Search results for: circular economy model

Authors: Seyedsamad Tahani, Samira Ghorbanpour

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

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

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Authors: Jia Li, Huacong Li, Xiaobao Han

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

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

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Authors: Niladri Sekhar Barma, Satish Dhandole

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

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

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Authors: Vishwambhar Prasad Sati

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India’s economy is agriculture dominated. About 70% of the total population depends on practicing agriculture. Out of an estimated 140.3 million ha net cultivated area, 79.44 million ha (57%) is rain-fed, contributing 44% of the total food grain production. Meanwhile, India ranks second and shares 11.3% of the arable land of the world. It means that India has a high potential to harness agricultural resources for present and future food security. However, about 21.9% of people are living below the poverty line, and similarly, a large number of people are deprived or insecure about food. This situation is most critical in rural areas, where about 70% population lives. The study examines the present status, future trends, and challenges of food and agriculture in India. Time series data of the last three decades was gathered from secondary sources on area, production, and yield of crops; irrigated area; production of major crops; area, production, and yield of crops in the major food-producing states of India; food storage and poverty. The data were analyzed using descriptive statistics, correlation methods, and a regression model. State-level data on area, production, and yield of crops and irrigation facilities were indexed into levels, and the potentials of food production in the major food-producing states were observed. It was noted that the progressive growth rate of food production is higher than the population, which means that food is enough to feed the population; however, it is not accessible to all optimally because of wastage, leakage, lack of food storage, and proper distribution of food. If food is stored and distributed properly, there would not be any food shortage in India, the study revealed.

Keywords: agriculture, food production, population growth, poverty, future trends

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Authors: Youngjae Jin, Daeshik Kim

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

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

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Authors: Xiaojing Wang, Ann-Marie Ward, Tony Wall

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The problem of over-indebtedness has increased since deregulation of the banking industry in the 1980s, and now it has become a major problem for most countries in Europe, including Germany. Consumer debt issues have attracted not only the attention of academics but also government and debt counselling institutions. Overall, this research aims to contribute to the knowledge gap regarding the causes of consumer over-indebtedness in Germany and to develop predictive models for assessing consumer over-indebtedness risk at consumer level. The situation of consumer over-indebtedness is serious in Germany. The relatively high level of social welfare support in Germany suggests that consumer debt problems are caused by other factors, other than just over-spending and income volatility. Prior literature suggests that the overall stability of the economy and level of welfare support for individuals from the structural environment contributes to consumers’ debt problems. In terms of cultural influence, the conspicuous consumption theory in consumer behaviour suggests that consumers would spend more than their means to be seen as similar profiles to consumers in a higher socio-economic class. This results in consumers taking on more debt than they can afford, and eventually becoming over-indebted. Studies have also shown that financial literacy is negatively related to consumer over-indebtedness risk. Whilst prior literature has examined structural and cultural influences respectively, no study has taken a collective approach. To address this gap, a model is developed to investigate the association between consumer over-indebtedness and proxies for influences from the structural and cultural environment based on the above theories. The model also controls for consumer demographic characteristics identified as being of influence in prior literature, such as gender and age, and adverse shocks, such as divorce or bereavement in the household. Benefiting from SOEP regional data, this study is able to conduct quantitative empirical analysis to test both structural and cultural influences at a localised level. Using German Socio-Economic Panel (SOEP) study data from 2006 to 2016, this study finds that social benefits, financial literacy and the existence of conspicuous consumption all contribute to being over-indebted. Generally speaking, the risk of becoming over-indebted is high when consumers are in a low-welfare community, have little awareness of their own financial situation and always over-spend. In order to tackle the problem of over-indebtedness, countermeasures can be taken, for example, increasing consumers’ financial awareness, and the level of welfare support. By analysing causes of consumer over-indebtedness in Germany, this study also provides new insights on the nature and underlying causes of consumer debt issues in Europe.

Keywords: consumer, debt, financial literacy, socio-economic

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Authors: Yang Yang, Dan Liu

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

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

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Authors: Karim Kheloufi, El Hachemi Amara

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

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

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Authors: Probir Kumar Banerjee

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

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

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

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

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

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

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

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

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Authors: Hamid Ahmadi, Neda Azari-Dodaran

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A total of 270 nonlinear steady-state finite element (FE) analyses were performed on 54 FE models of two-planar circular hollow section (CHS) KK-joints subjected to axial loading at five different temperatures (20 ºC, 200 ºC, 400 ºC, 550 ºC, and 700 ºC). The primary goal was to investigate the effects of temperature and geometrical characteristics on the ultimate strength, modes of failure, and initial stiffness of the KK-joints. Results indicated that on an average basis, the ultimate load of a two-planar tubular KK-joint at 200 ºC, 400 ºC, 550 ºC, and 700 ºC is 90%, 75%, 45%, and 16% of the joint’s ultimate load at ambient temperature, respectively. Outcomes of the parametric study showed that replacing the yield stress at ambient temperature with the corresponding value at elevated temperature to apply the EN 1993-1-8 equations for the calculation of the joint’s ultimate load at elevated temperatures may lead to highly unconservative results that might endanger the safety of the structure. Results of the parametric study were then used to develop a set of design formulas, through nonlinear regression analyses, to calculate the ultimate load of two-planar tubular KK-joints subjected to axial loading at elevated temperatures.

Keywords: ultimate load, two-planar tubular KK-joint, axial loading, elevated temperature, parametric equation

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Authors: Chongyang Ye, Rong Liu

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

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

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Authors: Nighat Bibi

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The differential diagnosis of brain diseases by magnetic resonance imaging (MRI) is a crucial step in the diagnostic process, and deep learning (DL) has the potential to significantly improve the accuracy and efficiency of these diagnoses. This study focuses on creating an ensemble learning (EL) model that utilizes the ResNet50, DenseNet121, and EfficientNetB1 architectures to concurrently and accurately classify various brain conditions from MRI images. The proposed ensemble learning model identifies a range of brain disorders that encompass different types of brain tumors, as well as multiple sclerosis. The proposed model was trained on two open-source datasets, consisting of MRI images of glioma, meningioma, pituitary tumors, and multiple sclerosis. Central to this research is the integration of gradient-weighted class activation mapping (Grad-CAM) for model interpretability, aligning with the growing emphasis on explainable AI (XAI) in medical imaging. The application of Grad-CAM improves the transparency of the model's decision-making process, which is vital for clinical acceptance and trust in AI-assisted diagnostic tools. The EL model achieved an impressive 99.84% accuracy in classifying these various brain conditions, demonstrating its potential as a versatile and effective tool for differential diagnosis in neuroimaging. The model’s ability to distinguish between multiple brain diseases underscores its significant potential in the field of medical imaging. Additionally, Grad-CAM visualizations provide deeper insights into the neural network’s reasoning, contributing to a more transparent and interpretable AI-driven diagnostic process in neuroimaging.

Keywords: brain tumour, differential diagnosis, ensemble learning, explainability, grad-cam, multiple sclerosis

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

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

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

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

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

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

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Authors: Sajjad Baghernezhad

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Meta-heuristic and hybrid algorithms have high adeer in modeling medical problems. In this study, a neural network was used to predict covid-19 among high-risk and low-risk patients. This study was conducted to collect the applied method and its target population consisting of 550 high-risk and low-risk patients from the Kerman University of medical sciences medical center to predict the coronavirus. In this study, the memetic algorithm, which is a combination of a genetic algorithm and a local search algorithm, has been used to update the weights of the neural network and develop the accuracy of the neural network. The initial study showed that the accuracy of the neural network was 88%. After updating the weights, the memetic algorithm increased by 93%. For the proposed model, sensitivity, specificity, positive predictivity value, value/accuracy to 97.4, 92.3, 95.8, 96.2, and 0.918, respectively; for the genetic algorithm model, 87.05, 9.20 7, 89.45, 97.30 and 0.967 and for logistic regression model were 87.40, 95.20, 93.79, 0.87 and 0.916. Based on the findings of this study, neural network models have a lower error rate in the diagnosis of patients based on individual variables and vital signs compared to the regression model. The findings of this study can help planners and health care providers in signing programs and early diagnosis of COVID-19 or Corona.

Keywords: COVID-19, decision support technique, neural network, genetic algorithm, memetic algorithm

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Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

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In this paper, altera de1-SoC FPGA board technology is utilized as a distinguished tool for nondestructive characterization of an aluminum circular cylindrical shell of radius ratio b/a (a: outer radius; b: inner radius). The acoustic backscattered signal processing system has been developed using OpenMP architecture. The design is built in three blocks; it is implemented per functional block, in a heterogeneous Intel-Altera system running under Linux. The useful data to determine the performances of SoC FPGA is computed by the analytical method. The exploitation of SoC FPGA has lead to obtain the backscattering form function and resonance spectra. A0 and S0 modes of propagation in the tube are shown. The findings are then compared to those achieved from the Matlab simulation of analytical method. A good agreement has, therefore, been noted. Moreover, the detailed SoC FPGA-based system has shown that acoustic spectra are performed at up to 5 times faster than the Matlab implementation using almost the same data. This FPGA-based system implementation of processing algorithms is realized with a coefficient of correlation R and absolute error respectively about 0.962 and 5 10⁻⁵.

Keywords: OpenMP, signal processing system, acoustic backscattering, nondestructive characterization, thin tubes

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Authors: Rumeysa Terzioglu

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Social entrepreneurship is not only a new concept but also an engaging factor of development that utilizes opportunities in economic and social areas for women. Social entrepreneurs have experience in determining and solving social problems with community participation. Social entrepreneurship is a consequence of individual social and economic initiatives contributing to women’s social and economic development against poverty. Women’s empowerment is an essential point for development. Türkiye has been developing an alternative empowerment model for women affected by the national development plan. Social entrepreneurship is an alternative model of social and economic empowerment of women’s status in Türkiye.

Keywords: social entrepreneurship, women, women empowerment, development

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Authors: Zhuang Guo

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In the field of GaN-based resonant tunneling diodes (RTDs) simulations, the traditional Tsu-Esaki formalism failed to predict the values of peak currents and peak voltages in the simulated current-voltage(J-V) characteristics. The main reason is that due to the strong internal polarization fields, two-dimensional electron gas(2DEG) accumulates at emitters, resulting in 2D-2D resonant tunneling currents, which become the dominant parts of the total J-V characteristics. By comparison, based on the 3D-2D resonant tunneling mechanism, the traditional Tsu-Esaki formalism cannot predict the J-V characteristics correctly. To overcome this shortcoming, we develop a new analytical model for the 2D-2D resonant tunneling currents generated in GaN-based RTDs. Compared with Tsu-Esaki formalism, the new model has made the following modifications: Firstly, considering the Heisenberg uncertainty, the new model corrects the expression of the density of states around the 2DEG eigenenergy levels at emitters so that it could predict the half width at half-maximum(HWHM) of resonant tunneling currents; Secondly, taking into account the effect of bias on wave vectors on the collectors, the new model modifies the expression of the transmission coefficients which could help to get the values of peak currents closer to the experiment data compared with Tsu-Esaki formalism. The new analytical model successfully predicts the J-V characteristics of GaN-based RTDs, and it also reveals more detailed mechanisms of resonant tunneling happened in GaN-based RTDs, which helps to design and fabricate high-performance GaN RTDs.

Keywords: GaN-based resonant tunneling diodes, tsu-esaki formalism, 2D-2D resonant tunneling, heisenberg uncertainty

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Authors: Hyun Joon Chang, Jae In Kim, Sungsoo Na

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Kinesin-1 (hereafter called kinesin) is a molecular motor protein that moves cargos toward the end of microtubules using the energy of adenosine triphosphate (ATP) hydrolysis. When kinesin is inactive, its tail autoinhibits the motor chain in order to prevent from reacting with the ATP by cross-linking of the tail domain to the motor domains at two positions. However, the morphological study of kinesin during autoinhibition is yet remained obscured. In this study, we report the effect of the binding site of the tail domain using the normal mode analysis of the elastic network model on kinesin in the tail-free form and tail-bind form. Considering the relationship between the connectivity of conventional network model with respect to the cutoff length and the functionality of the binding site of the tail, we revaluated the network model to observe the key role of the tail domain in its structural aspect. Contingent on the existence of the tail domain, the results suggest the morphological stability of the motor domain. Furthermore, employing the results from normal mode analysis, we have determined the strain energy of the neck linker, an essential portion of the motor domain for ATP hydrolysis. The results of the neck linker also converge to the same indication, i.e. the morphological analysis of the motor domain.

Keywords: elastic network model, Kinesin-1, autoinhibition

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Authors: Slim Amami

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A model is developed to prevent the risks related to climate conditions in the agricultural sector. It will determine the yearly optimum premium to be paid by a farmer in order to reach his required turnover. The model is mainly based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, main ones of which are daily average sunlight, rainfall and temperature. By a simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is deduced from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. Optimal premium is then deduced, and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect their harvest. The application to wheat production in the French Oise department illustrates the reliability of the present model with as low as 6% difference between predicted and real data. The model can be adapted to almost every agricultural field by changing state parameters and calibrating their associated coefficients.

Keywords: agriculture, database, meteorological factors, production model, optimal price

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Authors: Lailial Muhtifah, Sirtul Marhamah

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This article forwards the conceptual framework of continuous academic lecturer model in Islamic higher education (IHE). It is intended to make a contribution to the broader issue of how the concept of excellence can promote adherence to standards in higher education and drive quality enhancement. This model reveals a process and steps to increase performance and achievement of excellence regular lecturer gradually. Studies in this model are very significant to realize excellence academic culture in IHE. Several steps were identified from previous studies through literature study and empirical findings. A qualitative study was conducted at institute. Administrators and lecturers were interviewed, and lecturers learning communities observed to explore institute culture policies, and procedures. The original in this study presents and called Continuous Academic Lecturer Model (CALM) with its components, namely Standard, Quality, and Excellent as the basis for this framework (SQE). Innovation Excellence Framework requires Leaders to Support (LS) lecturers to achieve a excellence culture. So, the model named CALM-SQE+LS. Several components of performance and achievement of CALM-SQE+LS Model should be disseminated and cultivated to all lecturers in university excellence in terms of innovation. The purpose of this article is to define the concept of “CALM-SQE+LS”. Originally, there were three components in the Continuous Academic Lecturer Model i.e. standard, quality, and excellence plus leader support. This study is important to the community as specific cases that may inform educational leaders on mechanisms that may be leveraged to ensure successful implementation of policies and procedures outline of CALM with its components (SQE+LS) in institutional culture and professional leader literature. The findings of this study learn how continuous academic lecturer is part of a group's culture, how it benefits in university. This article blends the available criteria into several sub-component to give new insights towards empowering lecturer the innovation excellence at the IHE. The proposed conceptual framework is also presented.

Keywords: continuous academic lecturer model, excellence, quality, standard

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Authors: Oktofa Y. Sudrajad, Didier V. Caillie

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Association of Southeast Asian Countries Nations (ASEAN) is moving forward to the next level of regional integration by the initiation of ASEAN Economic Community (AEC) which is already started in 2015, 8 years after its declaration for the creation of AEC in 2007. This commitment imposes financial integration in the region is one of the main agenda which will be achieved until 2025. Therefore, the commitment to financial integration including banking integration will bring new landscape in the competition and business model in this region. This study investigates the effect of competition on bank business model using a sample of 324 banks from seven members of Association of Southeast Asian Nations (ASEAN) countries (Cambodia, Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam). We use market power approach and Boone indicator as competition measures, while income diversification and bank funding strategies are employed as bank business model representation. Moreover, we also evaluate bank business model based by grouping the banks based on the main banking characteristics. We use unbalanced bank-specific annual panel data over the period of 2003 – 2015. Our empirical analysis shows that the banking industries in ASEAN countries adapt their business model by increasing non-interest income proportion due to the level of competition increase in the sector.

Keywords: bank business model, banking competition, Boone indicator, market power

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Authors: Martín Pratto Burgos

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The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

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Authors: Victoria Goodall, Paul Fatti, Norman Owen-Smith

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Hidden Markov Models have become popular for the analysis of animal tracking data. These models are being used to model the movements of a variety of species in many areas around the world. A common assumption of the model is that the observations need to have regular time steps. In many ecological studies, this will not be the case. The objective of the research is to modify the movement model to allow for irregularly spaced locations and investigate the effect on the inferences which can be made about the latent states. A modification of the likelihood function to allow for these irregular spaced locations is investigated, without using interpolation or averaging the movement rate. The suitability of the modification is investigated using GPS tracking data for lion (Panthera leo) in South Africa, with many observations obtained during the night, and few observations during the day. Many nocturnal predator tracking studies are set up in this way, to obtain many locations at night when the animal is most active and is difficult to observe. Few observations are obtained during the day, when the animal is expected to rest and is potentially easier to observe. Modifying the likelihood function allows the popular Hidden Markov Model framework to be used to model these irregular spaced locations, making use of all the observed data.

Keywords: hidden Markov Models, irregular observations, animal movement modelling, nocturnal predator

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Authors: Justyna P. Majewska, Szymon M. Truskolaski

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The growing importance of digitalized services in the so-called new economy, including the e-sports industry, can be observed recently. Various demographic or technological changes lead consumers to modify their needs, not regarding the services themselves but the method of their application (attracting customers, forms of payment, new content, etc.). In the case of leisure-related to competitive spectating activities, there is a growing need to participate in events whose content is not sports competitions but computer games challenge – e-sport. The literature in this area so far focuses on determining the number of e-sport fans with elements of a simple statistical description (mainly concerning demographic characteristics such as age, gender, place of residence). Meanwhile, the development of the industry is influenced by a combination of many different, intertwined demographic, personality and psychosocial characteristics of customers, as well as the characteristics of their environment. Therefore, there is a need for a deeper recognition of the determinants of the behavioral patterns upon selecting digitalized services by customers, which, in the absence of available large data sets, can be achieved by using econometric simulations – multi-agent modeling. The cognitive aim of the study is to reveal internal and external determinants of behavioral patterns of customers taking into account various variants of economic development (the pace of digitization and technological development, socio-demographic changes, etc.). In the paper, an agent-based model with heterogeneous agents (characteristics of customers themselves and their environment) was developed, which allowed identifying a three-stage development scenario: i) initial interest, ii) standardization, and iii) full professionalization. The probabilities regarding the transition process were estimated using the Method of Simulated Moments. The estimation of the agent-based model parameters and sensitivity analysis reveals crucial factors that have driven a rising trend in e-sport spectating and, in a wider perspective, the development of digitalized services. Among the psychosocial characteristics of customers, they are the level of familiarization with the rules of games as well as sports disciplines, active and passive participation history and individual perception of challenging activities. Environmental factors include general reception of games, number and level of recognition of community builders and the level of technological development of streaming as well as community building platforms. However, the crucial factor underlying the good predictive power of the model is the level of professionalization. While in the initial interest phase, the entry barriers for new customers are high. They decrease during the phase of standardization and increase again in the phase of full professionalization when new customers perceive participation history inaccessible. In this case, they are prone to switch to new methods of service application – in the case of e-sport vs. sports to new content and more modern methods of its delivery. In a wider context, the findings in the paper support the idea of a life cycle of services regarding methods of their application from “traditional” to digitalized.

Keywords: agent-based modeling, digitalized services, e-sport, spectators motives

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Authors: Bita Mashayekhi, Azadeh Maddahi, Arash Tahriri

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The purpose of this paper is developing a model for audit quality, with regard to the contextual and environmental attributes of the audit profession in Iran. For this purpose, using an exploratory approach, and because of the special attributes of the auditing profession in Iran in terms of the legal environment, regulatory and supervisory mechanisms, audit firms size, and etc., we used grounded theory approach as a qualitative research method. Therefore, we got the opinions of the experts in the auditing and capital market areas through unstructured interviews. As a result, the authors revealed the determinants of audit quality, and by using these determinants, developed an Integrated Audit Quality Model, including causal conditions, intervening conditions, context, as well as action strategies related to AQ and their consequences. In this research, audit quality is studied using a systemic approach. According to this approach, the quality of inputs, processes, and outputs of auditing determines the quality of auditing, therefore, the quality of all different parts of this system is considered.

Keywords: audit quality, integrated audit quality model, demand for audit service, supply of audit, grounded theory

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Authors: Aedah Abd Rahman

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Software organisations may implement single or multiple frameworks in order to remain competitive. There are wide selection of generic Software Process Improvement (SPI) frameworks, best practices and standards implemented with different focuses and goals. Issues and difficulties emerge in the SPI practices from the context of software development and IT Service Management (ITSM). This research looks into the integration of multiple frameworks from the perspective of software development and ITSM. The research question of this study is how to define steps of methodology to solve the multi model software process improvement problem. The objective of this study is to define the research approach and methodologies to produce a more integrated and efficient Multi Model Process Improvement (MMPI) solution. A multi-step methodology is used which contains the case study, framework mapping and Delphi study. The research outcome has proven the usefulness and appropriateness of the proposed framework in SPI and quality practice in Malaysian software industries. This mixed method research approach is used to tackle problems from every angle in the context of software development and services. This methodology is used to facilitate the implementation and management of multi model environment of SPI frameworks in multiple domains.

Keywords: Delphi study, methodology, multi model software process improvement, service management

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Authors: Ahmad Khoirul Umam

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This paper investigates the role of vested interests and its impacts on anti-corruption agenda in Indonesia following the collapse of authoritarian regime in 1998. A pervasive and rampant corruption has been believed as the main cause of the state economy’s fragility. Hence, anti-corruption measures were implemented by applying democratization and market liberalization since the establishment of a consolidated democracy which go hand in hand with a liberal market economy is convinced to be an efficacious prescription for effective anti-corruption. The reform movement has also mandated the establishment of the independent, neutral and professional special anti-corruption agency namely Corruption Eradication Commission (KPK) to more intensify the fight against the systemic corruption. This paper will examine whether these anti-corruption measures have been effective to combat corruption, and investigate to what extend have the anti-corruption efforts, especially those conducted by KPK, been impeded by the emergence of a nexus of vested interests as the side-effect of democratization and market liberalization. Based on interviews with key stakeholders from KPK, other law enforcement agencies, government, prominent scholars, journalists and NGOs in Indonesia, it is found that since the overthrow of Soeharto, anti-corruption movement in the country have become more active and serious. After gradually winning the hearth of people, KPK successfully touched the untouchable corruption perpetrators who were previously protected by political immunity, legal protection and bureaucratic barriers. However, these changes have not necessarily reduced systemic and structural corruption practices. Ironically, intensive and devastating counterattacks were frequently posed by the alignment of business actors, elites of political parties, government, and also law enforcement agencies by hijacking state’s instruments to make KPK deflated, powerless, and surrender. This paper concludes that attempts of democratization, market liberalization and the establishment of anti-corruption agency may have helped Indonesia to reduce corruption. However, it is still difficult to imply that such anti-corruption measures have fostered the more effective anti-corruption works in the newly democratized and weakly regulated liberal economic system.

Keywords: vested interests, democratization, market liberalization, anti-corruption, Indonesia

Procedia PDF Downloads 231