as principles and yet often violated on digital platforms as well as in the analog world. Digital platforms in this study are different Internet sites, blogs, discussion platforms, social media apps, and gaming. Various actors, from human rights activists and non-governmental organizations to individual people, governments, and corporations, use digital platforms along with analog arenas to discuss and defend human rights, while violators can find new victims and continue violating rights on the same platforms. Digital platforms create opportunities for various women and minorities to empower themselves and others and to be active in various arenas of society and policymaking. At the same time, digital platforms pose threats to human rights globally, especially to women, girls, and minorities. The results of this meta-study of n=120 academic case studies indicate that more research is needed to determine the framework of human rights and human rights on digital platforms. A broad discussion must be had on what human rights require in the digital realm and how ICTs may enhance or threaten our ability to respect, protect, and fulfill a wide variety of human rights while various digital platforms pose multiple threats to human rights. This relates to the willingness of political decision-makers to act upon various crimes committed on and with online platforms. More research is needed to determine the framework of digital human rights and human rights on digital platforms in relation to political communication and decision-making. It is important to develop a framework in which these are defined. It must be discussed who participates in this process: those whose rights are violated, companies that profit by selling our personal data, activists, governments, and some unknown actors. In the end, the question comes back to who has the power to define what we talk about, when, and where. This use of power plays a big role. Digital platforms illustrate the darker side of technological progress, which, on the one hand, has given various people the possibility to engage in society, empower themselves, and take ownership of their rights globally. At the same time, the platforms enable others to use the same platforms to find victims, abuse them, and exploit them. Bullying, harassment, and violence are rampant on various digital platforms, where minorities and people with limited support are victims. There is indeed a need for a discussion of normative values in the era of fake news, the power of influencers, Trumpism, and institutionalized disregard for human rights, gender equality, and the elimination of gender-based violence online. Attention and obligations must be placed on politicians and internet architecture, such as corporations, and their roles in human rights and their violations online.

Keywords: human rights, digital platforms, violations, internet, social media

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Authors: P. T. Collett, M. Kershaw

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Introduction: The discussion regarding which method of anesthesia provides better results for lower limb arthroplasty is a continuing debate. Multiple meta-analysis has been performed with no clear consensus. The current recommendation is to use neuraxial anesthesia for lower limb arthroplasty; however, the evidence to support this decision is weak. The Enhanced Recovery After Surgery (ERAS) society has recommended, either technique can be used as part of a multimodal anesthetic regimen. A local study was performed to see if the current anesthetic practice correlates with the current recommendations and to evaluate the efficacy of the different techniques utilized. Method: 90 patients who underwent total hip or total knee replacements at Nevill Hall Hospital between February 2019 to July 2019 were reviewed. Data collected included the anesthetic technique, day one opiate use, pain score, and length of stay. The data was collected from anesthetic charts, and the pain team follows up forms. Analysis: The average of patients undergoing lower limb arthroplasty was 70. Of those 83% (n=75) received a spinal anaesthetic and 17% (n=15) received a general anaesthetic. For patients undergoing knee replacement under general anesthetic the average day, one pain score was 2.29 and 1.94 if a spinal anesthetic was performed. For hip replacements, the scores were 1.87 and 1.8, respectively. There was no statistical significance between these scores. Day 1 opiate usage was significantly higher in knee replacement patients who were given a general anesthetic (45.7mg IV morphine equivalent) vs. those who were operated on under spinal anesthetic (19.7mg). This difference was not noticeable in hip replacement patients. There was no significant difference in length of stay between the two anesthetic techniques. Discussion: There was no significant difference in the day one pain score between the patients who received a general or spinal anesthetic for either knee or hip replacements. The higher pain scores in the knee replacement group overall are consistent with this being a more painful procedure. This is a small patient population, which means any difference between the two groups is unlikely to be representative of a larger population. The pain scale has 4 points, which means it is difficult to identify a significant difference between pain scores. Conclusion: There is currently little standardization between the different anesthetic approaches utilized in Nevill Hall Hospital. This is likely due to the lack of adherence to a standardized anesthetic regimen. In accordance with ERAS recommends a standard anesthetic protocol is a core component. The results of this study and the guidance from the ERAS society will support the implementation of a new health board wide ERAS protocol.

Keywords: anaesthesia, orthopaedics, intensive care, patient centered decision making, treatment escalation

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Authors: N. Sopipan

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In this paper, we study of rainfall time series of weather stations in Nakhon Ratchasima province in Thailand using various statistical methods enabled to analyse the behaviour of rainfall in the study areas. Time-series analysis is an important tool in modelling and forecasting rainfall. ARIMA and Holt-Winter models based on exponential smoothing were built. All the models proved to be adequate. Therefore, could give information that can help decision makers establish strategies for proper planning of agriculture, drainage system and other water resource applications in Nakhon Ratchasima province. We found the best perform for forecasting is ARIMA(1,0,1)(1,0,1)12.

Keywords: ARIMA Models, exponential smoothing, Holt-Winter model

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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: Z. Ulukan, E. Demircioğlu,

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Facility location is a complex real-world problem which needs a strategic management decision. This paper provides a general review on studies, efforts and developments in Facility Location Problems which are classical optimization problems having a wide-spread applications in various areas such as transportation, distribution, production, supply chain decisions and telecommunication. Our goal is not to review all variants of different studies in FLPs or to describe very detailed computational techniques and solution approaches, but rather to provide a broad overview of major location problems that have been studied, indicating how they are formulated and what are proposed by researchers to tackle the problem. A brief, elucidative table based on a grouping according to “General Problem Type” and “Methods Proposed” used in the studies is also presented at the end of the work.

Keywords: discrete location problems, exact methods, heuristic algorithms, single source capacitated facility location problems

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Authors: R. Dariani, S. Schmidt, R. Kasper

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Based on a non-linear single track model which describes the dynamics of vehicle, an optimal path planning strategy is developed. Real time optimization is used to generate reference control values to allow leading the vehicle alongside a calculated lane which is optimal for different objectives such as energy consumption, run time, safety or comfort characteristics. Strict mathematic formulation of the autonomous driving allows taking decision on undefined situation such as lane change or obstacle avoidance. Based on position of the vehicle, lane situation and obstacle position, the optimization problem is reformulated in real-time to avoid the obstacle and any car crash.

Keywords: autonomous driving, obstacle avoidance, optimal control, path planning

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Authors: Maryam Mostafaee, Hassan Sadeghi Naeini, Sara Mostowfi

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Today’s Knowledge management (KM), plays an important role in organizations. Basically, knowledge management is in the relation of using it for taking advantage of work forces in an organization for forwarding the goals and demand of that organization used at the most. The purpose of knowledge management is not only to manage existing documentation, information, and Data through an organization, but the most important part of KM is to control most important and key factor of those information and Data. For sure it is to chase the information needed for the employees in the right time of needed to take from genuine source for bringing out the best performance and result then in this matter the performance of organization will be at most of it. There are a lot of definitions over the objective of management released. Management is the science that in force the accurate knowledge with repeating to the organization to shape it and take full advantages for reaching goals and targets in the organization to be used by employees and users, but the definition of Knowledge based on Kalinz dictionary is: Facts, emotions or experiences known by man or group of people is ‘ knowledge ‘: Based on the Merriam Webster Dictionary: the act or skill of controlling and making decision about a business, department, sport team, etc, based on the Oxford Dictionary: Efficient handling of information and resources within a commercial organization, and based on the Oxford Dictionary: The art or process of designing manufactured products: the scale is a beautiful work of industrial design. When knowledge management performed executive in universities, discovery and create a new knowledge be facilitated. Make procedures between different units for knowledge exchange. College's officials and employees understand the importance of knowledge for University's success and will make more efforts to prevent the errors. In this strategy, is explored factors and affective trends and manage of it in University. In this research, Iranian universities for a time being analyzed that over usage of knowledge management, how they are behaving and having understood this matter: 1. Discovery of knowledge management in Iranian Universities, 2. Transferring exciting knowledge between faculties and unites, 3. Participate of employees for getting and using and transferring knowledge, 4.The accessibility of valid sources, 5. Researching over factors and correct processes in the university. We are pointing in some examples that we have already analyzed which is: -Enabling better and faster decision-making, -Making it easy to find relevant information and resources, -Reusing ideas, documents, and expertise, -Avoiding redundant effort. Consequence: It is found that effectiveness of knowledge management in the Industrial design field is low. Based on filled checklist by Education officials and professors in universities, and coefficient of effectiveness Calculate, knowledge management could not get the right place.

Keywords: knowledge management, industrial design, educational curriculum, learning performance

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Authors: M. S. Sreejith, Steffy Joy, Abhishesh Pal, Beom-Sahng Ryuh, V. R. Sanal Kumar

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In this paper an attempt has been made for the design of a robotic library using an intelligent system. The robot works on the ARM microprocessor, motor driver circuit with 5 degrees of freedom with Wi-Fi and GPS based communication protocol. The authenticity of the library books is controlled by RFID. The proposed robotic library system is facilitated with embedded system and ARM. In this library issuance system the previous potential readers’ authentic review reports have been taken into consideration for recommending suitable books to the deserving new users and the issuance of books or periodicals is based on the users’ decision. We have conjectured that the Wi-Fi based robotic library management system would allow fast transaction of books issuance and it also produces quality readers.

Keywords: GPS bsed based Robotic library, library management system, robotic library, Wi-Fi library

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Authors: Nazri Kama, Sufyan Basri, Roslina Ibrahim

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It is important to manage the changes in the software to meet the evolving needs of the customer. Accepting too many changes causes delay in the completion and it incurs additional cost. One type of information that helps to make the decision is through change impact analysis. Current impact analysis approaches assume that all classes in the class artifact are completely developed and the class artifact is used as a source of analysis. However, these assumptions are impractical for impact analysis in the software development phase as some classes in the class artifact are still under development or partially developed that leads to inaccuracy. This paper presents a novel impact analysis approach to be used in the software development phase. The significant achievements of the approach are demonstrated through an extensive experimental validation using three case studies.

Keywords: software development, impact analysis, traceability, static analysis.

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Authors: Nayera E. Hassan, Sahar A. El-Masry, Rokia El-Banna, Mohamed S. El Hussieny

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There are several different modalities for treatment of obesity. Common intervention methods for obesity include low-calorie diet, exercise. Also acupuncture has shown good therapeutic results in the treatment of obesity. A recent clinical observation showed that laser acupuncture could reduce body weight and body mass index in obese persons. So, the aim of this research is focused on body composition changes as related to type of intervention, before and after intentional weight loss in overweight and obesity. 76 subjects were included in the study analysis. The present study recommended that every obese female must do lipid profile and fasting blood sugar analysis before weight-loss intervention to take the decision of which method should be used.

Keywords: obesity, weight-loss, body composition, modalities

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Authors: Patricia Sanz-Cordoba, Bernd Theilen

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This article analyzes the conditions where decentralization and partial tax harmonization in a coalition of asymmetric jurisdictions plays a role in the fight of fiscal competition (i.e. the race to bottom). Starting from a centralized economies, we use the ZM-W model to analyze the fiscal competition and coordination among three countries. We find that the asymmetry of jurisdictions facilitates partial tax harmonization between jurisdictions when these asymmetries are not too large. Furthermore, when the asymmetries are large enough, the level of labor tax plays an important role in the decision of decentralize capital tax. Accordingly, decentralization is achievable when labor tax is low. This result indicates that decentralization and partial tax harmonization between jurisdictions can be possible results in order to fight the negative externalities from fiscal competition, and more in the European Union countries where the asymmetries are substantial.

Keywords: centralization, decentralization, fiscal competition, partial tax harmonization

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

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Authors: Sakapas Saengchai

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Study on the development of people's participation in environmental development was a qualitative research method. Data were collected by participant observation, in-depth interview and discussion group in Pathumthani province. The study indicated that 1) People should be aware of environmental information from government agencies. 2) People in the community should be able to brainstorm information, exchange information about community environment development. 3) People should have a role with community leaders. 4) People in the community should have a role to play in the implementation of projects and activities in the development of the environment and 5) citizens, community leaders, village committee have directed the development of the area. Maintaining a community environment with a shared decision. By emphasizing the process of participation, self-reliance, mutual help, and responsibility for one's own community. Community empowerment strengthens the sustainable spatial development of the environment.

Keywords: people, participation, community, environment

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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: 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

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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 275

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 436

Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

Abstract:

In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Irfan Ullah Munir, Shen Yue, Muhammad Shahzad Ijaz, Saad Hussain, Syeda Yumna Zaidi

Abstract:

Financial literacy is fundamental to every decision-making process and has received attention from researchers, regulatory bodies and policy makers in the recent past. This study is an attempt to evaluate financial literacy in an emerging economy, particularly Pakistan, and its influence on people's stock market participation. Data of this study was collected through a structured questionnaire from a sample of 300 respondents. EFA is used to check the convergent and discriminant validity. Data is analyzed using Hayes (2013) approach. A set of demographic control variables that have passed the mean difference test is used. We demonstrate that participants with financial literacy tend to invest more in the stock market. We also find that association among financial literacy and participation in stock market gets moderated by gender.

Keywords: Financial literacy, Stock market participation, Gender, PSX

Procedia PDF Downloads 187

Authors: Le Chen

Abstract:

This paper presents an efficient tool platform scheme to ensure quality protection throughout the software development process. The main principle is to manage the information of requirements, design, development, testing, operation and maintenance process with proper tools, and to set up the quality standards of each process. Through the tools’ display and summary of quality standards, the quality standards can be visualizad and ready for policy decision, which is called Quality Gate in this paper. In addition, the tools are also integrated to achieve the exchange and relation of information which highly improving operational efficiency. In this paper, the feasibility of the scheme is verified by practical application of development projects, and the overall information display and data mining are proposed to be further improved.

Keywords: efficiency, quality gate, software process, tools

Procedia PDF Downloads 348