Search results for: predictive modelling

Authors: Seyedehfatemeh Golrizgashti, Seyedali Dalil

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The goal of this paper is proposing a supply chain value dashboard in home appliance manufacturing firms to create more value for all stakeholders via balanced scorecard approach. Balanced scorecard is an effective approach that managers have used to evaluate supply chain performance in many fields but there is a lack of enough attention to all supply chain stakeholders, improving value creation and, defining correlation between value indicators and performance measuring quantitatively. In this research the key stakeholders in home appliance supply chain, value indicators with respect to create more value for stakeholders and the most important metrics to evaluate supply chain value performance based on balanced scorecard approach have been selected via literature review. The most important indicators based on expert’s judgment acquired by in survey focused on creating more value for. Structural equation modelling has been used to disclose relations between value indicators and balanced scorecard metrics. The important result of this research is identifying effective value dashboard to create more value for all stakeholders in the supply chain via balanced scorecard approach and based on an empirical study covering ten home appliance manufacturing firms in Iran. Home appliance manufacturing firms can increase their stakeholder's satisfaction by using this value dashboard.

Keywords: supply chain management, balanced scorecard, value, structural modeling, stakeholders

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Authors: Kimuli Ismail, Michael Lubwama, John Baptist Kirabira, Adam Sebbit

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This study develops 4 energy scenarios for Greater Kampala Metropolitan Area (GKMA). GKMA is Uganda’s capital with a population of 4.1million and a GDP growth rate of 5.8 with a nonsustainable energy management system. The study uses TIMES-VEDA to examine the energy impacts of business as usual (BAU), Kabejja, Carbon-Tax, and Lutta scenarios in commercial, industrial, transportation, residential, agricultural, and electricity generation activities. BAU is the baseline scenario with limited CO2 emissions restrictions against which Kabejja with 20% CO2 emissions restriction, a carbon tax of $100/ton imposed in 2050 for Carbon-Tax scenario, and Lutta with 95% CO2 emissions restriction is made. The analysis suggests that if the current policy trends continue as BAU, consumption would increase from 139.6PJ to 497.42PJ and CO2 emissions will increase from 4.6mtns to 7mtns. However, consumption would decrease by 2.3% in Kabejja, 3.4% in Carbon-Tax, and 3.3 % in Lutta compared to BAU. The CO2 emissions would decrease by 8.57% in Kabejja, 55.14% in Carbon-Tax, and 60% in Lutta compared to BAU. Sustainability is achievable when low-carbon electricity is increased by 53.68% in the EMS, and setting up an electrified Kampala metro. The study recommends Lutta as the sustainable pathway to a lowcarbon 2050.

Keywords: Sustainability, Scenario Plannnig, Times-Veda Modelling, Energy Policy Development

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Authors: M. Draman, S. Z. Muhamad Yassin, M. S. Alias, Z. Lambak, M. I. Zulkifli, S. N. Padhi, K. N. Baharim, F. Maskuriy, A. I. A. Rahim

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The performance of Malay automatic speech recognition (ASR) system for the call centre environment is presented. The system utilizes Kaldi toolkit as the platform to the entire library and algorithm used in performing the ASR task. The acoustic model implemented in this system uses a deep neural network (DNN) method to model the acoustic signal and the standard (n-gram) model for language modelling. With 80 hours of training data from the call centre recordings, the ASR system can achieve 72% of accuracy that corresponds to 28% of word error rate (WER). The testing was done using 20 hours of audio data. Despite the implementation of DNN, the system shows a low accuracy owing to the varieties of noises, accent and dialect that typically occurs in Malaysian call centre environment. This significant variation of speakers is reflected by the large standard deviation of the average word error rate (WERav) (i.e., ~ 10%). It is observed that the lowest WER (13.8%) was obtained from recording sample with a standard Malay dialect (central Malaysia) of native speaker as compared to 49% of the sample with the highest WER that contains conversation of the speaker that uses non-standard Malay dialect.

Keywords: conversational speech recognition, deep neural network, Malay language, speech recognition

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Authors: Abed Ahmed, Mehrdad Asadi, Jennifer Martay

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Stainless steel pipelines are crucial components to transportation and storage in the oil and gas industry. However, the rise of random attacks and vandalism on these pipes for their valuable transport has led to more security and protection for incoming surface impacts. These surface impacts can lead to large global deformations of the pipe and place the pipe under strain, causing the eventual failure of the pipeline. Therefore, understanding how these surface impact loads affect the pipes is vital to improving the pipes’ security and protection. In this study, experimental test and finite element analysis (FEA) have been carried out on EN3B stainless steel specimens to study the impact behaviour. Low velocity impact tests at 9 m/s with 16 kg dome impactor was used to simulate for high momentum impact for localised failure. FEA models of clamped and deformable boundaries were modelled to study the effect of the boundaries on the pipes impact behaviour on its impact resistance, using experimental and FEA approach. Comparison of experimental and FE simulation shows good correlation to the deformable boundaries in order to validate the robustness of the FE model to be implemented in pipe models with complex anisotropic structure.

Keywords: dynamic impact, deformable boundary conditions, finite element modelling, LS-DYNA, stainless steel pipe

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Authors: Sonda Jallouli, Sameh Ghroubi, Salma Sakka, Abdelmoneem Yahia, Mohamed Habib Elleuch, Imen Ben Dhia, Chokri Mhiri, Omar Hammouda

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The pathophysiology, prevalence, and progression of MS are gender dependent. Indeed, the inflammation is more pronounced in women, but the neurodegeneration is more important in men. In addition, women have more sleep disorders while men suffer more from cognitive decline. These non-physical disorders can negatively affect postural balance and fall risk. However, no study has examined the difference between men and women in those physical parameters in MS. Our objective was to determine the effect gender difference on postural balance and fall risk in MS persons. Methods: Eight men and twelve women with relapsing remitting-MS participated in this study. The assessment includes a posturographic examination to assess static (with eyes opened (EO) and eyes closed (EC)) and dynamic (with EO) postural balance. Unipedal balance and fall risk were assessed by a clinical unipedal balance test and the Four Square Step Test, respectively. Sleep quality was assessed using Spiegel's questionnaire, and cognitive assessment was performed using the Montreal Cognitive Assessment (MoCA) and the Simple Reaction Time Test. Results: Compared to men, women showed an increase in CdPVm in static bipedal condition with EC (p=0.037; d=0.71) and a decrease in MoCA scores (p=0.028; d=1.06). No gender differences were found in the other tests. Discussion: Static postural balance was more impaired in women compared to men. This result could be explained by the more pronounced cognitive decline observed in women compared to men. Indeed, cognitive disorders have been shown to be predictive factors of postural balance impairment. Conclusion: women were less stable than men in the static condition, possibly due to their lower cognitive performance. This gender difference could be taken into account by therapists in training programs.

Keywords: multiple sclerosis, bipedal postural balance, fall risk, sleep disturbance, cognitive deficiency

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Authors: Aliana Leong, T. C. Huan

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The purpose of Nostalgic themed tourism product is becoming popular in many countries. This study intends to investigate the role of nostalgia in destination image, experiential value and their effect on subsequent behavioral intention. The survey used stratified sampling method to include respondents from all the nearby Asian regions. The sampling is based on the data of inbound tourists provided by the Statistics and Census Service (DSEC) of government of Macau. The questionnaire consisted of five sections of 5 point Likert scale questions: (1) nostalgia, (2) destination image both before and after experience, (3) expected value, (4) experiential value, and (5) future visit intention. Data was analysed with structural equation modelling. The result indicates that nostalgia plays an important part in forming destination image and experiential value before individual had a chance to experience the destination. The destination image and experiential value share a bidirectional causal relationship that eventually contributes to future visit intention. The study also discovered that while experiential value is more effective in generating destination image, the later contribute more to future visit intention. The research design measures destination image and experiential value before and after respondents had experience the destination. The distinction between destination image and expected/experiential value can be examined because the longitudinal design of research method. It also allows this study to observe how nostalgia translates to future visit intention.

Keywords: nostalgia, destination image, experiential value, future visit intention

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Authors: Shazia Anwer Bukhari, Madiha Javeed Ghani, Muhammad Ibrahim Rajoka

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Objective: Biochemical, environmental, physical and genetic factors have a strong effect on the development of coronary disease (CAD). Plasma homocysteine (Hcy) level and DNA damage play a pivotal role in its development and progression. The aim of this study was to investigate the predictive strength of an oxidative stress, clinical biomarkers and total antioxidant status (TAS) in CAD patients to find the correlation of homocysteine, TOS and oxidative DNA damage with other clinical parameters. Methods: Sixty confirmed patients with CAD and 60 healthy individuals as control were included in this study. Different clinical and laboratory parameters were studied in blood samples obtained from patients and control subjects using commercially available biochemical kits and statistical software Results: As compared to healthy individuals, CAD patients had significantly higher concentrations of indices of oxidative stress: homocysteine (P=0.0001), total oxidative stress (TOS) (P=0.0001), serum cholesterol (P=0.04), low density lipoprotein cholesterol (LDL) (P=0.01), high density lipoprotein-cholesterol (HDL) (P=0.0001), and malondialdehyde (MDA) (P=0.001) than those of healthy individuals. Plasma homocysteine level and oxidative DNA damage were positively correlated with cholesterol, triglycerides, systolic blood pressure, urea, total protein and albumin (P values= 0.05). Both Hcy and oxidative DNA damage were negatively correlated with TAS and proteins. Conclusion: Coronary artery disease patients had a significant increase in homocysteine level and DNA damage due to increased oxidative stress. In conclusion, our study shows a significantly increase in lipid peroxidation, TOS, homocysteine and DNA damage in the erythrocytes of patients with CAD. A significant decrease level of HDL-C and TAS was observed only in CAD patients. Therefore these biomarkers may be useful diagnosis of patients with CAD and play an important role in the pathogenesis of CAD.

Keywords: antioxidants, coronary artery disease, DNA damage, homocysteine, oxidative stress, malondialdehyde, 8-Hydroxy-2’deoxyguanosine

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Authors: Jane N. O'Sullivan

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Although it is widely believed that fertility decline has benefitted economic advancement, particularly in East and South-East Asian countries, the causal mechanisms for this stimulus are contested. Since the turn of this century, demographic dividend theory has been increasingly recognised, hypothesising that higher proportions of working-age people can contribute to economic expansion if conditions are met to employ them productively. Population growth rate, as a systemic condition distinct from age composition, has not been similar attention since the 1970s and has lacked methodology for quantitative assessment. This paper explores conceptual and empirical quantification of the burden of expanding physical capital to accommodate a growing population. In proof-of-concept analyses of Australia and the United Kingdom, actual expenditure on gross fixed capital formation was compiled over four decades and apportioned to maintenance/turnover or expansion to accommodate population growth, based on lifespan of capital assets and population growth rate. In both countries, capital expansion was estimated to cost 6.5-7.0% of GDP per 1% population growth rate. This opportunity cost impedes the improvement of per capita capacity needed to realise the potential of the working-age population. Economic modelling of demographic scenarios have to date omitted this channel of influence; the implications of its inclusion are discussed.

Keywords: age dependency, demographic dividend, infrastructure, population growth rate

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Authors: Anton Golubkov, Gleb Ermachkov, Aleksandr Smerdin, Oleg Sidorov, Victor Philippov

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Current collection quality is one of the limiting factors when increasing trains movement speed in the rail sector. With the movement speed growth, the impact forces on the current collector from the rolling stock and the aerodynamic influence increase, which leads to the spread in the contact pressure values, separation of the current collector head from the contact wire, contact arcing and excessive wear of the contact elements. The upcoming trend in resolving this issue is the use of the automatic control systems providing stabilization of the contact pressure value. The present paper considers the features of the contemporary automatic control systems of the current collector’s pressure; their major disadvantages have been stated. A scheme of current collector pressure automatic control has been proposed, distinguished by a proactive influence on undesirable effects. A mathematical model of contact strips wearing has been presented, obtained in accordance with the provisions of the central composition rotatable design program. The analysis of the obtained dependencies has been carried out. The procedures for determining the optimal current collector pressure on the contact wire and the pressure control principle in the pneumatic drive have been described.

Keywords: contact strip, current collector, high-speed running, program control, wear

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Authors: Mikiyas Adugna

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Effort estimation is among the activities carried out in software development processes. An accurate model of estimation leads to project success. The method of agile effort estimation is a complex task because of the dynamic nature of software development. Researchers are still conducting studies on agile effort estimation to enhance prediction accuracy. Due to these reasons, we investigated and proposed a model on LASSO and Elastic Net regression to enhance estimation accuracy. The proposed model has major components: preprocessing, train-test split, training with default parameters, and cross-validation. During the preprocessing phase, the entire dataset is normalized. After normalization, a train-test split is performed on the dataset, setting training at 80% and testing set to 20%. We chose two different phases for training the two algorithms (Elastic Net and LASSO) regression following the train-test-split. In the first phase, the two algorithms are trained using their default parameters and evaluated on the testing data. In the second phase, the grid search technique (the grid is used to search for tuning and select optimum parameters) and 5-fold cross-validation to get the final trained model. Finally, the final trained model is evaluated using the testing set. The experimental work is applied to the agile story point dataset of 21 software projects collected from six firms. The results show that both Elastic Net and LASSO regression outperformed the compared ones. Compared to the proposed algorithms, LASSO regression achieved better predictive performance and has acquired PRED (8%) and PRED (25%) results of 100.0, MMRE of 0.0491, MMER of 0.0551, MdMRE of 0.0593, MdMER of 0.063, and MSE of 0.0007. The result implies LASSO regression algorithm trained model is the most acceptable, and higher estimation performance exists in the literature.

Keywords: agile software development, effort estimation, elastic net regression, LASSO

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Authors: Ali A. Al-Jazaairry, Tahsin T. Sabbagh

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Presence of cavities in soil predictably induces ground deformation and changes in soil stress, which might influence adjacent existing pile foundations, though the effect of twin cavities on a nearby pile needs to be understood. This research is an attempt to identify the behaviour of piles subjected to axial load and embedded in cavitied clayey soil. A series of finite element modelling were conducted to investigate the performance of piled foundation located in such soils. The validity of the numerical simulation was evaluated by comparing it with available field test and alternative analytical model. The study involved many parameters such as twin cavities size, depth, spacing between cavities, and eccentricity of cavities from the pile axis on the pile performance subjected to axial load. The study involved many cases; in each case, a critical value has been found in which cavities’ presence has shown minimum impact on the behaviour of pile. Load-displacement relationships of the affecting parameters on the pile behaviour were presented to provide helpful information for designing piled foundation situated near twin underground cavities. It was concluded that the presence of the cavities within the soil mass reduces the ultimate capacity of pile. This reduction differs according to the size and location of the cavity.

Keywords: axial load, clay, finite element, pile, twin cavities, ultimate capacity

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Oday Al-Mamoori, J. Enrique Martinez-Rueda

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'C' shape yielding devices (C-devices) are effective tools for introducing supplemental sources of energy dissipation by hysteresis. Studies have shown that C-devices made of mild steel can be successfully applied as integral parts of seismic retrofitting schemes. However, explicit modelling of these devices can become cumbersome, expensive and time consuming. The device under study in this article has been previously used in non-invasive dissipative bracing for seismic retrofitting. The device is cut from a mild steel plate and has an overall shape that resembles that of a rectangular portal frame with circular interior corner transitions to avoid stress concentration and to control the extension of the dissipative region of the device. A number of inelastic finite element (FE) analyses using either inelastic 2D plane stress elements or inelastic fibre frame elements are reported and used to calibrate a 1D equivalent inelastic spring model that effectively reproduces the cyclic response of the device. The more elaborate FE model accounts for the frictional forces developed between the steel plate and the bolts used to connect the C-device to structural members. FE results also allow the visualization of the inelastic regions of the device where energy dissipation is expected to occur. FE analysis results are in a good agreement with experimental observations.

Keywords: C-device, equivalent nonlinear spring, FE analyses, reversed cyclic tests

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Authors: J. Sharon Mano Pappu, Sathyanarayana N. Gummadi

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Growth of Debaryomyces nepalensis on mixed substrates in batch culture follows diauxic pattern of completely utilizing glucose during the first exponential growth phase, followed by an intermediate lag phase and a second exponential growth phase consuming xylose. The present study deals with the development of cybernetic mathematical model for prediction of xylitol production and yield. Production of xylitol from xylose in batch fermentation is investigated in the presence of glucose as the co-substrate. Different ratios of glucose and xylose concentrations are assessed to study the impact of multi substrate on production of xylitol in batch reactors. The parameters in the model equations were estimated from experimental observations using integral method. The model equations were solved simultaneously by numerical technique using MATLAB. The developed cybernetic model of xylose fermentation in the presence of a co-substrate can provide answers about how the ratio of glucose to xylose influences the yield and rate of production of xylitol. This model is expected to accurately predict the growth of microorganism on mixed substrate, duration of intermediate lag phase, consumption of substrate, production of xylitol. The model developed based on cybernetic modelling framework can be helpful to simulate the dynamic competition between the metabolic pathways.

Keywords: co-substrate, cybernetic model, diauxic growth, xylose, xylitol

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Authors: Justyna Rybicka, Ashutosh Tiwari, Shane Enticott

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In the age of automation and computation aiding manufacturing, it is clear that manufacturing systems have become more complex than ever before. Although technological advances provide the capability to gain more value with fewer resources, sometimes utilisation of the manufacturing capabilities available to organisations is difficult to achieve. Flexible manufacturing systems (FMS) provide a unique capability to manufacturing organisations where there is a need for product range diversification by providing line efficiency through production flexibility. This is very valuable in trend driven production set-ups or niche volume production requirements. Although FMS provides flexible and efficient facilities, its optimal set-up is key in achieving production performance. As many variables are interlinked due to the flexibility provided by the FMS, analytical calculations are not always sufficient to predict the FMS’ performance. Simulation modelling is capable of capturing the complexity and constraints associated with FMS. This paper demonstrates how discrete event simulation (DES) can address complexity in an FMS to optimise the production line performance. A case study of an automotive FMS is presented. The DES model demonstrates different configuration options depending on prioritising objectives: utilisation and throughput. Additionally, this paper provides insight into understanding the impact of system set-up constraints on the FMS performance and demonstrates the exploration into the optimal production set-up.

Keywords: discrete event simulation, flexible manufacturing system, capacity performance, automotive

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Authors: Ryo Shikimoto, Hidehito Niimura, Hisashi Kida, Kota Suzuki, Yukiko Miyasaka, Masaru Mimura

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Introduction: In Japan, the most aged country in the world, it is important to explore predictive factors of cognitive function among the elderly. Coping behavior relieves chronic stress and improves lifestyle, and consequently may reduce the risk of cognitive impairment. One of the most widely investigated frameworks evaluated in previous studies is approach-oriented and avoidance-oriented coping strategies. The purpose of this study is to investigate the relationship between cognitive function and coping strategies among elderly residents in urban areas of Japan. Method: This is a part of the cross-sectional Arakawa geriatric cohort study for 1,099 residents (aged 65 to 86 years; mean [SD] = 72.9 [5.2]). Participants were assessed for cognitive function using the Mini-Mental State Examination (MMSE) and diagnosed by psychiatrists in face-to-face interviews. They were then investigated for their each coping behaviors and coping strategies (approach- and avoidance-oriented coping) using stress and coping inventory. A multiple regression analysis was used to investigate the relationship between MMSE score and each coping strategy. Results: Of the 1,099 patients, the mean MMSE score of the study participants was 27.2 (SD = 2.7), and the numbers of the diagnosis of normal, mild cognitive impairment (MCI), and dementia were 815 (74.2%), 248 (22.6%), and 14 (1.3%), respectively. Approach-oriented coping score was significantly associated with MMSE score (B [partial regression coefficient] = 0.12, 95% confidence interval = 0.05 to 0.19) after adjusting for confounding factors including age, sex, and education. Avoidance-oriented coping did not show a significant association with MMSE score (B [partial regression coefficient] = -0.02, 95% confidence interval = -0.09 to 0.06). Conclusion: Approach-oriented coping was clearly associated with neurocognitive function in the Japanese population. A future longitudinal trial is warranted to investigate the protective effects of coping behavior on cognitive function.

Keywords: approach-oriented coping, cognitive impairment, coping behavior, dementia

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Authors: A. T. Kassem

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Fires areconsidered a common hazardous action that any building may face. Most buildings’ structural elements are designed, taking into consideration precautions for fire safety, using deterministic design approaches. Public and highly important buildings are commonly designed considering standard fire rating and, in many cases, contain large compartments with central domes. Real fire scenarios are not commonly brought into action in structural design of buildings because of complexities in both scenarios and analysis tools. This paper presents a modern approach towards analysis of spherical domes in real fire condition via implementation of building information modelling, and adopting a probabilistic approach. BIMhas been implemented to bridge the gap between various software packages enabling them to function interactively to model both real fire and corresponding structural response. Ventilation controlled fires scenarios have been modeled using both “Revit” and “Pyrosim”. Monte Carlo simulation has been adopted to engage the probabilistic analysis approach in dealing with various parameters. Conclusions regarding failure probability and fire endurance, in addition to the effects of various parameters, have been extracted.

Keywords: concrete, spherical domes, ventilation controlled fires, BIM, monte carlo simulation, pyrosim, revit

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Authors: Rasha Aljaryian, Lalit Kumar

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Climate is undergoing continuous change and this trend will affect the cultivation areas ofmost crops, including wheat (Triticum aestivum L.), in the future. The current suitable cultivation areas may become unsuitable climatically. Countries that depend on wheat cultivation and export may suffer an economic loss because of production decline. On the other hand, some regions of the world could gain economically by increasing cultivation areas. This study models the potential future climatic suitability of wheat by using CLIMEX software. Two different global climate models (GCMs) were used, CSIRO-Mk3.0 (CS) and MIROC-H (MR), with two emission scenarios (A2, A1B). The results of this research indicate that the suitable climatic areas for wheat in the southern hemisphere, such as Australia, are expected to contract by the end of this century. However, some unsuitable or marginal areas will become climatically suitable under future climate scenarios. In North America and Europe further expansion inland could occur. Also, the results illustrate that heat and dry stresses as abiotic climatic factors will play an important role in wheat distribution in the future. Providing sufficient information about future wheat distribution will be useful for agricultural ministries and organizations to manage the shift in production areas in the future. They can minimize the expected harmful economic consequences by preparing strategic plans and identifying new areas for wheat cultivation.

Keywords: Climate change, Climate modelling, CLIMEX, Triticum aestivum, Wheat

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Authors: Omar Moafaq Saleh Aljanabi, Noradiva Hamzah, Ruhanita Maelah

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In today’s challenging global economy, which is driven by information and knowledge, risk management is undergoing a great change, as organizations shift from traditional and compartmental risk management to an enterprise-wide approach. Enterprise risk management (ERM), which aims at increasing the sustainability of an organization and achieving competitive advantage, is gaining global attention and fast becoming an essential concern in all industries. Furthermore, in order to be effective, ERM should be managed by managers with high-level skills and knowledge. Despite the importance of the knowledge embedded in, there remains a paucity of evidence concerning how human capital could influence the organization’s ERM. Responses from 116 public listed companies (PLCs) on the main market of Bursa Malaysia were analyzed using Structural Equation Modelling (SEM). This study found that there is a significant association between ERM and organizational performance. The results also indicate that human capital has a positive moderating effect on the relationship between ERM and performance. The study contributes to the ERM literature by providing empirical evidence on the relationship between ERM, human capital, and organizational performance. Findings from this study also provide guidelines for managers, policy makers, and the regulatory bodies, to evaluate the ERM practices in PLCs.

Keywords: enterprise risk management, human capital, organizational performance, Malaysian public listed companies

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Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

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In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

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Authors: Samson Mil'shtein, Dhawal N. Asthana

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The presented heterostructure n-p-n bipolar transistor is comprised of Ge/GaAs heterojunctions consisting of 0.15µm thick emitter and 0.65µm collector junctions. High diffusivity of carriers in GaAs base was major motivation of current design. We avoided grading of the base which is common in heterojunction bipolar transistors, in order to keep the electron diffusivity as high as possible. The electrons injected into the 0.25µm thick p-type GaAs base with not very high doping (1017cm-3). The designed HBT enables cut off frequency on the order of 150GHz. The Ge/GaAs heterojunctions presented in our paper have proved to work better than comparable HBTs having GaAs bases and emitter/collector junctions made, for example, of AlGaAs/GaAs or other III-V compound semiconductors. The difference in lattice constants between Ge and GaAs is less than 2%. Therefore, there is no need of transition layers between Ge emitter and GaAs base. Significant difference in energy gap of these two materials presents new scope for improving performance of the emitter. With the complete structure being modelled and simulated using TCAD SILVACO, the collector/ emitter offset voltage of the device has been limited to a reasonable value of 63 millivolts by the dint of low energy band gap value associated with Ge emitter. The efficiency of the emitter in our HBT is 86%. Use of Germanium in the emitter and collector regions presents new opportunities for integration of this vertical device structure into silicon substrate.

Keywords: Germanium, Gallium Arsenide, heterojunction bipolar transistor, high cut-off frequency

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Authors: L. Atif, C. Rosenthal-Sabroux, M. Grundstein

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The requirements engineering process is a crucial phase in the design of complex systems. The purpose of our research is to present a collaborative problem-driven requirements engineering approach that aims at improving the design of a Decision Support System as an Analytics application. This approach has been adopted to design a Human Resource management DSS. The Requirements Engineering process is presented as a series of guidelines for activities that must be implemented to assure that the final product satisfies end-users requirements and takes into account the limitations identified. For this, we know that a well-posed statement of the problem is “a problem whose crucial character arises from collectively produced estimation and a formulation found to be acceptable by all the parties”. Moreover, we know that DSSs were developed to help decision-makers solve their unstructured problems. So, we thus base our research off of the assumption that developing DSS, particularly for helping poorly structured or unstructured decisions, cannot be done without considering end-user decision problems, how to represent them collectively, decisions content, their meaning, and the decision-making process; thus, arise the field issues in a multidisciplinary perspective. Our approach addresses a problem-driven and collaborative approach to designing DSS technologies: It will reflect common end-user problems in the upstream design phase and in the downstream phase these problems will determine the design choices and potential technical solution. We will thus rely on a categorization of HR’s problems for a development mirroring the Analytics solution. This brings out a new data-driven DSS typology: Descriptive Analytics, Explicative or Diagnostic Analytics, Predictive Analytics, Prescriptive Analytics. In our research, identifying the problem takes place with design of the solution, so, we would have to resort a significant transformations of representations associated with the HR Analytics application to build an increasingly detailed representation of the goal to be achieved. Here, the collective cognition is reflected in the establishment of transfer functions of representations during the whole of the design process.

Keywords: DSS, collaborative design, problem-driven requirements, analytics application, HR decision making

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Authors: Mahdi Saadat, Abbas Taheri

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Understanding the cracking response of crystalline rocks at mineralogical scale is of great importance during the design procedure of mining structures. A grain-based distinct element model (GBM) is employed to numerically study the cracking response of Barre granite at micro- and macro-scales. The GBM framework is augmented with a proposed distinct element-based cohesive model to reproduce the micro-cracking response of the inter- and intra-grain contacts. The cohesive GBM framework is implemented in PFC2D distinct element codes. The microstructural properties of Barre granite are imported in PFC2D to generate synthetic specimens. The microproperties of the model is calibrated against the laboratory uniaxial compressive and Brazilian split tensile tests. The calibrated model is then used to simulate the fracturing behaviour of pre-cracked Barre granite with different flaw configurations. The numerical results of the proposed model demonstrate a good agreement with the experimental counterparts. The GBM framework proposed thus appears promising for further investigation of the influence of grain microstructure and mineralogical properties on the cracking behaviour of crystalline rocks.

Keywords: discrete element modelling, cohesive grain-based model, crystalline rock, fracturing behavior

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Authors: Akaash Tawade, Manan Khattar, Lucas Spangher, Costas J. Spanos

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Many grids are increasing the share of renewable energy in their generation mix, which is causing the energy generation to become less controllable. Buildings, which consume nearly 33% of all energy, are a key target for demand response: i.e., mechanisms for demand to meet supply. Understanding the behavior of office workers is a start towards developing demand response for one sector of building technology. The literature notes that dynamic computational modeling can be predictive of individual action, especially given that occupant behavior is traditionally abstracted from demand forecasting. Recent work founded on Social Cognitive Theory (SCT) has provided a promising conceptual basis for modeling behavior, personal states, and environment using control theoretic principles. Here, an adapted linear dynamical system of latent states and exogenous inputs is proposed to simulate energy demand amongst office workers engaged in a social energy shifting game. The energy shifting competition is implemented in an office in Singapore that is connected to a minigrid of buildings with a consistent 'price signal.' This signal is translated into a 'points signal' by a reinforcement learning (RL) algorithm to influence participant energy use. The dynamic model functions at the intersection of the points signals, baseline energy consumption trends, and SCT behavioral inputs to simulate future outcomes. This study endeavors to analyze how the dynamic model trains an RL agent and, subsequently, the degree of accuracy to which load deferability can be simulated. The results offer a generalizable behavioral model for energy competitions that provides the framework for further research on transfer learning for RL, and more broadly— transactive control.

Keywords: energy demand forecasting, social cognitive behavioral modeling, social game, transfer learning

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Authors: Heba Kamal, Ghada Saudi

Abstract:

Due to The rapid expansion of energy and growing number of wind turbines construction in earthquake areas, a design method for simple and accurate evaluation of seismic load to ensure structural integrity is required. In Egypt, there are some appropriate places to build wind turbine towers lie in active seismically regions, so accurate analysis is necessary for prediction of seismic loads with consideration of intensity of the earthquake, soil and structural characteristics. In this research, seismic behavior of wind turbine towers Gamesa Type G52 in Zafarana Wind Farm Egypt is investigated using experimental work by ambient vibration test, and fully dynamic analysis based on time history from El Aqaba Earthquake 1995 using 3D by PLAXIS 3D software, including the soil structure interaction effect. The results obtained from dynamic analyses are discussed. From this study, it is concluded that, the fully dynamic seismic analysis based on used PLAXIS 3D with the aid of the full scale ambient vibration test gives almost good simulation for the seismic loads that can be applied to wind turbine tower design in Egypt.

Keywords: Wind turbine towers, Zafarana Wind Farm, Gamesa Type G52, ambient vibration test

Procedia PDF Downloads 205

Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Hans-Peter Piepho

Abstract:

We aim to model dynamics of wildlife or pastoral livestock population for understanding of their population change and hence for wildlife conservation and promoting human welfare. The study is motivated by an age-sex structured population counts in different regions of Serengeti-Mara during the period 1989-2003. Developing reliable and realistic models for population dynamics of large herbivore population can be a very complex and challenging exercise. However, the Bayesian statistical domain offers some flexible computational methods that enable the development and efficient implementation of complex population dynamics models. In this work, we have used a novel Bayesian state-space model to analyse the dynamics of topi and hartebeest populations in the Serengeti-Mara Ecosystem of East Africa. The state-space model involves survival probabilities of the animals which further depend on various factors like monthly rainfall, size of habitat, etc. that cause recent declines in numbers of the herbivore populations and potentially threaten their future population viability in the ecosystem. Our study shows that seasonal rainfall is the most important factors shaping the population size of animals and indicates the age-class which most severely affected by any change in weather conditions.

Keywords: bayesian state-space model, Markov Chain Monte Carlo, population dynamics, conservation

Procedia PDF Downloads 199

Authors: M. Ezkurra, J. A. Esnaola, M. Martinez-Agirre, U. Etxeberria, U. Lertxundi, L. Colomo, M. Begiristain, I. Zurutuza

Abstract:

Butterfly valves are widely used industrial piping components as on-off and flow controlling devices. The main challenge in the design process of this type of valves is the correct dimensioning to ensure proper mechanical performance as well as to minimise flow losses that affect the efficiency of the system. Butterfly valves are typically dimensioned in a closed position based on mechanical approaches considering uniform hydrostatic pressure, whereas the flow losses are analysed by means of CFD simulations. The main limitation of these approaches is that they do not consider either the influence of the dynamics of the manoeuvring stage or coupled phenomena. Recent works have included the influence of the flow on the mechanical behaviour for different opening angles by means of one-way FSI approach. However, these works consider steady-state flow for the selected angles, not capturing the effect of the transient flow evolution during the manoeuvring stage. Two-way FSI modelling approach could allow overcoming such limitations providing more accurate results. Nevertheless, the use of this technique is limited due to the increase in the computational cost. In the present work, the applicability of FSI one-way and two-way approaches is evaluated for the analysis of butterfly valves, showing that not considering fluid-structure coupling involves not capturing the most critical situation for the valve disc.

Keywords: butterfly valves, fluid-structure interaction, one-way approach, two-way approach

Procedia PDF Downloads 159

Authors: Natcha Laethongkham, Gayan Ramanayake, Philip Charlesworth, Leshan Uggalla

Abstract:

The throttling process in hybrid rocket engines (HREs) poses challenges due to inherent instability, impacting the engine’s reliability and robustness. Identifying and advancing existing technology is crucial to meet the demands of complex mission profiles required for next-generation launch vehicles. This paper reviews the current literature, focusing on oxidiser flow control for throttling purposes in HREs. Covered areas include oxidiser choices, commonly used throttle valves, and literature trends. Common oxidisers for throttling are hydrogen peroxide, nitrous oxide, and liquid oxygen. Two frequently chosen valves for throttling are the ball and variation pintle valves. The review identifies two primary research focuses: flow control valve studies and control system design. The current research stage is highlighted, and suggestions for future directions are proposed to advance thrust control systems in HREs. This includes further studies in existing research focuses and exploring new approaches such as system scheme design, numerical modelling, and applications.

Keywords: hybrid rocket engines, oxidiser flow control, thrust control, throttle valve, review

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Authors: Stephen Acheampong Amoafoh

Abstract:

In today's dynamic economic landscape, businesses face multifaceted challenges that demand strategic foresight and informed decision-making. This abstract explores the pivotal role of financial analytics in driving business performance amidst evolving market conditions. By integrating accounting principles with economic insights, organizations can harness the power of data-driven strategies to optimize resource allocation, mitigate risks, and capitalize on emerging opportunities. This presentation will delve into the practical applications of financial analytics across various sectors, highlighting case studies and empirical evidence to underscore its efficacy in enhancing operational efficiency and fostering sustainable growth. From predictive modeling to performance benchmarking, attendees will gain invaluable insights into leveraging advanced analytics tools to drive profitability, streamline processes, and adapt to changing market dynamics. Moreover, this abstract will address the ethical considerations inherent in financial analytics, emphasizing the importance of transparency, integrity, and accountability in data-driven decision-making. By fostering a culture of ethical conduct and responsible stewardship, organizations can build trust with stakeholders and safeguard their long-term viability in an increasingly interconnected global economy. Ultimately, this abstract aims to stimulate dialogue and collaboration among scholars, practitioners, and policymakers, fostering knowledge exchange and innovation in the realms of accounting, business, and economics. Through interdisciplinary insights and actionable recommendations, participants will be equipped to navigate the complexities of today's business environment and seize opportunities for sustainable success.

Keywords: financial analytics, business performance, data-driven strategies, sustainable growth

Procedia PDF Downloads 44

Authors: Golaleh Ghaffari

Abstract:

A basin sediment yield refers to the amount of sediment exported by a basin over a period of time, which will enter a reservoir located at the downstream limit of the basin. The Soil and Water Assessment Tool (SWAT, 2008) was used to hydrology and sediment transport modeling at daily and monthly time steps within the Gheshlagh dam basin in north-west of Iran. The SWAT model and Geographic Information System (GIS) techniques were applied to evaluate basin hydrology and sediment yield using historical flow and sediment data and to identify and prioritize critical sub-basins based on sediment transport. The results of this study indicated that simulated daily discharge and sediment values matched the observed values satisfactorily. The model predicted that mean annual basin precipitation for the total study period (413 mm) was partitioned in to evapotranspiration (36%), percolation/groundwater recharge (21%) and stream water (25%), yielding 18% surface runoff. Potential source areas of erosion were also identified with the model. The range of the annual contributing erosive zones varied spatially from 0.1 to 103 t/ha according to the slope and land use at the basin scale. Also the fifteen sub basins create the 60% of the total sediment yield between the all (102) sub basins. The results of the study indicated that SWAT can be a useful tool for assessing hydrology and sediment yield response of the watersheds in the region.

Keywords: erosion, Gheshlagh dam, sediment yield, SWAT

Procedia PDF Downloads 516