Search results for: medical decision

Authors: R. H. Fattepur, Sameer R. Fattepur, D. K. Sreekantha

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Dairy Farming is one of the key industries in India. India is the leading producer and also the consumer of milk, milk-based products in the world. In this paper, we have attempted to the replace the human expert system and to develop an artificial expert system prototype to increase the speed and accuracy of decision making dairy farming credit risk evaluation. Fuzzy logic is used for dealing with uncertainty, vague and acquired knowledge, fuzzy rule base method is used for representing this knowledge for building an effective expert system.

Keywords: expert system, fuzzy logic, knowledge base, dairy farming, credit risk

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Authors: Emmanuel Barrantes Chaves, Ernesto Rivera Alvarado

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This paper presents a method to enable agents for the Terraria game to evaluate algorithms commonly used in general video game artificial intelligence competitions. The usage of the ‘You Only Look Once’ model in the first layer of the process obtains information from the screen, translating this information into a video game description language known as “Video Game Description Language”; the agents take that as input to make decisions. For this, the state-of-the-art algorithms were tested and compared; Monte Carlo Tree Search and Rolling Horizon Evolutionary; in this case, Rolling Horizon Evolutionary shows a better performance. This approach’s main advantage is that a VGDL beforehand is unnecessary. It will be built on the fly and opens the road for using more games as a framework for AI.

Keywords: AI, MCTS, RHEA, Terraria, VGDL, YOLOv5

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Authors: ATM Emdadul Haque

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Phosphorus is an essential nutrient which is regularly consumed with food and exists in the body as phosphate. Phosphate is an important component of cellular structures and needed for bone mineralization. Excessive accumulation of phosphate is an important driving factor of mortality in chronic renal failure patients; of relevance, these patients are usually provided health care by doctors, nurses, and pharmacists. Hence, this study was planned to determine the level of awareness of the future healthcare providers about the phosphate-containing foods and beverages and to access their knowledge on the harmful effects of excess phosphate consumption. A questionnaire was developed and distributed among the year-1 medical, nursing and pharmacy students. 432 medical, nursing and pharmacy students responded with age ranging from 18-24 years. About 70% of the respondents were female with a majority (90.7%) from Malay ethnicity. Among the respondents, 29.9% were medical, 35.4% were the pharmacy and 34.7% were nursing students. 79.2% students knew that phosphate was an important component of the body, but only 61.8% knew that consuming too much phosphate could be harmful to the body. Despite 97% of the students knew that carbonated soda contained high sugar, surprisingly 77% of them did not know the presence of high phosphate in the same soda drinks; in the similar line of observation, 67% did not know the presence of it in the fast food. However, it was encouraging that 94% of the students wanted to know more about the effects of phosphate consumption, 74.3% were willing to give up drinking soda and eating fast food, and 52% considered taking green coconut water instead of soda drinks. It is, therefore, central to take an educational initiative to increase the awareness of the future healthcare providers about phosphate-containing food and its harmful effects in excessive consumptions.

Keywords: high phosphate containing foods and beverages, excessive consumption, future health care providers, phosphorus

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Authors: Ruzanna Muradyan

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Medical data mining is a crucial field in contemporary healthcare that offers cutting-edge tactics with enormous potential to transform patient care. This abstract examines how sophisticated data mining techniques could transform the healthcare industry, with a special focus on how they might improve patient outcomes. Healthcare data repositories have dynamically evolved, producing a rich tapestry of different, multi-dimensional information that includes genetic profiles, lifestyle markers, electronic health records, and more. By utilizing data mining techniques inside this vast library, a variety of prospects for precision medicine, predictive analytics, and insight production become visible. Predictive modeling for illness prediction, risk stratification, and therapy efficacy evaluations are important points of focus. Healthcare providers may use this abundance of data to tailor treatment plans, identify high-risk patient populations, and forecast disease trajectories by applying machine learning algorithms and predictive analytics. Better patient outcomes, more efficient use of resources, and early treatments are made possible by this proactive strategy. Furthermore, data mining techniques act as catalysts to reveal complex relationships between apparently unrelated data pieces, providing enhanced insights into the cause of disease, genetic susceptibilities, and environmental factors. Healthcare practitioners can get practical insights that guide disease prevention, customized patient counseling, and focused therapies by analyzing these associations. The abstract explores the problems and ethical issues that come with using data mining techniques in the healthcare industry. In order to properly use these approaches, it is essential to find a balance between data privacy, security issues, and the interpretability of complex models. Finally, this abstract demonstrates the revolutionary power of modern data mining methodologies in transforming the healthcare sector. Healthcare practitioners and researchers can uncover unique insights, enhance clinical decision-making, and ultimately elevate patient care to unprecedented levels of precision and efficacy by employing cutting-edge methodologies.

Keywords: data mining, healthcare, patient care, predictive analytics, precision medicine, electronic health records, machine learning, predictive modeling, disease prognosis, risk stratification, treatment efficacy, genetic profiles, precision health

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Authors: Nahid Tavakoli, Mohammad H. Yarmohammadian, Ali Samimi

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In earthquake situation, medical response communities such as field and referral hospitals are challenged with injured victims’ identification and tracking. In our project, it was developed a patient tracking platform (PTP) where first responders triage the patients with an electronic tag which report the location and some information of each patient during his/her movement. This platform includes: 1) near field communication (NFC) tags (ISO 14443), 2) smart mobile phones (Android-base version 4.2.2), 3) Base station laptops (Windows), 4) server software, 5) Android software to use by first responders, 5) disaster command software, and 6) system architecture. Our model has been completed through literature review, Delphi technique, focus group, design the platform, and implement in an earthquake exercise. This paper presents consideration for content, function, and technologies that must apply for patient tracking in medical emergencies situations. It is demonstrated the robustness of the patient tracking platform (PTP) in tracking 6 patients in a simulated earthquake situation in the yard of the relief and rescue department of Isfahan’s Red Crescent.

Keywords: test and evaluation, patient tracking platform, earthquake, simulation

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Authors: Razieh Khalafi

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The brain is the information processing centre of the human body. Stimuli in the form of information are transferred to the brain and then brain makes the decision on how to respond to them. In this research, we propose a new partial differential equation which analyses the EEG signals and make a relationship between the incoming stimuli and the brain response to them. In order to test the proposed model, a set of external stimuli applied to the model and the model’s outputs were checked versus the real EEG data. The results show that this model can model the EEG signal well. The proposed model is useful not only for modelling of EEG signal in case external stimuli but it can be used for modelling of brain response in case of internal stimuli.

Keywords: brain, stimuli, partial differential equation, response, EEG signal

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Authors: Emily Gould, Walter Wehremeyer, David Greaves, Rodney Turtle

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This paper considers current thinking on the pathway for electric vehicles, identifying the development blocks of alternative innovation within the market and analyse technological lock-in. The relationship between transition pathways and technological lock-in is largely under-researched particularly in the field of e-mobility. This paper is based on a study with three commercial-urban fleets that examines strategic decisions in new technology adaption alongside vehicle procurement and driver perspective. The paper will analyse the fleet’s decision matrix upon electric vehicles and seek to understand the influence of company culture, strategy and technology applicability, within the context of transition pathways.

Keywords: electric vehicles, fleets, path dependencies, transition pathways

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Authors: Soheila Sadeghi

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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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Authors: Melvin Ouma

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Language is one of the most crucial tools in medical interaction. Its importance is as great today as it was many decades ago. Difficulty in openly discussing certain diseases and body parts is one of the challenges in language use in medical contexts. Guided by H. P. Grice’s Cooperative Principle, this paper explores the flouting of the cooperative principles in Swahili speaking medical setting. The paper examines how men flout the maxims using the Swahili language when reporting reproductive health problems to the doctor. The data used was gathered from a qualitative study carried out in a reproductive health clinic in a public facility in Nakuru County, Kenya. All the research protocols were observed by acquiring all the research permits. Respondents' ethical considerations of consent, privacy, and confidentiality were observed. The respondents recruited were men who visited the reproductive health clinic and voluntarily agreed to participate in the study without coercion or compensation. Participant observation was the key data collection tool, with the doctor and patient conversation digitally recorded. The researcher was allowed into the clinic in a socially acceptable role. Male patients flouted the maxims of quantity, quality, relation, and manner in order to describe their reproductive health problems without embarrassment using the Swahili language. The flouting was done through the discursive strategies of narration and circumlocution. Flouting of the maxims was acceptable to the doctor and patient due to the fact that sexual intercourse and private body parts are taboo topics and uncomfortable to talk about. The quality of health care received by the patient depended on the doctor’s patience when all the maxims were flouted. In the reproductive health clinic, flouting of maxims hindered communication and, at the same time, enhanced communication between the doctor and patient.

Keywords: cooperative principle, doctor, men, reproductive health

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Authors: Luciano Oliveira, Elsa Vásquez-Alvarez

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The increase in rail freight transport in Brazil in recent years requires new railway lines and the maintenance of existing ones, which generates high costs for concessionaires. It is in this context that this work is inserted, whose objective is to propose a method that uses Binary Linear Programming for the choice of sleeper and rail fastening, from various options, including the way to apply these materials, with focus to minimize costs. Unit value information, the life cycle each of material type, and service expenses are considered. The model was implemented in commercial software using real data for its validation. The formulated model can be replicated to support decision-making for other railway projects in the choice of sleepers and rail fastening with lowest cost.

Keywords: linear programming, rail fastening, rail sleeper, railway

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Authors: Karl Owen L. Suan, Juliet Marie S. Lambayan, Floramay P. Salo-Curato

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Objective: To predict the outcome among patients admitted with community-acquired pneumonia (ages 3 months to 59 months old) admitted in Visayas Community Medical Center using the Respiratory Index of Severity in Children (RISC). Design: A cross-sectional study design was used. Setting: The study was done in Visayas Community Medical Center, which is a private tertiary level in Cebu City from January-June 2013. Patients/Participants: A total of 72 patients were initially enrolled in the study. However, 1 patient transferred to another institution, thus 71 patients were included in this study. Within 24 hours from admission, patients were assigned a RISC score. Statistical Analysis: Cohen’s kappa coefficient was used for inter-rater agreement for categorical data. This study used frequency and percentage distribution for qualitative data. Mean, standard deviation and range were used for quantitative data. To determine the relationship of each RISC score parameter and the total RISC score with the outcome, a Mann Whitney U Test and 2x2 Fischer Exact test for testing associations were used. A p value less of than 0.05 alpha was considered significant. Results: There was a statistical significance between RISC score and clinical outcome. RISC score of greater than 4 was correlated with intubation and/or mortality. Conclusion: The RISC scoring system is a simple combination of clinical parameters and a reliable tool that will help stratify patients aged 3 months to 59 months in predicting clinical outcome.

Keywords: RISC, clinical outcome, community-acquired pneumonia, patients

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Chhavi Rana

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The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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Authors: Mohammed Qutishat, Khaldoun Aldiabat, Khaled Bader, Mohammad Al Qadire

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Cyberchondria refers to the irrational increase of distress about the condition of one's health as a consequence of the World Wide Web quest for medical details. The aim of this study was to examine the relationship between emotional intelligence and cyberchondria among Omani university students. A descriptive correlational design was used to collect data from eligible 370 participants using the Emotional Intelligence Questionnaire, and the short-form version of the Cyberchondria Severity Scale (CSS-12) between January and May 2020 at XX University-Oman. The participants’ age ranged between 18 and 37 years (M = 20.28). The majority of the participants were female, 59.7% (n = 221), single 99.5% (368), in their second academic year, 29.2% (n =108). The mean score of cyberchondria experiences was 32.51, and the mean score of emotional intelligence was 34.91. Linear regression indicated a strong association between cyberchondria and emotional intelligence [F (34.639) = 5.885, P=.000], with a .086 R². In conclusion, the exchange of expertise and peer networking for health-related details utilizing the Internet can benefit students with and without having health problems. Further research and methods should be developed to help students track the online medical tools effectively for the right purposes.

Keywords: emotional intelligence, cyberchondria, smartphone addiction, social media

Procedia PDF Downloads 248

Authors: Louise Bernier

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Under some jurisdictions (including Canada), eligible patients can request and receive medical assistance in dying (MAiD) through lethal injections, inducing their cardiocirculatory death. Those same patients can also wish to donate their organs in the process. If they qualify as organ donors, a clinical and ethical rule called the 'dead donor rule' (DDR) requires the transplant teams to wait after cardiocirculatory death is confirmed, followed by a 'no touch' period (5 minutes in Canada) before they can proceed with organ removal. The medical procedures (lethal injections) as well as the delays associated with the DDR can damage organs (mostly thoracic organs) due to prolonged anoxia. Yet, strong scientific evidences demonstrate that operating differently and reconsidering the DDR would result in more organs of better quality available for transplant. This idea generates discomfort and resistance, but it is also worth considering, especially in a context of chronic shortage of available organs. One option that could be examined for MAiD’ patients who wish and can be organ donors would be to remove vital organs while patients are still alive (and under sedation). This would imply accepting that patient’s death would occur through organ donation instead of lethal injections required under MAiD’ legal rules. It would also mean that patients requesting MAiD and wishing to be organ donors could aspire to donate better quality organs, including their heart, an altruistic gesture that carries important symbolic value for many donors and their families. Following a patient centered approach, our hypothesis is that preventing vital organ donation from a living donor in all circumstance is neither perfectly coherent with how legal mentalities have evolved lately in the field of fundamental rights nor compatible with the clinical and ethical frameworks that shape the landscape in which those complex medical decisions unfold. Through a study of the legal, ethical, and clinical rules in place, both at the national and international levels, this analysis raises questions on the numerous inconsistencies associated with respecting the DDR with patients who have chosen to die through MAiD. We will begin with an assessment of the erosion of certain national legal frameworks that pertain to the sacred nature of the right to life which now also includes the right to choose how one wishes to die. We will then study recent innovative clinical protocols tested in different countries to help address acute organ shortage problems in creative ways. We will conclude this analysis with an ethical assessment of the situation, referring to principles such as justice, autonomy, altruism, beneficence, and non-malfeasance. This study will build a strong argument in favor of starting to allow vital organ donations from living donors in countries where MAiD is already permitted.

Keywords: altruism, autonomy, dead donor rule, medical assistance in dying, non-malfeasance, organ donation

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Authors: Djamila Meghraoui, Bachir Boudraa, Thouraya Meksen, M.Boudraa

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Parkinson's disease is a pathology that involves characteristic perturbations in patients’ voices. This paper describes a proposed method that aims to diagnose persons with Parkinson (PWP) by analyzing on line their voices signals. First, Thresholds signals alterations are determined by the Multi-Dimensional Voice Program (MDVP). Principal Analysis (PCA) is exploited to select the main voice principal componentsthat are significantly affected in a patient. The decision phase is realized by a Mul-tinomial Bayes (MNB) Classifier that categorizes an analyzed voice in one of the two resulting classes: healthy or PWP. The prediction accuracy achieved reaching 98.8% is very promising.

Keywords: Parkinson’s disease recognition, PCA, MDVP, multinomial Naive Bayes

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Authors: Chuan-Ming Tung, Tzu-Chiao Yuan

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This research aims to construct the supply indicators and weights of shelter space from a perspective of the needs of the elderly by virtue of literature review, a systematical compilation of related regulations, and the use of the Analytical Hierarchy Process method, the questionnaires regarding the indicators filled out by 16 experts and scholars. The researcher then used 3 schools and 2 activity centers in Banqiao District, New Taipei City, as study cases to evaluate the ‘friendliness’ degree/level for the supply of shelters meeting the needs of elderly people. The supply evaluation indicators of friendly shelters meeting the needs of the elderly include "Administrative Operations and Service Needs" and "Residence-related and Living Needs"; under the "Administrative Operations and Service Needs" are "Management Operations and Information Provision", "Shelter Space Preparedness and Logistics Support", "Medical Care and Social Support", and "Shelters and Medical Environment", a total of 17 assessment items in four indicators, while under the "Residence-related and Living Needs" are "Dietary Needs", "Sleep Needs", "Hygiene and Sanitation Needs", "Accessibility and Convenience Needs ", etc., a total of 18 assessment items in four indicators. The results show that "Residence-related and Living Needs" is the most important item in the main levels of the supply indicators of the needs for friendly shelters to elderly people (weigh value 0.5504), followed by "Administrative Operations and Service Needs" (0.4496). The order of importance of the supply indicators of friendly shelters for the needs of elderly people is as follows: "Hygiene and Sanitation Needs" (0.1721), "Dietary Needs" (0.1340), "Medical Care and Social Support" (0.1300), "Sleep Needs" (0.1277), "Accessibility and Convenience Needs" (0.1166), "Basic Environment of Shelters" (0.1145), "Shelter Space Preparedness and Logistics Support" (0.1115) and "Management Operations and Information Provision" (0.0936). In addition, it can be noticed from the results of the case evaluation that the provision of refuges and shelters, mainly from schools and activity centers, is extremely inadequate for the needs of the elderly. In a set of comprehensive comparisons and contrasts, the evaluation indicators of refuges and shelters that need to be improved are "Medical Care and Social Support", "Hygiene and Sanitation Needs", "Sleep Needs", "Dietary Needs", and "Shelter Space Preparedness and Logistics Support".

Keywords: needs of the elderly people, urban shelters, evaluation indicators/indices., taiwan

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Authors: Hira Jabbar, Tanzeel-Ur Rehman

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Urban parks and open spaces play a significant role in improving physical and mental health of the citizens, strengthen the societies and make the cities more attractive places to live and work. As the world’s cities continue to grow, continuing to value green space in cities is vital but is also a challenge, particularly in developing countries where there is pressure for space, resources, and development. Offering equal opportunity of accessibility to parks is one of the important issues of park distribution. The distribution of parks should allow all inhabitants to have close proximity to their residence. Remote sensing and Geographic information systems (GIS) can provide decision makers with enormous opportunities to improve the planning and management of Park facilities. This study exhibits the capability of GIS and RS techniques to provide baseline knowledge about the distribution of parks, level of accessibility and to help in identification of potential areas for such facilities. For this purpose Landsat OLI imagery for year 2016 was acquired from USGS Earth Explorer. Preprocessing models were applied using Erdas Imagine 2014v for the atmospheric correction and NDVI model was developed and applied to quantify the land use/land cover classes including built up, barren land, water, and vegetation. The parks amongst total public green spaces were selected based on their signature in remote sensing image and distribution. Percentages of total green and parks green were calculated for each town of Lahore City and results were then synchronized with the recommended standards. ANGSt model was applied to calculate the accessibility from parks. Service area analysis was performed using Network Analyst tool. Serviceability of these parks has been evaluated by employing statistical indices like service area, service population and park area per capita. Findings of the study may contribute in helping the town planners for understanding the distribution of parks, demands for new parks and potential areas which are deprived of parks. The purpose of present study is to provide necessary information to planners, policy makers and scientific researchers in the process of decision making for the management and improvement of urban parks.

Keywords: accessible natural green space standards (ANGSt), geographic information systems (GIS), remote sensing (RS), United States geological survey (USGS)

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Authors: Bikshalu Kalagadda, Srikanth Rangu

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The important object of images segmentation is to extract objects with respect to some input features. One of the important methods for image segmentation is Level set method. Generally medical images and synthetic images with low contrast of pixel profile, for such images difficult to locate interested features in images. In conventional level set function, develops irregularity during its process of evaluation of contour of objects, this destroy the stability of evolution process. For this problem a remedy is proposed, a new hybrid algorithm is Clustering Level Set Evolution. Kernel fuzzy particles swarm optimization clustering with the Distance Regularized Level Set (DRLS) and Selective Binary, and Gaussian Filtering Regularized Level Set (SBGFRLS) methods are used. The ability of identifying different regions becomes easy with improved speed. Efficiency of the modified method can be evaluated by comparing with the previous method for similar specifications. Comparison can be carried out by considering medical and synthetic images.

Keywords: segmentation, clustering, level set function, re-initialization, Kernel fuzzy, swarm optimization

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Authors: Tizian Matschak, Ilja Nastjuk, Stephan Kühnel, Simon Trang

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We argue that besides well-known primary effects of information security controls (ISCs), namely confidentiality, integrity, and availability, ISCs can also have secondary effects. For example, while IT can add business value through impacts on business processes, ISCs can be a barrier and distort the relationship between IT and organizational value through the impact on business processes. By applying the Delphi method with 28 experts, we derived 27 business process influence dimensions of ISCs. Defining and understanding these mechanisms can change the common understanding of the cost-benefit valuation of IT security investments and support managers' effective and efficient decision-making.

Keywords: business process dimensions, dark side of information security, Delphi study, IT security controls

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Authors: Susana Marques

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Research on how store environment cues influence consumers’ store choice decision criteria, such as store operations, product quality, monetary price, store image and sales promotion, is sparse. Especially absent research on the simultaneous impact of multiple store environment cues. The authors propose a comprehensive store choice model that includes: three types of store environment cues as exogenous constructs; various store choice criteria as possible mediating constructs, and store patronage intentions as an endogenous construct. On the basis of testing with a sample of 561 customers of hypermarkets, the model is partially supported. This study used structural equation modelling to test the proposed model.

Keywords: store choice, store patronage, structural equation modelling, retailing

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Authors: Erika Yamaguchi, Sirawadee Arunyanrt, Shunichi Ohmori, Kazuho Yoshimoto

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In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.

Keywords: capacity-booking, SPA, monthly production planning, linear programming

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Authors: Berrin Şentürk

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In this study, due to the recurrence of bovine tuberculosis, in the same areas, the risk factors for the disease were determined and evaluated at the local level. This study was carried out in 32 farms where the disease was detected in the district and center of Samsun province in 2014. Predetermined risk factors, such as farm, environmental and economic risks, were investigated with the survey method. It was predetermined that risks in the three groups are similar to the risk variables of the disease on the global scale. These risk factors that increase the susceptibility of the infection must be understood by the herd owners. The risk-based contagious disease management system approach should be applied for bovine tuberculosis by farmers, animal health professionals and public and private sector decision makers.

Keywords: bovine tuberculosis, disease management, control, outbreak, risk analysis

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Authors: Hashini E. Mohottala

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We report the combine use of Wikispaces (WikiS) and Group Problem Solving (GPS) sessions conducted in the introductory level physics classes. As a part of this new teaching tool, some essay type problems were posted on the WikiS in weekly basis and students were encouraged to participate in problem solving without providing numerical final answers but the steps. Wikispace is used as a platform for students to meet online and create discussions. Each week students were further evaluated on problem solving skills opening up more opportunity for peer interaction through GPS. Each group was given a different problem to solve and the answers were graded. Students developed a set of skills in decision-making, problem solving, communication, negotiation, critical and independent thinking and teamwork through the combination of WikiS and GPS.

Keywords: group problem solving (GPS), wikispace (WikiS), physics education, learning

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Authors: Abbas Al-Refaie

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The research examines the factors that affect customer churn (CC) in the Jordanian telecom industry. A total of 700 surveys were distributed. Cluster analysis revealed three main clusters. Results showed that CC and customer satisfaction (CS) were the key determinants in forming the three clusters. In two clusters, the center values of CC were high, indicating that the customers were loyal and SC was expensive and time- and energy-consuming. Still, the mobile service provider (MSP) should enhance its communication (COM), and value added services (VASs), as well as customer complaint management systems (CCMS). Finally, for the third cluster the center of the CC indicates a poor level of loyalty, which facilitates customers churn to another MSP. The results of this study provide valuable feedback for MSP decision makers regarding approaches to improving their performance and reducing CC.

Keywords: cluster analysis, telecom industry, switching cost, customer churn

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Authors: Masih Nikgou

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ICU nurses or intensive care nurses are highly specialized and trained healthcare personnel. These nurses provide nursing care for patients with life-threatening illnesses or conditions. They provide the experience, knowledge and specialized skills that patients need to survive and recover. Intensive care nurses (ICU) are trained to make momentary decisions and act quickly when the patient's condition changes. Their primary work environment is in the hospital in intensive care units. Typically, ICU patients require a high level of care. ICU nurses work in challenging and complex fields in their nursing profession. They have the primary duty of caring for and saving patients who are fighting for their lives. Intensive care (ICU) nurses are highly trained to provide exceptional care to patients who depend on 24/7 nursing care. A patient in the ICU is often equipped with a ventilator, intubated and connected to several life support machines and medical equipment. Intensive Care Nurses (ICU) have full expertise in considering all aspects of bringing back their patients. Some of the specific responsibilities of ICU nurses include (a) Assessing and monitoring the patient's progress and identifying any sudden changes in the patient's medical condition. (b) Administration of drugs intravenously by injection or through gastric tubes. (c) Provide regular updates on patient progress to physicians, patients, and their families. (d) According to the clinical condition of the patient, perform the approved diagnostic or treatment methods. (e) In case of a health emergency, informing the relevant doctors. (f) To determine the need for emergency interventions, evaluate laboratory data and vital signs of patients. (g) Caring for patient needs during recovery in the ICU. (h) ICU nurses often provide emotional support to patients and their families. (i) Regulating and monitoring medical equipment and devices such as medical ventilators, oxygen delivery devices, transducers, and pressure lines. (j) Assessment of pain level and sedation needs of patients. (k) Maintaining patient reports and records. As the name suggests, critical care nurses work primarily in ICU health care units. ICUs are completely healthy and have proper lighting with strict adherence to health and safety from medical centers. ICU nurses usually move between the intensive care unit, the emergency department, the operating room, and other special departments of the hospital. ICU nurses usually follow a standard shift schedule that includes morning, afternoon, and night schedules. There are also other relocation programs depending on the hospital and region. Nurses who are passionate about data and managing a patient's condition and outcomes typically do well as ICU nurses. An inquisitive mind and attention to processes are equally important. ICU nurses are completely compassionate and are not afraid to advocate for their patients and family members. who are distressed.

Keywords: nursing, intensive care unit, pediatric intensive care unit, mobile intensive care unit, surgical intensive care unite

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Authors: Olga Blasco-Blasco, Vicente Liern

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The development of tourism since the mid-20th century has raised problems of overcrowding, indiscriminate construction in seaside areas and gentrification. Increasingly, the World Tourism Organisation and public institutions are promoting policies that encourage sustainability. From the perspective of sustainability, three types of tourism can be established: traditional tourism, sustainable tourism and sustainable impact tourism. Measuring sustainability is complex due to its multiple dimensions of different relative importance and diversity in nature. In order to try to answer this problem and to identify the benefits of applying policies that promote sustainable tourism, a decision-making analysis will be carried out through the application of a multicriteria analysis method. The proposal is applied to hotel reservations and to the evaluation and management of tourism sustainability in the Spanish Autonomous Communities.

Keywords: sustainable tourism, multicriteria analysis, flexible optimization, composite indicators

Procedia PDF Downloads 310

Authors: Chusit Apirumanekul, Chayanis Krittasudthacheewa, Ratchapat Ratanavaraha, Yanyong Inmuong

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Rapid economic development in the Lower Mekong region is leading to changes in water quantity and quality. Changes in land- and forest-use, infrastructure development, increasing urbanization, migration patterns and climate risks are increasing demands for water, within various sectors, placing pressure on scarce water resources. Appropriate policies, strategies, and planning are urgently needed for improved water resource management. Over the last decade, Thailand has experienced more frequent and intense drought situations, affecting the level of water storage in reservoirs along with insufficient water allocation for agriculture during the dry season. The Huay Saibat River Basin, one of the well-known water-scarce areas in the northeastern region of Thailand, is experiencing ongoing water scarcity that affects both farming livelihoods and household consumption. Drought management in Thailand mainly focuses on emergency responses, rather than advance preparation and mitigation for long-term solutions. Despite many efforts from local authorities to mitigate the drought situation, there is yet no long-term comprehensive water management strategy, that integrates climate risks alongside other uncertainties. This paper assesses the application in the Huay Saibat River Basin, of the Robust Decision Support framework, to explore the feasibility of multiple drought management policies; including a shift in cropping season, in crop changes, in infrastructural operations and in the use of groundwater, under a wide range of uncertainties, including climate and land-use change. A series of consultative meetings were organized with relevant agencies and experts at the local level, to understand and explore plausible water resources strategies and identify thresholds to evaluate the performance of those strategies. Three different climate conditions were identified (dry, normal and wet). Other non-climatic factors influencing water allocation were further identified, including changes from sugarcane to rubber, delaying rice planting, increasing natural retention storage and using groundwater to supply demands for household consumption and small-scale gardening. Water allocation and water use in various sectors, such as in agriculture, domestic, industry and the environment, were estimated by utilising the Water Evaluation And Planning (WEAP) system, under various scenarios developed from the combination of climatic and non-climatic factors mentioned earlier. Water coverage (i.e. percentage of water demand being successfully supplied) was defined as a threshold for water resource strategy assessment. Thresholds for different sectors (agriculture, domestic, industry, and environment) were specified during multi-stakeholder engagements. Plausible water strategies (e.g. increasing natural retention storage, change of crop type and use of groundwater as an alternative source) were evaluated based on specified thresholds in 4 sectors (agriculture, domestic, industry, and environment) under 3 climate conditions. 'Business as usual' was evaluated for comparison. The strategies considered robust, emerge when performance is assessed as successful, under a wide range of uncertainties across the river basin. Without adopting any strategy, the water scarcity situation is likely to escalate in the future. Among the strategies identified, the use of groundwater as an alternative source was considered a potential option in combating water scarcity for the basin. Further studies are needed to explore the feasibility for groundwater use as a potential sustainable source.

Keywords: climate change, robust decision support, scenarios, water resources management

Procedia PDF Downloads 168

Authors: Ida Bagus Made Putra Jandhana, Teuku Yuri M. Zagloel, Rahmat Nurchayo

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Having several crises that affect industrial sector performance in the past decades, decision makers should utilize measurement application that enables them to measure industrial resiliency more precisely. It provides not only a framework for the development of resilience measurement application, but also several theories for the concept building blocks, such as performance measurement management, and resilience engineering in real world environment. This research is a continuation of previously published paper on performance measurement in the industrial sector. Finally, this paper contributes an alternative performance measurement method in industrial sector based on resilience concept. Moreover, this research demonstrates how applicable the concept of resilience engineering is and its method of measurement.

Keywords: industrial, measurement, resilience, sector

Procedia PDF Downloads 273

Authors: Heshalini Rajagopal, Li Sze Chow, Raveendran Paramesran

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Magnetic Resonance Imaging (MRI) is one of the most important medical imaging modality. Subjective assessment of the image quality is regarded as the gold standard to evaluate MR images. In this study, a database of 210 MR images which contains ten reference images and 200 distorted images is presented. The reference images were distorted with four types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur and DCT compression. The 210 images were assessed by ten subjects. The subjective scores were presented in Difference Mean Opinion Score (DMOS). The DMOS values were compared with four FR-IQA metrics. We have used Pearson Linear Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) to validate the DMOS values. The high correlation values of PLCC and SROCC shows that the DMOS values are close to the objective FR-IQA metrics.

Keywords: medical resonance (MR) images, difference mean opinion score (DMOS), full reference image quality assessment (FR-IQA)

Procedia PDF Downloads 457