Search results for: medical model

Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Tyler D. Cesarone, Tatiana M. Wugalter

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The movement of patients from the Global North to the Global South in pursuit of inexpensive healthcare and touristic experiences dominates the academic discourse on international medical travel (IMT). However, medical travel exists in higher numbers between Global South countries as patients who lack trust in, and feel disenfranchised by, their national healthcare systems seek treatment in nearby countries. Through a review of the existing literature, this paper examines patterns of IMT in the Middle East, Southeast Asia, and Southern Africa, distinguishing North-South medical tourism from South-South intra-regional medical mobility (IRMM). Evidence from these case studies demonstrates that notions of medical distrust and disenfranchisement, rooted in low-resourced and poor quality healthcare systems, are key drivers of IRMM in the Global South. The movement of patients from lower income to proximate higher income countries not only reveals tensions between patients and their healthcare systems but widens gaps in the quality of healthcare between departing and destination countries. In analyzing these cross-regional similarities, the paper moves beyond the current literature’s focus on singular case studies to expose global patterns of South-South IRMM. This presents a shift from the traditional focus on North-South medical tourism, demonstrating how disparities in healthcare systems both influence and are influenced by IRMM.

Keywords: global South, healthcare quality, international medical travel (IMT), intra-regional medical mobility (IRMM), medical disenfranchisement, medical distrust, medical tourism

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Authors: Segen Asayehegn

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Introduction: In Tigray, Ethiopia, next to cervical cancer, breast cancer is one of the most common cancer health problems for women. Objectives: This article is proposed to identify the prospective and potential risk factors affecting the time-to-first-recurrence of breast cancer patients in Tigray, Ethiopia. Methods: The data were taken from the patient’s medical record that registered from January 2010 to January 2020. The study considered a sample size of 1842 breast cancer patients. Powerful non-parametric and parametric shared frailty survival regression models (FSRM) were applied, and model comparisons were performed. Results: Out of 1842 breast cancer patients, about 1290 (70.02%) recovered/cured the disease. The median cure time from breast cancer is found at 12.8 months. The model comparison suggested that the lognormal parametric shared a frailty survival regression model predicted that treatment, stage of breast cancer, smoking habit, and marital status significantly affects the first recurrence of breast cancer. Conclusion: Factors like treatment, stages of cancer, and marital status were improved while smoking habits worsened the time to cure breast cancer. Recommendation: Thus, the authors recommend reducing breast cancer health problems, the regional health sector facilities need to be improved. More importantly, concerned bodies and medical doctors should emphasize the identified factors during treatment. Furthermore, general awareness programs should be given to the community on the identified factors.

Keywords: acceleration factor, breast cancer, Ethiopia, shared frailty survival models, Tigray

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Authors: L. S. Zavodna, J. Zavodny Pospisil

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The aim of this paper is to identify the factors for sustainability in the accommodation sector. Although sustainability is a current trend in tourism, not many facilities know how to apply the concept in practice. This paper presents a model for the implementation of sustainability in hotels, hostels, campgrounds, or other facilities. First, there are identified sections of each accommodation facility, which can contribute to sustainability. Furthermore, concrete steps are presented to transfer this model into reality.

Keywords: accommodation sector, model, sustainable tourism, sustainability

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Authors: Urmi Khatri

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Capital asset pricing model (CAPM) draws a direct relationship between the risk and the expected rate of return. There was a criticism on the beta and the assumptions of CAPM, as they are not applicable in the real world. Fama French Three Factor Model and Fama French Five Factor Model have given different factors, which have an impact on the return of any asset like size, value, investment and profitability. This study proposes to see Capital Asset pricing Model through the lenses of the quality aspect. In the study, the six factors are studied. The Fama French Five Factor Model and addition of the quality dimension are studied. Here, Graham’s seven quality and quantity criteria are measured to determine the score of the sample firms. Thus, this study tries to check the model fit. The beta coefficient of the quality dimension and the R square value is seen to determine validity of the proposed model. The sample is drawn from the firms listed on Indian Stock Exchange (BSE). For the study, only nonfinancial firms are been selected. The time period of the study is from January 1999 to December 2019. Hence, the primary objective of the study is to check how robust the model becomes after giving the quality dimension to the capital asset pricing model in addition to the size, value, profitability and investment.

Keywords: asset pricing model, CAPM, Graham’s score, G-score, multifactor model, quality

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Authors: Abdelouaheb Rouabhi

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In order to study the plastic resource of structures, the elastic-plastic single degree of freedom model described by Prandtl diagram is widely used. The generalization of this model to tow degree of freedom beyond the scope of a simple rigid-plastic system allows investigating the plastic resource of structures under complex disproportionate by individual components of deformation (earthquake). This macro-model greatly increases the accuracy of the calculations carried out. At the same time, the implementation of the proposed macro-model calculations easier than the detailed dynamic elastic-plastic calculations existing software systems such as ANSYS.

Keywords: elastic-plastic, single degree of freedom model, rigid-plastic system, plastic resource, complex plastic deformation, macro-model

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

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In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for the balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: power spectral density, 3D EEG model, brain balancing, kNN

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Authors: Ahlad Neti, Elisa Arch, Martha Hall

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Studies have shown that individuals who use Ankle-Foot-Orthoses (AFOs) have a high level of dissatisfaction regarding their current AFOs. Studies point to the focus on technical design with little attention given to the user perspective as a source of AFO designs that leave users dissatisfied. To design a new AFO that satisfies users and thereby improves their quality of life, the reasons for their dissatisfaction and their wants and needs for an improved AFO design must be identified. There has been little research into the user perspective on AFO use and desired improvements, so the relationship between AFO design and satisfaction in daily use must be assessed to develop appropriate metrics and constraints prior to designing a novel AFO. To assess the user perspective on AFO design, structured interviews were conducted with 7 individuals (average age of 64.29±8.81 years) who use AFOs. All interviews were transcribed and coded to identify common themes using Grounded Theory Method in NVivo 12. Qualitative analysis of these results identified sources of user dissatisfaction such as heaviness, bulk, and uncomfortable material and overall needs and wants for an AFO. Beyond the user perspective, certain objective factors must be considered in the construction of metrics and constraints to ensure that the AFO fulfills its medical purpose. These more objective metrics are rooted in a common medical device market and technical standards. Given the large body of research concerning these standards, these objective metrics and constraints were derived through a literature review. Through these two methods, a comprehensive list of metrics and constraints accounting for both the user perspective on AFO design and the AFO’s medical purpose was compiled. These metrics and constraints will establish the framework for designing a new AFO that carries out its medical purpose while also improving the user experience. The metrics can be categorized into several overarching areas for AFO improvement. Categories of user perspective related metrics include comfort, discreteness, aesthetics, ease of use, and compatibility with clothing. Categories of medical purpose related metrics include biomechanical functionality, durability, and affordability. These metrics were used to guide an iterative prototyping process. Six concepts were ideated and compared using system-level analysis. From these six concepts, two concepts – the piano wire model and the segmented model – were selected to move forward into prototyping. Evaluation of non-functional prototypes of the piano wire and segmented models determined that the piano wire model better fulfilled the metrics by offering increased stability, longer durability, fewer points for failure, and a strong enough core component to allow a sock to cover over the AFO while maintaining the overall structure. As such, the piano wire AFO has moved forward into the functional prototyping phase, and healthy subject testing is being designed and recruited to conduct design validation and verification.

Keywords: ankle-foot orthotic, assistive technology, human centered design, medical devices

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Authors: Martin Goubej, Tomas Popule, Alois Krejci

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This paper deals with experimental identification of mechanical systems with nonlinear friction characteristics. Dynamic LuGre friction model is adopted and a systematic approach to parameter identification of both linear and nonlinear subsystems is given. The identification procedure consists of three subsequent experiments which deal with the individual parts of plant dynamics. The proposed method is experimentally verified on an industrial-grade robotic manipulator. Model fidelity is compared with the results achieved with a static friction model.

Keywords: mechanical friction, LuGre model, friction identification, motion control

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Authors: Arash Najmaei, Jo Rhodes, Peter Lok, Zahra Sadeghinejad

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In this article, we endeavor to explore how a new business model comes into existence in the Australian cloud-computing eco-system. Findings from multiple case study methodology reveal that to develop a business model new ventures adopt a three-phase approach. In the first phase, labelled as business model ideation (BMID) various ideas for a viable business model are generated from both internal and external networks of the entrepreneurial team and the most viable one is chosen. Strategic consensus and commitment are generated in the second phase. This phase is a business modelling strategic action phase. We labelled this phase as business model strategic commitment (BMSC) because through commitment and the subsequent actions of executives resources are pooled, coordinated and allocated to the business model. Three complementary sets of resources shape the business model: managerial (MnRs), marketing (MRs) and technological resources (TRs). The third phase is the market-test phase where the business model is reified through the delivery of the intended value to customers and conversion of revenue into profit. We labelled this phase business model actualization (BMAC). Theoretical and managerial implications of these findings will be discussed and several directions for future research will be illuminated.

Keywords: entrepreneur business model, high-tech venture, resources, conversion of revenue

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Authors: Ariba Siddiqui, Amber Khan

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The need for bio-implantable devices in the field of medical sciences has been increasing day by day; however, the charging of these devices is a major issue. Batteries, a very common method of powering the implants, have a limited lifetime and bulky nature. Therefore, as a replacement of batteries, acoustic power transfer (APT) technology is being accepted as the most suitable technique to wirelessly power the medical implants in the present scenario. The basic model of APT consists of piezoelectric transducers that work on the principle of converse piezoelectric effect at the transmitting end and direct piezoelectric effect at the receiving end. This paper provides mechanistic insight into the parameters affecting the design and efficient working of acoustic power transfer systems. The optimum design considerations have been presented that will help to compress the size of the device and augment the intensity of the pressure wave. A COMSOL model of the PZT (Lead Zirconate Titanate) transducer was developed. The model was simulated and analyzed on a frequency spectrum. The simulation results displayed that the efficiency of these devices is strongly dependent on the frequency of operation, and a wrong choice of the operating frequency leads to the high absorption of acoustic field inside the tissue (medium), poor power strength, and heavy transducers, which in effect influence the overall configuration of the acoustic systems. Considering all the tradeoffs, the simulations were performed again by determining an optimum frequency (900 kHz) that resulted in the reduction of the transducer's thickness to 1.96 mm and augmented the power strength with an intensity of 432 W/m². Thus, the results obtained after the second simulation contribute to lesser attenuation, lightweight systems, high power intensity, and also comply with safety limits provided by the U.S Food and Drug Administration (FDA). It was also found that the chosen operating frequency enhances the directivity of the acoustic wave at the receiver side.

Keywords: acoustic power, bio-implantable, COMSOL, Lead Zirconate Titanate, piezoelectric, transducer

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Authors: Juraj Camaj, Martin Kendra, Jaroslav Masek

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The paper is focused to the evaluation railway tracks in the Slovakia by using Multi-Criteria method. Evaluation of railway tracks has important impacts for the assessment of investment in technical equipment. Evaluation of railway tracks also has an important impact for the allocation of marshalling yards. Marshalling yards are in transport model as centers for the operation assigned catchment area. This model is one of the effective ways to meet the development strategy of the European Community's railways. By applying this model in practice, a transport company can guarantee a higher quality of service and then expect an increase in performance. The model is also applicable to other rail networks. This model supplements a theoretical problem of train formation problem of new ways of looking at evaluation of factors affecting the organization of wagon flows.

Keywords: railway track, multi-criteria methods, evaluation, transportation model

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Authors: Changtong Wang, Lingyun Wei

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The combination of auctions and supply chains is of great significance in improving the supply chain management system and enhancing the efficiency of economic and social operations. To address the gap in research on supply chain strategies under the auction mechanism, a model is developed for the 1-N auction model in a complete information environment, and it is concluded that the two-part contract auction model for retailers in this model can achieve supply chain coordination. The model is validated by substituting the model into the scenario of a fresh-cut flower industry flower auction in exchange for arithmetic examples to further prove the validity of the conclusions.

Keywords: auction mechanism, supply chain coordination strategy, fresh cut flowers industry, supply chain management

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Authors: B. T. Chew, S. N. Kazi, A. Amiri

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This paper presents an adaptive thermal comfort model study in the tropical country of Malaysia. A number of researchers have been interested in applying the adaptive thermal comfort model to different climates throughout the world, but so far no study has been performed in Malaysia. For the use as a thermal comfort model, which better applies to hot and humid climates, the adaptive thermal comfort model was developed as part of this research by using the collected results from a large field study in six lecture halls with 178 students. The relationship between the operative temperature and behavioral adaptations was determined. In the developed adaptive model, the acceptable indoor neutral temperatures lay within the range of 23.9-26.0 oC, with outdoor temperatures ranging between 27.0–34.6oC. The most comfortable temperature for students in the lecture hall was 25.7 oC.

Keywords: hot and humid, lecture halls, neutral temperature, adaptive thermal comfort model

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Authors: Xiang Zhang, David Rey, S. Travis Waller

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Stochastic User Equilibrium (SUE) model is a widely used traffic assignment model in transportation planning, which is regarded more advanced than Deterministic User Equilibrium (DUE) model. However, a problem exists that the performance of the SUE model depends on its error term parameter. The objective of this paper is to propose a systematic method of determining the appropriate error term parameter value for the SUE model. First, the significance of the parameter is explored through a numerical example. Second, the parameter calibration method is developed based on the Logit-based route choice model. The calibration process is realized through multiple nonlinear regression, using sequential quadratic programming combined with least square method. Finally, case analysis is conducted to demonstrate the application of the calibration process and validate the better performance of the SUE model calibrated by the proposed method compared to the SUE models under other parameter values and the DUE model.

Keywords: parameter calibration, sequential quadratic programming, stochastic user equilibrium, traffic assignment, transportation planning

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Authors: Jin-Wei Liang, Hung-Yi Chen, Lung Lin

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In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller.

Keywords: the Bouc-Wen hysteresis model, particle swarm optimization, Prandtl-Ishlinskii model, automation engineering

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Authors: Seung-Yeon Kim

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The Ising model, consisting magnetic spins, is the simplest system showing phase transitions and critical phenomena at finite temperatures. The Ising model has played a central role in our understanding of phase transitions and critical phenomena. Also, the Ising model explains the gas-liquid phase transitions accurately. However, the Ising model in a nonzero magnetic field has been one of the most intriguing and outstanding unsolved problems. We study analytically the partition function zeros in the complex magnetic-field plane and the Yang-Lee edge singularity of the infinite-range Ising model in an external magnetic field. In addition, we compare the Yang-Lee edge singularity of the infinite-range Ising model with that of the square-lattice Ising model in an external magnetic field.

Keywords: Ising ferromagnet, magnetic field, partition function zeros, Yang-Lee edge singularity

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Authors: O. Iyare, A. H. Afolayan, O. T. Oluwadare, B. K. Alese

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Access to advanced medical services has been one of the medical challenges faced by our present society especially in distant geographical locations which may be inaccessible. Then the need for telemedicine arises through which live videos of a doctor can be streamed to a patient located anywhere in the world at any time. Patients’ medical records contain very sensitive information which should not be made accessible to unauthorized people in order to protect privacy, integrity and confidentiality. This research work focuses on a more robust security measure which is biometric (fingerprint) as a form of access control to data of patients by the medical specialist/practitioner.

Keywords: biometrics, telemedicine, privacy, patient information

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Authors: K. Khanafer

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The aim of this investigation was to validate the fluid-structure interaction (FSI) model of type B aortic dissection with our experimental results from a bench-top-model. Another objective was to study the relationship between the size of a septectomy that increases the outflow of the false lumen and its effect on the values of the differential of pressure between true lumen and false lumen. FSI analysis based on Galerkin’s formulation was used in this investigation to study flow pattern and hemodynamics within a flexible type B aortic dissection model using boundary conditions from our experimental data. The numerical results of our model were verified against the experimental data for various tear size and location. Thus, CFD tools have a potential role in evaluating different scenarios and aortic dissection configurations.

Keywords: aortic dissection, fluid-structure interaction, in vitro model, numerical

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Authors: I. Alhajri, G. Zahedi, R. Alazmi, A. Akbari

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In this paper, an Artificial Neural Network (ANN) was developed to predict Asphaltene Precipitation (AP) during the injection of carbon dioxide into crude oil reservoirs. In this study, the experimental data from six different oil fields were collected. Seventy percent of the data was used to develop the ANN model, and different ANN architectures were examined. A network with the Trainlm training algorithm was found to be the best network to estimate the AP. To check the validity of the proposed model, the model was used to predict the AP for the thirty percent of the data that was unevaluated. The Mean Square Error (MSE) of the prediction was 0.0018, which confirms the excellent prediction capability of the proposed model. In the second part of this study, the ANN model predictions were compared with modified Hirschberg model predictions. The ANN was found to provide more accurate estimates compared to the modified Hirschberg model. Finally, the proposed model was employed to examine the effect of different operating parameters during gas injection on the AP. It was found that the AP is mostly sensitive to the reservoir temperature. Furthermore, the carbon dioxide concentration in liquid phase increases the AP.

Keywords: artificial neural network, asphaltene, CO2 injection, Hirschberg model, oil reservoirs

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Authors: Saadia Drissi

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The cloud computing is an innovative paradigm that introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. As consequence, there is a need of risk assessment model adapted to cloud computing. This paper requires a new risk assessment model based on multi-agent system and AHP model as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.

Keywords: cloud computing, risk assessment model, multi-agent system, AHP model, cloud consumer

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Authors: Ashlesha Khanapure, Harsh Kashyap, Abhinav Anand, Sanjana Habib, Anupama Bidargaddi

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Technologies that are developing quickly are being developed daily in a variety of disciplines, particularly the medical field. For the purpose of detecting bone fractures in X-ray pictures of different body segments, our work compares the ResNet-50 and MobileNetV3 architectures. It evaluates accuracy and computing efficiency with X-rays of the elbow, hand, and shoulder from the MURA dataset. Through training and validation, the models are evaluated on normal and fractured images. While ResNet-50 showcases superior accuracy in fracture identification, MobileNetV3 showcases superior speed and resource optimization. Despite ResNet-50’s accuracy, MobileNetV3’s swifter inference makes it a viable choice for real-time clinical applications, emphasizing the importance of balancing computational efficiency and accuracy in medical imaging. We created a graphical user interface (GUI) for MobileNet V3 model bone fracture detection. This research underscores MobileNetV3’s potential to streamline bone fracture diagnoses, potentially revolutionizing orthopedic medical procedures and enhancing patient care.

Keywords: CNN, MobileNet V3, ResNet-50, healthcare, MURA, X-ray, fracture detection

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Authors: Eti Dwi Wiraningsih, Folashade Agusto, Lina Aryati, Syamsuddin Toaha, Suzanne Lenhart, Widodo, Willy Govaerts

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This paper considers a deterministic model for the transmission dynamics of rabies virus in the wild dogs-domestic dogs-human zoonotic cycle. The effect of vaccination and culling in dogs is considered on the model, then the stability was analysed to get basic reproduction number. We use the next generation matrix method and Routh-Hurwitz test to analyze the stability of the Disease-Free Equilibrium and Endemic Equilibrium of this model.

Keywords: stability analysis, rabies model, vaccination effect, culling in dogs

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Authors: Lakrim Abderrazak, Tahri Driss

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This paper presents a new behavioural electrothermal model of power Silicon Carbide (SiC) MOSFET under SPICE. This model is based on the MOS model level 1 of SPICE, in which phenomena such as Drain Leakage Current IDSS, On-State Resistance RDSon, gate Threshold voltage VGSth, the transconductance (gfs), I-V Characteristics Body diode, temperature-dependent and self-heating are included and represented using behavioural blocks ABM (Analog Behavioural Models) of Spice library. This ultimately makes this model flexible and easily can be integrated into the various Spice -based simulation softwares. The internal junction temperature of the component is calculated on the basis of the thermal model through the electric power dissipated inside and its thermal impedance in the form of the localized Foster canonical network. The model parameters are extracted from manufacturers' data (curves data sheets) using polynomial interpolation with the method of simulated annealing (S A) and weighted least squares (WLS). This model takes into account the various important phenomena within transistor. The effectiveness of the presented model has been verified by Spice simulation results and as well as by data measurement for SiC MOS transistor C2M0025120D CREE (1200V, 90A).

Keywords: SiC power MOSFET, DC electro-thermal model, ABM Spice library, SPICE modelling, behavioural model, C2M0025120D CREE.

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Authors: S. O. Oyamakin, A. U. Chukwu,

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We proposed a Hyperbolic Gompertz Growth Model (HGGM), which was developed by introducing a stabilizing parameter called θ using hyperbolic sine function into the classical gompertz growth equation. The resulting integral solution obtained deterministically was reprogrammed into a statistical model and used in modeling the height and diameter of Pines (Pinus caribaea). Its ability in model prediction was compared with the classical gompertz growth model, an approach which mimicked the natural variability of height/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using goodness of fit tests and model selection criteria. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the compliance of the error term to normality assumptions while using testing the independence of the error term using the runs test. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic gompertz growth models better than the source model (classical gompertz growth model) while the results of R2, Adj. R2, MSE, and AIC confirmed the predictive power of the Hyperbolic Monomolecular growth models over its source model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, gompertz

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Authors: Tiexin Wang, Sebastien Truptil, Frederick Benaben

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Model transformation, as a pivotal aspect of Model-driven engineering, attracts more and more attentions both from researchers and practitioners. Many domains (enterprise engineering, software engineering, knowledge engineering, etc.) use model transformation principles and practices to serve to their domain specific problems; furthermore, model transformation could also be used to fulfill the gap between different domains: by sharing and exchanging knowledge. Since model transformation has been widely used, there comes new requirement on it: effectively and efficiently define the transformation process and reduce manual effort that involved in. This paper presents an automatic model transformation methodology based on semantic and syntactic comparisons, and focuses particularly on granularity issue that existed in transformation process. Comparing to the traditional model transformation methodologies, this methodology serves to a general purpose: cross-domain methodology. Semantic and syntactic checking measurements are combined into a refined transformation process, which solves the granularity issue. Moreover, semantic and syntactic comparisons are supported by software tool; manual effort is replaced in this way.

Keywords: automatic model transformation, granularity issue, model-driven engineering, semantic and syntactic comparisons

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Authors: Razieh Khalafi

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

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

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents a model predictive control (MPC) of a utility interactive (UI) single phase inverter (SPI) for a photovoltaic (PV) system at residential/distribution level. The proposed model uses single-phase phase locked loop (PLL) to synchronize SPI with the grid and performs MPC control in a dq reference frame. SPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a full bridge (FB) voltage source inverter (VSI). No PI regulators to tune and carrier and modulating waves are required to produce switching sequence. Instead, the operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a three kW PV system at the input of UI-SPI in Matlab/Simulink. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: phase locked loop, voltage source inverter, single phase inverter, model predictive control, Matlab/Simulink

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Authors: Ronald Blough

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Hospitals, clinics, and medical facilities are the core of the Health Services sector providing 24/7 medical care to those in need. Any disruption of these important medical services highlights the vulnerabilities in the medical system. An internal or external event can create a catastrophic incident paralyzing the medical services causing the facility to shift into emergency operations with the possibility of evacuation. The hospital administrator and government officials must decide in a very short amount of time whether to shelter in place or evacuate. This presentation will identify best practice recommendations regarding the hospital evacuation decision and response analyzing previous hospital evacuations to encourage hospitals in the region to review or develop their own emergency evacuation plans.

Keywords: disaster preparedness, hospital evacuation, shelter-in-place, incident containment, health services vulnerability, hospital resources

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Authors: Muneer Abbad

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This research explains the e-learning usage in a university in Jordan. Unified theory of acceptance and use of technology (UTAUT) model has been used as a base model to explain the usage. UTAUT is a model of individual acceptance that is compiled mainly from different models of technology acceptance. This research is the initial part from full explanations of the users' acceptance model that use Structural Equation Modelling (SEM) method to explain the users' acceptance of the e-learning systems based on UTAUT model. In this part data has been collected and prepared for further analysis. The main factors of UTAUT model has been tested as different factors using exploratory factor analysis (EFA). The second phase will be confirmatory factor analysis (CFA) and SEM to explain the users' acceptance of e-learning systems.

Keywords: e-learning, moodle, adoption, Unified Theory of Acceptance and Use of Technology (UTAUT)

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