Search results for: equivalent linear model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19021

Search results for: equivalent linear model

11011 Heat and Mass Transfer of Triple Diffusive Convection in a Rotating Couple Stress Liquid Using Ginzburg-Landau Model

Authors: Sameena Tarannum, S. Pranesh

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A nonlinear study of triple diffusive convection in a rotating couple stress liquid has been analysed. It is performed to study the effect of heat and mass transfer by deriving Ginzburg-Landau equation. Heat and mass transfer are quantified in terms of Nusselt number and Sherwood numbers, which are obtained as a function of thermal and solute Rayleigh numbers. The obtained Ginzburg-Landau equation is Bernoulli equation, and it has been elucidated numerically by using Mathematica. The effects of couple stress parameter, solute Rayleigh numbers, and Taylor number on the onset of convection and heat and mass transfer have been examined. It is found that the effects of couple stress parameter and Taylor number are to stabilize the system and to increase the heat and mass transfer.

Keywords: couple stress liquid, Ginzburg-Landau model, rotation, triple diffusive convection

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11010 Adsorptive Desulfurization of Using Cu(I) – Y Zeolite via π-Complexation

Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng, Itumeleng Kohitlhetse

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The accelerating requirement to reach 0% sulfur content in liquid fuels demand researchers to seek efficient alternative technologies to challenge the predicament. In this current study, the adsorption capabilities of modified Cu(I)-Y zeolite were tested for the removal of organosulfur compounds (OSC) present in tire pyrolytic oil (TPO). The π-complexation-based adsorbent was obtained by ion exchanging Y-zeolite with Cu+ cation using liquid phase ion exchange (LPIE). Preparation of the adsorbent involved firstly ion exchange between Na-Y zeolite with a Cu(NO₃)₂ aqueous solution of 0.5M for 48 hours followed by reduction of Cu²⁺ to Cu+. Fixed-bed breakthrough studies for TPO in comparison with model diesel comprising of sulfur compounds such as thiophene, benzothiophenes (BT), and dibenzothiophenes (DBT) showed that modified Cu(I)-Y zeolite is an effective adsorbent for removal of OSC in liquid fuels. The effect of operating conditions such as adsorbent dosage and reaction time were studied to optimize the adsorptive desulfurization process. For model diesel fuel, the selectivity for adsorption of sulfur compounds followed the order DBT> BT> Thiophene. The Cu(I)-Y zeolite is fully regeneratable and this is achieved by a simple procedure of blowing the adsorbent with air at 350 °C, followed by reactivation at 450 °C in a rich helium surrounding.

Keywords: adsorption, desulfurization, TPO, zeolite

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11009 Impact of Customer Experience Quality on Loyalty of Mobile and Fixed Broadband Services: Case Study of Telecom Egypt Group

Authors: Nawal Alawad, Passent Ibrahim Tantawi, Mohamed Abdel Salam Ragheb

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Providing customers with quality experiences has been confirmed to be a sustainable, competitive advantage with a distinct financial impact for companies. The success of service providers now relies on their ability to provide customer-centric services. The importance of perceived service quality and customer experience is widely recognized. The focus of this research is in the area of mobile and fixed broadband services. This study is of dual importance both academically and practically. Academically, this research applies a new model investigating the impact of customer experience quality on loyalty based on modifying the multiple-item scale for measuring customers’ service experience in a new area and did not depend on the traditional models. The integrated scale embraces four dimensions: service experience, outcome focus, moments of truth and peace of mind. In addition, it gives a scientific explanation for this relationship so this research fill the gap in such relations in which no one correlate or give explanations for these relations before using such integrated model and this is the first time to apply such modified and integrated new model in telecom field. Practically, this research gives insights to marketers and practitioners to improve customer loyalty through evolving the experience quality of broadband customers which is interpreted to suggested outcomes: purchase, commitment, repeat purchase and word-of-mouth, this approach is one of the emerging topics in service marketing. Data were collected through 412 questionnaires and analyzed by using structural equation modeling.Findings revealed that both outcome focus and moments of truth have a significant impact on loyalty while both service experience and peace of mind have insignificant impact on loyalty.In addition, it was found that 72% of the variation occurring in loyalty is explained by the model. The researcher also measured the net prompters score and gave explanation for the results. Furthermore, assessed customer’s priorities of broadband services. The researcher recommends that the findings of this research will extend to be considered in the future plans of Telecom Egypt Group. In addition, to be applied in the same industry especially in the developing countries that have the same circumstances with similar service settings. This research is a positive contribution in service marketing, particularly in telecom industry for making marketing more reliable as managers can relate investments in service experience directly with the performance closest to income for instance, repurchasing behavior, positive word of mouth and, commitment. Finally, the researcher recommends that future studies should consider this model to explain significant marketing outcomes such as share of wallet and ultimately profitability.

Keywords: broadband services, customer experience quality, loyalty, net promoters score

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11008 Nursing Experience in Improving Physical and Mental Well-Being of a Patient with Premature Menopause Osteoporosis and Sarcopenia in Nursing-Led Multi-Discipline Care

Authors: Huang Chiung Chiu

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This article is about the nursing experience of assisting an outpatient with premature menopause, osteoporosis and sarcopenia through a multi-discipline care model. The nursing period is from September 22nd, 2020, to December 7th, 2020, collecting data through interviews with the patient, observation, and physical assessment. It was found that the main health problems were insufficient nutrition, less physical need, insomnia, and potentially dangerous falls. As an outpatient nurse, the author observed that in recent years, the age group of women with premature menopause, osteoporosis and sarcopenia had shifted downward. Integrated multi-disciplinary interventions were provided upon the initial diagnosis of osteoporosis and sarcopenia. Under the outpatient care setting, the collaborative team works between the doctors, nutritionists, osteoporosis educators, rehabilitates, physical therapists and other specialized teams were applied to provide individualized, integrated multi-disciplinary care. Through empathy and the establishment of attentive care, companionship and trust, we discussed care plans and treatment guidelines with the case, providing accurate, complete disease information and feedback education to strengthen the patient’s knowledge and motivation for exercise. Nursing guidance regarding the dietary nutrition and adjustment of daily routine was provided to increase the self-care ability, improve the health problems of muscle weakness and insomnia, and prevent falls. For patients with postmenopausal osteoporosis and sarcopenia, it is recommended that the nurses coordinate the multi-discipline integrated care model, adjust patients’ lifestyle and diet, and establish a regular exercise plan so that the cases can be evaluated holistically to improve the quality of care and physical and mental comfort.

Keywords: multi-discipline care model, premature menopause, osteoporosis, sarcopenia, insomnia

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11007 Transformation of Industrial Policy towards Industry 4.0 and Its Impact on Firms' Competition

Authors: Arūnas Burinskas

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Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.

Keywords: Bertrand and Cournot Competition, competition model, industry 4.0, industrial organisation, monopolistic competition

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11006 An Efficient Robot Navigation Model in a Multi-Target Domain amidst Static and Dynamic Obstacles

Authors: Michael Ayomoh, Adriaan Roux, Oyindamola Omotuyi

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This paper presents an efficient robot navigation model in a multi-target domain amidst static and dynamic workspace obstacles. The problem is that of developing an optimal algorithm to minimize the total travel time of a robot as it visits all target points within its task domain amidst unknown workspace obstacles and finally return to its initial position. In solving this problem, a classical algorithm was first developed to compute the optimal number of paths to be travelled by the robot amidst the network of paths. The principle of shortest distance between robot and targets was used to compute the target point visitation order amidst workspace obstacles. Algorithm premised on the standard polar coordinate system was developed to determine the length of obstacles encountered by the robot hence giving room for a geometrical estimation of the total surface area occupied by the obstacle especially when classified as a relevant obstacle i.e. obstacle that lies in between a robot and its potential visitation point. A stochastic model was developed and used to estimate the likelihood of a dynamic obstacle bumping into the robot’s navigation path and finally, the navigation/obstacle avoidance algorithm was hinged on the hybrid virtual force field (HVFF) method. Significant modelling constraints herein include the choice of navigation path to selected target points, the possible presence of static obstacles along a desired navigation path and the likelihood of encountering a dynamic obstacle along the robot’s path and the chances of it remaining at this position as a static obstacle hence resulting in a case of re-routing after routing. The proposed algorithm demonstrated a high potential for optimal solution in terms of efficiency and effectiveness.

Keywords: multi-target, mobile robot, optimal path, static obstacles, dynamic obstacles

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11005 Predicting Loss of Containment in Surface Pipeline using Computational Fluid Dynamics and Supervised Machine Learning Model to Improve Process Safety in Oil and Gas Operations

Authors: Muhammmad Riandhy Anindika Yudhy, Harry Patria, Ramadhani Santoso

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Loss of containment is the primary hazard that process safety management is concerned within the oil and gas industry. Escalation to more serious consequences all begins with the loss of containment, starting with oil and gas release from leakage or spillage from primary containment resulting in pool fire, jet fire and even explosion when reacted with various ignition sources in the operations. Therefore, the heart of process safety management is avoiding loss of containment and mitigating its impact through the implementation of safeguards. The most effective safeguard for the case is an early detection system to alert Operations to take action prior to a potential case of loss of containment. The detection system value increases when applied to a long surface pipeline that is naturally difficult to monitor at all times and is exposed to multiple causes of loss of containment, from natural corrosion to illegal tapping. Based on prior researches and studies, detecting loss of containment accurately in the surface pipeline is difficult. The trade-off between cost-effectiveness and high accuracy has been the main issue when selecting the traditional detection method. The current best-performing method, Real-Time Transient Model (RTTM), requires analysis of closely positioned pressure, flow and temperature (PVT) points in the pipeline to be accurate. Having multiple adjacent PVT sensors along the pipeline is expensive, hence generally not a viable alternative from an economic standpoint.A conceptual approach to combine mathematical modeling using computational fluid dynamics and a supervised machine learning model has shown promising results to predict leakage in the pipeline. Mathematical modeling is used to generate simulation data where this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the supervised machine learning model requires a large training dataset for the development of accurate models, mathematical modeling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modeling for the development of robust real-time leak detection and localization system for surface pipelines. A case study is also presented.

Keywords: pipeline, leakage, detection, AI

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11004 Computational Study of Chromatographic Behavior of a Series of S-Triazine Pesticides Based on Their in Silico Biological and Lipophilicity Descriptors

Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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In this paper, quantitative structure-retention relationships (QSRR) analysis was applied in order to correlate in silico biological and lipophilicity molecular descriptors with retention values for the set of selected s-triazine herbicides. In silico generated biological and lipophilicity descriptors were discriminated using generalized pair correlation method (GPCM). According to this method, the significant difference between independent variables can be noticed regardless almost equal correlation with dependent variable. Using established multiple linear regression (MLR) models some biological characteristics could be predicted. Established MLR models were evaluated statistically and the most suitable models were selected and ranked using sum of ranking differences (SRD) method. In this method, as reference values, average experimentally obtained values are used. Additionally, using SRD method, similarities among investigated s-triazine herbicides can be noticed. These analysis were conducted in order to characterize selected s-triazine herbicides for future investigations regarding their biodegradability. This study is financially supported by COST action TD1305.

Keywords: descriptors, generalized pair correlation method, pesticides, sum of ranking differences

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11003 Fuzzy-Machine Learning Models for the Prediction of Fire Outbreak: A Comparative Analysis

Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

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This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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11002 Effect of Pack Aluminising Conditions on βNiAl Coatings

Authors: A. D. Chandio, P. Xiao

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In this study, nickel aluminide coatings were deposited onto CMSX-4 single crystal superalloy and pure Ni substrates by using in-situ chemical vapour deposition (CVD) technique. The microstructural evolutions and coating thickness (CT) were studied upon the variation of processing conditions i.e. time and temperature. The results demonstrated (under identical conditions) that coating formed on pure Ni contains no substrate entrapments and have lower CT in comparison to one deposited on the CMSX-4 counterpart. In addition, the interdiffusion zone (IDZ) of Ni substrate is a γ’-Ni3Al in comparison to the CMSX-4 alloy that is βNiAl phase. The higher CT on CMSX-4 superalloy is attributed to presence of γ-Ni/γ’-Ni3Al structure which contains ~ 15 at.% Al before deposition (that is already present in superalloy). Two main deposition parameters (time and temperature) of the coatings were also studied in addition to standard comparison of substrate effects. The coating formation time was found to exhibit profound effect on CT, whilst temperature was found to change coating activities. In addition, the CT showed linear trend from 800 to 1000 °C, thereafter reduction was observed. This was attributed to the change in coating activities.

Keywords: βNiAl, in-situ CVD, CT, CMSX-4, Ni, microstructure

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11001 Local Government Digital Attention and Green Technology Innovation: Analysis Based on Spatial Durbin Model

Authors: Xin Wang, Chaoqun Ma, Zheng Yao

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Although green technology innovation faces new opportunities and challenges in the digital era, its theoretical research remains limited. Drawing on the attention-based view, this study employs the spatial Durbin model to investigate the impact of local government digital attention and digital industrial agglomeration on green technology innovation across 30 Chinese provinces from 2011 to 2021, as well as the spatial spillover effects present. The results suggest that both government digital attention and digital industrial agglomeration positively influence green technology innovation in local and neighboring provinces, with digital industrial agglomeration exhibiting a positive moderating effect on this direct local and indirect spatial spillover relationship. The findings of this study provide a new theoretical perspective for green technology innovation research and hold valuable implications for the advancement of the attention-based view and green technology innovation.

Keywords: local government digital attention, digital industrial agglomeration, green technology innovation, attention-based view

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11000 Iraqi Short Term Electrical Load Forecasting Based on Interval Type-2 Fuzzy Logic

Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

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Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

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10999 An Efficient FPGA Realization of Fir Filter Using Distributed Arithmetic

Authors: M. Iruleswari, A. Jeyapaul Murugan

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Most fundamental part used in many Digital Signal Processing (DSP) application is a Finite Impulse Response (FIR) filter because of its linear phase, stability and regular structure. Designing a high-speed and hardware efficient FIR filter is a very challenging task as the complexity increases with the filter order. In most applications the higher order filters are required but the memory usage of the filter increases exponentially with the order of the filter. Using multipliers occupy a large chip area and need high computation time. Multiplier-less memory-based techniques have gained popularity over past two decades due to their high throughput processing capability and reduced dynamic power consumption. This paper describes the design and implementation of highly efficient Look-Up Table (LUT) based circuit for the implementation of FIR filter using Distributed arithmetic algorithm. It is a multiplier less FIR filter. The LUT can be subdivided into a number of LUT to reduce the memory usage of the LUT for higher order filter. Analysis on the performance of various filter orders with different address length is done using Xilinx 14.5 synthesis tool. The proposed design provides less latency, less memory usage and high throughput.

Keywords: finite impulse response, distributed arithmetic, field programmable gate array, look-up table

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10998 Large Amplitude Free Vibration of a Very Sag Marine Cable

Authors: O. Punjarat, S. Chucheepsakul, T. Phanyasahachart

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This paper focuses on a variational formulation of large amplitude free vibration behavior of a very sag marine cable. In the static equilibrium state, the marine cable has a very large sag configuration. In the motion state, the marine cable is assumed to vibrate in in-plane motion with large amplitude from the static equilibrium position. The total virtual work-energy of the marine cable at the dynamic state is formulated which involves the virtual strain energy due to axial deformation, the virtual work done by effective weight, and the inertia forces. The equations of motion for the large amplitude free vibration of marine cable are obtained by taking into account the difference between the Euler’s equation in the static state and the displaced state. Based on the Galerkin finite element procedure, the linear and nonlinear stiffness matrices, and mass matrices of the marine cable are obtained and the eigenvalue problem is solved. The natural frequency spectrum and the large amplitude free vibration behavior of marine cable are presented.

Keywords: axial deformation, free vibration, Galerkin finite element method, large amplitude, variational method

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10997 Determination of Chemical and Adsorption Kinetics: An Investigation of a Petrochemical Wastewater Treatment Utilizing GAC

Authors: Leila Vafajoo, Feria Ghanaat, Alireza Mohmadi Kartalaei, Amin Ghalebi

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Petrochemical industries are playing an important role in producing wastewaters. Nowadays different methods are employed to treat these materials. The goal of the present research was to reduce the COD of a petrochemical wastewater via adsorption technique using a commercial granular activated carbon (GAC) as adsorbent. In the current study, parameters of kinetic models as well as; adsorption isotherms were determined through utilizing the Langmuir and Freundlich isotherms. The key parameters of KL= 0.0009 and qm= 33.33 for the former and nf=0.5 and Kf= 0.000004 for the latter isotherms resulted. Moreover, a correlation coefficient of above 90% for both cases proved logical use of such isotherms. On the other hand, pseudo-first and -second order kinetics equations were implemented. These resulted in coefficients of k1=0.005 and qe=2018 as well as; K2=0.009 and qe=1250; respectively. In addition, obtaining the correlation coefficients of 0.94 and 0.68 for these 1st and 2nd order kinetics; respectively indicated advantageous use of the former model. Furthermore, a significant experimental reduction of the petrochemical wastewater COD revealed that, using GAC for the process undertaken was an efficient mean of treatment. Ultimately, the current investigation paved down the road for predicting the system’s behavior on industrial scale.

Keywords: petrochemical wastewater, adsorption, granular activated carbon, equilibrium isotherm, kinetic model

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10996 Sequence Component-Based Adaptive Protection for Microgrids Connected Power Systems

Authors: Isabelle Snyder

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Microgrid protection presents challenges to conventional protection techniques due to the low induced fault current. Protection relays present in microgrid applications require a combination of settings groups to adjust based on the architecture of the microgrid in islanded and grid-connected mode. In a radial system where the microgrid is at the other end of the feeder, directional elements can be used to identify the direction of the fault current and switch settings groups accordingly (grid connected or microgrid connected). However, with multiple microgrid connections, this concept becomes more challenging, and the direction of the current alone is not sufficient to identify the source of the fault current contribution. ORNL has previously developed adaptive relaying schemes through other DOE-funded research projects that will be evaluated and used as a baseline for this research. The four protection techniques in this study are the following: (1) Adaptive Current only Protection System (ACPS), Intentional (2) Unbalanced Control for Protection Control (IUCPC), (3) Adaptive Protection System with Communication Controller (APSCC) (4) Adaptive Model-Driven Protective Relay (AMDPR). The first two methods focus on identifying the islanded mode without communication by monitoring the current sequence component generated by the system (ACPS) or induced with inverter control during islanded mode (IUCPC) to identify the islanding condition without communication at the relay to adjust the settings. These two methods are used as a backup to the APSCC, which relies on a communication network to communicate the islanded configuration to the system components. The fourth method relies on a short circuit model inside the relay that is used in conjunction with communication to adjust the system configuration and computes the fault current and adjusts the settings accordingly.

Keywords: adaptive relaying, microgrid protection, sequence components, islanding detection, communication controlled protection, integrated short circuit model

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10995 Application of Mathematical Models for Conducting Long-Term Metal Fume Exposure Assessments for Workers in a Shipbuilding Factory

Authors: Shu-Yu Chung, Ying-Fang Wang, Shih-Min Wang

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To conduct long-term exposure assessments are important for workers exposed to chemicals with chronic effects. However, it usually encounters with several constrains, including cost, workers' willingness, and interference to work practice, etc., leading to inadequate long-term exposure data in the real world. In this study, an integrated approach was developed for conducting long-term exposure assessment for welding workers in a shipbuilding factory. A laboratory study was conducted to yield the fume generation rates under various operating conditions. The results and the measured environmental conditions were applied to the near field/far field (NF/FF) model for predicting long term fume exposures via the Monte Carlo simulation. Then, the predicted long-term concentrations were used to determine the prior distribution in Bayesian decision analysis (BDA). Finally, the resultant posterior distributions were used to assess the long-term exposure and serve as basis for initiating control strategies for shipbuilding workers. Results show that the NF/FF model was a suitable for predicting the exposures of metal contents containing in welding fume. The resultant posterior distributions could effectively assess the long-term exposures of shipbuilding welders. Welders' long-term Fe, Mn and Pb exposures were found with high possibilities to exceed the action level indicating preventive measures should be taken for reducing welders' exposures immediately. Though the resultant posterior distribution can only be regarded as the best solution based on the currently available predicting and monitoring data, the proposed integrated approach can be regarded as a possible solution for conducting long term exposure assessment in the field.

Keywords: Bayesian decision analysis, exposure assessment, near field and far field model, shipbuilding industry, welding fume

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10994 Evaluating Generative Neural Attention Weights-Based Chatbot on Customer Support Twitter Dataset

Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are playing an increasingly important role in automated customer service. These models, which are able to recognize complex relationships between input and output sequences, are crucial for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the focus of the model during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the domain of chatbots using the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Utilizing the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k=3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k=3). These results emphasize the crucial influence of selecting an appropriate attention-scoring function in improving the performance of seq2seq models for chatbots. Particularly, the model that integrates tanh activation proves to be a promising approach to improve the quality of chatbots in the customer support context.

Keywords: attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence

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10993 Modeling of Polyethylene Particle Size Distribution in Fluidized Bed Reactors

Authors: R. Marandi, H. Shahrir, T. Nejad Ghaffar Borhani, M. Kamaruddin

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In the present study, a steady state population balance model was developed to predict the polymer particle size distribution (PSD) in ethylene gas phase fluidized bed olefin polymerization reactors. The multilayer polymeric flow model (MPFM) was used to calculate the growth rate of a single polymer particle under intra-heat and mass transfer resistance. The industrial plant data were used to calculate the growth rate of polymer particle and the polymer PSD. Numerical simulations carried out to describe the influence of effective monomer diffusion coefficient, polymerization rate and initial catalyst size on the catalyst particle growth and final polymer PSD. The results present that the intra-heat and mass limitation is important for the ethylene polymerization, the growth rate of particle and the polymer PSD in the fluidized bed reactor. The effect of the agglomeration on the PSD is also considered. The result presents that the polymer particle size distribution becomes broader as the agglomeration exits.

Keywords: population balance, olefin polymerization, fluidized bed reactor, particle size distribution, agglomeration

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10992 Unbreakable Obedience of Safety Regulation: The Study of Authoritarian Leadership and Safety Performance

Authors: Hong-Yi Kuo

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Leadership is a key factor of improving workplace safety, and there have been abundant of studies which support the positive effects of appropriate leadership on employee safety performance in the western academic. However, little safety research focus on the Chinese leadership style like paternalistic leadership. To fill this gap, the resent study aims to examine the relationship between authoritarian leadership (one of the ternary mode in paternalistic leadership) and safety outcomes. This study makes hypothesis on different levels. First, on the group level, as an authoritarian leader regards safety value as the most important tasks, there would be positive effect on group safety outcomes through strengthening safety group norms by the emphasis on etiquette. Second, on the cross level, when a leader with authoritarian style has high priority on safety, employees may more obey the safety rules because of fear due to emphasis on absolute authority over the leader. Therefore, employees may show more safety performance and then increase individual safety outcomes. Survey data would be collected from 50 manufacturing groups (each group with more than 5 members and a leader) and a hierarchical linear modeling analysis would be conducted to analyze the hypothesis. Above the predictive result, the study expects to be a cornerstone of safety leadership research in the Chinese academic and practice.

Keywords: safety leadership, authoritarian leadership, group norms, safety behavior, supervisor safety priority

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10991 Selection of Social and Sustainability Criteria for Public Investment Project Evaluation in Developing Countries

Authors: Pintip Vajarothai, Saad Al-Jibouri, Johannes I. M. Halman

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Public investment projects are primarily aimed at achieving development strategies to increase national economies of scale and overall improvement in a country. However, experience shows that public projects, particularly in developing countries, struggle or fail to fulfill the immediate needs of local communities. In many cases, the reason for that is that projects are selected in a subjective manner and that a major part of the problem is related to the evaluation criteria and techniques used. The evaluation process is often based on a broad strategic economic effects rather than real benefits of projects to society or on the various needs from different levels (e.g. national, regional, local) and conditions (e.g. long-term and short-term requirements). In this paper, an extensive literature review of the types of criteria used in the past by various researchers in project evaluation and selection process is carried out and the effectiveness of such criteria and techniques is discussed. The paper proposes substitute social and project sustainability criteria to improve the conditions of local people and in particular the disadvantaged groups of the communities. Furthermore, it puts forward a way for modelling the interaction between the selected criteria and the achievement of the social goals of the affected community groups. The described work is part of developing a broader decision model for public investment project selection by integrating various aspects and techniques into a practical methodology. The paper uses Thailand as a case to review what and how the various evaluation techniques are currently used and how to improve the project evaluation and selection process related to social and sustainability issues in the country. The paper also uses an example to demonstrates how to test the feasibility of various criteria and how to model the interaction between projects and communities. The proposed model could be applied to other developing and developed countries in the project evaluation and selection process to improve its effectiveness in the long run.

Keywords: evaluation criteria, developing countries, public investment, project selection methodology

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10990 Crop Productivity, Nutrient Uptake and Apparent Balance for Rice Based Cropping Systems under Improved Crop Varieties and Nutrient Management Practices in Previous Enclaves of Bangladesh

Authors: Md. Samim Hossain Molla, Md. Mazharul Anwar, Md. Akkas Ali, Mian Sayeed Hassan

Abstract:

Being detached about 68 years from the mainland, the previous enclaves’ (Chhitmohal) farmers were engaged only in subsistence farming with low agricultural productivity and restricted access to inputs technology. To increase crop productivity for attaining food security by addressing soil status, the experiments were undertaken in 2017 and 2018 in three previous enclaves of Northern Bangladesh i.e. Dasiarchhara of Kurigram district; Dahalakhagrabari of Panchagarh district and Banskata of Lalmonirhat district under On-Farm Research Division, Bangladesh Agricultural Research Institute, Rangpur. The Mustard (var. BARI Sarisha-14)-Boro rice (var. BRRI dhan58)-T. Aman rice (var. BRRI dhan49) cropping pattern using soil test based (STB) fertilizer with cowdung (T1) or recommended fertilizer dose (T2) were tested against existing cropping pattern Fallow-Boro rice (var. BRRI dhan28)-T. Aman rice (var. Swarna) using farmers’ practices fertilizer dose (T3) in six disperse replications at each location maintaining Randomized Complete Block design. Almost all crops yields were relatively higher in T1 followed by T2. Farmers existing pattern with local varieties and imbalance fertilizer (T3) use may be decreased the crop yield. The rice equivalent yield of T1 was 109, 103 and 95% higher than T3 and the gross margin was 164, 153 and 133% higher in T1 than T3 at Dasiarchhara, Dahalakhagrabari and Banskata, respectively. The Benefit Cost Ratio for T1, T2 and T3 were 1.99, 1.78 and 1.28 in Dasiarchhara; 1.93, 1.81 and 1.27 in Dahalakhagrabari and 1.78, 1.71 and 1.25 in Banskata, respectively. There was a remarkable decrease in mineral N, P and K in the topsoil (0–15 cm) of T3 and T2 treatments at Dasiarchhara and Dahalakhagrabari, and a generally less marked decline under the same treatments at Banskata. The same practices (T1) exhibited the greatest nutrients uptake by the test crops. The apparent balance of N, P and K was negative in most cases, where it was less negative in T1 treatment. However, from the experimentation, it is revealed that balanced fertilization (STB) and inclusion of National Agricultural Research Institutes developed improved crops varieties in cropping pattern may increase the crop productivity, farm efficiency and farmer’s income in a remarkable level.

Keywords: cropping pattern, fertilizer management, nutrient balance, previous enclaves

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10989 Numerical Modelling and Experiment of a Composite Single-Lap Joint Reinforced by Multifunctional Thermoplastic Composite Fastener

Authors: Wenhao Li, Shijun Guo

Abstract:

Carbon fibre reinforced composites are progressively replacing metal structures in modern civil aircraft. This is because composite materials have large potential of weight saving compared with metal. However, the achievement to date of weight saving in composite structure is far less than the theoretical potential due to many uncertainties in structural integrity and safety concern. Unlike the conventional metallic structure, composite components are bonded together along the joints where structural integrity is a major concern. To ensure the safety, metal fasteners are used to reinforce the composite bonded joints. One of the solutions for a significant weight saving of composite structure is to develop an effective technology of on-board Structural Health Monitoring (SHM) System. By monitoring the real-life stress status of composite structures during service, the safety margin set in the structure design can be reduced with confidence. It provides a means of safeguard to minimize the need for programmed inspections and allow for maintenance to be need-driven, rather than usage-driven. The aim of this paper is to develop smart composite joint. The key technology is a multifunctional thermoplastic composite fastener (MTCF). The MTCF will replace some of the existing metallic fasteners in the most concerned locations distributed over the aircraft composite structures to reinforce the joints and form an on-board SHM network system. Each of the MTCFs will work as a unit of the AU and AE technology. The proposed MTCF technology has been patented and developed by Prof. Guo in Cranfield University, UK in the past a few years. The manufactured MTCF has been successfully employed in the composite SLJ (Single-Lap Joint). In terms of the structure integrity, the hybrid SLJ reinforced by MTCF achieves 19.1% improvement in the ultimate failure strength in comparison to the bonded SLJ. By increasing the diameter or rearranging the lay-up sequence of MTCF, the hybrid SLJ reinforced by MTCF is able to achieve the equivalent ultimate strength as that reinforced by titanium fastener. The predicted ultimate strength in simulation is in good agreement with the test results. In terms of the structural health monitoring, a signal from the MTCF was measured well before the load of mechanical failure. This signal provides a warning of initial crack in the joint which could not be detected by the strain gauge until the final failure.

Keywords: composite single-lap joint, crack propagation, multifunctional composite fastener, structural health monitoring

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10988 Prediction of Fracture Aperture in Fragmented Rocks

Authors: Hossein Agheshlui, Stephan Matthai

Abstract:

In fractured rock masses open fractures tend to act as the main pathways of fluid flow. The permeability of a rock fracture depends on its aperture. The change of aperture with stress can cause a many-orders-of-magnitude change in the hydraulic conductivity at moderate compressive stress levels. In this study, the change of aperture in fragmented rocks is investigated using finite element analysis. A full 3D mechanical model of a simplified version of an outcrop analog is created and studied. A constant initial aperture value is applied to all fractures. Different far field stresses are applied and the change of aperture is monitored considering the block to block interaction. The fragmented rock layer is assumed to be sandwiched between softer layers. Frictional contact forces are defined at the layer boundaries as well as among contacting rock blocks. For a given in situ stress, the blocks slide and contact each other, resulting in new aperture distributions. A map of changed aperture is produced after applying the in situ stress and compared to the initial apertures. Subsequently, the permeability of the system before and after the stress application is compared.

Keywords: fractured rocks, mechanical model, aperture change due to stress, frictional interface

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10987 Novel Recommender Systems Using Hybrid CF and Social Network Information

Authors: Kyoung-Jae Kim

Abstract:

Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

Procedia PDF Downloads 275
10986 Simulation with Uncertainties of Active Controlled Vibration Isolation System for Astronaut’s Exercise Platform

Authors: Shield B. Lin, Ziraguen O. Williams

Abstract:

In a task to assist NASA in analyzing the dynamic forces caused by operational countermeasures of an astronaut’s exercise platform impacting the spacecraft, an active proportional-integral-derivative controller commanding a linear actuator is proposed in a vibration isolation system to regulate the movement of the exercise platform. Computer simulation shows promising results that most exciter forces can be reduced or even eliminated. This paper emphasizes on parameter uncertainties, variations and exciter force variations. Drift and variations of system parameters in the vibration isolation system for astronaut’s exercise platform are analyzed. An active controlled scheme is applied with the goals to reduce the platform displacement and to minimize the force being transmitted to the spacecraft structure. The controller must be robust enough to accommodate the wide variations of system parameters and exciter forces. Computer simulation for the vibration isolation system was performed via MATLAB/Simulink and Trick. The simulation results demonstrate the achievement of force reduction with small platform displacement under wide ranges of variations in system parameters.

Keywords: control, counterweight, isolation, vibration

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10985 Design Manufacture and Testing of a Combined Alpha-Beta Double Piston Stirling Engine

Authors: A. Calvin Antony, Sakthi Kumar Arul Prakash, V. R. Sanal Kumar

Abstract:

In this paper a unique alpha-beta double piston 'stirling engine' is designed, manufactured and conducted laboratory test to ameliorate the efficiency of the stirling engine. The paper focuses on alpha and beta type engines, capturing their benefits and eradicating their short comings; along with the output observed from the flywheel. In this model alpha engine is kinematically with a piston cylinder arrangement which works quite like a beta engine. The piston of the new cylinder is so designed that it replicates a glued displacer and power piston as similar to that of beta engine. The bigger part of the piston is the power piston, which has a gap around it, while the smaller part of the piston is tightly fit in the cylinder and acts like the displacer piston. We observed that the alpha-beta double piston stirling engine produces 25% increase in power compare to a conventional alpha stirling engine. This working model is a pointer towards for the design and development of an alpha-beta double piston Stirling engine for industrial applications for producing electricity from the heat producing exhaust gases.

Keywords: alpha-beta double piston stirling engine , alpha stirling engine , beta double piston stirling engine , electricity from stirling engine

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10984 Modeling the International Economic Relations Development: The Prospects for Regional and Global Economic Integration

Authors: M. G. Shilina

Abstract:

The interstate economic interaction phenomenon is complex. ‘Economic integration’, as one of its types, can be explored through the prism of international law, the theories of the world economy, politics and international relations. The most objective study of the phenomenon requires a comprehensive multifactoral approach. In new geopolitical realities, the problems of coexistence and possible interconnection of various mechanisms of interstate economic interaction are actively discussed. Currently, the Eurasian continent states support the direction to economic integration. At the same time, the existing international economic law fragmentation in Eurasia is seen as the important problem. The Eurasian space is characterized by a various types of interstate relations: international agreements (multilateral and bilateral), and a large number of cooperation formats (from discussion platforms to organizations aimed at deep integration). For their harmonization, it is necessary to have a clear vision to the phased international economic relations regulation options. In the conditions of rapid development of international economic relations, the modeling (including prognostic) can be optimally used as the main scientific method for presenting the phenomenon. On the basis of this method, it is possible to form the current situation vision and the best options for further action. In order to determine the most objective version of the integration development, the combination of several approaches were used. The normative legal approach- the descriptive method of legal modeling- was taken as the basis for the analysis. A set of legal methods was supplemented by the international relations science prognostic methods. The key elements of the model are the international economic organizations and states' associations existing in the Eurasian space (the Eurasian Economic Union (EAEU), the European Union (EU), the Shanghai Cooperation Organization (SCO), Chinese project ‘One belt-one road’ (OBOR), the Commonwealth of Independent States (CIS), BRICS, etc.). A general term for the elements of the model is proposed - the interstate interaction mechanisms (IIM). The aim of building a model of current and future Eurasian economic integration is to show optimal options for joint economic development of the states and IIMs. The long-term goal of this development is the new economic and political space, so-called the ‘Great Eurasian Community’. The process of achievement this long-term goal consists of successive steps. Modeling the integration architecture and dividing the interaction into stages led us to the following conclusion: the SCO is able to transform Eurasia into a single economic space. Gradual implementation of the complex phased model, in which the SCO+ plays a key role, will allow building an effective economic integration for all its participants, to create an economically strong community. The model can have practical value for politicians, lawyers, economists and other participants involved in the economic integration process. A clear, systematic structure can serve as a basis for further governmental action.

Keywords: economic integration, The Eurasian Economic Union, The European Union, The Shanghai Cooperation Organization, The Silk Road Economic Belt

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10983 Evaluation of QSRR Models by Sum of Ranking Differences Approach: A Case Study of Prediction of Chromatographic Behavior of Pesticides

Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

Abstract:

The present study deals with the selection of the most suitable quantitative structure-retention relationship (QSRR) models which should be used in prediction of the retention behavior of basic, neutral, acidic and phenolic pesticides which belong to different classes: fungicides, herbicides, metabolites, insecticides and plant growth regulators. Sum of ranking differences (SRD) approach can give a different point of view on selection of the most consistent QSRR model. SRD approach can be applied not only for ranking of the QSRR models, but also for detection of similarity or dissimilarity among them. Applying the SRD analysis, the most similar models can be found easily. In this study, selection of the best model was carried out on the basis of the reference ranking (“golden standard”) which was defined as the row average values of logarithm of retention time (logtr) defined by high performance liquid chromatography (HPLC). Also, SRD analysis based on experimental logtr values as reference ranking revealed similar grouping of the established QSRR models already obtained by hierarchical cluster analysis (HCA).

Keywords: chemometrics, chromatography, pesticides, sum of ranking differences

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10982 Thermomechanical Behaviour of Various Pressurized Installations Subjected to Thermal Load Due to the Combustion of Metal Particles

Authors: Khaled Ayfi, Morgan Dal, Frederic Coste, Nicolas Gallienne, Martina Ridlova, Philippe Lorong

Abstract:

In the gas industry, contamination of equipment by metal particles is one of the feared phenomena. Indeed, particles inside equipment can be driven by the gas flow and accumulate in places where the velocity is low. As they constitute a potential ignition hazard, particular attention is paid to the presence of particles in the oxygen industry. Indeed, the heat release from ignited particles may damage the equipment and even result in a loss of integrity. The objective of this work is to support the development of new design criteria. Studying the thermomechanical behavior of this equipment, thanks to numerical simulations, allows us to test the influence of various operating parameters (oxygen pressure, wall thickness, initial operating temperature, nature of the metal, etc.). Therefore, in this study, we propose a numerical model that describes the thermomechanical behavior of various pressurized installations heated locally by the combustion of small particles. This model takes into account the geometric and material nonlinearity and has been validated by the comparison of simulation results with experimental measurements obtained by a new device developed in this work.

Keywords: ignition, oxygen, numerical simulation, thermomechanical behaviour

Procedia PDF Downloads 140