Search results for: agent based model

Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

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The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: acoustic model, direction of arrival, inverse source problem, sound localization, urban noises

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Authors: Aid Asma, Dahdouh Nadjib, Amokrane Samira, Ladjali Samir, Nibou Djamel

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The present work has for main objective the elimination of the textile dye Maxilon Red (MR) by two processes, adsorption on activated clay followed by photocatalysis in presence of ZnO as a photocatalyst. The influence of the physical parameters like the initial pH, adsorbent dose of the activated clay, the MR concentration and temperature has been studied. The best adsorption yield occurs at neutral pH ~ 7 within 60 min with an uptake percentage of 97% for a concentration of 25 mg L⁻¹ and a dose of 0.5 g L⁻¹. The adsorption data were suitably fitted by the Langmuir model with a maximum capacity of 176 mg g⁻¹. The MR adsorption is well described by the pseudo second order kinetic. The second part of this work was dedicated to the photocatalytic degradation onto ZnO under solar irradiation of the residual MR concentration, remained after adsorption. The effect of ZnO dose and MR concentration has also been investigated. The parametric study showed that the elimination is very effective by this process, based essentially on the in situ generation of free radicals *OH which are non-selective and very reactive. The photodegradation process follows a first order kinetic model according to the Langmuir-Hinshelwood model.

Keywords: maxilon red, adsorption, photodegradation, ZnO, coupling

Procedia PDF Downloads 192

Authors: Allyson Dale, Max Hlywa

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The Canadian public expects the highest moral standards from Canadian Armed Forces (CAF) members and Department of National Defence (DND) employees. The Chief, Professional Conduct and Culture (CPCC) stood up in April 2021 with the mission of ensuring that the defence culture and members’ conduct are aligned with the ethical principles and values that the organization aspires towards. The Defence Ethics Program (DEP), which stood up in 1997, is a values-based ethics program for individuals and organizations within the DND/CAF and now falls under CPCC. The DEP is divided into five key functional areas, including policy, communications, collaboration, training and education, and advice and guidance. The main focus of the DEP is to foster an ethical culture within defence so that members and organizations perform to the highest ethical standards. The measurement of organizational ethics is often complex and challenging. In order to monitor whether the DEP is achieving its intended outcomes, a performance measurement framework (PMF) was developed using the Director General Military Personnel Research and Analysis (DGMPRA) PMF development process. This evidence-based process is based on subject-matter expertise from the defence team. The goal of this presentation is to describe each stage of the DGMPRA PMF development process and to present and discuss the products of the DEP PMF (e.g., logic model). Specifically, first, a strategic framework was developed to provide a high-level overview of the strategic objectives, mission, and vision of the DEP. Next, Key Performance Questions were created based on the objectives in the strategic framework. A logic model detailing the activities, outputs (what is produced by the program activities), and intended outcomes of the program were developed to demonstrate how the program works. Finally, Key Performance Indicators were developed based on both the intended outcomes in the logic model and the Key Performance Questions in order to monitor program effectiveness. The Key Performance Indicators measure aspects of organizational ethics such as ethical conduct and decision-making, DEP collaborations, and knowledge and awareness of the Defence Ethics Code while leveraging ethics-related items from multiple DGMPRA surveys where appropriate.

Keywords: defence ethics, ethical culture, organizational performance, performance measurement framework

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Authors: K. B. Rajasekarababu, J. Karthik, G. Vinayagamurthy

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This paper is intended to explain the influence of major axis on aerodynamic characteristics of elliptical section. Many engineering applications such as off shore structures, bridge piers, civil structures and pipelines can be modelled as a circular cylinder but flow over complex bodies like, submarines, Elliptical wing, fuselage, missiles, and rotor blades, in which the parameters such as axis ratio can influence the flow characteristics of the wake and nature of separation. Influence of Major axis in Flow characteristics of elliptical sections are examined both experimentally and computationally in this study. For this research, four elliptical models with varying major axis [*AR=1, 4, 6, 10] are analysed. Experimental works have been conducted in a subsonic wind tunnel. Furthermore, flow characteristics on elliptical model are predicted from k-ε turbulence model using the commercial CFD packages by pressure based transient solver with Standard wall conditions.The analysis can be extended to estimation and comparison of Drag coefficient and Fatigue analysis of elliptical sections.

Keywords: elliptical section, major axis, aerodynamic characteristics, k-ε turbulence model

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Authors: Yifu Ding, Vijay Avinash, Malcolm McCulloch

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As the proliferation of decentralized energy systems, the UK power system allows small-scale entities such as microgrids (MGs) to tender multiple energy services including energy arbitrage and frequency responses (FRs). However, its operation requires the balance between the uncertain renewable generations and loads in real-time and has to fulfill their provision requirements of contract services continuously during the time window agreed, otherwise it will be penalized for the under-delivered provision. To hedge against risks due to uncertainties and maximize the economic benefits, we propose a stochastic model predictive control (SMPC) framework to optimize its operation for the multi-service provision. Distinguished from previous works, we include a detailed economic-degradation model of the lithium-ion battery to quantify the costs of different service provisions, as well as accurately describe the changing dynamics of the battery. Considering a branch of load and generation scenarios and the battery aging, we formulate a risk-averse cost function using conditional value at risk (CVaR). It aims to achieve the maximum expected net revenue and avoids severe losses. The framework will be performed on a case study of a PV-battery grid-tied microgrid in the UK with real-life data. To highlight its performance, the framework will be compared with the case without the degradation model and the deterministic formulation.

Keywords: model predictive control (MPC), battery degradation, frequency response, microgrids

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Authors: Shinji Ukita, Naohiro Nakamura, Yuji Miyazu

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In considering the dynamic characteristics of structure, natural frequency and damping ratio are useful indicator. When performing dynamic design, it's necessary to select an appropriate initial damping model and hysteretic model. In the linear region, the setting of initial damping model influences the response, and in the nonlinear region, the combination of initial damping model and hysteretic model influences the response. However, the dynamic characteristics of structure in the nonlinear region remain unclear. In this paper, we studied the effect of setting of initial damping model and hysteretic model on the dynamic characteristics of structure. On initial damping model setting, Initial stiffness proportional, Tangent stiffness proportional, and Rayleigh-type were used. On hysteretic model setting, TAKEDA model and Normal-trilinear model were used. As a study method, dynamic analysis was performed using a lumped mass model of base-fixed. During analysis, the maximum acceleration of input earthquake motion was gradually increased from 1 to 600 gal. The dynamic characteristics were calculated using the ARX model. Then, the characteristics of 1st and 2nd natural frequency and 1st damping ratio were evaluated. Input earthquake motion was simulated wave that the Building Center of Japan has published. On the building model, an RC building with 30×30m planes on each floor was assumed. The story height was 3m and the maximum height was 18m. Unit weight for each floor was 1.0t/m2. The building natural period was set to 0.36sec, and the initial stiffness of each floor was calculated by assuming the 1st mode to be an inverted triangle. First, we investigated the difference of the dynamic characteristics depending on the difference of initial damping model setting. With the increase in the maximum acceleration of the input earthquake motions, the 1st and 2nd natural frequency decreased, and the 1st damping ratio increased. Then, in the natural frequency, the difference due to initial damping model setting was small, but in the damping ratio, a significant difference was observed (Initial stiffness proportional≒Rayleigh type>Tangent stiffness proportional). The acceleration and the displacement of the earthquake response were largest in the tangent stiffness proportional. In the range where the acceleration response increased, the damping ratio was constant. In the range where the acceleration response was constant, the damping ratio increased. Next, we investigated the difference of the dynamic characteristics depending on the difference of hysteretic model setting. With the increase in the maximum acceleration of the input earthquake motions, the natural frequency decreased in TAKEDA model, but in Normal-trilinear model, the natural frequency didn’t change. The damping ratio in TAKEDA model was higher than that in Normal-trilinear model, although, both in TAKEDA model and Normal-trilinear model, the damping ratio increased. In conclusion, in initial damping model setting, the tangent stiffness proportional was evaluated the most. In the hysteretic model setting, TAKEDA model was more appreciated than the Normal-trilinear model in the nonlinear region. Our results would provide useful indicator on dynamic design.

Keywords: initial damping model, damping ratio, dynamic analysis, hysteretic model, natural frequency

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Authors: Indrajit Ghosh, Jaydip Roy

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Literacy rate is an important indicator for measurement of human development. But this is not a good one to capture the qualitative dimension of educational attainment of an individual or a society. The overall educational level of an area is an important issue beyond the literacy rate. The overall educational level can be thought of as an outcome of the educational levels of individuals. But there is no well-defined algorithm and mathematical model available to measure the overall educational level of an area. A heuristic approach based on accumulated experience of experts is effective one. It is evident that fuzzy logic offers a natural and convenient framework in modeling various concepts in social science domain. This work suggests the implementation of fuzzy logic to develop a mathematical model for measurement of educational attainment of an area in terms of Education Index. The contribution of the study is two folds: conceptualization of “Education Profile” and proposing a new mathematical model to measure educational attainment in terms of “Education Index”.

Keywords: education index, education profile, fuzzy logic, literacy

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Authors: Jiahui Yang, John Quigley, Lesley Walls

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In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

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Authors: Zdzislaw Piotr Kaminski, Miroslaw Wendeker, Zbigniew Czyz

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The paper describes the geometric model, calculation algorithm and results of the CFD simulation of the airflow around a rotor in the vertical axis wind turbine (VAWT) with the ANSYS Fluent computational solver. The CFD method enables creating aerodynamic characteristics of forces acting on rotor working surfaces and determining parameters such as torque or power generated by the rotor assembly. The object of the research was a rotor whose construction is based on patent no.PL219985. The conducted tests enabled a mathematical model with a description of the generation of aerodynamic forces acting on each rotor blade. Additionally, this model was compared to the results of the wind tunnel tests. The analysis also focused on the influence of the blade angle on turbine power and the TSR. The research has shown that the turbine blade angle has a significant impact on the optimal value of the TSR.

Keywords: computational fluid dynamics, numerical analysis, renewable energy, wind turbine

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Authors: Ebrahim H. Kapeel, Ahmed M. Kamel, Hossam Hendy, Yehia Z. Elhalwagy

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Interest in autopilot design has been raised intensely as a result of recent advancements in Unmanned Aerial vehicles (UAVs). Due to the enormous number of applications that UAVs can achieve, the number of applied control theories used for them has increased in recent years. These small fixed-wing UAVs are suffering high non-linearity, sensitivity to disturbances, and coupling effects between their channels. In this work, the nonlinear dynamic inversion (NDI) control law is designed for a nonlinear small fixed-wing UAV model. The NDI is preferable for varied operating conditions, there is no need for a scheduling controller. Moreover, it’s applicable for high angles of attack. For the designed flight controller validation, a nonlinear Modified PI-D controller is performed with our model. A comparative study between both controllers is achieved to evaluate the NDI performance. Simulation results and analysis are proposed to illustrate the effectiveness of the designed controller based on NDI.

Keywords: attitude control, nonlinear PID, dynamic inversion

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Authors: Lachin Mikjtarnejad, Mohsen Farzaneh

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Various microbes, such as fungi and bacteria species, are naturally found in the fruit microbiota, and some of them act as a pathogen and result in fruit rot. Among non-pathogenic microbes, yeasts (single-celled microorganisms belonging to the fungi kingdom) can colonize fruit tissues and interact with them without causing any damage to them. Although yeasts are part of the plant microbiota, there is little information about their interactions with plants in comparison with bacteria and filamentous fungi. According to several existing studies, some yeasts can colonize different plant species and have the biological control ability to suppress some of the plant pathogens. It means those specific yeast-colonized plants are more resistant to some plant pathogens. The major objective of the present investigation is to isolate yeast strains from apple fruit and screen their ability to control Penicillium expansum, the causal agent of blue mold of fruits. In the present study, psychrotrophic and epiphytic yeasts were isolated from apple fruits that were stored at low temperatures (0–1°C). Totally, 42 yeast isolates were obtained and identified by molecular analysis based on genomic sequences of the D1/D2 and ITS1/ITS4 regions of their rDNA. All isolated yeasts were primarily screened by' in vitro dual culture assay against P. expansum by measuring the fungus' relative growth inhibition after 10 days of incubation. The results showed that the mycelial growth of P. expansum was reduced between 41–53% when challenged by promising yeast strains. The isolates with the strongest antagonistic activity belonged to Metschnikowia pulcherrima A13, Rhodotorula mucilaginosa A41, Leucosporidium Scottii A26, Aureobasidium pullulans A19, Pichia guilliermondii A32, Cryptococcus flavescents A25, and Pichia kluyveri A40. The results of seven superior isolates to inhibit blue mold decay on fruit showed that isolates A. pullulans A19, L. scottii A26, and Pi. guilliermondii A32 could significantly reduce the fruit rot and decay with 26 mm, 22 mm and 20 mm zone diameter, respectively, compared to the control sample with 43 mm. Our results show Pi. guilliermondii strain A13 was the most effective yeast isolates in inhibiting P. expansum on apple fruits. In addition, various biological control mechanisms of promising biological isolates against blue mold have been evaluated to date, including competition for nutrients and space, production of volatile metabolites, reduction of spore germination, production of siderophores and production of extracellular lytic enzymes such as chitinase and β-1,3-glucanase. However, the competition for nutrients and the ability to inhibit P. expansum spore growth have been introduced as the prevailing mechanisms among them. Accordingly, in our study, isolates A13, A41, A40, A25, A32, A19 and A26 inhibited the germination of P. expansum, whereas isolates A13 and A19 were the strongest inhibitors of P. expansum mycelia growth, causing 89.13% and 81.75 % reduction in the mycelial surface, respectively. All the promising isolates produced chitinase and β-1,3-glucanase after 3, 5 and 7 days of cultivation. Finally, based on our findings, we are proposing that, Pi. guilliermondiias as an effective biocontrol agent and alternative to chemical fungicides to control the blue mold of apple fruit.

Keywords: yeast, yeast enzymes, biocontrol, post harvest diseases

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Authors: C. M. Segning, H. Ezzaidi, S. Nogomo, M. Otis

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Our proposal aims for developing an objective pain discrimination system, i.e., to discriminate between two neuronal conditions affecting the same neurophysiological signal. In this study, we present an approach to identify, in the first instance, two types of pain based on the analysis of the EEG signal decomposition coefficients. Each EEG segment of one second duration is analyzed using the Chebyshev and linear prediction transform to extract a set of non-linear features, namely the Chebyshev and linear prediction coefficients. These features are used as the input vector of the Gaussian mixture model (GMM) for classification to differentiate two types of pain. To evaluate the performance of the proposed approach, we used an EEG dataset recorded in the left temporal (T7) and left fronto-central (FC5) regions. The experimental results demonstrate the effectiveness of Chebyshev coefficients for accurate differentiation of chronic fibromyalgia-like pain and experimental pain in the resting gamma band, with an accuracy of 93.9%. These results suggest a potential for discrimination of clinical pain according to its mechanism.

Keywords: chronic fibromyalgia pain, Chebyshev coefficients, healthy with induced pain, electroencephalogram, Gaussian mixture model

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Authors: Peng Wang, Tigang Jiang

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The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

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Authors: Naeim Akbari Shahkhosravi, Reza Kakavand, Helen M. S. Davies, Amin Komeili

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Equine locomotion and performance are significantly affected by hoof health. One of the most critical diseases of the hoof is laminitis, which can lead to horse lameness in a severe condition. This disease exhibits the mechanical properties degradation of the laminar junction tissue within the hoof. Therefore, it is essential to investigate the biomechanics of the hoof, focusing specifically on excessive and cumulatively accumulated stresses within the laminar junction tissue. For this aim, the current study generated a novel equine hoof Finite Element (FE) model under dynamic physiological loading conditions and employing a hyperelastic material model. Associated tissues of the equine hoof were segmented from computed tomography scans of an equine forelimb, including the navicular bone, third phalanx, sole, frog, laminar junction, digital cushion, and medial- dorsal- lateral wall areas. The inner tissues were connected based on the hoof anatomy, and the hoof was under a dynamic loading over cyclic strides at the trot. The strain distribution on the hoof wall of the model was compared with the published in vivo strain measurements to validate the model. Then the validated model was used to study the development of laminitis. The ultimate stress tolerated by the laminar junction before rupture was considered as a stress threshold. The tissue damage was simulated through iterative reduction of the tissue’s mechanical properties in the presence of excessive maximum principal stresses. The findings of this investigation revealed how damage initiates from the medial and lateral sides of the tissue and propagates through the hoof dorsal area.

Keywords: horse hoof, laminitis, finite element model, continuous damage

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Authors: H. Abas Nejad, A. R. Teymoori

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Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, etc. in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as the user stays neutral for the majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this work, we propose a light-weight neutral vs. emotion classification engine, which acts as a preprocessor to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at Key Emotion (KE) points using a textural statistical model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a textural statistical model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves ER accuracy and simultaneously reduces the computational complexity of ER system, as validated on multiple databases.

Keywords: neutral vs. emotion classification, Constrained Local Model, procrustes analysis, Local Binary Pattern Histogram, statistical model

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Authors: Nureni O. Adeboye, Dawud A. Agunbiade

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This research attempts to investigate the effects of heteroscedasticity and periodicity in a Panel Data Regression Model (PDRM) by extending previous works on balanced panel data estimation within the context of fitting PDRM for Banks audit fee. The estimation of such model was achieved through the derivation of Joint Lagrange Multiplier (LM) test for homoscedasticity and zero-serial correlation, a conditional LM test for zero serial correlation given heteroscedasticity of varying degrees as well as conditional LM test for homoscedasticity given first order positive serial correlation via a two-way error component model. Monte Carlo simulations were carried out for 81 different variations, of which its design assumed a uniform distribution under a linear heteroscedasticity function. Each of the variation was iterated 1000 times and the assessment of the three estimators considered are based on Variance, Absolute bias (ABIAS), Mean square error (MSE) and the Root Mean Square (RMSE) of parameters estimates. Eighteen different models at different specified conditions were fitted, and the best-fitted model is that of within estimator when heteroscedasticity is severe at either zero or positive serial correlation value. LM test results showed that the tests have good size and power as all the three tests are significant at 5% for the specified linear form of heteroscedasticity function which established the facts that Banks operations are severely heteroscedastic in nature with little or no periodicity effects.

Keywords: audit fee lagrange multiplier test, heteroscedasticity, lagrange multiplier test, Monte-Carlo scheme, periodicity

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Authors: Oloruntegbe Kunle Oke, Alake Ese Monica, Odutuyi Olubu Musili

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This research explores the differing effectiveness of cascade and cluster models in professional development programs for educators in Ondo State, Nigeria. The cascade model emphasizes a top-down approach, where training is cascaded from expert trainers to lower levels of teachers. In contrast, the cluster model, a bottom-up approach, fosters collaborative learning among teachers within specific clusters. Through a review of the literature and empirical studies of the implementations of the former in two academic sessions followed by the cluster model in another two, the study examined their effectiveness on teacher development, productivity and students’ achievements. The study also drew a comparative analysis of the strengths and weaknesses associated with each model, considering factors such as scalability, cost-effectiveness, adaptability in various contexts, and sustainability. 2500 teachers from Ondo State Primary Schools participated in the cascade with intensive training in five zones for a week each in two academic sessions. On the other hand, 1,980 and 1,663 teachers in 52 and 34 clusters, respectively, were in the first and the following session. The programs were designed for one week of rigorous training of teachers by facilitators in the former while the latter was made up of four components: sit-in-observation, need-based assessment workshop, pre-cluster and the actual cluster meetings in addition to sensitization, and took place one day a week for ten weeks. Validated Cluster Impact Survey Instruments, CISI and Teacher’s Assessment Questionnaire (TAQ) were administered to ascertain the effectiveness of the models during and after implementation. The findings from the literature detailed specific effectiveness, strengths and limitations of each approach, especially the potential for inconsistencies and resistance to change. Findings from the data collected revealed the superiority of the cluster model. Response to TAQ equally showed content knowledge and skill update in both but were more sustained in the cluster model. Overall, the study contributes to the ongoing discourse on effective strategies for improving teacher training and enhancing student outcomes, offering practical recommendations for the development and implementation of future professional development projects.

Keywords: cascade model, cluster model, teachers’ development, productivity, students’ achievement

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Authors: S. Zolghadri, M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani

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In this study, the absorbed dose of human organs after injection of ¹⁷⁷Lu-DOTATOC was studied based on the biodistribution of the complex in adenocarcinoma breast cancer bearing mice. For this purpose, the biodistribution of the radiolabelled complex was studied and compartmental modeling was applied to calculate the absorbed dose with high precision. As expected, ¹⁷⁷Lu-DOTATOC illustrated a notable specific uptake in tumor and pancreas, organs with high level of somatostatin receptor on their surface and the effectiveness of the radio-conjugate for targeting of the breast adenocarcinoma tumors was indicated. The elicited results of modeling were the exponential equations, and those are utilized for obtaining the cumulated activity data by taking their integral. The results also exemplified that non-target absorbed-doses such as the liver, spleen and pancreas were approximately 0.008, 0.004, and 0.039, respectively. While these values were so much lower than target (tumor) absorbed-dose, it seems due to this low toxicity, this complex is a good agent for therapy.

Keywords: ¹⁷⁷Lu, breast cancer, compartmental modeling, dosimetry

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Authors: Cristina da Silva Torres, José Luis Duarte Ribeiro, Maria Auxiliadora Cannarozzo Tinoco

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As a result of the rapid growth of the Brazilian Air Transport, many airports are at the limit of their capacities and have a reduction in the quality of services provided. Thus, there is a need of models for assessing the quality of airport services. Because of this, the main objective of this work is to propose a model for the evaluation of quality attributes in airport services. To this end, we used the method composed by literature review and interview. Structured a working method composed by 5 steps, which resulted in a model to evaluate the quality of airport services, consisting of 8 dimensions and 45 attributes. Was used as base for model definition the process mapping of boarding and landing processes of passengers and luggage. As a contribution of this work is the integration of management process with structuring models to assess the quality of services in airport environments.

Keywords: quality airport services, model for identification of attributes quality, air transport, passenger

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Authors: Tayib Bromand, Keisuke Sato

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This paper presents the introduction to current water balance and climate change assessment in the Kabul river basin. The historical and future impacts of climate change on different components of water resources and hydrology in the Kabul river basin. The eastern part of Afghanistan, the Kabul river basin was chosen due to rapid population growth and land degradation to quantify the potential influence of Gobal Climate Change on its hydrodynamic characteristics. Luck of observed meteorological data was the main limitation of present research, few existed precipitation stations in the plain area of Kabul basin selected to compare with TRMM precipitation records, the result has been evaluated satisfactory based on regression and normal ratio methods. So the TRMM daily precipitation and NCEP temperature data set applied in the SWAT model to evaluate water balance for 2008 to 2012. Middle of the twenty – first century (2064) selected as the target period to assess impacts of climate change on hydrology aspects in the Kabul river basin. For this purpose three emission scenarios, A2, A1B and B1 and four GCMs, such as MIROC 3.2 (Med), CGCM 3.1 (T47), GFDL-CM2.0 and CNRM-CM3 have been selected, to estimate the future initial conditions of the proposed model. The outputs of the model compared and calibrated based on (R2) satisfactory. The assessed hydrodynamic characteristics and precipitation pattern. The results show that there will be significant impacts on precipitation patter such as decreasing of snowfall in the mountainous area of the basin in the Winter season due to increasing of 2.9°C mean annual temperature and land degradation due to deforestation.

Keywords: climate change, emission scenarios, hydrological components, Kabul river basin, SWAT model

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Authors: Motonobu Hattori

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In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudo patterns. Because, temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.

Keywords: catastrophic forgetting, dual-network, temporal sequences, hippocampal

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Authors: Liu Canqi, Zeng Junsheng

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This study identifies two typical bottlenecks that occur when a vehicle cannot change lanes: car following and car stopping. The ideas of traffic field and traffic mass are presented in this work. When there are other vehicles in front of the target vehicle within a particular distance, a force is created that affects the target vehicle's driving speed. The characteristics of the driver and the vehicle collectively determine the traffic mass; the driving speed of the vehicle and external variables have no bearing on this. From a physical level, this study examines the vehicle's bottleneck when following a car, identifies the outside factors that have an impact on how it drives, takes into account that the vehicle will transform kinetic energy into potential energy during deceleration, and builds a calculation model for traffic mass. The energy-time conversion coefficient is created from an economic standpoint utilizing the social average wage level and the average cost of motor fuel. Vissim simulation program measures the vehicle's deceleration distance and delays under the Wiedemann car-following model. The difference between the measured value of deceleration delay acquired by simulation and the theoretical value calculated by the model is compared using the conversion calculation model of traffic mass and deceleration delay. The experimental data demonstrate that the model is reliable since the error rate between the theoretical calculation value of the deceleration delay obtained by the model and the measured value of simulation results is less than 10%. The article's conclusion is that the traffic field has an impact on moving cars on the road and that physical and socioeconomic factors should be taken into account while studying vehicle-following behavior. The deceleration delay value of a vehicle's driving and traffic mass have a socioeconomic relationship that can be utilized to calculate the energy-time conversion coefficient when dealing with the bottleneck of cars stopping and starting.

Keywords: traffic field, social economics, traffic mass, bottleneck, deceleration delay

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Authors: Karthiyayini Nagarajan, P. V. Ramakrishna

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Radar Imaging techniques provides extensive applications in the field of remote sensing, majorly Synthetic Aperture Radar (SAR) that provide high resolution target images. This paper work puts forward the effective and realizable signal generation and processing for SAR images. The major units in the system include camera, signal generation unit, signal processing unit and display screen. The real radio channel is replaced by its mathematical model based on optical image to calculate a reflected signal model in real time. Signal generation realizes the algorithm and forms the radar reflection model. Signal processing unit provides range and azimuth resolution through matched filtering and spectrum analysis procedure to form radar image on the display screen. The restored image has the same quality as that of the optical image. This SAR imaging system has been designed and implemented using MATLAB and Quartus II tools on Stratix III device as a System (Lab Bench) that works in real time to study/investigate on radar imaging rudiments and signal processing scheme for educational and research purposes.

Keywords: synthetic aperture radar, radio reflection model, lab bench, imaging engineering

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Authors: Surinder Deswal, Mahesh Pal

Abstract:

The paper investigates the potential of support vector machines based regression approach to model the mass transfer capacity of multiple plunging jets, both vertical (θ = 90°) and inclined (θ = 60°). The data set used in this study consists of four input parameters with a total of eighty eight cases. For testing, tenfold cross validation was used. Correlation coefficient values of 0.971 and 0.981 (root mean square error values of 0.0025 and 0.0020) were achieved by using polynomial and radial basis kernel functions based support vector regression respectively. Results suggest an improved performance by radial basis function in comparison to polynomial kernel based support vector machines. The estimated overall mass transfer coefficient, by both the kernel functions, is in good agreement with actual experimental values (within a scatter of ±15 %); thereby suggesting the utility of support vector machines based regression approach.

Keywords: mass transfer, multiple plunging jets, support vector machines, ecological sciences

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Authors: Peter J. Riley

Abstract:

Introductory courses in High Energy Physics (HEP) can be extended with the Tri-Preon (TP) model to both supplements and challenge the Standard Model (SM) theory. TP supplements by simplifying the tracking of Conserved Quantum Numbers at an interaction vertex, e.g., the lepton number can be seen as a di-preon current. TP challenges by proposing extended particle families to three generations of particle triplets for leptons, quarks, and weak bosons. There are extensive examples discussed at an introductory level in six arXiv publications, including supersymmetry, hyper color, and the Higgs. Interesting exercises include pion decay, kaon-antikaon mixing, neutrino oscillations, and K+ decay to muons. It is a revealing exercise for students to weigh the pros and cons of parallel theories at an early stage in their HEP journey.

Keywords: HEP, particle physics, standard model, Tri-Preon model

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Authors: Mutaz Dwairy

Abstract:

Solid tumors have high interstitial fluid pressure (IFP), high mechanical stress, and low oxygen levels. Solid stresses may induce apoptosis, stimulate the invasiveness and metastasis of cancer cells, and lower their proliferation rate, while oxygen concentration may affect the response of cancer cells to treatment. Although tumors grow in a nonhomogeneous environment, many existing theoretical models assume homogeneous growth and tissue has uniform mechanical properties. For example, the brain consists of three primary materials: white matter, gray matter, and cerebrospinal fluid (CSF). Therefore, tissue inhomogeneity should be considered in the analysis. This study established a physical model based on convection-diffusion equations and continuum mechanics principles. The model considers the geometrical inhomogeneity of the brain by including the three different matters in the analysis: white matter, gray matter, and CSF. The model also considers fluid-solid interaction and explicitly describes the effect of mechanical factors, e.g., solid stresses and IFP, chemical factors, e.g., oxygen concentration, and biological factors, e.g., cancer cell concentration, on growing tumors. In this article, we applied the model on a brain tumor positioned within the white matter, considering the brain inhomogeneity to estimate solid stresses, IFP, the cancer cell concentration, oxygen concentration, and the deformation of the tissues within the neoplasm and the surrounding. Tumor size was estimated at different time points. This model might be clinically crucial for cancer detection and treatment planning by measuring mechanical stresses, IFP, and oxygen levels in the tissue.

Keywords: biomechanical model, interstitial fluid pressure, solid stress, tumor microenvironment

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Authors: Vinod Kumar Jaysaval, Prateek Agarwal

Abstract:

Performance prediction of airborne radar is a challenging and cumbersome task in clutter scenario for different types of targets. A generalized model requires to predict the performance of Radar for air targets as well as ground moving targets. In this paper, we propose a generalized model to bring out the performance of airborne radar for different Pulsed Repetition Frequency (PRF) as well as different type of targets. The model provides a platform to bring out different subsystem parameters for different applications and performance requirements under different types of clutter terrain.

Keywords: airborne radar, blind zone, clutter, probability of detection

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Authors: K. Shoylekova, K. Grigorova

Abstract:

The Petri nets are the first standard for business process modeling. Most probably, it is one of the core reasons why all new standards created afterwards have to be so reformed as to reach the stage of mapping the new standard onto Petri nets. The paper presents a Business process repository based on a universal database. The repository provides the possibility the data about a given process to be stored in three different ways. Business process repository is developed with regard to the reformation of a given model to a Petri net in order to be easily simulated two different techniques for business process simulation based on Petri nets - Yasper and Woflan are discussed. Their advantages and drawbacks are outlined. The way of simulating business process models, stored in the Business process repository is shown.

Keywords: business process repository, petri nets, simulation, Woflan, Yasper

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Authors: Ziwei Chen, Yujiang Gao

Abstract:

The rapid urbanization has caused the massive physical space in Chinese cities to be in a state of duplication and dislocation through the rapid development, forming many daily spaces that cannot be standardized, typed, and identified, such as illegal construction. This phenomenon is known as urban spatial redundancy and is often excluded from mainstream architectural discussions because of its 'remaining' and 'excessive' derogatory label. In recent years, some practice architects have begun to pay attention to this phenomenon and tried to tap the value behind it. In this context, the author takes the redundancy phenomenon of resident space as the research object and explores the inspiration to the urban architectural renewal and the innovative residential area model, based on the urban survey of redundant living space in Hongkou District of Shanghai. On this basis, it shows that the changes accumulated in the long-term use of the building can be re-applied to the goals before the design, which is an important link and significance of the existence of an architecture.

Keywords: rapid urbanization, living space redundancy, architectural renewal, residential area model

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Authors: Hendrik Bernard Van Der Walt, Frik Van Niekerk

Abstract:

Fuel models render a reduction in BOL when thorium is added to a reactor core. Thorium emulates the role of a fertile poison, and is beneficial for reducing beginning of cycle (BOC) excess reactivity. In spite of the build-up of 233U over the duration of a fuel cycle, the effects of fuel reloading have a significant impact on fuel viability, especially in the case of heterogeneous thorium-based fuels. The most common practice of compensating for the reduction of BOC reactivity is the addition of fissile isotopes (uranium fuel with increased enrichment or plutonium). This study introduces a heterogeneous thorium-based fuel with minimal fissile isotope additions. A pseudo reloading scheme was developed for numerical simulations of an infinite reactor based on the North-Anna 1 reactor operating in Virginia, USA. Use of this reloading pattern allows new thorium-based fuel to be loaded into the reactor model as part of a phasing in strategy at the end of any conventional reactor cycle. Results demonstrate the effects of thorium-based fuel on fuel cycle characteristics such as fuel cycle length, neutron economy and material matrix. Application of the above mentioned approach delivered promising results and presents a heterogeneous thorium-based fuel which could replace conventional fuel of typical, currently operating (or future) reactors without the need for expensive reactor redesign or fuel recycling strategies.

Keywords: nuclear fuel, nuclear characteristics, nuclear fuel cycle, thorium-based fuel, heterogeneous design, fuel reloading

Procedia PDF Downloads 138