Search results for: clinical decision support systems

Authors: Ryan Dale B. Elnar

Abstract:

This study developed a multidimensional need assessment scale for college students called The University of Mindanao Needs Assessment Scale (UMNAS). Although there are context-specific instruments measuring the needs of clinical and non-clinical samples, literature reveals no standardized scales to measure the needs of the college students thus a four-phase item development process was initiated to support its content validity. Comprising seven broad facets namely spiritual-moral, intrapersonal, socio-personal, psycho-emotional, cognitive, physical and sexual, a pyramid model of college needs was deconstructed through FGD sample to support the literature review. Using various construct validity procedures, the model was further tested using a total of 881 Filipino college samples. The result of the study revealed evidences of the reliability and validity of the UMNAS. The reliability indices range from .929-.933. Exploratory and confirmatory factor analyses revealed a one-factor-six-dimensional instrument to measure the needs of the college students. Using multivariate regression analysis, year level and course are found predictors of students’ needs. Content analysis attested the usefulness of the instrument to diagnose students’ personal and academic issues and concerns in conjunction with other measures. The norming process includes 1728 students from the different colleges of the University of Mindanao. Further validation is recommended to establish a national norm for the instrument.

Keywords: needs assessment scale, validity, factor analysis, college students

Procedia PDF Downloads 443

Authors: Neha Ahirwar

Abstract:

In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

Procedia PDF Downloads 68

Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

Abstract:

Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

Procedia PDF Downloads 139

Authors: James Boag

Abstract:

The needs of people with a diagnosis of dementia and their carers and families are physical, psychosocial, and psychological and begin at the time of diagnosis. There is frequently a lack of emotional support and counselling. Care- giving support is required from the presentation of the first symptoms of dementia until death. Alzheimer's disease begins decades before the clinical symptoms begin to appear, and in many cases, it remains undiagnosed, or diagnosed too late for any possible interventions to have any effect. However, if an incorrect diagnosis is given, it may result in a person being treated, without effect, for a type of dementia they do not have and delaying the interventions they should have received. Being diagnosed with dementia can cause emotional distress to the person, and physical and emotional support is needed, which will become more important as the disease progresses. The severity of the patient's dementia and their symptoms has a bearing of the impact on the carer and the support needed. A lack of insight and /or a denial of the diagnosis, grief, reacting to anticipated future losses, and coping methods to maximise the disease outcome, are things that should be addressed. Because of the stigma, it is important for carers not to lose contact with family and others because social isolation leads to depression and burnout. The impact on a carer's well- being and quality of life can be influenced by the severity of the illness, its type of dementia, its symptoms, healthcare support, financial and social status, career, age, health, residential setting, and relationship to the patient. Carer burnout due to lack of support leads to people diagnosed with dementia being put into residential care prematurely. Often dementia is not recognised as a terminal illness, limiting the ability of the person diagnosed with dementia and their carers to work on advance care planning and getting access to palliative and other support. Many carers have been satisfied with the physical support they were given in their everyday life, however, it was agreed that there was an immense unmet need for psychosocial support, especially after diagnosis and approaching end of life. Providing continuity and coordination of care is important. Training is necessary for providers to understand that every case is different, and they should understand the complexities. Grief, the emotional response to loss, is suffered during the progression of the disease and long afterwards, and carers should continue to be supported after the death of the person they were caring for.

Keywords: dementia, caring, challenges, needs

Procedia PDF Downloads 101

Authors: Marwa Qaraqe, Muhammad Ismail, Erchin Serpedin

Abstract:

This paper presents a novel architecture for a patient-specific epileptic seizure onset detector using scalp electroencephalography (EEG). The proposed architecture is based on the decision fusion calculated from energy and neural synchronization related features. Specifically, one level of the detector calculates the condition number (CN) of an EEG matrix to evaluate the amount of neural synchronization present within the EEG channels. On a parallel level, the detector evaluates the energy contained in four EEG frequency subbands. The information is then fed into two independent (parallel) classification units based on support vector machines to determine the onset of a seizure event. The decisions from the two classifiers are then combined together according to two fusion techniques to determine a global decision. Experimental results demonstrate that the detector based on the AND fusion technique outperforms existing detectors with a sensitivity of 100%, detection latency of 3 seconds, while it achieves a 2:76 false alarm rate per hour. The OR fusion technique achieves a sensitivity of 100%, and significantly improves delay latency (0:17 seconds), yet it achieves 12 false alarms per hour.

Keywords: epilepsy, EEG, seizure onset, electroencephalography, neuron, detection

Procedia PDF Downloads 480

Authors: Abadi Berhane, Walelign Worku, Berhanu Abrha, Gebre Hadgu

Abstract:

Sesame is an important oilseed crop in Ethiopia, which is the second most exported agricultural commodity next to coffee. However, there is poor soil fertility management and a research-led farming system for the crop. The AquaCrop model was applied as a decision-support tool, which performs a semi-quantitative approach to simulate the yield of crops under different soil fertility levels. The objective of this experiment was to calibrate and validate the AquaCrop model for simulating the growth and yield of sesame under different nitrogen fertilizer levels and to test the performance of the model as a decision-support tool for improved sesame cultivation in the study area. The experiment was laid out as a randomized complete block design (RCBD) in a factorial arrangement in the 2016, 2017, and 2018 main cropping seasons. In this experiment, four nitrogen fertilizer rates, 0, 23, 46, and 69 Kg/ha nitrogen, and three improved varieties (Setit-1, Setit-2, and Humera-1). In the meantime, growth, yield, and yield components of sesame were collected from each treatment. Coefficient of determination (R2), Root mean square error (RMSE), Normalized root mean square error (N-RMSE), Model efficiency (E), and Degree of agreement (D) were used to test the performance of the model. The results indicated that the AquaCrop model successfully simulated soil water content with R2 varying from 0.92 to 0.98, RMSE 6.5 to 13.9 mm, E 0.78 to 0.94, and D 0.95 to 0.99, and the corresponding values for AB also varied from 0.92 to 0.98, 0.33 to 0.54 tons/ha, 0.74 to 0.93, and 0.9 to 0.98, respectively. The results on the canopy cover of sesame also showed that the model acceptably simulated canopy cover with R2 varying from 0.95 to 0.99 and a RMSE of 5.3 to 8.6%. The AquaCrop model was appropriately calibrated to simulate soil water content, canopy cover, aboveground biomass, and sesame yield; the results indicated that the model adequately simulated the growth and yield of sesame under the different nitrogen fertilizer levels. The AquaCrop model might be an important tool for improved soil fertility management and yield enhancement strategies of sesame. Hence, the model might be applied as a decision-support tool in soil fertility management in sesame production.

Keywords: aquacrop model, normalized water productivity, nitrogen fertilizer, canopy cover, sesame

Procedia PDF Downloads 80

Authors: Jarmila Zolnova, Lucia Hrebenarova, Veronika Palkova

Abstract:

The interconnections between supportive sources of authorities at school and students have been proved. Lacking research in this field in Slovakia translates into absenting perception of social support by students with special educational needs. The aim of this paper (presented by the poster) is to reveal and interpret the perception of frequency and importance of authorities at school from students' perspective. The sample included 718 students aged 10 years and 1 month on average. Eighty nine students of this count were students with special educational needs. Data were obtained from the Child and Adolescent Social Support Scale (CASSS) for students. Mutual relations between teachers acting as the source of support and students were not significant. Neither was significant the support of other school employees. Both groups of students assessed the frequency and importance of social support from teachers more positively than the support from other school employees.

Keywords: intact student, pedagogue, pupil with special education needs, school employee, social support

Procedia PDF Downloads 348

Authors: Jaime R. Silva, Gabriel E. Reyes, Marianne Krause

Abstract:

Background: The two-polarity model of the depressive personality argues that experience is organized around two axes: interpersonal relatedness and self-definition. Differential emphasis on one of these poles defines three types of depressive experience: Anaclitic, Introjective or Mixed pattern. On the one hand, Anaclitic pattern has been conceptually related with exaggerated biological stress sensitivity. On the other hand, the Introjective pattern was linked with anhedonic symptomatology. The general aim of the study was to find empirical support for this relationship. Methods: 101 non-clinical individuals participated in two experimental sessions. During the first session, the biological stress reactivity (cortisol concentration in saliva) and the subjective stress perceived (self-reported) during the Trier Social Stress Test (TSST), were investigated. In the second session, a visual discrimination task with a specific reward system, to study the reinforcement sensitivity (anhedonia), was performed. Results: Results evidenced that participants with Introjective depressive symptoms showed a higher interpersonal sensitivity and a diminished sensitivity to reinforcement. In addition, results also indicated that such a group has a poor psychological detection of its exacerbated reactivity to stress, which is the opposite pattern evidenced amongst the Anaclitic group. Conclusions: In perspective, these results empirically support the two-polarity of the depressive personality model. Clinical implications are discussed.

Keywords: depression, interpersonal stress, personality, trier social stress test

Procedia PDF Downloads 251

Authors: Benmansour Nassima, Benmansour Souheyla

Abstract:

The appropriate integration of reward processing and decision making provided by the environment is vital for behavioural success and individuals’ well being in everyday life. Functional neurological investigation has already provided an inclusive image on affective and emotional (motivational) processing in the healthy human brain and has recently focused its interest also on the assessment of brain function in anxious and depressed individuals. This article offers an overview on the theoretical approaches that relate emotion and decision-making, and spotlights investigation with anxious or depressed individuals to reveal how emotions can interfere with decision-making. This research aims at incorporating the emotional structure based on response and stimulation with a Bayesian approach to decision-making in terms of probability and value processing. It seeks to show how studies of individuals with emotional dysfunctions bear out that alterations of decision-making can be considered in terms of altered probability and value subtraction. The utmost objective is to critically determine if the probabilistic representation of belief affords could be a critical approach to scrutinize alterations in probability and value representation in subjective with anxiety and depression, and draw round the general implications of this approach.

Keywords: decision-making, motivation, alteration, reward processing, response selection

Procedia PDF Downloads 479

Authors: Peiran Ma

Abstract:

This study explored the role of political polarization in an individual's decision of receiving the COVID-19 vaccine. A total of 15 participants participated in individual interviews and focus group discussions about the relationships among domestic political polarization, vaccine hesitancy, and behavioral responses to the COVID-19 pandemic. Political affiliation affected an individual’s decision on the COVID-19 vaccination, such that people who identified as Liberals and Democrats were more accepting of the vaccine. On the other hand, the level of influence declined over time (2020-2022) when the general conception of COVID-19 immunization shifted from political to personal. Results provided qualitative support to the previously identified positive relationship between divided political opinions and COVID-19 vaccine hesitancy and highlighted the decreasing trend in the power of political polarization in vaccination and the existence of other factors.

Keywords: COVID-19, vaccine hesitancy, political polarization, partisanship, ideology

Procedia PDF Downloads 86

Authors: Abiola Falilat Ibraheem, Akinyimika Sowunmi, Valerie Otti

Abstract:

Background: Introduction of innovative cancer clinical trials to Nigeria is a critical step in addressing global inequities of cancer burden. Low health and clinical trial literacy among Nigerian patients have been sighted as a significant barrier to ensuring that patients enrolled in clinical trials are truly informed. Video intervention has been shown to be the most proactive method to improving patient’s clinical trial knowledge. In the US, video interventions have been successful at improving education about cancer clinical trials among minority patients. Thus, this study aimed to apply and adapt video interventions addressing attitudinal barriers peculiar to Nigerian patients. Methods: A hospital-based representative mixed-method study was conducted at the Lagos State University Teaching Hospital (LASUTH) from July to December 2020, comprising of cancer patients aged 18 and above. Patients were randomly selected during every clinic day, of which 63 patients volunteered to participate in this study. We first administered a cancer literacy survey to determine patients’ knowledge about clinical trials. For patients who had prior knowledge, a pre-intervention test was administered, after which a 15-minute video (attitudes and intention to enroll in therapeutic clinical trials (AIET)) to improve patients’ knowledge, perception, and attitudes towards clinical trials was played, and then ended by administering a post-intervention test to the patients. For patients who had no prior knowledge, the AIET video was played for them, followed by the post-intervention test. Results: Out of 63 patients sampled, 43 (68.3%) had breast cancer. On average, patients agreed to understand their cancer diagnosis and treatment very well. 84.1% of patients had never heard about cancer clinical trials, and 85.7% did not know what cancer clinical trials were. There was a strong positive relationship (r=0.916) between the pretest and posttest, which means that the intervention improved patients’ knowledge, perception, and attitudes about cancer clinical trials. In the focus groups, patients recommended adapting the video in Nigerian settings and representing all religions in order to address trust in local clinical trialists. Conclusion: Due to the small size of patients, change in clinical trial knowledge was not statistically significant. However, there is a trend suggesting that culturally adapted video interventions can be used to improve knowledge and perception about cancer clinical trials.

Keywords: clinical trials, culturally targeted intervention, patient education, video intervention

Procedia PDF Downloads 139

Authors: Eugene Y. C. Wong, Daniel Y. W. Mo, Cosmo T. Y. Ng, Jessica K. Y. Chan, Leith K. Y. Chan, Henry Y. K. Lau

Abstract:

The real-time planning visualisation, precise allocation and loading optimisation in air cargo load planning operations are increasingly important as more considerations are needed on dangerous cargo loading, locations of lithium batteries, weight declaration and limited aircraft capacity. The planning of the unit load devices (ULD) can often be carried out only in a limited number of hours before flight departure. A dynamic air cargo load planning system is proposed with the optimisation of cargo load plan and visualisation of planning results in virtual reality systems. The system aims to optimise the cargo load planning and visualise the simulated loading planning decision on air cargo terminal operations. Adopting simulation tools, Cave Automatic Virtual Environment (CAVE) and virtual reality technologies, the results of planning with reference to weight and balance, Unit Load Device (ULD) dimensions, gateway, cargo nature and aircraft capacity are optimised and presented. The virtual reality system facilities planning, operations, education and training. Staff in terminals are usually trained in a traditional push-approach demonstration with enormous manual paperwork. With the support of newly customized immersive visualization environment, users can master the complex air cargo load planning techniques in a problem based training with the instant result being immersively visualised. The virtual reality system is developed with three-dimensional (3D) projectors, screens, workstations, truss system, 3D glasses, and demonstration platform and software. The content will be focused on the cargo planning and loading operations in an air cargo terminal. The system can assist decision-making process during cargo load planning in the complex operations of air cargo terminal operations. The processes of cargo loading, cargo build-up, security screening, and system monitoring can be further visualised. Scenarios are designed to support and demonstrate the daily operations of the air cargo terminal, including dangerous goods, pets and animals, and some special cargos.

Keywords: air cargo load planning, optimisation, virtual reality, weight and balance, unit load device

Procedia PDF Downloads 348

Authors: Pisit Potjanajaruwit

Abstract:

TThe research objective was to study the integrated marketing communication strategy that is affecting the student’s decision making to study at Rajabhat University in Thailand. This research is a quantitative research. The sampling for this study is the first year students of Rajabhat University for 400 sampling. The data collection is made by a questionnaire. The data analysis by the descriptive statistic include frequency, percentage, mean and standardization and influence statistic as the multiple regression. The results show that integrated marketing communication including the advertising, public relation, sale promotion is important and significant with the student’s making decision in terms of brand awareness and brand recognized. The university scholar and word of mouth have an impact on decision-making of the student. The direct marketing such as Facebook also relate to the student decision. In addition, we found that the marketing communication budget, university brand positioning and university mission have the direct effect on the marketing communication.

Keywords: decision making of higher education, integrated marketing communication, rajabhat university, social media

Procedia PDF Downloads 341

Authors: Patricia Heredia, Isabel Saz, Marta Fernández

Abstract:

This article proposes that the decision regarding exporting and the choice of export channel are nested and non-independent decisions. We assume that firms make two sequential decisions before arriving at their final choice: the decision to access foreign markets and the decision about the type of channel. This hierarchical perspective of the choices involved in the process is appealing for two reasons. First, it supports the idea that people have a limited analytical capacity. Managers often break down a complex decision into a hierarchical process because this makes it more manageable. Secondly, it recognizes that important differences exist between entry modes. In light of the above, the objective of this study is to test different entry mode choice processes: independent decisions and nested and non-independent decisions. To do this, the methodology estimates and compares the following two models: (i) a simultaneous single-stage model with three entry mode choices (using a multinomial logit model); ii) a two-stage model with the export decision preceding the channel decision using a sequential logit model. The study uses resource-based factors in determining these decision processes concerning internationalization and the study carries out empirical analysis using a DOC Rioja sample of 177 firms.Using the Akaike and Schwarz Information Criteria, the empirical evidence supports the existence of a nested structure, where the decision about exporting precedes the export mode decision. The implications and contributions of the findings are discussed.

Keywords: sequential logit model, two-stage choice process, export mode, wine industry

Procedia PDF Downloads 33

Authors: M. Pushparani, A. Sagaya

Abstract:

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

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

Procedia PDF Downloads 286

Authors: Adel Ali Elshaibani

Abstract:

Risk management indicators augment the reporting infrastructure, particularly for the board and senior management, to identify, monitor, and manage risks. This enhancement facilitates improved decision-making throughout the banking organization. Decision tree analysis is a tool that visually outlines potential outcomes, costs, and consequences of complex decisions. It is particularly beneficial for analyzing quantitative data and making decisions based on numerical values. By calculating the expected value of each outcome, decision tree analysis can help assess the best course of action. In the context of banking, decision tree analysis can assist lenders in evaluating a customer’s creditworthiness, thereby preventing losses. However, applying these tools in developing countries may face several limitations, such as data availability, lack of technological infrastructure and resources, lack of skilled professionals, cultural factors, and cost. Moreover, decision trees can create overly complex models that do not generalize well to new data, known as overfitting. They can also be sensitive to small changes in the data, which can result in different tree structures and can become computationally expensive when dealing with large datasets. In conclusion, while risk management indicators and decision tree analysis are beneficial for decision-making in banks, their effectiveness is contingent upon how they are implemented and utilized by the board of directors, especially in the context of developing countries. It’s important to consider these limitations when planning to implement these tools in developing countries.

Keywords: risk management indicators, decision tree analysis, developing countries, board of directors, bank performance, risk management strategy, banking institutions

Procedia PDF Downloads 61

Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

Abstract:

Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

Procedia PDF Downloads 130

Authors: Te Kīpa Kēpa B. Morgan, Oliver W. Mcmillan, Dylan N. Taute, Tumanako N. Fa'aui

Abstract:

Epistemologies are ways of knowing. Indigenous Peoples are aware that they do not perceive and experience the world in the same way as others. So it is important when empowering Indigenous epistemologies, such as that of the New Zealand Māori, to also be able to represent a scientific understanding within the same analysis. A geothermal development assessment tool has been developed by adapting the Mauri Model Decision Making Framework. Mauri is a metric that is capable of representing the change in the life-supporting capacity of things and collections of things. The Mauri Model is a method of grouping mauri indicators as dimension averages in order to allow holistic assessment and also to conduct sensitivity analyses for the effect of worldview bias. R-shiny is the coding platform used for this Vision Mātauranga research which has created an expert decision support tool (DST) that combines a stakeholder assessment of worldview bias with an impact assessment of mauri-based indicators to determine the sustainability of proposed geothermal development. The initial intention was to develop guidelines for quantifying mātauranga Māori impacts related to geothermal resources. To do this, three typical scenarios were considered: a resource owner wishing to assess the potential for new geothermal development; another party wishing to assess the environmental and cultural impacts of the proposed development; an assessment that focuses on the holistic sustainability of the resource, including its surface features. Indicator sets and measurement thresholds were developed that are considered necessary considerations for each assessment context and these have been grouped to represent four mauri dimensions that mirror the four well-being criteria used for resource management in Aotearoa, New Zealand. Two case studies have been conducted to test the DST suitability for quantifying mātauranga Māori and other biophysical factors related to a geothermal system. This involved estimating mauri0meter values for physical features such as temperature, flow rate, frequency, colour, and developing indicators to also quantify qualitative observations about the geothermal system made by Māori. A retrospective analysis has then been conducted to verify different understandings of the geothermal system. The case studies found that the expert DST is useful for geothermal development assessment, especially where hapū (indigenous sub-tribal grouping) are conflicted regarding the benefits and disadvantages of their’ and others’ geothermal developments. These results have been supplemented with evaluations for the cumulative impacts of geothermal developments experienced by different parties using integration techniques applied to the time history curve of the expert DST worldview bias weighted plotted against the mauri0meter score. Cumulative impacts represent the change in resilience or potential of geothermal systems, which directly assists with the holistic interpretation of change from an Indigenous Peoples’ perspective.

Keywords: decision support tool, holistic geothermal assessment, indigenous knowledge, mauri model decision-making framework

Procedia PDF Downloads 187

Authors: D. K. Sreekantha, T. M. Girish, R. H. Fattepur

Abstract:

In this article, we have given an overview of medical expert systems, which can be used for the developed of physicians in making decisions such as appropriate, prognostic, and therapeutic decisions which help to organize, store, and gives appropriate medical knowledge needed by physicians and practitioners during medical operations or further treatment. If they support the studies by using these systems, advanced tools in medicine will be developed in the future. New trends in the methodology of development of medical expert systems have also been discussed in this paper. So Authors would like to develop an innovative IT based solution to help doctors in rural areas to gain expertise in Medical Science for treating patients. This paper aims to survey the Soft Computing techniques in treating patient’s problems used throughout the world.

Keywords: expert system, fuzzy logic, knowledge base, soft computing, epilepsy

Procedia PDF Downloads 255

Authors: Mayuri Roy Choudhury, Deepti Paul

Abstract:

Many states in the United States are aiming for high renewable energy targets by the year 2045. In order to achieve this goal, they must do transition to Electrical Vehicles (EVS). We first applied the Multi-Level perspective framework to describe the inter-disciplinary complexities associated with the transition to EVs. Thereafter we addressed these complexities by creating an inter-disciplinary policy framework that uses data science algorithms to create evidence-based policies in favor of EVs. Our policy framework uses a systems level approach as it addresses transitions to EVs from a technology, economic, business and social perspective. By Systems-Level we mean approaching a problem from a multi-disciplinary perspective. Our systems-level approach could be a beneficial decision-making tool to a diverse number of stakeholders such as engineers, entrepreneurs, researchers, and policymakers. In addition, it will add value to the literature of electrical vehicles, sustainable energy, energy economics, and management as well as efficient policymaking.

Keywords: transition, electrical vehicles, systems-level, algorithms

Procedia PDF Downloads 228

Authors: Reem Osama Yousif Ali, Osama Yousif Ali Al Gibali

Abstract:

Introduction: Balanced nutrition is undeniably essential for maintaining health, body functions, and integrity of cell metabolism; however, some sick patients cannot tolerate oral or enteral feeding to meet their nutritional needs, so partial or total parenteral nutrition (PN) may be the most suitable alternative route in such situations. Dietitians are fundamental personnel among the medical team to ensure the proper provision of PN service, which was introduced in Sudan in the 1980s. Objective: The study aimed to recognize the dietitians' awareness of parenteral nutrition and their role in providing this service in Sudan – Khartoum State. Methodology: Formulated questionnaire forms composed of twelve questions were distributed to the dietitians working in four tertiary level hospitals. Results: The majority (75%) of the responded dietitians had reasonable knowledge about the importance of PN, its advantages, and its indications. Sixty percent of them were mindful of the PN side effects. Most of the dietitians were aware of the different assessment measurements and PN calculations and were exposed in their clinical practice to patients who were in need of PN, but only a few of them (about 30%) had the actual chance to participate in the formulation and application of PN therapy. The unavailability of the multidisciplinary team, lack of the required equipment and financial support, and associated complications were basic obstacles to the provision of long-term PN service in Khartoum state hospitals. Conclusion: Although dietitians in Khartoum state hospitals have good information about PN definition, indications, accesses, and assessment measures, they do not have enough knowledge and clinical exposure that make them confident to provide the PN service. Establishing a few models of parenteral nutrition units in tertiary hospitals will be of great help, as well as providing the dietitian's training in the area of parenteral nutrition. Further study can explore more requirements to run this service.

Keywords: nutrition support, dietitian, Sudan, parenteral nutrition, nutrition support team

Procedia PDF Downloads 107

Authors: Mohamed H. Khalil

Abstract:

Water is one of the most crucial elements which influence human lives and development. Noteworthy, over the last few years, GIS plays a significant role in optimizing water management systems, especially after exponential developing in this sector. In this context, the Egyptian government initiated an advanced ‘GIS-Web Based System’. This system is efficiently designed to tangibly assist and optimize the complement and integration of data between departments of Call Center, Operation and Maintenance, and laboratory. The core of this system is a unified ‘Data Model’ for all the spatial and tabular data of the corresponding departments. The system is professionally built to provide advanced functionalities such as interactive data collection, dynamic monitoring, multi-user editing capabilities, enhancing data retrieval, integrated work-flow, different access levels, and correlative information record/track. Noteworthy, this cost-effective system contributes significantly not only in the completeness of the base-map (93%), the water network (87%) in high level of details GIS format, enhancement of the performance of the customer service, but also in reducing the operating costs/day-to-day operations (~ 5-10 %). In addition, the proposed system facilitates data exchange between different departments (Call Center, Operation and Maintenance, and laboratory), which allowed a better understanding/analyzing of complex situations. Furthermore, this system reflected tangibly on: (i) dynamic environmental monitor/water quality indicators (ammonia, turbidity, TDS, sulfate, iron, pH, etc.), (ii) improved effectiveness of the different water departments, (iii) efficient deep advanced analysis, (iv) advanced web-reporting tools (daily, weekly, monthly, quarterly, and annually), (v) tangible planning synthesizing spatial and tabular data; and finally, (vi) scalable decision support system. It is worth to highlight that the proposed future plan (second phase) of this system encompasses scalability will extend to include integration with departments of Billing and SCADA. This scalability will comprise advanced functionalities in association with the existing one to allow further sustainable contributions.

Keywords: GIS Web-Based, base-map, water network, decision support system

Procedia PDF Downloads 98

Authors: Yong Bum Shin

Abstract:

This case focuses on Weighted additive difference, Conjunctive, Disjunctive, and Elimination by aspects methodologies in consumer decision-making models and the Simple additive weighting (SAW) approach in the multi-criteria decision-making (MCDM) area. Most decision-making models illustrate that the rank reversal phenomenon is unpreventable. This paper presents that rank reversal occurs in popular managerial methods such as Weighted Additive Difference (WAD), Conjunctive Method, Disjunctive Method, Elimination by Aspects (EBA) and MCDM methods as well as such as the Simple Additive Weighting (SAW) and finally Unified Commensurate Multiple (UCM) models which successfully addresses these rank reversal problems in most popular MCDM methods in decision-making area.

Keywords: multiple criteria decision making, rank inconsistency, unified commensurate multiple, analytic hierarchy process

Procedia PDF Downloads 82

Authors: Emmanuel Chibuogu Asogwa, Tochukwu Sunday Belonwu

Abstract:

An urgent demand for creative solutions has been created by the rapid expansion of medical knowledge, the complexity of patient care, and the requirement for more precise decision-making. As a solution to this problem, the creation of a Medical Intelligent Process Model (MIPM) utilizing ontology-based appears as a promising way to overcome this obstacle and unleash the full potential of healthcare systems. The development of a Medical Intelligent Process Model (MIPM) using ontology-based techniques is motivated by a lack of quick access to relevant medical information and advanced tools for treatment planning and clinical decision-making, which ontology-based techniques can provide. The aim of this work is to develop a structured and knowledge-driven framework that leverages ontology, a formal representation of domain knowledge, to enhance various aspects of healthcare. Object-Oriented Analysis and Design Methodology (OOADM) were adopted in the design of the system as we desired to build a usable and evolvable application. For effective implementation of this work, we used the following materials/methods/tools: the medical dataset for the test of our model in this work was obtained from Kaggle. The ontology-based technique was used with Confusion Matrix, MySQL, Python, Hypertext Markup Language (HTML), Hypertext Preprocessor (PHP), Cascaded Style Sheet (CSS), JavaScript, Dreamweaver, and Fireworks. According to test results on the new system using Confusion Matrix, both the accuracy and overall effectiveness of the medical intelligent process significantly improved by 20% compared to the previous system. Therefore, using the model is recommended for healthcare professionals.

Keywords: ontology-based, model, database, OOADM, healthcare

Procedia PDF Downloads 79

Authors: Vinod Kumar, Navin Kumar, Surjit Angra, Prince Sharma

Abstract:

This paper presents the design analysis of saddle support of a horizontal pressure vessel. Since saddle have the vital role to support the pressure vessel and to maintain its stability, it should be designed in such a way that it can afford the vessel load and internal pressure of the vessel due to liquid contained in the vessel. A model of horizontal pressure vessel and saddle support is created in Ansys. Stresses are calculated using mathematical approach and Ansys software. The analysis reveals the zone of high localized stress at the junction part of the pressure vessel and saddle support due to operating conditions. The results obtained by both the methods are compared with allowable stress value for safe designing.

Keywords: ANSYS, pressure vessel, saddle, support

Procedia PDF Downloads 745

Authors: Mohanad Rezeq, Tarik Aouam, Frederik Gailly

Abstract:

In times of armed conflicts, various security checkpoints are placed by authorities to control the flow of merchandise into and within areas of conflict. The flow of humanitarian trucks that is added to the regular flow of commercial trucks, together with the complex security procedures, creates congestion and long waiting times at the security checkpoints. This causes distribution costs to increase and shortages of relief aid to the affected people to occur. Our research proposes a decision-support tool to assist planners and policymakers in building efficient plans for the distribution of relief aid, taking into account congestion at security checkpoints. The proposed tool is built around a multi-item humanitarian distribution planning model based on multi-phase design science methodology that has as its objective to minimize distribution and back ordering costs subject to capacity constraints that reflect congestion effects using nonlinear clearing functions. Using the 2014 Gaza War as a case study, we illustrate the application of the proposed tool, model the underlying relief-aid humanitarian supply chain, estimate clearing functions at different security checkpoints, and conduct computational experiments. The decision support tool generated a shipment plan that was compared to two benchmarks in terms of total distribution cost, average lead time and work in progress (WIP) at security checkpoints, and average inventory and backorders at distribution centers. The first benchmark is the shipment plan generated by the fixed capacity model, and the second is the actual shipment plan implemented by the planners during the armed conflict. According to our findings, modeling and optimizing supply chain flows reduce total distribution costs, average truck wait times at security checkpoints, and average backorders when compared to the executed plan and the fixed-capacity model. Finally, scenario analysis concludes that increasing capacity at security checkpoints can lower total operations costs by reducing the average lead time.

Keywords: humanitarian distribution planning, relief-aid distribution, congestion, clearing functions

Procedia PDF Downloads 82

Authors: Gül Fatma Türker, Hatice Akman

Abstract:

Portable muscle stimulators for real-time applications has first introduced by Liberson in 1961. Now these systems has been advanced. In this study, FES (Functional Electrical Stimulator) and NMES (Neuromuscular Electrostimulator) systems are analyzed through their hardware and their quality of life improvements for foot drop patients. FES and NMES systems are used for people whose leg muscles and leg neural connections are healty but not able to walk properly because of their injured central nervous system like spinal cord injuries. These systems are used to stimulate neurons or muscles by getting information from other movements and programming these stimulations to get natural walk and it is accepted as a rehabilitation method for the correction of drop foot. This systems support person to approach natural form of walking. Foot drop is characterized by steppage gait. It is a gait abnormality. This systems helps to person for plantar and dorse reflection movements which are hard to done for foot drop patients.

Keywords: FES, foot drop, NMES, stimulator

Procedia PDF Downloads 388

Authors: Ananda Perera

Abstract:

Diet therapy has a positive impact on many diseases in General Practice. If a meal plan can be generated as easily as writing a drug prescription for dyspepsia, then the evidence and practice gap in nutrition therapy can be narrowed. Meal plans of 50 diet prescriptions were compared with the criteria for a healthy diet given by Australian authorities. The energy value of each meal plan was compared with the recommended daily energy requirements of the authorities for Diet Prescription Generator (DPG) accuracy. Meal plans generated were within the criteria laid down by the Australian authorities for a healthy diet.

Keywords: dieting, obesity, diabetes, weight loss, computerized decision support systems, dieting software, CDSS, meal plans

Procedia PDF Downloads 143

Authors: Festus Adedoyin, Nana Mbeah Otoo, Sofia Meacham

Abstract:

Hypertension is one of the main health issues in Ghana, where prevalence is higher in rural than in urban areas. This is due to the challenges rural areas have in accessing technology and healthcare services for hypertension control. This study's goal is to create a digital healthcare solution to alleviate this inequality. Through an analysis of current technology and problems, using the ring onion methodology, the study determined the needs for the intervention and evaluated healthcare disparities. An online application with teleconsultation capabilities, reminder mechanisms, and clinical decision support is part of the suggested solution. In outlying areas, mobile clinics in containers with the required equipment will be established. Heuristic evaluation and think-aloud sessions were used to assess the prototype's usability and navigational problems. This study highlights the need to develop digital health interventions to help manage hypertension in rural locations and decrease healthcare disparities. To develop and improve digital healthcare solutions for rural areas worldwide and in Ghana, this study might be used as a tool for future research.

Keywords: digital health, health inequalities, hypertension management, rural areas

Procedia PDF Downloads 112

Authors: Fadwa Chtioui

Abstract:

Vital Pulp Therapy (VPT) is nowadays challenging the deep-rooted dogma of root canal treatment, being the only therapeutic option for permanent teeth diagnosed with irreversible pulpitis or carious pulp exposure. Histologic and clinical research has shown that compromised dental pulp can be treated without the full removal or excavation of all healthy pulp, and the outcome of the partial or full pulpotomy followed by a Tricalcium-Silicate-based dressing seems to show promising results in maintaining pulp vitality and preserving affected teeth in the long term. By reviewing recent advances in the techniques of VPT and their clinical effectiveness and safety in permanent teeth with irreversible Pulpitis, this work provides a new understanding of pulp pathophysiology and defense mechanisms and will reform dental practitioners' decision-making in treating irreversible pulpits from root canal therapy to vital pulp therapy by taking advantage of the biological effects of Tricalcium Silicate materials.

Keywords: irreversible pulpitis, vital pulp therapy, pulpotomy, Tricalcium Silicate

Procedia PDF Downloads 61