Search results for: hill type muscle model

Authors: Deepen Sharma, Eugene F. Hill

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For nearly 100 years, hydro-turbine governors have operated with only a frequency set point. This natural governor action means that the governor responds with changing megawatt output to disturbances in system frequency. More and more, power system managers are demanding that governors operate with constant megawatt output. One way of doing this is to introduce a second set point in the control structure called a power set point. The control structure investigated and analyzed in this paper is unique in the way that it utilizes a power reference set point in addition to the conventional frequency reference set point. An optimum set of temporary droop parameters derived based on the turbine-generator inertia constant and the penstock water start time for stable islanded operation are shown to be also equally applicable for a satisfactory rate of generator loading during its grid connected mode. A theoretical development shows why this is the case. The performance of the control structure has been investigated and established based on the simulation study made in MATLAB/Simulink as well as through testing the real time controller performance on a 15 MW Kaplan Turbine and generator. Recordings have been made using the labVIEW data acquisition platform. The hydro-turbine governor control structure and its performance investigated in this paper thus eliminates the need to have a separate set of temporary droop parameters, one valid for islanded mode and the other for interconnected operations mode.

Keywords: frequency set point, hydro governor, interconnected operation, isolated operation, power set point

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Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine

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Authors: Loreine Makki, Marc Anthony Mannah, Christophe Batard, Nicolas Ginot, Julien Weckbrodt

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Planar transformers are extensively utilized in high-frequency, high power density power electronic converters. The breakthrough of wide-bandgap technology compelled power electronic system miniaturization while inducing pivotal effects on system modeling and manufacturing within the power electronics industry. A significant consideration to simulate and model the unanticipated parasitic parameters emerges with the requirement to mitigate electromagnetic disturbances. This paper will present an equivalent circuit model of a shielded pulse planar transformer quantifying leakage inductance and resistance in addition to the interwinding capacitance of the primary and secondary windings. ANSYS Q3D Extractor was utilized to model and simulate the transformer, intending to study the immunity of the simulated equivalent model to high dv/dt occurrences. A convenient correlation between simulation and experimental results is presented.

Keywords: Planar transformers, wide-band gap, equivalent circuit model, shielded, ANSYS Q3D Extractor, dv/dt

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Authors: Ridha Salhi, Mondher Labidi, Fethi Choubani

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Metamaterials have attracted much attention in recent years because of their electromagnetic exquisite proprieties. We will present, in this paper, the modeling of three metamaterial structures by equivalent circuit model. We begin by modeling the SRR (Split Ring Resonator), then we model the HIS (High Impedance Surfaces), and finally, we present the model of the CPW (Coplanar Wave Guide). In order to validate models, we compare the results obtained by an equivalent circuit models with numerical simulation.

Keywords: metamaterials, SRR, HIS, CPW, IDC

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Authors: Aid Abdelkrim

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A method of fatigue damage accumulation based upon application of energy parameters of the fatigue process is proposed in the paper. Using this model is simple, it has no parameter to be determined, it requires only the knowledge of the curve W–N (W: strain energy density N: number of cycles at failure) determined from the experimental Wöhler curve. To examine the performance of nonlinear models proposed in the estimation of fatigue damage and fatigue life of components under random loading, a batch of specimens made of 6082 T 6 aluminium alloy has been studied and some of the results are reported in the present paper. The paper describes an algorithm and suggests a fatigue cumulative damage model, especially when random loading is considered. This work contains the results of uni-axial random load fatigue tests with different mean and amplitude values performed on 6082T6 aluminium alloy specimens. The proposed model has been formulated to take into account the damage evolution at different load levels and it allows the effect of the loading sequence to be included by means of a recurrence formula derived for multilevel loading, considering complex load sequences. It is concluded that a ‘damaged stress interaction damage rule’ proposed here allows a better fatigue damage prediction than the widely used Palmgren–Miner rule, and a formula derived in random fatigue could be used to predict the fatigue damage and fatigue lifetime very easily. The results obtained by the model are compared with the experimental results and those calculated by the most fatigue damage model used in fatigue (Miner’s model). The comparison shows that the proposed model, presents a good estimation of the experimental results. Moreover, the error is minimized in comparison to the Miner’s model.

Keywords: damage accumulation, energy model, damage indicator, variable loading, random loading

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Authors: Rosa Hendijani, Mohammadhesam Hajighasemi

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As of late, the sharing economy has become an important type of business model. Online taxi services are one example that has grown rapidly around the world. This study examines the factors influencing the use of online taxis as one form of IT-enabled sharing services based on the theory of planned behavior (TPB). Based on the theory of planned behavior, these factors can be divided into three categories, including the ones related to attitude (e.g., image and perceived usefulness), normative believes (e.g., subjective norms), and behavioral control (e.g., technology facilitating conditions and self-efficacy). Three other factors were also considered based on the literature, including perceived economic benefits, openness towards using shared services, and perceived availability. The effect of all these variables was tested both directly and indirectly through intention as the mediating variable. A survey method was used to test the research hypotheses. In total, 361 individuals partook in the study. The results of a multiple regression analysis on behavior showed that perceived economic benefits, compatibility, and subjective norms were important factors influencing behavior among online taxi users. In addition, intention partially mediated the effect of perceived economic benefits and compatibility on behavior. It can be concluded that perceived economic benefits, compatibility, and subjective norms are the three main factors that influence behavior among online taxi users.

Keywords: collaborative consumption, IT-enabled sharing services model, online taxi, sharing economy, theory of planned behavior

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Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone

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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.

Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder

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Authors: Mehdi Rastegari Ghiri, Mohammad Reza Baradaran, Zahra Mirsanjari

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The aim of the present study was the investigation of DNA Corporate General Administration of Sports and Youth in Fars province. The descriptive research method is a survey that was conducted by field survey. For data collection, questionnaires were used that designed based on Hnald and Silverman model. In this model the organizational DNA model is stated in four types: objective, individualistic, field-oriented and Spiritual. The reliability of the questionnaire by the researcher obtained by using Cronbach's alpha equal to 89/0 respectively. The statistical population includes all managers and specialists of Fars Province Directorate of Youth and Sport that 48 of them were selected as the samples of the research. The results showed the organizational DNA Directorate General for Youth and Sports Organization of Fars province has a field –oriented and nearly field-oriented DNA.

Keywords: organizational, DNA, Hnald, Silverman model

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Authors: Mohamed Rajab Peer Mohamed, Thiruvenkatasamy Kannabiran

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In the present investigation, the scour around a circular pier subjected to a steady current were studied numerically using two-dimensional MIKE21 Flow Model (FM) and Sand Transport (ST)Modulewhich is developed by Danish Hydraulic Institute (DHI), Denmark. The unstructured flexible mesh generated with rectangular flume dimension of 10 m wide, 1 m deep, and 30 m long. The grain size of the sand was d50 = 0.16 mm, sediment size, sediment gradation=1.16, pier diameter D= 30 mm and depth-averaged current velocity, U = 0.449 m/s are considered in the model. The estimated scour depth obtained from this model is validated and it is observed that the results of the model have good agreement with flume experimental results.In order to estimate the scour depth, several simulations were made for three cases viz., Case I:change in sediment transport model description in the numerical model viz, i) Engelund-Hansen model, ii) Engelund-Fredsøe model, and iii) Van Rijn model, Case II: change in current velocity for keeping constant pile diameter D=0.03 m and Case III:change in pier diameter for constant depth averaged current speed U=0.449 m/s.In case I simulations, the results indicate that the scour depth S/D is the order of 1.73 for Engelund-Hansen model, 0.64 for Engelund-Fredsøe model and 0.46 for VanRijn model. The scour depth estimates using Engelund-Hansen method compares well the experimental results.In case II, simulations show that the scour depth increases with increasing current component of the flow.In case III simulations, the results indicate that the scour depth increases with increase in pier diameter and it stabilize attains steady value when the Froude number> 2.71.All the results of the numerical simulations are clearly matches with reported values of the experimental results. Hence, this MIKE21 FM –Sand Transport model can be used as a suitable tool to estimate the scour depth for field applications. Moreover, to provide suitable scour protection methods, the maximum scour depth is to be predicted, Engelund-Hansen method can be adopted to estimate the scour depth in the steady current region.

Keywords: circular pier, MIKE21, numerical model, scour, sediment transport

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Authors: Marizia Roberta Rasoanandrasana, Hery Lisy Tiana. Ranarijaona, Herintsitohaina Razakamanarivo, Eric Delaitre, Nandrianina Ramifehiarivo

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Madagascar is one of the producer’s countries of world's fine cocoa. Cocoa-based agroforestry systems (CBAS) plays a very important economic role for over 75% of the population in the north of Madagascar, the island's main cocoa-producing area. It is also viewed as a key factor in the deforestation of local protected areas. It is therefore urgent to establish a compromise between cocoa production and forest conservation in this region which is difficult due to a lack of accurate cocoa agro-systems data. In order to fill these gaps and to response to these socio-economic and environmental concerns, this study aims to describe CBAS by providing precise data on their characteristics and to establish a typology. To achieve this, 150 farms were surveyed and observed to characterize CBAS based on 11 agronomic and 6 socio-economic data. Also, 30 representative plots of CBAS among the 150 farms were inventoried for providing accurate ecological data (6 variables) as an additional data for the typology determination. The results showed that Madagascar’s CBAS systems are generally extensive and practiced by smallholders. Four types of cocoa-based agroforestry system were identified, with significant differences between the following variables: yield, planting age, cocoa density, density of associated trees, preceding crop, associated crops, Shannon-Wiener indices and species richness in the upper stratum. Type 1 is characterized by old systems (>45 years) with low crop density (425 cocoa trees/ha), installed after conversion of crops other than coffee (> 50%) and giving low yields (427 kg/ha/year). Type 2 consists of simple agroforestry systems (no associated crop 0%), fairly young (20 years) with low density of associated trees (77 trees/ha) and low species diversity (H'=1.17). Type 3 is characterized by high crop density (778 trees/ha and 175 trees/ha for cocoa and associated trees respectively) and a medium level of species diversity (H'=1.74, 8 species). Type 4 is particularly characterized by orchard regeneration method involving replanting and tree lopping (100%). Analysis of the potential of these four types has identified Type 4 as a promising practice for sustainable agriculture.

Keywords: conservation, practices, productivity, protect areas, smallholder, trade-off, typology

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Authors: Nqobile Muleya, Winston Garira, Godwin Mchau

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Citrus Black Spot (CBS) is a fungal disease that is responsible for huge economical loss and poses a threat to the citrus industry worldwide. We construct a mathematical model framework for citrus black spot between fruits to characterise the dynamics of the disease development, paying attention to the pathogen life cycle. We have made an observation from the model analysis that the initial inoculum from ascomata is very important for disease development and thereafter it is no longer important due to conidia which is responsible for secondary infection. Most importantly, the model indicated that ascospores and conidia are very important parameters in developing citrus black spot within a short distance. The basic reproductive number and its importance in relation to citrus black spot persistence are outlined. A numerical simulation of the model was done to explain the theoretical findings.

Keywords: epidemiological modelling, Guidnardia citricarpa, life cycle stage, fungal, disease development

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Authors: Mohammad Ridzwan Bin Abd Rahim, Siegfried Schmauder, Yupiter HP Manurung, Peter Binkele, Meor Iqram B. Meor Ahmad, Kiarash Dogahe

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This paper deals with the short crack initiation of the material P91 under cyclic loading at two different temperatures, concluded with the estimation of the short crack initiation Wöhler (S/N) curve. An artificial but representative model microstructure was generated using Voronoi tessellation and the Finite Element Method, and the non-uniform stress distribution was calculated accordingly afterward. The number of cycles needed for crack initiation is estimated on the basis of the stress distribution in the model by applying the physically-based Tanaka-Mura model. Initial results show that the number of cycles to generate crack initiation is strongly correlated with temperature.

Keywords: short crack initiation, P91, Wöhler curve, Voronoi tessellation, Tanaka-Mura model

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Authors: Hung-Jiun Chi, Cheng-En Tsai, Jia-Ying Tu

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Semi-active control of Magnetorheological (MR) dampers for vibration reduction of structural systems has received considerable attention in civil and earthquake engineering, because the effective stiffness and damping properties of MR fluid can change in a very short time in reaction to external loading, requiring only a low level of power. However, the inherent nonlinear dynamics of hysteresis raise challenges in the modeling and control processes. In order to control the MR damper, an innovative Duffing-like equation is proposed to approximate the hysteresis dynamics in a deterministic and systematic manner than previously has been possible. Then, the model-reference adaptive control technique based on the Duffing-like model and the Lyapunov method is discussed. Parameter identification work with experimental data is presented to show the effectiveness of the Duffing-like model. In addition, simulation results show that the resulting adaptive gains enable the MR damper force to track the desired response of the reference model satisfactorily, verifying the effectiveness of the proposed modeling and control techniques.

Keywords: magnetorheological damper, duffing equation, model-reference adaptive control, Lyapunov function, hysteresis

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Authors: Cristian Patrascioiu, Loredana Negoita

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This paper is focused on modeling and simulation of the tubular heaters. The paper is structured in four parts: the structure of the tubular convection section, the heat transfer model, the adaptation of the mathematical model and the solving model. The main hypothesis of the heat transfer modeling is that the heat exchanger of the convective tubular heater is a lumped system. In the same time, the model uses the heat balance relations, Newton’s law and criteria relations. The numerical program achieved allows for the estimation of the burn gases outlet temperature and the heated flow outlet temperature.

Keywords: heat exchanger, mathematical modelling, nonlinear equation system, Newton-Raphson algorithm

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Authors: Gang Liu, Huimin Song, Can Wang, Runnan Zhang, Lu Fang

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Currently, resource sharing and system security are critical issues. This paper proposes a POL module composed of PRIV ILEGE attribute (PA), obligation and log which improves attribute based access control (ABAC) model in dynamically granting authorizations and revoking authorizations. The following describes the new model termed PABAC in terms of the POL module structure, attribute definitions, policy formulation and authorization architecture, which demonstrate the advantages of it. The POL module addresses the problems which are not predicted before and not described by access control policy. It can be one of the subject attributes or resource attributes according to the practical application, which enhances the flexibility of the model compared with ABAC. A scenario that illustrates how this model is applied to the real world is provided.

Keywords: access control, attribute based access control, granting authorizations, privilege, revoking authorizations, system security

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Authors: Vivek Hokam, Vishrut Landge

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An ideal maintenance program for an industrial road network is one that would maintain all sections at a sufficiently high level of functional and structural conditions. However, due to various constraints such as budget, manpower and equipment, it is not possible to carry out maintenance on all the needy industrial road sections within a given planning period. A rational and systematic priority scheme needs to be employed to select and schedule industrial road sections for maintenance. Priority analysis is a multi-criteria process that determines the best ranking list of sections for maintenance based on several factors. In priority setting, difficult decisions are required to be made for selection of sections for maintenance. It is more important to repair a section with poor functional conditions which includes uncomfortable ride etc. or poor structural conditions i.e. sections those are in danger of becoming structurally unsound. It would seem therefore that any rational priority setting approach must consider the relative importance of functional and structural condition of the section. The maintenance priority index and pavement performance models tend to focus mainly on the pavement condition, traffic criteria etc. There is a need to develop the model which is suitably used with respect to limited budget provisions for maintenance of pavement. Linear programming is one of the most popular and widely used quantitative techniques. A linear programming model provides an efficient method for determining an optimal decision chosen from a large number of possible decisions. The optimum decision is one that meets a specified objective of management, subject to various constraints and restrictions. The objective is mainly minimization of maintenance cost of roads in industrial area. In order to determine the objective function for analysis of distress model it is necessary to fix the realistic data into a formulation. Each type of repair is to be quantified in a number of stretches by considering 1000 m as one stretch. A stretch considered under study is having 3750 m length. The quantity has to be put into an objective function for maximizing the number of repairs in a stretch related to quantity. The distress observed in this stretch are potholes, surface cracks, rutting and ravelling. The distress data is measured manually by observing each distress level on a stretch of 1000 m. The maintenance and rehabilitation measured that are followed currently are based on subjective judgments. Hence, there is a need to adopt a scientific approach in order to effectively use the limited resources. It is also necessary to determine the pavement performance and deterioration prediction relationship with more accurate and economic benefits of road networks with respect to vehicle operating cost. The infrastructure of road network should have best results expected from available funds. In this paper objective function for distress model is determined by linear programming and deterioration model considering overloading is discussed.

Keywords: budget, maintenance, deterioration, priority

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Authors: M. L. McLain, R. Sreelakshmi, Abhishek, Rajeshwaran, Bhavani Rao, Kamal Bijlani, R. Jayakrishnan

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Technology enhanced learning has brought drastic changes in the field of education in the modern world. In this study we explore a novel way to improve how high school students learn by building a serious game that uses a pedagogical model developed by Robert Gagne. By integrating serious game with principles of Gagne’s learning model can provide engaging and meaningful instructions to students. The game developed in this study is a waste sorting game that can easily and succinctly demonstrate the principles of this learning model. All the tasks in the game that the player has to accomplish correspond to Gagne’s “Nine Events of Learning”. A quiz is incorporated in order to get data on the progress made by the player in understanding the concept and as well as to assess them. Additionally, an experimental study was conducted which demonstrates that game based learning using Gagne’s event is more effective than a traditional classroom setup.

Keywords: game based learning, sorting and recycling of waste, Gagne’s learning model, e-Learning, technology enhanced learning

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Authors: Reemiah Alotaibi, Muthu Ramachandran, Ah-Lian Kor, Amin Hosseinian-Far

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In the past decade, developers of Web 2.0 technologies have shown increasing interest in the topic of e-government. There has been a rapid growth in social media technology because of its significant role in backing up some essential social needs. Its importance and power is derived from its capacity to support two-way communication. Governments are curious to get engaged in these websites, hoping to benefit from the new forms of communication and interaction offered by such technology. Greater participation by the public can be viewed as a chief indicator of effective government communication. Yet, the level of public participation in government 2.0 is not quite satisfactory. In general, it is still at the early stage in most developing countries, including Saudi Arabia. Although it is a fact that Saudi people are among the most active in using social media, the number of people who use social media to communicate with the public institutions is not high. Furthermore, most of the governmental organisations are not using social media tools to communicate with the public. They use these platforms to disseminate information. Our study focuses on the factors affecting citizens’ adoption of social media in Saudi Arabia. Our research question is: what are the factors affecting Saudi citizens’ use of social media to communicate with the government? To answer this research question, the research aims to validate the UTAUT model for examining social media tools from the citizen perspective. An amendment will be proposed to fit the adoption of social media platforms as a communication channel in government by using a developed conceptual model which integrates constructs from the UTAUT model and others external variables based on the literature review. The set of potential factors that affect these citizens' decisions to adopt social media to communicate with their government has been identified as perceived encouragement, trust and cultural influence. The connection between the above-mentioned constructs from the basis for the research hypothesis will be examined in the light of a quantitative methodology. Data collection will be performed through a survey targeting a number of Saudi citizens who are social media users. The data collected from the primary survey will later be analysed by using statistical methods. The outcomes of this research project are argued to have potential contributions to the fields of social media and e-Government adoption, both on the theoretical and practical levels. It is believed that this research project is the first of its type that attempts to identify the factors that affect citizens’ adoption of social media to communicate with the government. The importance of identifying these factors stems from the potential use of them to enhance the government’s implementation of social media and help in making more accurate decisions and strategies based on comprehending the most important factors that affect citizens’ decisions.

Keywords: social media, adoption, citizen, UTAUT model

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Authors: Bin Mu, Site Li, Shijin Yuan

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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.

Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model

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Authors: Anik Sarminingsih, Krishna V. Pradana

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The failure of flood control system can be caused by various factors, such as not considering the uncertainty of designed flood causing the capacity of the flood control system is exceeded. The presence of the uncertainty factor is recognized as a serious issue in hydrological studies. Uncertainty in hydrological analysis is influenced by many factors, starting from reading water elevation data, rainfall data, selection of method of analysis, etc. In hydrological modeling selection of models and parameters corresponding to the watershed conditions should be evaluated by the hydraulic model in the river as a drainage channel. River cross-section capacity is the first defense in knowing the reliability of the flood control system. Reliability of river capacity describes the potential magnitude of flood risk. Case study in this research is Wulan River in Central Java. This river occurring flood almost every year despite some efforts to control floods such as levee, floodway and diversion. The flood-affected areas include several sub-districts, mainly in Kabupaten Kudus and Kabupaten Demak. First step is analyze the frequency of discharge observation from Klambu weir which have time series data from 1951-2013. Frequency analysis is performed using several distribution frequency models such as Gumbel distribution, Normal, Normal Log, Pearson Type III and Log Pearson. The result of the model based on standard deviation overlaps, so the maximum flood discharge from the lower return periods may be worth more than the average discharge for larger return periods. The next step is to perform a hydraulic analysis to evaluate the reliability of river capacity based on the flood discharge resulted from several methods. The selection of the design flood discharge of flood control system is the result of the method closest to bankfull capacity of the river.

Keywords: design flood, hydrological model, reliability, uncertainty, Wulan river

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Authors: Tz-Bang Du, Cheng-Han Hsieh, Li-Ping Ju, Hung-Jie Liou

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Polyether amines synthesize by secondary hydroxyl polyether diol play an important role in epoxy hardener. The low molecular weight product is used in low viscosity and high transparent polyamine product for the logo, ground cover, especially for wind turbine blade, while the high molecular weight products are used in advanced agricultures such as a high-speed railway. High-pressure reductive amination process is required for producing these amines. In the condition of higher than 150 atm pressure and 200 degrees Celsius temperature, supercritical ammonia is used as a reactant and also a solvent. It would be a great challenge to select a catalyst support for such high-temperature alkaline circumstance. In this study, we have established a six-autoclave-type (SAT) high-pressure reactor for amination catalyst screening, which six experiment conditions with different temperature and pressure could be examined at the same time. We synthesized copper-nickel catalyst on different shaped alumina catalyst support and evaluated the catalyst activity for high-pressure reductive amination of polypropylene glycol (PPG) by SAT reactor. Ball type gamma alumina, ball type activated alumina and pellet type gamma alumina catalyst supports are evaluated in this study. Gamma alumina supports have shown better activity on PPG reductive amination than activated alumina support. In addition, the catalysts are evaluated in fixed bed reactor. The diamine product was successfully synthesized via this catalyst and the strength of the catalysts is measured. The crush strength of blank supports is about 13.5 lb for both gamma alumina and activated alumina. The strength increases to 20.3 lb after synthesized to be copper-nickel catalyst. After test in the fixed bed high-pressure reductive amination process for 100 hours, the crush strength of the used catalyst is 3.7 lb for activated alumina support, 12.0 lb for gamma alumina support. The gamma alumina is better than activated alumina to use as catalyst support in high-pressure reductive amination process.

Keywords: high pressure reductive amination, copper nickel catalyst, polyether amine, alumina

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Authors: Bela Sulistyaguna, Yuli Chomsatu Samrotun, Endang Masitoh Wahyuningsih

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The purpose of this research was to analyze the influence of company size, liquidity, profitability, leverage, company age, industry type, board of director, board of commissioner, audit committee and public ownership on the corporate social responsibility disclosure. The grand theories of this research are agency theory, stakeholders theory, and legitimacy theory. Analysis of data using multiple linear regression method with SPSS 22.0 for mac. The sample consists of companies listed on the Indonesia Stock Exchange (IDX) and disclosed the Global Reporting Initiative (GRI) sustainability reports from 2013 to 2018. The final sample of this research was 19 companies that obtained by purposive sampling. The results of the research showed that, simultaneously, company size, liquidity, profitability, leverage, company age, industry type, board of director, board of commissioner, audit committee and public ownership has an influence on the corporate social responsibility disclosure. Partially, the results showed that liquidity and leverage has an influence on the corporate social responsibility disclosure. Meanwhile, company size, profitability, company age, industry type, board of director, board of commissioner, audit committee and public ownership has no influence on corporate social responsibility disclosure.

Keywords: corporate social responsibility, CSR disclosure, Indonesia

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Authors: E. Stepanova, N. Popov, S. Demakov, S. Stepanov

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This paper examines the so-called invar-type behavior of metastable titanium alloy subjected to cold rolling. The effect was shown to occur due to the anisotropy of thermal expansion of titanium orthorhombic martensite. By means of X-ray diffraction analysis and dilatometry analyses, the influence of crystallographic texture of orthorhombic martensite on the coefficient of thermal expansion of sheets of metastable titanium alloy VT23 was examined. Anisotropy of the coefficient of thermal expansion has been revealed. It was lower in the rolling plane and higher along the transverse direction of the cold-rolled sheet comparing to the coefficient of thermal expansion of the unprocessed alloy.

Keywords: invar-type, cold rolling, metastable titanium alloy, texture

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Jae Won Shin

Abstract:

We develop an evaluated nuclear data based photonuclear reaction model of GEANT4 for a more accurate simulation of photon-induced neutron production. The evaluated photonuclear data libraries from the ENDF/B-VII.1 are taken as input. Incident photon energies up to 140 MeV which is the threshold energy for the pion production are considered. For checking the validity of the use of the data-based model, we calculate the photoneutron production cross-sections and yields and compared them with experimental data. The results obtained from the developed model are found to be in good agreement with the experimental data for (γ,xn) reactions.

Keywords: ENDF/B-VII.1, GEANT4, photoneutron, photonuclear reaction

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Authors: Zainal Abidin Akasah, Maizam Alias, Azuin Ramli

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The safety and health performances aspects of a building are the most challenging aspect of facility management. It requires a deep understanding by the building managers on the factors that contribute to health and safety performances. This study attempted to develop an explanatory architectural safety performance model for stratified low-cost housing in Malaysia. The proposed Building Safety and Health Performance (BSHP) model was tested empirically through a survey on 308 construction practitioners using Partial Least Squares (PLS) and Structural Equation Modelling (SEM) tool. Statistical analysis results supports the conclusion that architecture, building services, external environment, management approaches and maintenance management have positive influence on safety and health performance of stratified low-cost housing in Malaysia. The findings provide valuable insights for construction industry to introduce BSHP model in the future where the model could be used as a guideline for training purposes of managers and better planning and implementation of building management.

Keywords: building management, stratified low-cost housing, safety, health model

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Authors: Eun-Soo Lim, Young-Min Kang

Abstract:

M-type Sr-hexaferrite (SrFe₁₂O₁₉) have been studied during the past decades because it is the most utilized materials in permanent magnets due to their low price, outstanding chemical stability, and appropriate hard magnetic properties. Many attempts have been made to improve the intrinsic magnetic properties of M-type Sr-hexaferrites (SrM), such as by improving the saturation magnetization (MS) and crystalline anisotropy by cation substitution. It is well proved that the Ca-La-Co substitutions are one of the most successful approaches, which lead to a significant enhancement in the crystalline anisotropy without reducing MS, and thus the Ca-La-Co-doped SrM have been commercialized in high-grade magnet products. In this research, the effect of respective doping of Ca and La into the SrM lattices were studied with assumptions that these elements could substitute both of Fe and Sr sites. The hexaferrite samples of stoichiometric SrFe₁₂O₁₉ (SrM) and the Ca substituted SrM with formulae of Sr₁₋ₓCaₓFe₁₂Oₐ (x = 0.1, 0.2, 0.3, 0.4) and SrFe₁₂₋ₓCaₓOₐ (x = 0.1, 0.2, 0.3, 0.4), and also La substituted SrM of Sr₁₋ₓLaₓFe₁₂Oₐ (x = 0.1, 0.2, 0.3, 0.4) and SrFe₁₂₋ₓLaₓOₐ (x = 0.1, 0.2, 0.3, 0.4) were prepared by conventional solid state reaction processes. X-ray diffraction (XRD) with a Cu Kα radiation source (λ=0.154056 nm) was used for phase analysis. Microstructural observation was conducted with a field emission scanning electron microscopy (FE-SEM). M-H measurements were performed using a vibrating sample magnetometer (VSM) at 300 K. Almost pure M-type phase could be obtained in the all series of hexaferrites calcined at > 1250 ºC. Small amount of Fe₂O₃ phases were detected in the XRD patterns of Sr₁₋ₓCaₓFe₁₂Oₐ (x = 0.2, 0.3, 0.4) and Sr₁₋ₓLaₓFe₁₂Oₐ (x = 0.1, 0.2, 0.3, 0.4) samples. Also, small amount of unidentified secondary phases without the Fe₂O₃ phase were found in the samples of SrFe₁₂₋ₓCaₓOₐ (x = 0.4) and SrFe₁₂₋ₓLaₓOₐ (x = 0.3, 0.4). Although the Ca substitution (x) into SrM structure did not exhibit a clear tendency in the cell parameter change in both series of samples, Sr₁₋ₓCaₓFe₁₂Oₐ and SrFe₁₂₋ₓCaₓOₐ , the cell volume slightly decreased with doping of Ca in the Sr₁₋ₓCaₓFe₁₂Oₐ samples and increased in the SrFe₁₂₋ₓCaₓOₐ samples. Considering relative ion sizes between Sr²⁺ (0.113 nm), Ca²⁺ (0.099 nm), Fe³⁺ (0.064 nm), these results imply that the Ca substitutes both of Sr and Fe in the SrM. A clear tendency of cell parameter change was observed in case of La substitution into Sr site of SrM ( Sr₁₋ₓLaₓFe₁₂Oₐ); the cell volume decreased with increase of x. It is owing to the similar but smaller ion size of La³⁺ (0.106 nm) than that of Sr²⁺. In case of SrFe₁₂₋ₓLaₓOₐ, the cell volume first decreased at x = 0.1 and then remained almost constant with increase of x from 0.2 to 0.4. These results mean that La only substitutes Sr site in the SrM structure. Besides, the microstructure and magnetic properties of these samples, and correlation between them will be revealed.

Keywords: M-type hexaferrite, substitution, cell parameter, magnetic properties

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Authors: Changgil Lee, Junkyeong Kim, Jihwan Park, Seunghee Park

Abstract:

In this study, bridge weigh-in-motion (BWIM) system was simulated under various environmental conditions such as temperature, humidity, wind and so on to improve the performance of the BWIM system. The environmental conditions can make difficult to analyze measured data and hence those factors should be compensated. Various conditions were considered as input parameters for ANN (Artificial Neural Network). The number of hidden layers for ANN was decided so that nonlinearity could be sufficiently reflected in the BWIM results. The weight of vehicles and axle weight were more accurately estimated by applying ANN approach. Additionally, the type of bridge which was a target structure was considered as an input parameter for the ANN.

Keywords: bridge weigh-in-motion (BWIM) system, environmental conditions, artificial neural network, type of bridges

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Authors: Khaled Khaladi, Rafika Bibi, Hind Mokrane, Boubekeur Nadjemi

Abstract:

Sorghum (Sorghum bicolor (L.) Moench) is an important cereal crop grown in the semi-arid tropics of Africa and Asia due to its drought tolerance. Sorghum grain has protein content varying from 6 to 18%, with an average of 11%, Sorghum proteins can be broadly classified into prolamin and non-prolamin proteins. Kafirins, the major storage proteins, are classified as prolamins, and as such, they contain high levels of proline and glutamine and are soluble in non-polar solvents such as aqueous alcohols. Kafirins account for 77 to 82% of the protein in the endosperm, whereas non-prolamin proteins (namely, albumins, globulins, and glutelins) make up about 30% of the proteins. To optimize the extraction of sorghum proteins, several variables were examined: detergent type and concentration, reducing agent type and concentration, and buffer pH and concentration. Samples were quantified and characterized by RP-HPLC.

Keywords: sorghum, protein extraction, detergent, food science

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Authors: Trevor Sabiston, Mohsen Mohammadi, Mohammed Cherkaoui, Kaan Inal

Abstract:

A new micromechanics framework is developed for long fibre reinforced composites using a single fibre surrounded by a functionally graded interphase and matrix as a representative unit cell. The unit cell is formulated to represent any number of aligned fibres by a single fibre. Using this model the elastic response of long fibre composites is predicted in all directions. The model is calibrated to experimental results and shows very good agreement in the elastic regime. The differences between the proposed model and existing models are discussed.

Keywords: computational mechanics, functionally graded interphase, long fibre composites, micromechanics

Procedia PDF Downloads 319