Search results for: medical decision

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: 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: Javed Mohammed

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Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

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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: 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: Selina Schwaabe

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Community pharmacies deliver high-quality health care and are responsible for medication safety. During the pandemic, accessibility to the nearest pharmacy became more essential to get vaccinated against Covid-19 and to get medical aid. The government's goal is to ensure nationwide, reachable, and affordable medical health care services by pharmacies. Therefore, the density of community pharmacies matters. Overall, the density of community pharmacies is fluctuating, with slightly decreasing tendencies in some countries. So far, the literature has shown that changes in the system affect prices and density. However, a European overview of the development of the density of community pharmacies and its triggers is still missing. This research is essential to counteract against decreasing density consulting in a lack of professional health care through pharmacies. The analysis focuses on liberal versus regulated market structures, mail-order prescription drug regulation, and third-party ownership consequences. In a panel analysis, the relative influence of the measures is examined across 27 European countries over the last 21 years. In addition, the paper examines seven selected countries in depth, selected for the substantial variance in their pharmacy system: Germany, Austria, Portugal, Denmark, Sweden, Finland and Poland. Overall, the results show that regulated pharmacy markets have over 10.75 pharmacies/100.000 inhabitants more than liberal markets. Further, mail-order prescription drugs decrease the density by -17.98 pharmacies/100.000 inhabitants. Countries allowing third-party ownership have 7.67 pharmacies/100.000 inhabitants more. The results are statistically significant at a 0.001 level. The output of this analysis recommends regulated pharmacy markets, with a ban on mail-order prescription drugs allowing third-party ownership to support nationwide medical health care through community pharmacies.

Keywords: community pharmacy, market conditions, pharmacy, pharmacy market, pharmacy lobby, prescription, e-prescription, ownership structures

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Authors: M. G. Ghanem, A. M. M. A. Allam, Diaa E. Fawzy, Mehmet Faruk Cengiz

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This paper is devoted to the design and implementation of a smartwatch textile antenna for Wi-Fi bio-medical applications in millimetric wave bands. The antenna is implemented on a leather textile-based substrate to be embedded in a smartwatch. It enables the watch to pick Wi-Fi signals without the need to be connected to a mobile through Bluetooth. It operates at 60 GHz or WiGig (Wireless Gigabit Alliance) band with a wide band for higher rate applications. It also could be implemented over many stratified layers of the body organisms to be used in the diagnosis of many diseases like diabetes and cancer. The structure is designed and simulated using CST (Studio Suite) program. The wearable patch antenna has an octagon shape, and it is implemented on leather material that acts as a flexible substrate with a size of 5.632 x 6.4 x 2 mm3, a relative permittivity of 2.95, and a loss tangent of 0.006. The feeding is carried out using differential feed (discrete port in CST). The work provides five antenna implementations; antenna without ground, a ground is added at the back of the antenna in order to increase the antenna gain, the substrate dimensions are increased to 15 x 30 mm2 to resemble the real hand watch size, layers of skin and fat are added under the ground of the antenna to study the effect of human body tissues human on the antenna performance. Finally, the whole structure is bent. It is found that the antenna can achieve a simulated peak realized gain in dB of 5.68, 7.28, 6.15, 3.03, and 4.37 for antenna without ground, antenna with the ground, antenna with larger substrate dimensions, antenna with skin and fat, and bent structure, respectively. The antenna with ground exhibits high gain; while adding the human organisms absorption, the gain is degraded because of human absorption. The bent structure contributes to higher gain.

Keywords: bio medical engineering, millimetric wave, smart watch, textile antennas, Wi-Fi

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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: Eunkyo Kang, Jihye Lee, Jiyeon Choo

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Background: Pediatric palliative care has been increasing, and the number of studies has focused on the age at which pediatric patient can be notified their terminal illness, pediatric advanced care planning (ACP) and palliative care. However, there is a lack of research on health professionals’ perception. Aim: We aimed to investigate the perceptions of healthcare professionals about appropriate age disclosing terminal illness, awareness of ACP, and the relationship between ACP knowledge and the preference for palliative care for children. Methods: We administered nationwide questionnaires to 928 physicians from the 12 hospitals and the Korean Medical Association and 1,241 individuals of the general Korean population. We asked about the age at which the pediatric patients could be notified of their terminal illness, by 4 groups; 4 years old or older, 12 years old or older, 15 years old or older, or not. In addition, we surveyed the questionnaires about the knowledge of ACP of the medical staff, the preference of the pediatric hospice palliative care, aggressive treatment, and life-sustaining treatment preference. Results: In the appropriate age disclosing terminal illness, there were more respondents in the physicians than in the general population who thought that it was possible even at a younger age. Palliative care preference in pediatric patients who were expected to expire within months was higher when health care professionals had knowledge of ACPs compared to those without knowledge. The same results were obtained when deaths were expected within weeks or days. The age of the terminal status notification, the health care professionals who thought to be available at a lower age have a higher preference for palliative care and has less preference for aggressive treatment and life-sustaining treatment. Conclusion: Despite the importance of pediatric palliative care, our study confirmed that there is a difference in the preference of the health care professionals for pediatric palliative care according to the ACP knowledge of the medical staff or the appropriate age disclosing terminal illness. Future research should focus on strategies for inducing changes in perceptions of health care professionals and identifying other obstacles for the pediatric palliative care.

Keywords: pediatric palliative care, disclosing terminal illness, palliative care, advanced care planning

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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: Miriam I. Jimenez-Perez, Mariana C. Orellana-Haro, Carolina Guzman-Brambila

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As part of microbiology and dietetics courses, students of medicine and nutrition analyze the main pathogenic microorganisms and perform dietary analyzes. The course of microbiology describes in a general way the main pathogens including bacteria, viruses, fungi, and parasites, as well as their interaction with the human species. We hypothesize that lack of practical application of the course causes the students not to find the value and the clinical application of it when in reality it is a matter of great importance for healthcare in our country. The courses of the medical microbiology and dietetics are mostly theoretical and only a few hours of laboratory practices. Therefore, it is necessary the incorporation of new innovative techniques that involve more practices and community fieldwork, real cases analysis and real-life situations. The purpose of this intervention was to incorporate real-world learning experiences in the instruction of medical microbiology and dietetics courses, in order to improve the learning process, understanding and the application in the field. During a period of 6 months, medicine and nutrition students worked in a community of urban poverty. We worked with 90 children between 4 and 6 years of age from low-income families with no access to medical services, to give an infectious diagnosis related to nutritional status in these children. We expect that this intervention would give a different kind of context to medical microbiology and dietetics students improving their learning process, applying their knowledge and laboratory practices to help a needed community. First, students learned basic skills in microbiology diagnosis test during laboratory sessions. Once, students acquired abilities to make biochemical probes and handle biological samples, they went to the community and took stool samples from children (with the corresponding informed consent). Students processed the samples in the laboratory, searching for enteropathogenic microorganism with RapID™ ONE system (Thermo Scientific™) and parasites using Willis and Malloy modified technique. Finally, they compared the results with the nutritional status of the children, previously measured by anthropometric indicators. The anthropometric results were interpreted by the OMS Anthro software (WHO, 2011). The microbiological result was interpreted by ERIC® Electronic RapID™ Code Compendium software and validated by a physician. The results were analyses of infectious outcomes and nutritional status. Related to fieldwork community learning experiences, our students improved their knowledge in microbiology and were capable of applying this knowledge in a real-life situation. They found this kind of learning useful when they translate theory to a real-life situation. For most of our students, this is their first contact as health caregivers with real population, and this contact is very important to help them understand the reality of many people in Mexico. In conclusion, real-world or fieldwork learning experiences empower our students to have a real and better understanding of how they can apply their knowledge in microbiology and dietetics and help a much- needed population, this is the kind of reality that many people live in our country.

Keywords: real-world learning experiences, medical microbiology, dietetics, nutritional status, infectious status.

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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: N. H. D. P. Fonseka, I. H. Rajapakse, A. S. Dissanayake

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Background: Problem drinking, namely alcohol dependence (AD) and alcohol abuse (AA) are associated with major medical, social and economic adverse consequences. Problem drinking behavior is noted among those admitted to hospitals due to alcohol-related medical/surgical complaints as well as those with unrelated complaints. Literature shows an association between alcohol consumption and depression. Aims of this study were to determine the frequency of problem drinking and depression among males with a history of alcohol consumption tertiary care setting in Southern Sri Lanka. Method: Two-hundred male patients who consumed alcohol, receiving care in medical and surgical wards in Teaching Hospital Galle, were assessed. A validated J12 questionnaire of the Mini International Neuropsychiatric Interview was administered to determine frequency AA and AD. A validated PHQ 9 questionnaire to determine the prevalence and severity of depression. Results: Sixty-three participants (31%) had problem drinking. Of them, 61% had AD, and 39% had AA. Depression was noted in 39 (19%) subjects. In those who reported alcohol consumption not amounting to problem drinking, depression was noted in 23 (16%) participants. Mild depression was seen in 17, moderate in five and moderately severe in one. Among those who had problem drinking, 16 (25%) had depression. Mild depression was seen in four, moderate in seven, moderately severe in three and severe in two. Conclusions: A high proportion alcohol users had problem drinking. Adverse consequences associated with problem drinking places a major strain on the health system especially in a low resource setting where healthcare spending is limited and alcohol cessation support services are not well organised. Thus alcohol consumption and problem drinking behaviour need to be inquired into all medical consultations. Community prevalence of depression in Sri Lanka is approximately 10%. Depression among those consuming alcohol was two times higher compared to the general population. The rates of depression among those with problem drinking were especially high being 2.5 times more common than in the general population. A substantial proportion of these patients with depression had moderately severe or severe depression. When depression coexists with problem drinking, it may increase the tendency to consume alcohol as well as act as a barrier to the success of alcohol cessation interventions. Thus screening all patients who consume alcohol for depression, especially those who are problem drinkers becomes an important step in their clinical evaluation. In addition, in view of the high prevalence of problem drinking and coexistent depression, the need to organize a structured alcohol cessation support service in Sri Lanka as well as the need for increasing access to psychological evaluation and treatment of those with problem drinking are highlighted.

Keywords: alcohol abuse, alcohol, depression, problem drinking

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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: Yong Seong Kim, Seongbin Hong, So Hun Kim, Moonsuk Nam

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Background: Patients who undergo thyroidectomy due to thyroid cancer often complain weight gain, although they are on suppressive thyroid hormone treatment. The aim of this study is to know whether thyroid cancer patients gain the weight after thyroidectomy and weight change is dependent on estrogen state or use of rhTSH. Material and Method: We performed a retrospective chart review of subjects receiving medical care at an academic medical center. Two hundred two patients who underwent total thyroidectomy were included. As a control group, patients with thyroid nodule and euthyroidism were matched for age, gender, menopausal status. The weight changes occurring over first one year and thyroid function were assessed. Results: Mean age was 51±12 years and patients was composed with 38% of premenopausal, 15 % perimenopausal women, 37% of postmenopausal women and 20% of men. Patients with thyroid cancer gained 2.2 kg during the first year. It’ was not significantly different with control. However, weigh change in perimenopausal and post menopausal women gained more weight than control (P <0.05). Age, baseline body weight and weight gain were not correlated. Discussion: Patient who had undergone thyroidectomy gained more weight than their control, especially in peri- and postmenopausal women. Patients in this age should be monitored for their weight carefully.

Keywords: weight gain, thyroidectomy, thyroid cancer, weight chance

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Authors: Sakapas Saengchai

Abstract:

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

Abstract:

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

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

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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

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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

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