Search results for: H₂-optimal model reduction

Authors: Weera Weerasophon

Abstract:

This research paper is to study the development of a management model for promoting sustainable tourism of Rajabhat universities in Thailand. Mixed Method Research is applied under the said topic. The researcher has developed a management model to promote sustainable tourism. The objectives of the research are 1) to study the readiness in management sustainable tourism of Rajabhat universities in Thailand 2) to develop a management model for promoting sustainable tourism of those universities. The process of this research is organized in two steps according to the objectives. The results of the research are as in the following: 1. Rajabhat universities have the readiness in management for promoting sustainable tourism. The universities can be developed to be sustainable tourist attraction under the admistrators who have vision and realize the importance of tourism, eager to promote sustainable tourism of the universities by specifying obvious policy plans and management. 2. The management model for promoting sustainable tourism of Rajabhat universities is consisted of the main following factors : 2.1 Master plan and policy, 2.2 Rajabhat universities organization management and personnel administration, 2.3 Assignment and authority, leadership, 2.4 Join network, 2.5 Assurance of quality and controlling, 2.6 Budget management, 2.7 Human Resources management, 2.8 Alliance and co-ordination, 2.9 Tool of marketing. There are also other communal factors for promoting sustainable tourism. They are: local communities, local communities, tourism activities, government and private sectors, communicative technology system, history, tourist attractive, art and culture, internal and external environment including local wisdom heritage. The management model for promoting sustainable tourism can be concluded from these main and communal factors mentioned above.

Keywords: tourism, sustainable tourism, management, Rajabhat University

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: brain-computer interface, speech recognition, artificial neural network, electroencephalography, EEG, wernicke area

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Authors: Yunyong Guo, Man Wang, Bryan Guo, Nathan Guo

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This paper introduces an advanced security and privacy model tailored for Telehealth systems, emphasizing end-to-end protection across IoT, Fog, and Cloud components. The proposed model integrates encryption, key management, intrusion detection, and privacy-preserving measures to safeguard patient data. A comprehensive simulation study evaluates the model's effectiveness in scenarios such as unauthorized access, physical breaches, and insider threats. Results indicate notable success in detecting and mitigating threats yet underscore areas for refinement. The study contributes insights into the intricate balance between security and usability in Telehealth environments, setting the stage for continued advancements.

Keywords: cloud, enhancing security, fog, IoT, telehealth

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Authors: Kai Jin, Hua Li, Qing Song

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Homeland security and border safety is an issue for any country. This paper takes the border security of US as an example to discuss the usage and efficiency of simulation tools in the homeland security application. In this study, available resources and different illegal infiltration parameters are defined, including their individual behavior and objective, in order to develop a model that describes border patrol system. A simulation model is created in Arena. This simulation model is used to study the dynamic activities in the border security. Possible factors that may affect the effectiveness of the border patrol system are proposed. Individual and factorial analysis of these factors is conducted and some suggestions are made.

Keywords: resource optimization, simulation, modeling, border security

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Authors: Tu-Chieh Hung, Wei-Mon Yan, Xiao-Dong Wang, Yu-Xian Huang

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This work employs a combined optimization procedure including a simplified conjugate-gradient method and a three-dimensional fluid flow and heat transfer model to study the optimal geometric parameter design of double-layered microchannel heat sinks. The overall thermal resistance RT is the objective function to be minimized with number of channels, N, the channel width ratio, β, the bottom channel aspect ratio, αb, and upper channel aspect ratio, αu, as the search variables. It is shown that, for the given bottom area (10 mm×10 mm) and heat flux (100 W cm-2), the optimal (minimum) thermal resistance of double-layered microchannel heat sinks is about RT=0.12 ℃/m2W with the corresponding optimal geometric parameters N=73, β=0.50, αb=3.52, and, αu= 7.21 under a constant pumping power of 0.05 W. The optimization process produces a maximum reduction by 52.8% in the overall thermal resistance compared with an initial guess (N=112, β=0.37, αb=10.32 and, αu=10.93). The results also show that the optimal thermal resistance decreases rapidly with the pumping power and tends to be a saturated value afterward. The corresponding optimal values of parameters N, αb, and αu increase while that of β decrease as the pumping power increases. However, further increasing pumping power is not always cost-effective for the application of heat sink designs.

Keywords: optimization, double-layered microchannel heat sink, simplified conjugate-gradient method, thermal resistance

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: Monika Chuchro

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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.

Keywords: clustering, data analysis, data mining, predictive models

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Authors: Mohamed Abd Esselem Dems, Souhila Laib, Nadjia Latelli, Nadia Ouddai

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In this work, we have developed QSAR model for Relative Binding Affinity (RBA) of a large diverse set of estradiol among these derivatives, the organometallic derivatives. By dividing the dataset into a training set of 24 compounds and a test set of 6 compounds. The DFT method was used to calculate quantum chemical descriptors and physicochemical descriptors (MR and MLOGP) were performed using E-Dragon. All the validations indicated that the QSAR model built was robust and satisfactory (R2 = 90.12, Q2LOO = 86.61, RMSE = 0.272, F = 60.6473, Q2ext =86.07). We have therefore apply this model to predict the RBA, for two isomers β and α wherein Mn(CO)3 complex with the aromatic ring of estradiol, and the two isomers show little appreciation for the estrogenic receptor (RBAβ = 1.812 and RBAα = 1.741).

Keywords: DFT, estradiol, haptotropic rearrangement, QSAR, relative binding affinity

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Authors: Elina Bakhtieva

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The variety of available digital tools, strategies and activities might confuse and disorient even an experienced marketer. This applies in particular to B2B companies, which are usually less flexible in uptaking of digital technology than B2C companies. B2B companies are lacking a framework that corresponds to the specifics of the B2B business, and which helps to evaluate a company’s capabilities and to choose an appropriate path. A B2B digital marketing maturity model helps to fill this gap. However, modern marketing offers no widely approved digital marketing maturity model, and thus, some marketing institutions provide their own tools. The purpose of this paper is building an optimized B2B digital marketing maturity model based on a SWOT (strengths, weaknesses, opportunities, and threats) analysis of existing models. The current study provides an analytical review of the existing digital marketing maturity models with open access. The results of the research are twofold. First, the provided SWOT analysis outlines the main advantages and disadvantages of existing models. Secondly, the strengths of existing digital marketing maturity models, helps to identify the main characteristics and the structure of an optimized B2B digital marketing maturity model. The research findings indicate that only one out of three analyzed models could be used as a separate tool. This study is among the first examining the use of maturity models in digital marketing. It helps businesses to choose between the existing digital marketing models, the most effective one. Moreover, it creates a base for future research on digital marketing maturity models. This study contributes to the emerging B2B digital marketing literature by providing a SWOT analysis of the existing digital marketing maturity models and suggesting a structure and main characteristics of an optimized B2B digital marketing maturity model.

Keywords: B2B digital marketing strategy, digital marketing, digital marketing maturity model, SWOT analysis

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Authors: Fatema-Tuz-Zahura, Raquib Ahsan

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Punching shear failure is usually the governing failure mode of flat plate structures. Punching failure is brittle in nature which induces more vulnerability to this type of structure. In the present study, a 3D finite element model of a flat plate with low reinforcement ratio and without any transverse reinforcement has been developed. Punching shear stress and the deflection data were obtained on the surface of the flat plate as well as through the thickness of the model from numerical simulations. The obtained data were compared with the experimental results. Variation of punching stress with respect to deflection as obtained from numerical results is found to be in good agreement with the experimental results; the range of variation of punching stress is within 5%. The numerical simulation shows an early and gradual onset of nonlinearity, whereas the same is late and abrupt as observed in the experimental results. The range of variation of punching stress for different slab thicknesses between experimental and numerical results is less than 15%. The developed numerical model is useful to complement available punching test series performed in the past. The results obtained from the numerical model will be helpful for designing retrofitting schemes of flat plates.

Keywords: flat plate, finite element model, punching shear, reinforcement ratio

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Authors: Rajkumar Kolangarakandy

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Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

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Authors: P. Panwalkar, K. Veravalli, M. Tofighi, A. Mofidi

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Introduction: Anterior femoral perforation or distal anterior nail position is a known complication of femoral nailing specifically in pertrochantric fractures fixed with cephalomedullary nail. This has been attributed to wrong entry point for the femoral nail, nail with large radius of curvature or malreduced fracture. Left alone anterior perforation of femur or abutment of nail on anterior femur will result in pain and risk stress riser at distal femur and periprosthetic fracture. There have been multiple techniques described to avert or correct this problem ranging from using different nail, entry point change, poller screw to deflect the nail position, use of shorter nail or use of curved guidewire or change of nail to ensure a nail with large radius of curvature Methods: We present this technique which we have used in order to centralise the femoral nail either when the nail has been put anteriorly or when the guide wire has been inserted too anteriorly prior to the insertion of the nail. This technique requires the use of femoral reduction spool from the nailing set. This technique was used by eight trainees of different level of experience under supervision. Results: This technique was easily reproducible without any learning curve without a need for opening of fracture site or change in the entry point with three different femoral nailing sets in twenty-five cases. The process took less than 10 minutes even when revising a malpositioned femoral nail. Conclusion: Our technique of using femoral reduction spool is easily reproducible and repeatable technique for avoidance of non-centralised femoral nail insertion and distal anterior perforation of femoral nail.

Keywords: femoral fracture, nailing, malposition, surgery

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Authors: Javad Khaligh, Aghileh Heydari, Ali Akbar Heydari

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Mathematical epidemiological models for the spread of disease through a population are used to predict the prevalence of a disease or to study the impacts of treatment or prevention measures. Initial conditions for these models are measured from statistical data collected from a population since these initial conditions can never be exact, the presence of chaos in mathematical models has serious implications for the accuracy of the models as well as how epidemiologists interpret their findings. This paper confirms the chaotic behavior of a model for dengue fever and SI by investigating sensitive dependence, bifurcation, and 0-1 test under a variety of initial conditions.

Keywords: epidemiological models, SEIR disease model, bifurcation, chaotic behavior, 0-1 test

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Authors: Adekunle Taiwo Adenike, I. K. Ogundoyin

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Lassa fever is a neglected tropical virus that has become a significant public health issue in Nigeria, with the country having the greatest burden in Africa. This paper presents a Geo-Computational Model for Analysis and Prediction of Lassa Fever Dynamics and Outbreaks in Nigeria. The model investigates the dynamics of the virus with respect to environmental factors and human populations. It confirms the role of the rodent host in virus transmission and identifies how climate and human population are affected. The proposed methodology is carried out on a Linux operating system using the OSGeoLive virtual machine for geographical computing, which serves as a base for spatial ecology computing. The model design uses Unified Modeling Language (UML), and the performance evaluation uses machine learning algorithms such as random forest, fuzzy logic, and neural networks. The study aims to contribute to the control of Lassa fever, which is achievable through the combined efforts of public health professionals and geocomputational and machine learning tools. The research findings will potentially be more readily accepted and utilized by decision-makers for the attainment of Lassa fever elimination.

Keywords: geo-computational model, lassa fever dynamics, lassa fever, outbreak prediction, nigeria

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Authors: Rizwan Arshad, Alessio Panza, Nimra Inayat, Syeda Mariam Batool Kazmi, Shawana Azmat

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The rapidly expanding use of immunotherapy for a wide range of cancers from late to early stages has, predictably, been accompanied by evidence of inequities in access to these highly effective but costly treatments. In this survey-based case study, we aimed to develop a One-window services model (OWSM) based on Anderson’s behavioral model to enhance competence in accessing cancer medications, particularly immunotherapies, through the analysis of 20 patient surveys conducted in the Armed forces bone marrow transplant center of the district, Rawalpindi from November to December 2022. The purposive sampling technique was used. Cronbach’s alpha coefficient was found to be 0.71. It was analyzed using SPSS version 26 with descriptive analysis, and results showed that the majority of the cancer patients were non-competent to access their prescribed cancer immunotherapy because of individual-level, socioeconomic, and organizational barriers.

Keywords: cancer immunotherapy, one-window services model, accessibility, competence

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Authors: Mustafa Tufekci, Caner Guven

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In Automotive Industry, sliding door systems that are also used as body closures, are safety members. Extreme product tests are realized to prevent failures in a design process, but these tests realized experimentally result in high costs. Finite element analysis is an effective tool used for the design process. These analyses are used before production of a prototype for validation of design according to customer requirement. In result of this, the substantial amount of time and cost is saved. Finite element model is created for geometries that are designed in 3D CAD programs. Different element types as bar, shell and solid, can be used for creating mesh model. The cheaper model can be created by the selection of element type, but combination of element type that was used in model, number and geometry of element and degrees of freedom affects the analysis result. Sliding door system is a good example which used these methods for this study. Structural analysis was realized for sliding door mechanism by using FE models. As well, physical tests that have same boundary conditions with FE models were realized. Comparison study for these element types, were done regarding test and analyses results then the optimum combination was achieved.

Keywords: finite element analysis, sliding door mechanism, element type, structural analysis

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Authors: Seyedsamad Tahani, Samira Ghorbanpour

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The global warming crisis forced humans to consider their place in the world and the earth's future. In this regard, Electric Vehicles (EVs) are a significant step toward protecting the environment. By identifying factors that influence people's behavior intentions toward using Electric Vehicles (EV), we proposed a theoretical model by extending the Technology Acceptance Model (TAM), including three more concepts, Subjective Norm (SN), Self-Efficacy (SE), and Perceived Behavior Control (PBC). The study was conducted in South Korea, and a random sample was taken at a specific time. In order to collect data, a questionnaire was created in a Google Form and sent via Kakao Talk, a popular social media application used in Korea. There were about 220 participants in this survey. However, 201 surveys were completely done. The findings revealed that all factors in the TAM model and the other added concepts such as subjective norms, self-efficacy and perceived behavior control significantly affect the behavioral intention of using EVs.

Keywords: electric vehicles, behavioral intention, perceived trust, perceived enjoyment, self-efficacy

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Authors: Jia Li, Huacong Li, Xiaobao Han

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Due to the more variable geometry parameters of VCE (variable cycle aircraft engine), presents an adaptive controller method based on the full-state linear model of VCE and has simulated to solve the multivariate controller design problem of the whole flight envelops. First, analyzes the static and dynamic performances of bypass ratio and other state parameters caused by variable geometric components, and develops nonlinear component model of VCE. Then based on the component model, through small deviation linearization of main fuel (Wf), the area of tail nozzle throat (A8) and the angle of rear bypass ejector (A163), setting up multiple linear model which variable geometric parameters can be inputs. Second, designs the adaptive controllers for VCE linear models of different nominal points. Among them, considering of modeling uncertainties and external disturbances, derives the adaptive law by lyapunov function. The simulation results showed that, the adaptive controller method based on full-state linear model used the angle of rear bypass ejector as input and effectively solved the multivariate control problems of VCE. The performance of all nominal points could track the desired closed-loop reference instructions. The adjust time was less than 1.2s, and the system overshoot was less than 1%, at the same time, the errors of steady states were less than 0.5% and the dynamic tracking errors were less than 1%. In addition, the designed controller could effectively suppress interference and reached the desired commands with different external random noise signals.

Keywords: variable cycle engine (VCE), full-state linear model, adaptive control, by-pass ratio

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Authors: Niladri Sekhar Barma, Satish Dhandole

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Damage identification in the context of safety, nowadays, has become a fundamental research interest area in the field of mechanical, civil, and aerospace engineering structures. The following research is aimed to identify damage in a mechanical beam structure and quantify the severity or extent of damage in terms of loss of stiffness, and obtain an updated analytical Finite Element (FE) model. An FE model is used for analysis, and the location of damage for single and multiple damage cases is identified numerically using the modal strain energy method and mode shape curvature method. Experimental data has been acquired with the help of an accelerometer. Fast Fourier Transform (FFT) algorithm is applied to the measured signal, and subsequently, post-processing is done in MEscopeVes software. The two sets of data, the numerical FE model and experimental results, are compared to locate the damage accurately. The extent of the damage is identified via modal frequencies using a mixed numerical-experimental technique. Mode shape comparison is performed by Modal Assurance Criteria (MAC). The analytical FE model is adjusted by the direct method of model updating. The same study has been extended to some real-life structures such as plate and GARTEUR structures.

Keywords: damage identification, damage quantification, damage detection using modal analysis, structural damage identification

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Authors: Youngjae Jin, Daeshik Kim

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This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

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Authors: Yang Yang, Dan Liu

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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

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Authors: Shashwat, Sandra G. L. Persiani, Yew Wah Wong, Pramod S. Kamath, Avinash H. Anantharam, Hui Ling Aw, Yann Grynberg

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Achieving zero-energy targets in existing buildings is known to be a difficult task, hence targets are addressed at new buildings almost exclusively. Although these ultra-efficient case-studies remain essential to develop future technologies and drive the concepts of Zero-energy, the immediate need to cut the consumption of the existing building stock remains unaddressed. This work aims to present a reliable and straightforward methodology for assessing the potential of energy-efficient upgrading in existing buildings. Public Singaporean school buildings, characterized by low energy use intensity and large roof areas, were identified as potential objects for conversion to highly-efficient buildings with a positive energy balance. A first study phase included the development of a detailed energy model for two case studies (a primary and a secondary school), based on the architectural drawings provided, site-visits and calibrated using measured end-use power consumption of different spaces. The energy model was used to demonstrate compliances or predict energy consumption of proposed changes in the two buildings. As complete energy monitoring is difficult and substantially time-consuming, short-term energy data was collected in the schools by taking spot measurements of power, voltage, and current for all the blocks of school. The figures revealed that the bulk of the consumption is attributed in decreasing order of magnitude to air-conditioning, plug loads, and lighting. In a second study-phase, a number of energy-efficient technologies and strategies were evaluated through energy-modeling to identify the alternatives giving the highest energy saving potential, achieving a reduction in energy use intensity down to 19.71 kWh/m²/y and 28.46 kWh/m²/y for the primary and the secondary schools respectively. This exercise of field evaluation and computer simulation of energy saving potential aims at a preliminary assessment of the positive-energy feasibility enabling future implementation of the technologies on the buildings studied, in anticipation of a broader and more widespread adoption in Singaporean schools.

Keywords: energy simulation, school building, tropical climate, zero energy buildings, positive energy

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Authors: Karim Kheloufi, El Hachemi Amara

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In the present study, a three-dimensional transient numerical model was developed to study the temperature field and cutting kerf shape during laser fusion cutting. The finite volume model has been constructed, based on the Navier–Stokes equations and energy conservation equation for the description of momentum and heat transport phenomena, and the Volume of Fluid (VOF) method for free surface tracking. The Fresnel absorption model is used to handle the absorption of the incident wave by the surface of the liquid metal and the enthalpy-porosity technique is employed to account for the latent heat during melting and solidification of the material. To model the physical phenomena occurring at the liquid film/gas interface, including momentum/heat transfer, a new approach is proposed which consists of treating friction force, pressure force applied by the gas jet and the heat absorbed by the cutting front surface as source terms incorporated into the governing equations. All these physics are coupled and solved simultaneously in Fluent CFD®. The main objective of using a transient phase change model in the current case is to simulate the dynamics and geometry of a growing laser-cutting generated kerf until it becomes fully developed. The model is used to investigate the effect of some process parameters on temperature fields and the formed kerf geometry.

Keywords: laser cutting, numerical simulation, heat transfer, fluid flow

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Authors: Probir Kumar Banerjee

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Though the revised DeLone and McLean (DM) model of IS success is found to be effective at the individual level of analysis, there is lack of consensus in regard to its effectiveness at the organisational level. This research reviews the DM model in the light of business/IT alignment theory and supporting literature, and suggests its reconceptualization. Specifically, arguments are made for augmenting it with business process quality. Business process quality, it is argued, captures the effect of intent to use, use and user satisfaction interactions, thus eliminating the need to capture their interaction effects in explaining organisational IS success. It is also argued that ‘operational performance’ driven by systems and business process quality, and higher order measures of organisational performance tied to operational performance are appropriate measures of ‘net benefit’. Suggestions are made for reconceptualisation of the other constructs and an adapted model of organisational IS success is proposed.

Keywords: organisational IS success, business/IT alignment, systems quality, business process quality, operational performance, market performance

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Authors: A. Nabhan, Mohamed R. El-Sharkawy, A. Rashed

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The main aim of this paper is to dedicate the belt drive system faults like cogs missing, misalignment and belt worm using vibration analysis technique. Experimentally, the belt drive test-rig is equipped to measure vibrations signals under different operating conditions. Finite element 3D model of belt drive system is created and vibration response analyzed using commercial finite element software ABAQUS/CAE.  Root mean square (RMS) and Crest Factor will serve as indicators of average amplitude of envelope analysis signals. The vibration signals pattern obtained from the simulation model and experimental data have the same characteristics. It can be concluded that each case of the RMS is more effective in detecting the defect for acceleration response. While Crest Factor parameter has a response with the displacement and velocity of vibration signals. Also it can be noticed that the model has difficulty in completing the solution when the misalignment angle is higher than 1 degree.

Keywords: simulation model, misalignment, cogs missing, vibration analysis

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Authors: Tarannom Parhizkar, Halle Bakhteeyar

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This paper presents a feasibility assessment of an expansion system applied to the natural gas transportation process in Iran. Power can be generated from the pressure energy of natural gas along its supply chain at various pressure reduction points by using turboexpanders. This technology is being applied in different countries around the world. The system consists of a turboexpander reducing the natural gas pressure and providing mechanical energy to drive electric generator. Moreover, gas pre-heating, required to prevent hydrate formation, is performed upstream of expansion stage using burner. The city gate station (CGS) has a nominal flow rate in range of 45000 to 270000 cubic meters per hour and a pressure reduction from maximum 62 bar at the upstream to 6 bar. Due to variable feed pressure and temperature in this station sensitivity analysis of generated electricity and required heat is performed. Results show that plant gain is more sensible to pressure variation than temperature changes. Furthermore, using turboexpander to reduce the pressure result in an electrical generation of 2757 to 17574 kW with the value of approximately 4 million US$ per year. Moreover, the required heat range to prevent a hydrate formation is almost 2189 to 14157 kW. To provide this heat, a burner is used with a maximum annual cost of 268,640 $ burner fuel. Therefore, the actual annual benefit of proposed plant modification is approximately over 6,5 million US$.

Keywords: feasibility study, simulation, turboexpander, feed characteristic

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Authors: Mohammed A. Sakr, Tarek M. Khalifa, Walid N. Mansour

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Fiber reinforced polymer (FRP) installation is a very effective way to repair and strengthen structures that have become structurally weak over their life span. This technique attracted the concerning of researchers during the last two decades. This paper presents a simple uniaxial nonlinear finite element model (UNFEM) able to accurately estimate the load-carrying capacity, different failure modes and the interfacial stresses of reinforced concrete (RC) continuous beams flexurally strengthened with externally bonded FRP plates on the upper and lower fibers. Results of the proposed finite element (FE) model are verified by comparing them with experimental measurements available in the literature. The agreement between numerical and experimental results is very good. Considering fracture energy of adhesive is necessary to get a realistic load carrying capacity of continuous RC beams strengthened with FRP. This simple UNFEM is able to help design engineers to model their strengthened structures and solve their problems.

Keywords: continuous beams, debonding, finite element, fibre reinforced polymer

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Authors: Chongyang Ye, Rong Liu

Abstract:

Elastic compression stockings (ECSs) have been widely applied in prophylaxis and treatment of chronic venous insufficiency of lower extremities. The medical function of ECS is to improve venous return and increase muscular pumping action to facilitate blood circulation, which is largely determined by the complex interaction between the ECS and lower limb tissues. Understanding the mechanical transmission of ECS along the skin surface, deeper tissues, and vascular system is essential to assess the effectiveness of the ECSs. In this study, a three-dimensional (3D) finite element (FE) model of the leg-ECS system integrated with a 3D fluid-solid interaction (FSI) model of the leg-vein system was constructed to analyze the biomechanical properties of veins and soft tissues under different ECS compression. The Magnetic Resonance Imaging (MRI) of the human leg was divided into three regions, including soft tissues, bones (tibia and fibula) and veins (peroneal vein, great saphenous vein, and small saphenous vein). The ECSs with pressure ranges from 15 to 26 mmHg (Classes I and II) were adopted in the developed FE-FSI model. The soft tissue was assumed as a Neo-Hookean hyperelastic model with the fixed bones, and the ECSs were regarded as an orthotropic elastic shell. The interfacial pressure and stress transmission were simulated by the FE model, and venous hemodynamics properties were simulated by the FSI model. The experimental validation indicated that the simulated interfacial pressure distributions were in accordance with the pressure measurement results. The developed model can be used to predict interfacial pressure, stress transmission, and venous hemodynamics exerted by ECSs and optimize the structure and materials properties of ECSs design, thus improving the efficiency of compression therapy.

Keywords: elastic compression stockings, fluid-solid interaction, tissue and vein properties, prediction

Procedia PDF Downloads 112

Authors: Sung Hyun You, Jeong Hoon Kim, Dae Ki Kim, Choon Ki Ahn

Abstract:

In this paper, we proposed a new strategy for estimating indoor temperature based on the modified resistance capacitance (R–C) network thermal dynamic model. Using minimum variance finite impulse response (FIR) filter, accurate indoor temperature estimation can be achieved. Our study is clarified by the experimental validation of the proposed indoor temperature estimation method. This experiment scenario environment is composed of a demand response (DR) server and home energy management system (HEMS) in a test bed.

Keywords: energy consumption, resistance-capacitance network model, demand response, finite impulse response filter

Procedia PDF Downloads 448

Authors: Settapong Malisuwan, Jesada Sivaraks, Peerawat Promkladpanao, Nattakit Suriyakrai, Navneet Madan

Abstract:

In this paper, a compact microstrip patch antenna is designed for mobile LTE applications by applying the frequency-dependent Smith-Chart (FDSC) model. The FDSC model is adopted in this research to reduce the error on the frequency-dependent characteristics. The Ansoft HFSS and various techniques is applied to meet frequency and size requirements. The proposed method within this research is suitable for use in computer-aided microstrip antenna design and RF integrated circuit (RFIC) design.

Keywords: frequency-dependent, smith-chart, microstrip, antenna, LTE, CAD

Procedia PDF Downloads 374