Search results for: multivariate models.

Authors: Anwar Jarndal

Abstract:

In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design and modeling, neural networks, genetic optimization

Procedia PDF Downloads 369

Authors: Emad E. Abdallah, Alaa E. Abdallah, Bajes Y. Alskarnah

Abstract:

We introduce a robust three-dimensional watermarking algorithm for copyright protection and indexing. The basic idea behind our technique is to measure the interquartile range or the spread of the 3D model vertices. The algorithm starts by converting all the vertices to spherical coordinate followed by partitioning them into small groups. The proposed algorithm is slightly altering the interquartile range distribution of the small groups based on predefined watermark. The experimental results on several 3D meshes prove perceptual invisibility and the robustness of the proposed technique against the most common attacks including compression, noise, smoothing, scaling, rotation as well as combinations of these attacks.

Keywords: watermarking, three-dimensional models, perceptual invisibility, interquartile range, 3D attacks

Procedia PDF Downloads 462

Authors: Obasanjo Afolabi Bolarinwa

Abstract:

This study assesses the levels of knowledge of sexually transmitted infections among unmarried youths in Nigeria; examines the pattern of high risk sex among unmarried youths in Nigeria; investigate the socio-demographic factors (age, place of residence, religion, level of education, wealth index and employment status) affecting the practice of high-risk sexual behaviour and ascertain the relationships between knowledge of sexually transmitted infections and practice of high risk sex. The goal of the study is to identify the factors associated with the practice of high risk sex among youth. These were with a view to identifying critical actions needed to reduce high risk sexual behaviour among youths. The study employed secondary data. The data for the study were extracted from the 2013 Nigeria Demographic and Health Survey (NDHS). The 2013 NDHS collected information from 38,948 Women ages 15-49 years and 17,359 men ages 15-49. A total of 7,744 female and 6,027 male respondents were utilized in the study. In order to adjust for the effect of oversampling of the population, the weighting factor provided by Measure DHS was applied. The data were analysed using frequency distribution and logistic regression. The results show that both male (92.2%) and female (93.6%) have accurate knowledge of sexually transmitted infections. The study also revealed that prevalence of high risk sexual behavior is high among Nigerian youths; this is evident as 77.7% (female) and 78.4% (male) are engaging in high risk sexual behavior. The bivariate analysis shows that age of respondent (χ2=294.2; p < 0.05), religion (χ2=136.64; p < 0.05), wealth index (χ2=17.38; p < 0.05), level of education (χ2=34.73; p < 0.05) and employment status (χ2=94.54; p < 0.05) were individual factors significantly associated with high risk sexual behaviour among male while age of respondent (χ2=327.07; p < 0.05), place of residence (χ2=6.71; p < 0.05), religion (χ2=81.04; p < 0.05), wealth index (χ2=7.41; p < 0.05), level of education (χ2=18.12; p < 0.05) and employment status (χ2=51.02; p < 0.05) were individual factors significantly associated with high risk sexual behaviour among female. Furthermore, the study shows that there is a relationship between knowledge of sexually transmitted infections and high risk sex among male (χ2=38.32; p < 0.05) and female (χ2=18.37; p < 0.05). At multivariate level, the study revealed that individual characteristics such as age, religion, place of residence, wealth index, levels of education and employment status were statistically significantly related with high risk sexual behaviour among male and female (p < 0.05). Lastly, the study shows that knowledge of sexually transmitted infection was significantly related to high risk sexual behaviour among youths (p < 0.05). The study concludes that there is a high level of knowledge of sexually transmitted infections among unmarried youths in Nigeria. The practice of high risk sex is high among unmarried youths but higher among male youths. The prevalence of high risk sexual activity is higher for males when they are at disadvantage and higher for females when they are at advantage. Socio-demographic factors like age of respondents, religion, wealth index, place of residence, employment status and highest level of education are factors influencing high risk sexual behaviour among youths.

Keywords: high risk sex, wealth index, sexual behaviour, knowledge

Procedia PDF Downloads 245

Authors: Xiangtuo Chen, Paul-Henry Cournéde

Abstract:

Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

Procedia PDF Downloads 221

Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

Abstract:

Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

Procedia PDF Downloads 65

Authors: Arian Ebneyamini, Hoda Azimi, Jules Thibaults, F. Handan Tezel

Abstract:

In this study, a modification of Hennepe model for pervaporation separation of butanol from aqueous solutions using Polydimethylsiloxane (PDMS) mixed matrix membranes has been introduced and validated by experimental data. The model was compared to the original Hennepe model and few other models which are applicable for membrane gas separation processes such as Maxwell, Lewis Nielson and Pal. Theoretical modifications for non-ideal interface morphology have been offered to predict the permeability in case of interface void, interface rigidification and pore-blockage. The model was in a good agreement with experimental data.

Keywords: butanol, PDMS, modeling, pervaporation, mixed matrix membranes

Procedia PDF Downloads 204

Authors: Hung-Chi Chang

Abstract:

For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.

Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory

Procedia PDF Downloads 362

Authors: Monika Rani, Claudio Marchesi, Stefania Federici, Laura E. Depero

Abstract:

Degradation of the aquatic environment by plastic litter, especially microplastics (MPs), i.e., any water-insoluble solid plastic particle with the longest dimension in the range 1µm and 1000 µm (=1 mm) size, is an unfortunate indication of the advancement of the Anthropocene age on Earth. Microplastics formed due to natural weathering processes are termed as secondary microplastics, while when these are synthesized in industries, they are called primary microplastics. Their presence from the highest peaks to the deepest points in oceans explored and their resistance to biological and chemical decay has adversely affected the environment, especially marine life. Even though the presence of MPs in the marine environment is well-reported, a legitimate and authentic analytical technique to sample, analyze, and quantify the MPs is still under progress and testing stages. Among the characterization techniques, vibrational spectroscopic techniques are largely adopted in the field of polymers. And the ongoing miniaturization of these methods is on the way to revolutionize the plastic recycling industry. In this scenario, the capability and the feasibility of a miniaturized near-infrared (MicroNIR) spectroscopy combined with chemometrics tools for qualitative and quantitative analysis of urban plastic waste collected from a recycling plant and microplastic mixture fragmented in the lab were investigated. Based on the Resin Identification Code, 250 plastic samples were used for macroplastic analysis and to set up a library of polymers. Subsequently, MicroNIR spectra were analysed through the application of multivariate modelling. Principal Components Analysis (PCA) was used as an unsupervised tool to find trends within the data. After the exploratory PCA analysis, a supervised classification tool was applied in order to distinguish the different plastic classes, and a database containing the NIR spectra of polymers was made. For the microplastic analysis, the three most abundant polymers in the plastic litter, PE, PP, PS, were mechanically fragmented in the laboratory to micron size. The distinctive arrangement of blends of these three microplastics was prepared in line with a designed ternary composition plot. After the PCA exploratory analysis, a quantitative model Partial Least Squares Regression (PLSR) allowed to predict the percentage of microplastics in the mixtures. With a complete dataset of 63 compositions, PLS was calibrated with 42 data-points. The model was used to predict the composition of 21 unknown mixtures of the test set. The advantage of the consolidated NIR Chemometric approach lies in the quick evaluation of whether the sample is macro or micro, contaminated, coloured or not, and with no sample pre-treatment. The technique can be utilized with bigger example volumes and even considers an on-site evaluation and in this manner satisfies the need for a high-throughput strategy.

Keywords: chemometrics, microNIR, microplastics, urban plastic waste

Procedia PDF Downloads 143

Authors: Sariyapa Kantawan, Muanfun Kongsomsawaeng

Abstract:

Chanthaburi River community is an old mixed-culture village established in the 16th century. The town advanced more rapidly than others due to the ease of transportation at the time, which used the river as a road. Therefore, the province's first road begins here, propelling it to become an important commercial and trading center for almost a century. As a result of diverse culture, the architecture has been affected by Western, Thai, Chinese, and Vietnamese, resulting in a new and distinctive style. To share the realm of memory, digital media enable the city to communicate its history and culture. This article describes a project that combines the concepts of digital storytelling and augmented reality and connects them to Chanthaburi River Community Culture by using QR codes as makers to display 3D models on mobile screens.

Keywords: digital storytelling, community culture, river community, cultural heritage, augmented reality

Procedia PDF Downloads 42

Authors: Alexis Aldo Mendoza Villarroel, Ademir Clemente Villena Zevallos, Cristian Jose Lopez Del Alamo

Abstract:

With the advancement of technology it is now possible to scan entire objects and obtain their digital representation by using point clouds or polygon meshes. However, some objects may be broken or have missing parts; thus, several methods focused on this problem have been proposed based on Geometric Deep Learning, such as GCNN, ACNN, PointNet, among others. In this article an approach from a different paradigm is proposed, using metric data structures to index global descriptors in the spectral domain and allow the recovery of a set of similar models in polynomial time; to later use the Iterative Close Point algorithm and recover the parts of the incomplete model using the geometry and topology of the model with less Hausdorff distance.

Keywords: 3D reconstruction method, point cloud completion, shape completion, similarity search

Procedia PDF Downloads 111

Authors: Shuo Liu

Abstract:

In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

Procedia PDF Downloads 84

Authors: Majid Rezayi, Sh. Shahaboddin, HNM E. Mahmud, A. Yadollah, A. Saeid, A. Yatimah

Abstract:

In this study, the adaptive neuro-fuzzy inference system (ANFIS) was applied to obtain the membrane composition model affecting the potential response of our reported polymeric PVC sensor for determining the titanium (III) ions. The performance statistics of the artificial neural network (ANN) and linear regression models for potential slope prediction of membrane composition of titanium (III) ion selective electrode were compared with ANFIS technique. The results show that the ANFIS model can be used as a practical tool for obtaining the Nerntian slope of the proposed sensor in this study.

Keywords: adaptive neuro fuzzy inference, PVC sensor, titanium (III) ions, Nerntian slope

Procedia PDF Downloads 266

Authors: Priyanka Mondal, Santosh K. Sarkar

Abstract:

The present study investigated the spatiotemporal distribution and ecological risk assessment of trace elements of surface sediments (top 0 - 5 cm; grain size ≤ 0.63 µm) in relevance to sediment quality characteristics along the Ganges River Estuary, India. Sediment samples were collected during ebb tide from intertidal regions covering seven sampling sites of diverse environmental stresses. The elements were analyzed with the help of ICPAES. This positive, mixohaline, macro-tidal estuary has global significance contributing ecological and economic services. Presence of fine-clayey particle (47.03%) enhances the adsorption as well as transportation of trace elements. There is a remarkable inter-metallic variation (mg kg-1 dry weight) in the distribution pattern in the following manner: Al (31801± 15943) > Fe (23337± 7584) > Mn (461±147) > S(381±235) > Zn(54 ±18) > V(43 ±14) > Cr(39 ±15) > As (34±15) > Cu(27 ±11) > Ni (24 ±9) > Se (17 ±8) > Co(11 ±3) > Mo(10 ± 2) > Hg(0.02 ±0.01). An overall trend of enrichment of majority of trace elements was very much pronounced at the site Lot 8, ~ 35km upstream of the estuarine mouth. In contrast, the minimum concentration was recorded at site Gangasagar, mouth of the estuary, with high energy profile. The prevalent variations in trace element distribution are being liable for a set of cumulative factors such as hydrodynamic conditions, sediment dispersion pattern and textural variations as well as non-homogenous input of contaminants from point and non-point sources. In order to gain insight into the trace elements distribution, accumulation, and their pollution status, geoaccumulation index (Igeo) and enrichment factor (EF) were used. The Igeo indicated that surface sediments were moderately polluted with As (0.60) and Mo (1.30) and strongly contaminated with Se (4.0). The EF indicated severe pollution of Se (53.82) and significant pollution of As (4.05) and Mo (6.0) and indicated the influx of As, Mo and Se in sediments from anthropogenic sources (such as industrial and municipal sewage, atmospheric deposition, agricultural run-off, etc.). The significant role of the megacity Calcutta in relevance to the untreated sewage discharge, atmospheric inputs and other anthropogenic activities is worthwhile to mention. The ecological risk for different trace elements was evaluated using sediment quality guidelines, effects range low (ERL), and effect range median (ERM). The concentration of As, Cu and Ni at 100%, 43% and 86% of the sampling sites has exceeded the ERL value while none of the element concentration exceeded ERM. The potential ecological risk index values revealed that As at 14.3% of the sampling sites would pose relatively moderate risk to benthic organisms. The effective role of finer clay particles for trace element distribution was revealed by multivariate analysis. The authors strongly recommend regular monitoring emphasizing on accurate appraisal of the potential risk of trace elements for effective and sustainable management of this estuarine environment.

Keywords: pollution assessment, sediment contamination, sediment quality, trace elements

Procedia PDF Downloads 249

Authors: Phillipa Denise Peart

Abstract:

Black Asian and Minority Ethnic (BAME) people are more at risk of developing mental health disorders because they are more exposed to unfavorable social, economic, and environmental circumstances. These include housing, education, employment, community development, stigma, and discrimination. However, the majority of BAME mental health intervention studies focus on treatment with therapeutically effective drugs and use basic economic methods to evaluate their effectiveness; as a result, little is invested in the economic assessment of psychosocial interventions in BAME mental health. The UK government’s austerity programme and reduced funds for mental health services, has increased the need for the evaluation and assessment of initiatives to focus on value for money. The No Health without Mental Health policy (2011) provides practice guidance to practitioners, but there is little or no mention of the need to provide mental health initiatives targeted at BAME communities that are effective in terms of their impact and the cost-effectiveness. This, therefore, appears to contradict with and is at odds with the wider political discourse, which suggests there should be an increasing focus on health economic evaluation. As a consequence, it could be argued that whilst such policies provide direction to organisations to provide mental health services to the BAME community, by not requesting effective governance, assurance, and evaluation processes, they are merely paying lip service to address these problems and not helping advance knowledge and practice through evidence-based approaches. As a result, BAME communities suffer due to lack of efficient resources that can aid in the recovery process. This research study explores the mental health initiatives targeted at BAME communities, and analyses the techniques used when examining the cost effectiveness of mental health initiatives for BAME mental health communities. Using critical discourse analysis as an approach and method, mental health services will be selected as case studies, and their evaluations will be examined, alongside the political drivers that frame, shape, and direct their work. In doing so, it will analyse what the mental health policies initiatives are, how the initiatives are directed and demonstrate how economic models of evaluation are used in mental health programmes and how the value for money impacts and outcomes are articulated by mental health programme staff. It is anticipated that this study will further our understanding in order to provide adequate mental health resources and will deliver creative, supportive research to ensure evaluation is effective for the government to provide and maintain high quality and efficient mental health initiatives targeted at BAME communities.

Keywords: black, Asian and ethnic minority, economic models, mental health, health policy

Procedia PDF Downloads 103

Authors: Babak Daneshvar Rouyendegh

Abstract:

The aim of this study is to develop and describe a new methodology for the Multi-Criteria Decision-Making (MCDM) problem using Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE) model. The proposed models enable Decision-Makers (DMs) on the assessment and use Intuitionistic Fuzzy numbers (IFN). A numerical example is provided to demonstrate and clarify the proposed analysis procedure. Also, an empirical experiment is conducted to validation the effectiveness.

Keywords: Decision-Makers (DMs), Multi-Criteria Decision-Making (MCDM), Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE), Intuitionistic Fuzzy Numbers (IFN)

Procedia PDF Downloads 667

Authors: Cheng-Chi Yu, Yu-Shiue Wang, Kei-Lin Kuo

Abstract:

Active Independent Front Steering system is a steering system which can according to vehicle driving situation adjusts the relation of steering angle between inner wheel and outer wheel. In low-speed cornering, AIFS sets the steering angles of inner and outer wheel into Ackerman steering geometry to make vehicle has less cornering radius. Besides, AIFS changes the steering geometry to parallel or even anti-Ackerman steering geometry to keep vehicle stability in high-speed cornering. Therefore, based on the analysis of the vehicle steering behavior from different steering geometries, this study develops a new screw type of active independent front steering system to make vehicles best cornering performance at any speeds. The screw type of active independent front steering system keeps the pinion and separates the rack into main rack and second rack. Two racks connect by a screw. Extra screw rotated motion powered by assistant motor through coupler makes second rack move relative to main rack, which can adjust both steering ratio and steering geometry. First of all, this study distinguishes the steering geometry by using Ackerman percentage and utilizes the software of ADAMS/Car to construct diverse steering geometry models. The different steering geometries are compared at low-speed and high-speed cornering, and then control strategies of the active independent front steering systems could be formulated. Secondly, this study applies closed loop equation to analyze tire steering angles and carries out optimization calculations to make the steering geometry from traditional rack and pinion steering system near to Ackerman steering geometry. Steering characteristics of the optimum steering mechanism and motion characteristics of vehicle installed the steering mechanism are verified by ADAMS/Car models of front suspension and full vehicle respectively. By adding dual auxiliary rack and dual motor to the optimum steering mechanism, the active independent front steering system could be developed to achieve the functions of variable steering ratio and variable steering geometry. At last, this study uses ADAMS/Car and Matlab/Simulink to co-simulate the cornering motion of vehicles confirms the vehicle installed the Active Independent Front Steering (AIFS) system has better handling performance than that with Active Independent Steering (AFS) system or with Electric Power Steering (EPS) system. At low-speed cornering, the vehicles with AIFS system and with AFS system have better maneuverability, less cornering radius, than the traditional vehicle with EPS system because that AIFS and AFS systems both provide function of variable steering ratio. However, there is a slight penalty in the motor(s) power consumption. In addition, because of the capability of variable steering geometry, the vehicle with AIFS system has better high-speed cornering stability, trajectory keeping, and even less motor(s) power consumption than that with EPS system and also with AFS system.

Keywords: active front steering system, active independent front steering system, steering geometry, steering ratio

Procedia PDF Downloads 175

Authors: Giuliana Murfet, Heidi Behrens

Abstract:

Chronic disease is Australia’s biggest health concern and obesity the leading risk factor for many. Obesity and chronic disease have a higher representation in rural Tasmania, where levels of socio-disadvantage are also higher. People living outside major cities have less access to health services and poorer health outcomes. To help primary healthcare professionals manage obesity, the Australian NHMRC evidence-based clinical practice guidelines for management of overweight and obesity in adults were developed. They include recommendations for practice and models for obesity management. To our knowledge there has been no research conducted that investigates translation of these guidelines into practice in rural-regional areas; where implementation can be complicated by limited financial and staffing resources. Also, the systematic review that informed the guidelines revealed a lack of evidence for chronic disease models of obesity care. The aim was to establish and evaluate a multidisciplinary model for obesity management in a group of adult people with type 2 diabetes in a dispersed rural population in Australia. Extensive stakeholder engagement was undertaken to both garner support for an obesity clinic and develop a sustainable model of care. A comprehensive nurse practitioner-led outpatient model for obesity care was designed. Multidisciplinary obesity clinics for adults with type 2 diabetes including a dietitian, psychologist, physiotherapist and nurse practitioner were set up in the north-west of Tasmania at two geographically-rural towns. Implementation was underpinned by the NHMRC guidelines and recommendations focused on: assessment approaches; promotion of health benefits of weight loss; identification of relevant programs for individualising care; medication and bariatric surgery options for obesity management; and, the importance of long-term weight management. A clinical pathway for adult weight management is delivered by the multidisciplinary team with recognition of the impact of and adjustments needed for other comorbidities. The model allowed for intensification of intervention such as bariatric surgery according to recommendations, patient desires and suitability. A randomised controlled trial is ongoing, with the aim to evaluate standard care (diabetes-focused management) compared with an obesity-related approach with additional dietetic, physiotherapy, psychology and lifestyle advice. Key barriers and enablers to guideline implementation were identified that fall under the following themes: 1) health care delivery changes and the project framework development; 2) capacity and team-building; 3) stakeholder engagement; and, 4) the research project and partnerships. Engagement of not only local hospital but also state-wide health executives and surgical services committee were paramount to the success of the project. Staff training and collective development of the framework allowed for shared understanding. Staff capacity was increased with most taking on other activities (e.g., surgery coordination). Barriers were often related to differences of opinions in focus of the project; a desire to remain evidenced based (e.g., exercise prescription) without adjusting the model to allow for consideration of comorbidities. While barriers did exist and challenges overcome; the development of critical partnerships did enable the capacity for a potential model of obesity care for rural regional areas. Importantly, the findings contribute to the evidence base for models of diabetes and obesity care that coordinate limited resources.

Keywords: diabetes, interdisciplinary, model of care, obesity, rural regional

Procedia PDF Downloads 217

Authors: Keith Schofield, Leigh Morland

Abstract:

Storytelling is an established means of leadership and management development and is also considered a form of leadership of self and others in its own right. This study focuses on the utility of storytelling in the development of management narratives in an MBA programme; sources include programme participants as well as international recruiters, whose voices are often only heard in terms of economic contribution and globalisation. For many MBA candidates, the return to study requires the development of a new identity which complements their professional identity; each candidate has their own journey and expectations, the use of story can enable candidates to explore their aspirations and assumptions and give voice to previously unspoken ideas. For international recruitment, the story of market development and change must be captured if MBAs are to remain fit for purpose. If used effectively, story acts as a form of critical reflection that can inform the learning journeys of individuals, emerging identities as well as the ongoing design and development of programmes. The landscape of management education is shifting; the MBA begins to attract a different kind of candidate, some are younger than before, others are seeking validation for their existing work practices, yet more are entrepreneurial and wish to capitalise on an institutional experience to further their career. There is a shift in context, creating uncertainty and ambiguity for programme managers and recruiters, thus requiring institutions to create a new MBA narrative. This study utilises Lego SeriousPlay as the means to engaging programme participants and international agents in telling the story of their MBA. We asked MBA participants to tell the story of their leadership and management aspirations and compare these to stories of their development journeys, allowing for critical reflection of their respective development gaps. We asked international recruiters, who act as university agents and promote courses in the student’s country of origin, to explore their mental models of MBA candidates and their learning agenda. The purpose of this process was to explore the agent’s perception of the MBA programme and to articulate the student journey from a recruitment perspective. The paper’s unique contribution is in combining these stories in order to explore the assumptions that determine programme design. Data drawn from reflective statements together with images of Lego ‘builds’ created the opportunity for reflection between the mental models of these groups. Findings will inform the design of the MBA journey and experience; we review the extent to which the changing identities of learners are congruent with programme design. Data from international recruiters also determines the extent to which marketing and recruitment strategies identify with would be candidates.

Keywords: critical reflection, programme management, recruitment, storytelling

Procedia PDF Downloads 215

Authors: Mohammad Ali Tabibi, Farzad Nazemi, Nasrin Salimian

Abstract:

Background: Peritoneal dialysis (PD) is a prevalent renal replacement therapy for patients with end-stage renal disease. Despite its benefits, PD patients often experience reduced physical activity and physical function, which can negatively impact dialysis adequacy and overall health outcomes. Despite the known benefits of maintaining physical activity in chronic disease management, the specific interplay between physical inactivity, physical function, and dialysis adequacy in PD patients remains underexplored. Understanding this relationship is essential for developing targeted interventions to enhance patient care and outcomes in this vulnerable population. This study aims to assess the impact of physical inactivity on dialysis adequacy and functional health in PD patients. Methods: This cross-sectional study included 135 peritoneal dialysis patients from multiple dialysis centers. Physical inactivity was measured using the International Physical Activity Questionnaire (IPAQ), while physical function was assessed using the Short Physical Performance Battery (SPPB). Dialysis adequacy was evaluated using the Kt/V ratio. Additional variables such as demographic data, comorbidities, and laboratory parameters were collected to control for potential confounders. Statistical analyses were performed to determine the relationships between physical inactivity, physical function, and dialysis adequacy. Results: The study cohort comprised 70 males and 65 females with a mean age of 55.4 ± 13.2 years. A significant proportion of the patients (65%) were categorized as physically inactive based on IPAQ scores. Inactive patients demonstrated significantly lower SPPB scores (mean 6.2 ± 2.1) compared to their more active counterparts (mean 8.5 ± 1.8, p < 0.001). Dialysis adequacy, as measured by Kt/V, was found to be suboptimal (Kt/V < 1.7) in 48% of the patients. There was a significant positive correlation between physical function scores and Kt/V values (r = 0.45, p < 0.01), indicating that better physical function is associated with higher dialysis adequacy. Also, there was a significant negative correlation between physical inactivity and physical function (r = -0.55, p < 0.01). Additionally, physically inactive patients had lower Kt/V ratios compared to their active counterparts (1.3 ± 0.3 vs. 1.8 ± 0.4, p < 0.05). Multivariate regression analysis revealed that physical inactivity was an independent predictor of reduced dialysis adequacy (β = -0.32, p < 0.01) and poorer physical function (β = -0.41, p < 0.01) after adjusting for age, sex, comorbidities, and dialysis vintage. Conclusion: This study underscores the critical role of physical activity and physical function in maintaining adequate dialysis in peritoneal dialysis patients. These findings highlight the need for targeted interventions to promote physical activity in this population to improve their overall health outcomes. Future research should focus on developing and evaluating exercise programs tailored for PD patients to enhance their physical function and dialysis adequacy. The findings suggest that interventions aimed at increasing physical activity and improving physical function may enhance dialysis adequacy and overall health outcomes in this population. Further research is warranted to explore the mechanisms underlying these associations and to develop targeted strategies for enhancing patient care.

Keywords: inactivity, physical function, peritoneal dialysis, dialysis adequacy

Procedia PDF Downloads 14

Authors: Mehdi Janbaz

Abstract:

The global financial crisis and the credit crunch that followed magnified the importance of credit risk management and its crucial role in the stability of all financial sectors and the whole of the system. Many believe that risks faced by the sovereign sector are highly interconnected with banking risks and most likely to trigger and reinforce each other. This study aims to examine (1) the impact of banking and interbank risk factors on the sovereign credit risk of Eurozone, and (2) how the EU Credit Default Swaps spreads dynamics are affected by the Crude Oil price fluctuations. The hypothesizes are tested by employing fitting risk measures and through a four-staged linear modeling approach. The sovereign senior 5-year Credit Default Swap spreads are used as a core measure of the credit risk. The monthly time-series data of the variables used in the study are gathered from the DataStream database for a period of 2008-2019. First, a linear model test the impact of regional macroeconomic and market-based factors (STOXX, VSTOXX, Oil, Sovereign Debt, and Slope) on the CDS spreads dynamics. Second, the bank-specific factors, including LIBOR-OIS spread (the difference between the Euro 3-month LIBOR rate and Euro 3-month overnight index swap rates) and Euribor, are added to the most significant factors of the previous model. Third, the global financial factors including EURO to USD Foreign Exchange Volatility, TED spread (the difference between 3-month T-bill and the 3-month LIBOR rate based in US dollars), and Chicago Board Options Exchange (CBOE) Crude Oil Volatility Index are added to the major significant factors of the first two models. Finally, a model is generated by a combination of the major factor of each variable set in addition to the crisis dummy. The findings show that (1) the explanatory power of LIBOR-OIS on the sovereign CDS spread of Eurozone is very significant, and (2) there is a meaningful adverse co-movement between the Crude Oil price and CDS price of Eurozone. Surprisingly, adding TED spread (the difference between the three-month Treasury bill and the three-month LIBOR based in US dollars.) to the analysis and beside the LIBOR-OIS spread (the difference between the Euro 3M LIBOR and Euro 3M OIS) in third and fourth models has been increased the predicting power of LIBOR-OIS. Based on the results, LIBOR-OIS, Stoxx, TED spread, Slope, Oil price, OVX, FX volatility, and Euribor are the determinants of CDS spreads dynamics in Eurozone. Moreover, the positive impact of the crisis period on the creditworthiness of the Eurozone is meaningful.

Keywords: CDS, crude oil, interbank risk, LIBOR-OIS, OVX, sovereign credit risk, TED

Procedia PDF Downloads 133

Authors: Julio Brégains, Ángel Carro, José-Manuel Andión

Abstract:

Virtual 3D objects constitute invaluable tools for teaching practical engineering subjects at all -from basic to advanced- educational levels. For instance, they can be equipped with animation or informative labels, manipulated by mouse movements, and even be immersed in a real environment through augmented reality. In this paper, we present the investigation and description of a set of applications prepared for creating, editing, and making use of interactive 3D models to represent electric and electronic devices and systems. Several examples designed with the described tools are exhibited, mainly to show their capabilities as educational technological aids, applicable not only to the field of electricity and electronics but also to a much wider range of technical areas.

Keywords: educational technology, Google model viewer, ICT educational tools, interactive teaching, new tools for teaching

Procedia PDF Downloads 58

Authors: Farzad Hosseini Hossein Abadi, Cristina Prieto Sierra, Cesar Álvarez Díaz

Abstract:

Predicting streamflow accurately in flashy catchments prone to floods is a major research and operational challenge in hydrological modeling. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have shown to be promising in achieving accurate hydrological predictions at daily and hourly time scales. In this work, a multi-timescale LSTM (MTS-LSTM) network was applied to the context of regional hydrological predictions at an hourly time scale in flashy catchments. The case study includes 40 catchments allocated in the Basque Country, north of Spain. We explore the impact of hyperparameters on the performance of streamflow predictions given by regional deep learning models through systematic hyperparameter tuning - where optimal regional values for different catchments are identified. The results show that predictions are highly accurate, with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) metrics values as high as 0.98 and 0.97, respectively. A principal component analysis reveals that a hyperparameter related to the length of the input sequence contributes most significantly to the prediction performance. The findings suggest that input sequence lengths have a crucial impact on the model prediction performance. Moreover, employing catchment-scale analysis reveals distinct sequence lengths for individual basins, highlighting the necessity of customizing this hyperparameter based on each catchment’s characteristics. This aligns with well known “uniqueness of the place” paradigm. In prior research, tuning the length of the input sequence of LSTMs has received limited focus in the field of streamflow prediction. Initially it was set to 365 days to capture a full annual water cycle. Later, performing limited systematic hyper-tuning using grid search, revealed a modification to 270 days. However, despite the significance of this hyperparameter in hydrological predictions, usually studies have overlooked its tuning and fixed it to 365 days. This study, employing a simultaneous systematic hyperparameter tuning approach, emphasizes the critical role of input sequence length as an influential hyperparameter in configuring LSTMs for regional streamflow prediction. Proper tuning of this hyperparameter is essential for achieving accurate hourly predictions using deep learning models.

Keywords: LSTMs, streamflow, hyperparameters, hydrology

Procedia PDF Downloads 41

Authors: Hamid Gholami

Abstract:

During the years, the language teaching methods have been the offshoots of schools of thought in psychology. The methods were mainly influenced by their contemporary psychological approaches, as Audiolingualism was based on behaviorism and Communicative Language Teaching on constructivism. In 1950s, the text books were full of repetition exercises which were encouraged by Behaviorism. In 1980s they got filled with communicative exercises as suggested by constructivism. The trend went on to nowadays that sees no specific method as prevalent since none of the schools of thought seem to be illustrative of the complexity in human being learning. But some changes can be notable; some textbooks are giving more and more space to repetition exercises at least to enhance some aspects of language proficiency, namely collocations, rhythm and intonation, and conversation models. These changes may mark the reemergence of one of the once widely accepted schools of thought in psychology; behaviorism.

Keywords: language teaching methods, psychology, schools of thought, Behaviorism

Procedia PDF Downloads 550

Authors: Gram Y. Rivas Sanchez

Abstract:

The seismic design codes in the world allow the analysis of structures considering an elastic-linear behavior; however, against earthquakes, the structures exhibit non-linear behaviors that induce damage to their elements. For this reason, it is necessary to use non-linear methods to analyze these structures, being the dynamic methods that provide more reliable results but require a lot of computational costs; on the other hand, non-linear static methods do not have this disadvantage and are being used more and more. In the present work, the nonlinear static analysis (pushover) of RC frame buildings of three, five, and seven stories is carried out considering models of concentrated plasticity using plastic hinges; and the seismic performance points are determined using ATC-40, FEMA 356, and FEMA 440 guidelines. Using this last standard, the highest inelastic displacements and basal shears are obtained, providing designs that are more conservative.

Keywords: pushover, nonlinear, RC building, FEMA 440, ATC 40

Procedia PDF Downloads 139

Authors: Thao Nguyen, Maximiliano Hyon, Sany Rajagukguk, Anna Melkonyan

Abstract:

Introduction: Type 2 Diabetes is a well-established risk factor for severe SARS-CoV-2 infection. Uncontrolled hyperglycemia in patients with established or newly diagnosed diabetes is associated with poor outcomes, including increased mortality and hospital length of stay. Objectives: Our study aims to compare three different glycemic management strategies and their association with clinical outcomes in patients hospitalized for moderate to severe SARS-CoV-2 infection. Identifying optimal glycemic management strategies will improve the quality of patient care and improve their outcomes. Method: This is a retrospective observational study on patients hospitalized at Adventist Health White Memorial with severe SARS-CoV-2 infection from 11/1/2020 to 02/28/2021. The following inclusion criteria were used: positive SARS-CoV-2 PCR test, age >18 yrs old, diabetes or random glucose >200 mg/dL on admission, oxygen requirement >4L/min, and treatment with glucocorticoids. Our exclusion criteria included: ICU admission within 24 hours, discharge within five days, death within five days, and pregnancy. The patients were divided into three glycemic management groups: Group 1, managed solely by the Primary Team, Group 2, by Pharmacy; and Group 3, by Endocrinologist. Primary outcomes were average glucose on Day 5, change in glucose between Days 3 and 5, and average insulin dose on Day 5 among groups. Secondary outcomes would be upgraded to ICU, inpatient mortality, and hospital length of stay. For statistics, we used IBM® SPSS, version 28, 2022. Results: Most studied patients were Hispanic, older than 60, and obese (BMI >30). It was the first CV-19 surge with the Delta variant in an unvaccinated population. Mortality was markedly high (> 40%) with longer LOS (> 13 days) and a high ICU transfer rate (18%). Most patients had markedly elevated inflammatory markers (CRP, Ferritin, and D-Dimer). These, in combination with glucocorticoids, resulted in severe hyperglycemia that was difficult to control. Average glucose on Day 5 was not significantly different between groups primary vs. pharmacy vs. endocrine (220.5 ± 63.4 vs. 240.9 ± 71.1 vs. 208.6 ± 61.7 ; P = 0.105). Change in glucose from days 3 to 5 was not significantly different between groups but trended towards favoring the endocrinologist group (-26.6±73.6 vs. 3.8±69.5 vs. -32.2±84.1; P= 0.052). TDD insulin was not significantly different between groups but trended towards higher TDD for the endocrinologist group (34.6 ± 26.1 vs. 35.2 ± 26.4 vs. 50.5 ± 50.9; P=0.054). The endocrinologist group used significantly more preprandial insulin compared to other groups (91.7% vs. 39.1% vs. 65.9% ; P < 0.001). The pharmacy used more basal insulin than other groups (95.1% vs. 79.5% vs. 79.2; P = 0.047). There were no differences among groups in the clinical outcomes: LOS, ICU upgrade, or mortality. Multivariate regression analysis controlled for age, sex, BMI, HbA1c level, renal function, liver function, CRP, d-dimer, and ferritin showed no difference in outcomes among groups. Conclusion: Given high-risk factors in our population, despite efforts from the glycemic management teams, it’s unsurprising no differences in clinical outcomes in mortality and length of stay.

Keywords: glycemic management, strategies, hospitalized, SARS-CoV-2, outcomes

Procedia PDF Downloads 432

Authors: Si Chen, Caroline Wiltshire, Bin Li

Abstract:

This study statistically models the surface f0 contour and the underlying pitch target of a well-studied third sandhi tone of Mandarin Chinese. Although the growth curve analysis on the surface f0 contours indicates non-neutralization of this sandhi tone (T3) and the base T2, their underlying pitch targets do show neutralization. These results in Mandarin are also consistent with the perception of native speakers, where they cannot distinguish the third T3 from the base T2, compensating contextual variation. It is possible to use the proposed statistical procedure of testing underlying pitch targets to verify tone sandhi processes in other tonal languages.

Keywords: growth curve analysis, Mandarin Chinese, tone sandhi, underlying pitch target

Procedia PDF Downloads 318

Authors: Pui-Lai To, Chechen Liao, Tzu-Ling Lin

Abstract:

Virtual communities have created a range of new social spaces in which to meet and interact with one another. Both as a stand-alone model or as a supplement to sustain competitive advantage for normal business models, building virtual communities has been hailed as one of the major strategic innovations of the new economy. However for a virtual community to evolve, the biggest challenge is how to make members actively give information or provide advice. Even in busy virtual communities, usually, only a small fraction of members post information actively. In order to investigate the determinants of information giving willingness of those contributors who usually actively provide their opinions, we proposed a model to understand the reasons for contribution in communities. The study will definitely serve as a basis for the future growth of information giving in virtual communities.

Keywords: information giving, social identity, trust, virtual community

Procedia PDF Downloads 309

Authors: Christopher Deekia Nwimae, Nigel Simms, Liyun Lao

Abstract:

Erosion in pipe bends caused by particles is a major obstacle in the oil and gas fields and might cause the breakdown of production equipment. This work studied the effects imposed by flow velocity and impact of solid particles diameter in an elbow; erosion rate was verified with experimental data using the computational fluid dynamics (CFD) approach. Two-way coupled Euler-Lagrange and discrete phase model was employed to calculate the air/solid particle flow in an elbow. One erosion model and three-particle rebound models were used to predict the erosion rate on the 90° elbows. The generic erosion model was used in the CFD-based erosion model, and after comparing it with experimental data, results showed agreement with the CFD-based predictions as observed.

Keywords: erosion, prediction, elbow, computational fluid dynamics

Procedia PDF Downloads 143

Authors: B. Güney, Ç. Teke

Abstract:

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

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

Procedia PDF Downloads 637

Authors: H. Benmoussa, A. A. El Kalam, A. Ait Ouahman

Abstract:

The design and implementation of intrusion detection systems (IDS) remain an important area of research in the security of information systems. Despite the importance and reputation of the current intrusion detection systems, their efficiency and effectiveness remain limited as they should include active defense approach to allow anticipating and predicting intrusions before their occurrence. Consequently, they must be readapted. For this purpose we suggest a new generation of distributed intrusion detection system based on preventive detection approach and using intelligent and mobile agents. Our architecture benefits from mobile agent features and addresses some of the issues with centralized and hierarchical models. Also, it presents advantages in terms of increasing scalability and flexibility.

Keywords: Intrusion Detection System (IDS), preventive detection, mobile agents, distributed architecture

Procedia PDF Downloads 568