Search results for: technological pedagogical model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18294

Search results for: technological pedagogical model

11394 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

Abstract:

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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11393 Temperature Rises Characteristics of Distinct Double-Sided Flat Permanent Magnet Linear Generator for Free Piston Engines for Hybrid Vehicles

Authors: Ismail Rahama Adam Hamid

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This paper presents the development of a thermal model for a flat, double-sided linear generator designed for use in free-piston engines. The study conducted in this paper examines the influence of temperature on the performance of the permeant magnet linear generator, an integral and pivotal component within the system. This research places particular emphasis on the Neodymium Iron Boron (NdFeB) permanent magnet, which serves as a source of magnetic field for the linear generator. In this study, an internal combustion engine that tends to produce heat is connected to a generator. Considering the temperatures rise from both the combustion process and the thermal contributions of current-carrying conductors and frictional forces. Utilizing Computational Fluid Dynamics (CFD) method, a thermal model of the (NdFeB) magnet within the linear generator is constructed and analyzed. Furthermore, the temperature field is examined to ensure that the linear generator operates under stable conditions without the risk of demagnetization.

Keywords: free piston engine, permanent magnet, linear generator, demagnetization, simulation

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11392 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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11391 Transformation of Industrial Policy towards Industry 4.0 and Its Impact on Firms' Competition

Authors: Arūnas Burinskas

Abstract:

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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11390 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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11389 Liquid-Liquid Plug Flow Characteristics in Microchannel with T-Junction

Authors: Anna Yagodnitsyna, Alexander Kovalev, Artur Bilsky

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The efficiency of certain technological processes in two-phase microfluidics such as emulsion production, nanomaterial synthesis, nitration, extraction processes etc. depends on two-phase flow regimes in microchannels. For practical application in chemistry and biochemistry it is very important to predict the expected flow pattern for a large variety of fluids and channel geometries. In the case of immiscible liquids, the plug flow is a typical and optimal regime for chemical reactions and needs to be predicted by empirical data or correlations. In this work flow patterns of immiscible liquid-liquid flow in a rectangular microchannel with T-junction are investigated. Three liquid-liquid flow systems are considered, viz. kerosene – water, paraffin oil – water and castor oil – paraffin oil. Different flow patterns such as parallel flow, slug flow, plug flow, dispersed (droplet) flow, and rivulet flow are observed for different velocity ratios. New flow pattern of the parallel flow with steady wavy interface (serpentine flow) has been found. It is shown that flow pattern maps based on Weber numbers for different liquid-liquid systems do not match well. Weber number multiplied by Ohnesorge number is proposed as a parameter to generalize flow maps. Flow maps based on this parameter are superposed well for all liquid-liquid systems of this work and other experiments. Plug length and velocity are measured for the plug flow regime. When dispersed liquid wets channel walls plug length cannot be predicted by known empirical correlations. By means of particle tracking velocimetry technique instantaneous velocity fields in a plug flow regime were measured. Flow circulation inside plug was calculated using velocity data that can be useful for mass flux prediction in chemical reactions.

Keywords: flow patterns, hydrodynamics, liquid-liquid flow, microchannel

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11388 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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11387 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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11386 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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11385 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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11384 Controlling Drone Flight Missions through Natural Language Processors Using Artificial Intelligence

Authors: Sylvester Akpah, Selasi Vondee

Abstract:

Unmanned Aerial Vehicles (UAV) as they are also known, drones have attracted increasing attention in recent years due to their ubiquitous nature and boundless applications in the areas of communication, surveying, aerial photography, weather forecasting, medical delivery, surveillance amongst others. Operated remotely in real-time or pre-programmed, drones can fly autonomously or on pre-defined routes. The application of these aerial vehicles has successfully penetrated the world due to technological evolution, thus a lot more businesses are utilizing their capabilities. Unfortunately, while drones are replete with the benefits stated supra, they are riddled with some problems, mainly attributed to the complexities in learning how to master drone flights, collision avoidance and enterprise security. Additional challenges, such as the analysis of flight data recorded by sensors attached to the drone may take time and require expert help to analyse and understand. This paper presents an autonomous drone control system using a chatbot. The system allows for easy control of drones using conversations with the aid of Natural Language Processing, thus to reduce the workload needed to set up, deploy, control, and monitor drone flight missions. The results obtained at the end of the study revealed that the drone connected to the chatbot was able to initiate flight missions with just text and voice commands, enable conversation and give real-time feedback from data and requests made to the chatbot. The results further revealed that the system was able to process natural language and produced human-like conversational abilities using Artificial Intelligence (Natural Language Understanding). It is recommended that radio signal adapters be used instead of wireless connections thus to increase the range of communication with the aerial vehicle.

Keywords: artificial ntelligence, chatbot, natural language processing, unmanned aerial vehicle

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11383 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

Abstract:

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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11382 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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11381 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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11380 Evaluating Generative Neural Attention Weights-Based Chatbot on Customer Support Twitter Dataset

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

Abstract:

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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11379 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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11378 Horizontal Stress Magnitudes Using Poroelastic Model in Upper Assam Basin, India

Authors: Jenifer Alam, Rima Chatterjee

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Upper Assam sedimentary basin is one of the oldest commercially producing basins of India. Being in a tectonically active zone, estimation of tectonic strain and stress magnitudes has vast application in hydrocarbon exploration and exploitation. This East North East –West South West trending shelf-slope basin encompasses the Bramhaputra valley extending from Mikir Hills in the southwest to the Naga foothills in the northeast. Assam Shelf lying between the Main Boundary Thrust (MBT) and Naga Thrust area is comparatively free from thrust tectonics and depicts normal faulting mechanism. The study area is bounded by the MBT and Main Central Thrust in the northwest. The Belt of Schuppen in the southeast, is bordered by Naga and Disang thrust marking the lower limit of the study area. The entire Assam basin shows low-level seismicity compared to other regions of northeast India. Pore pressure (PP), vertical stress magnitude (SV) and horizontal stress magnitudes have been estimated from two wells - N1 and T1 located in Upper Assam. N1 is located in the Assam gap below the Bramhaputra river while T1, lies in the Belt of Schuppen. N1 penetrates geological formations from top Alluvial through Dhekiajuli, Girujan, Tipam, Barail, Kopili, Sylhet and Langpur to the granitic basement while T1 in trusted zone crosses through Girujan Suprathrust, Tipam Suprathrust, Barail Suprathrust to reach Naga Thrust. Normal compaction trend is drawn through shale points through both wells for estimation of PP using the conventional Eaton sonic equation with an exponent of 1.0 which is validated with Modular Dynamic Tester and mud weight. Observed pore pressure gradient ranges from 10.3 MPa/km to 11.1 MPa/km. The SV has a gradient from 22.20 to 23.80 MPa/km. Minimum and maximum horizontal principal stress (Sh and SH) magnitudes under isotropic conditions are determined using poroelastic model. This approach determines biaxial tectonic strain utilizing static Young’s Modulus, Poisson’s Ratio, SV, PP, leak off test (LOT) and SH derived from breakouts using prior information on unconfined compressive strength. Breakout derived SH information is used for obtaining tectonic strain due to lack of measured SH data from minifrac or hydrofracturing. Tectonic strain varies from 0.00055 to 0.00096 along x direction and from -0.0010 to 0.00042 along y direction. After obtaining tectonic strains at each well, the principal horizontal stress magnitudes are calculated from linear poroelastic model. The magnitude of Sh and SH gradient in normal faulting region are 12.5 and 16.0 MPa/km while in thrust faulted region the gradients are 17.4 and 20.2 MPa/km respectively. Model predicted Sh and SH matches well with the LOT data and breakout derived SH data in both wells. It is observed from this study that the stresses SV>SH>Sh prevailing in the shelf region while near the Naga foothills the regime changes to SH≈SV>Sh area corresponds to normal faulting regime. Hence this model is a reliable tool for predicting stress magnitudes from well logs under active tectonic regime in Upper Assam Basin.

Keywords: Eaton, strain, stress, poroelastic model

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11377 Explaining Listening Comprehension among L2 Learners of English: The Contribution of Vocabulary Knowledge and Working Memory Capacity

Authors: Ahmed Masrai

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Listening comprehension constitutes a considerable challenge for the second language (L2) learners, but a little is known about the explanatory power of different variables in explaining variance in listening comprehension. Since research in this area, to the researcher's knowledge, is relatively small in comparison to that focusing on the relationship between reading comprehension and factors such as vocabulary and working memory, there is a need for studies that are seeking to fill the gap in our knowledge about the specific contribution of working memory capacity (WMC), aural vocabulary knowledge and written vocabulary knowledge to explaining listening comprehension. Among 130 English as foreign language learners, the present study examines what proportion of the variance in listening comprehension is explained by aural vocabulary knowledge, written vocabulary knowledge, and WMC. Four measures were used to collect the required data for the study: (1) A-Lex, a measure of aural vocabulary knowledge; (2) XK-Lex, a measure of written vocabulary knowledge; (3) Listening Span Task, a measure of WMC and; (4) IELTS Listening Test, a measure of listening comprehension. The results show that aural vocabulary knowledge is the strongest predictor of listening comprehension, followed by WMC, while written vocabulary knowledge is the weakest predictor. The study discusses implications for the explanatory power of aural vocabulary knowledge and WMC to listening comprehension and pedagogical practice in L2 classrooms.

Keywords: listening comprehension, second language, vocabulary knowledge, working memory

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11376 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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11375 Criminal Laws Associated with Cyber-Medicine and Telemedicine in Current Law Systems in the World

Authors: Shahryar Eslamitabar

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Currently, the internet plays an important role in the various scientific, commercial and service practices. Thanks to information and communication technology, the healthcare industry via the internet, generally known as cyber-medicine, can offer professional medical service in a wider geographical area. Having some appealing benefits such as convenience in offering healthcare services, improved accessibility to the services, enhanced information exchange, cost-effectiveness, time-saving, etc. Tele-health has increasingly developed innovative models of healthcare delivery. However, it presents many potential hazards to cyber-patients, inherent in the use of the system. First, there are legal issues associated with the communication and transfer of information on the internet. These include licensure, malpractice, liabilities and jurisdictions as well as privacy, confidentiality and security of personal data as the most important challenge brought about by this system. Additional items of concern are technological and ethical. Although, there are some rules to deal with pitfalls associated with cyber-medicine practices in the USA and some European countries, yet for all developments, it is being practiced in a legal vacuum in many countries. In addition to the domestic legislations to deal with potential problems arisen from the system, it is also imperative that some international or regional agreement should be developed to achieve the harmonization of laws among countries and states. This article discusses some implications posed by the practice of cyber-medicine in the healthcare system according to the experience of some developed countries using a comparative study of laws. It will also review the status of tele-health laws in Iran. Finally, it is intended to pave the way to outline a plan for countries like Iran, with newly-established judicial system for health laws, to develop appropriate regulations through providing some recommendations.

Keywords: tele-health, cyber-medicine, telemedicine, criminal laws, legislations, time-saving

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11374 Reconstruction of Wujiaochang Plaza: A Potential Avenue Towards Sustainability

Authors: Caiwei Chen, Jianhao Li, Jiasong Zhu

Abstract:

The reform and opening-up stimulated economic and technological take-off in China while resulting in massive urbanization and motorization. Wujiaochang area was set as a secondary business district in Shanghai to meet the growing demand, with the reconstruction of Wujiaochang Plaza in 2005 being a milestone of this intended urban renewal. Wujiaochang is now an economically dynamic area providing much larger traffic and transit capacity transportation-wise. However, this rebuilding has completely changed the face of the district. It is, therefore, appropriate to evaluate its impact on neighborhoods and communities while assessing the overall sustainability of such an operation. In this study, via an online questionnaire survey among local residents and daily visitors, we assess the perceptions and the estimated impact of Wujiaochang Plaza's reconstruction. We then confront these results to the 62 answers from local residents to a questionnaire collected on paper. The analysis of our data, along with observation and other forms of information -such as maps analysis or online applications (Dianping)- demonstrate major improvement in economic sustainability but also significant losses in environmental sustainability, especially in terms of active transportation. As for the social viewpoint, local residents' opinions tend to be rather positive, especially regarding traffic safety and access to consumption, despite the lack of connectivity and radical changes induced by Wujiaochang massive transformations. In general, our investigation exposes the overall positive outcomes of Wujiaochang Plaza reconstruction but also unveils major drawbacks, especially in terms of soft mobility and traffic fluidity. We gather that our approach could be of tremendous help for future major urban interventions, as such approaches in municipal regeneration are widely implemented in Chinese cities and yet still need to be thoroughly assessed in terms of sustainability.

Keywords: China's reform and opening-up, economical revitalization, neighborhood identity, sustainability assessment, urban renewal

Procedia PDF Downloads 218
11373 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

Procedia PDF Downloads 404
11372 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
11371 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

Procedia PDF Downloads 522
11370 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

Procedia PDF Downloads 138
11369 Pedagogical Effects of Using Workbooks in English Classes for the TOEIC Test: A Study on ESL Learners in Japanese Colleges

Authors: Mikako Nobuhara

Abstract:

The Test of English for International Communication (TOEIC) test, conducted by the Institute for International Business Communication (IIBC), has a huge impact on education in Japan. Almost all college students have to submit their TOEIC test scores when applying for entry-level jobs at companies. In addition, an increasing number of colleges are encouraging students to have a global vision. For this specific reason, studying for the TOEIC test is essential for English as a second language (ESL) learner to develop English communication skills. This study shows that studying by using some workbooks about the listening section of the TOEIC test clearly helps ESL learners to develop their listening skills. For this purpose, the listening test scores before and after classroom sessions were analyzed for each student. Students obtained higher scores in the listening section of the test and improved their English listening skills at the end of all the classroom sessions. In conclusion, it is important for English teachers to achieve the following objectives: (1) facilitate the learning of effective methods for correctly solving questions based on listening skills and (2) prepare listening tasks for reading aloud so as to keep up with the original speed, which is required for solving questions in the TOEIC test.

Keywords: education, ESL, listening skills, TOEIC test

Procedia PDF Downloads 244
11368 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

Procedia PDF Downloads 363
11367 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
11366 An AI-generated Semantic Communication Platform in HCI Course

Authors: Yi Yang, Jiasong Sun

Abstract:

Almost every aspect of our daily lives is now intertwined with some degree of human-computer interaction (HCI). HCI courses draw on knowledge from disciplines as diverse as computer science, psychology, design principles, anthropology, and more. Our HCI courses, named the Media and Cognition course, are constantly updated to reflect state-of-the-art technological advancements such as virtual reality, augmented reality, and artificial intelligence-based interactions. For more than a decade, our course has used an interest-based approach to teaching, in which students proactively propose some research-based questions and collaborate with teachers, using course knowledge to explore potential solutions. Semantic communication plays a key role in facilitating understanding and interaction between users and computer systems, ultimately enhancing system usability and user experience. The advancements in AI-generated technology, which have gained significant attention from both academia and industry in recent years, are exemplified by language models like GPT-3 that generate human-like dialogues from given prompts. Our latest version of the Human-Computer Interaction course practices a semantic communication platform based on AI-generated techniques. The purpose of this semantic communication is twofold: to extract and transmit task-specific information while ensuring efficient end-to-end communication with minimal latency. An AI-generated semantic communication platform evaluates the retention of signal sources and converts low-retain ability visual signals into textual prompts. These data are transmitted through AI-generated techniques and reconstructed at the receiving end; on the other hand, visual signals with a high retain ability rate are compressed and transmitted according to their respective regions. The platform and associated research are a testament to our students' growing ability to independently investigate state-of-the-art technologies.

Keywords: human-computer interaction, media and cognition course, semantic communication, retainability, prompts

Procedia PDF Downloads 92
11365 Simulation of 'Net' Nutrients Removal by Green Mussel (Perna viridis) in Estuarine and Coastal Areas

Authors: Chayarat Tantanasarit, Sandhya Babel

Abstract:

Green mussels (Perna viridis) can effectively remove nutrients from seawater through their filtration process. This study aims to estimate 'net' nutrient removal rate by green mussel through calculation of nutrient uptake and release. Nutrients (carbon, nitrogen, and phosphorus) uptake was calculated based on the mussel filtration rate. Nutrient release was evaluated from carbon, nitrogen, and phosphorus released as mussel feces. By subtracting nutrient release from nutrient uptake, net nutrient removal by green mussel can be found as 3302, 380 and 124 mg/year/indv. Mass balance model was employed to simulate nutrient removal in actual green mussel farming conditions. Mussels farm area, seawater flow rate and amount of mussels were considered in the model. Results show that although larger quantity of green mussel farms lead to higher nutrient removal rate, the maximum green mussel cultivation should be taken into consideration as nutrients released through mussel excretion can strongly affect marine ecosystem.

Keywords: carbon, ecretion, filtration, nitrogen, phosphorus

Procedia PDF Downloads 384