Search results for: low order model

Authors: N. P. Yadav, Deepti Verma

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This paper focuses on the mathematical modeling for solidification of Al alloy in a cube mould cavity to study the solidification behavior of casting process. The parametric investigation of solidification process inside the cavity was performed by using computational solidification/melting model coupled with Volume of fluid (VOF) model. The implicit filling algorithm is used in this study to understand the overall process from the filling stage to solidification in a model metal casting process. The model is validated with past studied at same conditions. The solidification process are analyzed by including the effect of pouring velocity and temperature of liquid metal, effect of wall temperature as well natural convection from the wall and geometry of the cavity. These studies show the possibility of various defects during solidification process.

Keywords: buoyancy driven flow, natural convection driven flow, residual flow, secondary flow, volume of fluid

Procedia PDF Downloads 417

Authors: Junfeng Yan, Wenkui Hou

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Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

Procedia PDF Downloads 377

Authors: Syed Adnan, Javed Iqbal

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In urban and rural areas groundwater is the most economic natural source of drinking. Groundwater resources of Pakistan are degraded due to high population growth and increased industrial development. A study was conducted in district Peshawar to assess groundwater vulnerable zones using GIS based DRASTIC model. Six input parameters (groundwater depth, groundwater recharge, aquifer material, soil type, slope and hydraulic conductivity) were used in the DRASTIC model to generate the groundwater vulnerable zones. Each parameter was divided into different ranges or media types and a subjective rating from 1-10 was assigned to each factor where 1 represented very low impact on pollution potential and 10 represented very high impact. Weight multiplier from 1-5 was used to balance and enhance the importance of each factor. The DRASTIC model scores obtained varied from 47 to 147. Using quantile classification scheme these values were reclassified into three zones i.e. low, moderate and high vulnerable zones. The areas of these zones were calculated. The final result indicated that about 400 km2, 506 km2, and 375 km2 were classified as low, moderate, and high vulnerable areas, respectively. It is recommended that the most vulnerable zones should be treated on first priority to facilitate the inhabitants for drinking purposes.

Keywords: DRASTIC model, groundwater vulnerability, GIS in groundwater, drinking sources

Procedia PDF Downloads 451

Authors: Wang Zhulin, Min Fuhong, Peng Guangya, Wang Yaoda, Cao Yi

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In this paper, a magnetron memristor model based on hyperbolic sine function is presented and the correctness proved by studying the trajectory of its voltage and current phase, and then a memristor chaotic system with the memristor model is presented. The phase trajectories and the bifurcation diagrams and Lyapunov exponent spectrum of the magnetron memristor system are plotted by numerical simulation, and the chaotic evolution with changing the parameters of the system is also given. The paper includes numerical simulations and mathematical model, which confirming that the system, has a wealth of dynamic behavior.

Keywords: memristor, chaotic circuit, dynamical behavior, chaotic system

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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There has been a need in recent years to predict student academic achievement prior to graduation. This is to assist them in improving their grades, especially for those who have struggled in the past. The purpose of this research is to use supervised learning techniques to create a model that predicts student academic progress. Many scholars have developed models that predict student academic achievement based on characteristics including smoking, demography, culture, social media, parent educational background, parent finances, and family background, to mention a few. This element, as well as the model used, could have misclassified the kids in terms of their academic achievement. As a prerequisite to predicting if the student will perform well in the future on related courses, this model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester. With a 96.7 percent accuracy, the model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost. This model is offered as a desktop application with user-friendly interfaces for forecasting student academic progress for both teachers and students. As a result, both students and professors are encouraged to use this technique to predict outcomes better.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

Procedia PDF Downloads 109

Authors: Mesbaholdin Salami, Farzad Movahedi Sobhani, Mohammad Sadegh Ghazizadeh

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Evaluation of organizational performance is among the most important measures that help organizations and entities continuously improve their efficiency. Organizations can use the existing data and results from the comparison of units under investigation to obtain an estimation of their performance. The Malmquist Productivity Index (MPI) is an important index in the evaluation of overall productivity, which considers technological developments and technical efficiency at the same time. This article proposed a model based on the multistage MPI, considering limited data (Grey’s theory). This model can evaluate the performance of units using limited and uncertain data in a multistage process. It was applied by the electricity market manager to Iran’s electric power supply chain (EPSC), which contains uncertain data, to evaluate the performance of its actors. Results from solving the model showed an improvement in the accuracy of future performance of the units under investigation, using the Grey’s system theory. This model can be used in all case studies, in which MPI is used and there are limited or uncertain data.

Keywords: Malmquist Index, Grey's Theory, CCR Model, network data envelopment analysis, Iran electricity power chain

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Authors: Pirom Thangchitpianpol, Suttipong Jumroonrut

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This research investigates the distribution of food demand for animal food and the optimum amount of that food production at minimum cost. The data consist of customer purchase orders for the food of laying hens, price of food for laying hens, cost per unit for the food inventory, cost related to food of laying hens in which the food is out of stock, such as fine, overtime, urgent purchase for material. They were collected from January, 1990 to December, 2013 from a factory in Nakhonratchasima province. The collected data are analyzed in order to explore the distribution of the monthly food demand for the laying hens and to see the rate of inventory per unit. The results are used in a stochastic linear programming model for aggregate planning in which the optimum production or minimum cost could be obtained. Programming algorithms in MATLAB and tools in Linprog software are used to get the solution. The distribution of the food demand for laying hens and the random numbers are used in the model. The study shows that the distribution of monthly food demand for laying has a normal distribution, the monthly average amount (unit: 30 kg) of production from January to December. The minimum total cost average for 12 months is Baht 62,329,181.77. Therefore, the production planning can reduce the cost by 14.64% from real cost.

Keywords: animal food, stochastic linear programming, aggregate planning, production planning, demand uncertainty

Procedia PDF Downloads 380

Authors: Kuo-Chun Chien, Chia-Hui Chang, Ren-Der Sun

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Legal Judgment Prediction (LJP) is a subtask for legal AI. Its main purpose is to use the facts of a case to predict the judgment result. In Taiwan's criminal procedure, when prosecutors complete the investigation of the case, they will decide whether to prosecute the suspect and which article of criminal law should be used based on the facts and evidence of the case. In this study, we collected 305,240 indictments from the public inquiry system of the procuratorate of the Ministry of Justice, which included 169 charges and 317 articles from 21 laws. We take the crime facts in the indictments as the main input to jointly learn the prediction model for law source, article, and charge simultaneously based on the pre-trained Bert model. For single article cases where the frequency of the charge and article are greater than 50, the prediction performance of law sources, articles, and charges reach 97.66, 92.22, and 60.52 macro-f1, respectively. To understand the big performance gap between articles and charges, we used a bipartite graph to visualize the relationship between the articles and charges, and found that the reason for the poor prediction performance was actually due to the wording precision. Some charges use the simplest words, while others may include the perpetrator or the result to make the charges more specific. For example, Article 284 of the Criminal Law may be indicted as “negligent injury”, "negligent death”, "business injury", "driving business injury", or "non-driving business injury". As another example, Article 10 of the Drug Hazard Control Regulations can be charged as “Drug Control Regulations” or “Drug Hazard Control Regulations”. In order to solve the above problems and more accurately predict the article and charge, we plan to include the article content or charge names in the input, and use the sentence-pair classification method for question-answer problems in the BERT model to improve the performance. We will also consider a sequence-to-sequence approach to charge prediction.

Keywords: legal judgment prediction, deep learning, natural language processing, BERT, data visualization

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Authors: Lucie Jirotková, Daniel Macek, Andrea Palazzo, Veronika Malinová

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Currently, the implementation of 3D models in the construction industry is gaining popularity. Countries around the world are developing their own modelling standards and implement the use of 3D models into their individual permitting processes. Another theme that needs to be addressed are public building spaces and their subsequent maintenance, where the usage of BIM methodology is directly offered. The significant benefit of the implementation of Building Information Management is the information transfer. The 3D model contains not only the spatial representation of the item shapes but also various parameters that are assigned to the individual elements, which are easily traceable, mainly because they are all stored in one place in the BIM model. However, it is important to keep the data in the models up to date to achieve useability of the model throughout the life cycle of the building. It is now becoming standard practice to use BIM models in the construction of buildings, however, the building environment is very often neglected. Especially in large-scale development projects, the public space of buildings is often forwarded to municipalities, which obtains the ownership and are in charge of its maintenance. A 3D model of the building surroundings would include both the above-ground visible elements of the development as well as the underground parts, such as the technological facilities of water features, electricity lines for public lighting, etc. The paper shows the possibilities of a model in the field of information for the handover of premises, the following maintenance and decision making. The attributes and spatial representation of the individual elements make the model a reliable foundation for the creation of "Smart Cities". The paper analyses the current use of the BIM methodology and presents the state-of-the-art possibilities of development.

Keywords: BIM model, urban space, BIM methodology, facility management

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Authors: Yasemin Akar, Jan G. Wissink, Herlina Herlina

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The effect of various levels of contamination on the interfacial air–water gas transfer velocity is studied by Direct Numerical Simulation (DNS). The interfacial gas transfer is driven by isotropic turbulence, introduced at the bottom of the computational domain, diffusing upwards. The isotropic turbulence is generated in a separate, concurrently running the large-eddy simulation (LES). The flow fields in the main DNS and the LES are solved using fourth-order discretisations of convection and diffusion. To solve the transport of dissolved gases in water, a fifth-order-accurate WENO scheme is used for scalar convection combined with a fourth-order central discretisation for scalar diffusion. The damping effect of the surfactant contamination on the near surface (horizontal) velocities in the DNS is modelled using horizontal gradients of the surfactant concentration. An important parameter in this model, which corresponds to the level of contamination, is ReMa⁄We, where Re is the Reynolds number, Ma is the Marangoni number, and We is the Weber number. It was previously found that even small levels of contamination (ReMa⁄We small) lead to a significant drop in the interfacial gas transfer velocity KL. It is known that KL depends on both the Schmidt number Sc (ratio of the kinematic viscosity and the gas diffusivity in water) and the surface divergence β, i.e. K_L∝√(β⁄Sc). Previously it has been shown that this relation works well for surfaces with low to moderate contamination. However, it will break down for β close to zero. To study the validity of this dependence in the presence of surface contamination, simulations were carried out for ReMa⁄We=0,0.12,0.6,1.2,6,30 and Sc = 2, 4, 8, 16, 32. First, it will be shown that the scaling of KL with Sc remains valid also for larger ReMa⁄We. This is an important result that indicates that - for various levels of contamination - the numerical results obtained at low Schmidt numbers are also valid for significantly higher and more realistic Sc. Subsequently, it will be shown that - with increasing levels of ReMa⁄We - the dependency of KL on β begins to break down as the increased damping of near surface fluctuations results in an increased damping of β. Especially for large levels of contamination, this damping is so severe that KL is found to be underestimated significantly.

Keywords: contamination, gas transfer, surfactants, turbulence

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Authors: Yunhui Sun, Qingquan Liu, Xiaoliang Wang

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Dense granular flows widely exist in geological flows such as debris flow, landslide, or sheet flow, where both the interparticle and solid-liquid interactions are important to modify the flow. So, a two-phase approach with both phases correctly modelled is important for a better investigation of the saturated granular flows. However, a proper closure model covering a wide range of flowing states for the solid phase is still lacking. This study first employs a chute flow experiment based on the refractive index matching method, which makes it possible to obtain internal flow information such as velocity, shear rate, granular fluctuation, and volume fraction. The granular stress is obtained based on a steady assumption. The kinetic theory is found to describe the stress dependence on the flow state well. More importantly, the granular rheology is found to be frictionally dominated under weak shear and collisionally dominated under strong shear. The results presented thus provide direct experimental evidence on a possible frictional-collisional closure model for the granular phase. The data indicates that both frictional stresses exist over a wide range of the volume fraction, though traditional theory believes it vanishes below a critical volume fraction. Based on the findings, a two-phase model is used to simulate the chute flow. Both phases are modelled as continuum media, and the inter-phase interactions, such as drag force and pressure gradient force, are considered. The frictional-collisional model is used for the closure of the solid phase stress. The profiles of the kinematic properties agree well with the experiments. This model is further used to simulate immersed granular collapse, which is unsteady in nature, to study the applicability of this model, which is derived from steady flow.

Keywords: closure model, collision, friction, granular flow, two-phase model

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Authors: Arth Bohra, Marwa Mahmoud

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In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

Procedia PDF Downloads 173

Authors: Kefaya Qaddoum

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The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: neural network, conformal prediction, cancer classification, regression

Procedia PDF Downloads 291

Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R²) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: time series modelling, ARIMA model, river runoff, Karkheh River, CLS method

Procedia PDF Downloads 341

Authors: Natasha Sharma, Kulbhushan Agnihotri

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Cellular Automata are discrete dynamical systems which are based on local character and spatial disparateness of the spreading process. These factors are generally neglected by traditional models based on differential equations for epidemic spread. The aim of this work is to introduce an SEIR model based on cellular automata on graphs to imitate epidemic spreading. Distinctively, it is an SEIR-type model where the population is divided into susceptible, exposed, infected and recovered individuals. The results obtained from simulations are in accordance with the spreading behavior of a real time epidemics.

Keywords: cellular automata, epidemic spread, graph, susceptible

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Authors: M. Jerold, V. Sivasubramanian

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This study reports the removal of Malachite Green (MG) from simulated wastewater by using marine macro algae Ulva lactuca. Batch biosorption experiments were carried out to determine the biosorption capacity. The biosorption capacity was found to be maximum at pH 10. The effect of various other operation parameters such as biosorbent dosage, initial dye concentration, contact time and agitation was also investigated. The equilibrium attained at 120 min with 0.1 g/L of biosorbent. The isotherm experimental data fitted well with Langmuir Model with R² value of 0.994. The maximum Langmuir biosorption capacity was found to be 76.92 mg/g. Further, Langmuir separation factor RL value was found to be 0.004. Therefore, the adsorption is favorable. The biosorption kinetics of MG was found to follow pseudo second-order kinetic model. The mechanistic study revealed that the biosorption of malachite onto Ulva lactuca was controlled by film diffusion. The solute transfer in a solid-liquid adsorption process is characterized by the film diffusion and/or particle diffusion. Thermodynamic study shows ΔG° is negative indicates the feasibility and spontaneous nature for the biosorption of malachite green. The biosorbent was characterized using Scanning Electron Microscopy, Fourier Transform Infrared Spectroscopy, and elemental analysis (CHNS: Carbon, Hydrogen, Nitrogen, Sulphur). This study showed that Ulva lactuca can be used as promising biosorbent for the removal of MG from wastewater.

Keywords: biosorption, Ulva lactuca, wastewater, malachite green, isotherm, kinetics

Procedia PDF Downloads 157

Authors: Cinthia Campoverde, Mateo Benavidez, Victor Arias, Milton Torres

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This article evaluates and compares three propagation models: the Okumura-Hata model, the Ericsson 9999 model, and the SUI model. The inclusion of vegetation attenuation in the area is also taken into account. These mathematical models aim to predict the power loss between a transmitting antenna (Tx) and a receiving antenna (Rx). The study was conducted in the open areas of the Livestock Department at the Escuela Superior Politécnica de Chimborazo (ESPOCH) University, located in the city of Riobamba, Ecuador. The necessary parameters for each model were calculated, considering LTE technology. The transmitting antenna belongs to the mobile phone company ”TUENTI” in Band 2, operating at a frequency of 1940 MHz. The reception power data in the area were empirically measured using the ”Network Cell Info” application. A total of 170 samples were collected, distributed across 19 radius, forming concentric circles around the transmitting antenna. The results demonstrate that the Okumura Hata urban model provides the best fit to the measured data.

Keywords: propagation models, reception power, LTE, power losses, correction factor

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Authors: Gilbert Makanda

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The problem of the teaching of mathematics is studied using differential equations. A mathematical model for knowledge acquisition in mathematics is developed. In this study we adopt the mathematical model that is normally used for disease modelling in the teaching of mathematics. It is assumed that teaching is 'infecting' students with knowledge thereby spreading this knowledge to the students. It is also assumed that students who gain this knowledge spread it to other students making disease model appropriate to adopt for this problem. The results of this study show that increasing recruitment rates, learning contact with teachers and learning materials improves the number of knowledgeable students. High dropout rates and forgetting taught concepts also negatively affect the number of knowledgeable students. The developed model is then solved using Matlab ODE45 and \verb"lsqnonlin" to estimate parameters for the actual data.

Keywords: differential equations, knowledge acquisition, least squares, dynamical systems

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Authors: Lele Zhang, Hui Leng Choo, Alexander Konyukhov, Shuguang Li

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Finite Element (FE) model of simplified e-bike structure was generated by main frame with two tiers, which consisted of pipe, mass, beam, and shell elements (pipe 289, beam188, shell 181, shell 281, combin14, link11, mass21). These elements would be introduced and demonstrated using mathematical formulas. Based on coupling theory, constrain equations was proposed. Exporting all the parameters obtained from theory part, the connection stiffness matrix of the whole e-bike structure between each of these elements was detected.

Keywords: coupling theory, stiffness matrix, e-bike, finite element model

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Authors: Pin-Ju Juan, Peng-Yu Juan, Yi-Shan Chen

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The main purpose of this paper is to present a fuzzy Analytic Network Process (ANP) model for the hostel organizational performance selection. In this article, we created 39 criteria for selecting hostel organizational performance acquired from literature's review and experts method practical investigations, and the methods of fuzzy analytic network process are used to consolidate decision-makers’ assessments about criteria weightings. Finally, we selected organizational performance of a hostel in Taiwan to determine the effectiveness of the proposed evaluation model in this paper.

Keywords: Fuzzy ANP, hostel, organizational performance, strategy management

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Authors: Raymond Chi Fai Si Tou, Jacey Ja Young Choe, Amy Siu Ian So

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Smart hotels can be defined as the hotel which has an intelligent system, through digitalization and networking which achieve hotel management and service information. In addition, smart hotels include high-end designs that integrate information and communication technology with hotel management fulfilling the guests’ needs and improving the quality, efficiency and satisfaction of hotel management. The purpose of this study is to identify appropriate factors that may influence guests’ satisfaction and intention to revisit Smart Hotels based on service quality measurement of lodging quality index and extended UTAUT theory. Unified Theory of Acceptance and Use of Technology (UTAUT) is adopted as a framework to explain technology acceptance and use. Since smart hotels are technology-based infrastructure hotels, UTATU theory could be as the theoretical background to examine the guests’ acceptance and use after staying in smart hotels. The UTAUT identifies four key drivers of the adoption of information systems: performance expectancy, effort expectancy, social influence, and facilitating conditions. The extended UTAUT modifies the definitions of the seven constructs for consideration; the four previously cited constructs of the UTAUT model together with three new additional constructs, which including hedonic motivation, price value and habit. Thus, the seven constructs from the extended UTAUT theory could be adopted to understand their intention to revisit smart hotels. The service quality model will also be adopted and integrated into the framework to understand the guests’ intention of smart hotels. There are rare studies to examine the service quality on guests’ satisfaction and intention to revisit in smart hotels. In this study, Lodging Quality Index (LQI) will be adopted to measure the service quality in smart hotels. Using integrated UTAUT theory and service quality model because technological applications and services require using more than one model to understand the complicated situation for customers’ acceptance of new technology. Moreover, an integrated model could provide more perspective insights to explain the relationships of the constructs that could not be obtained from only one model. For this research, ten in-depth interviews are planned to recruit this study. In order to confirm the applicability of the proposed framework and gain an overview of the guest experience of smart hotels from the hospitality industry, in-depth interviews with the hotel guests and industry practitioners will be accomplished. In terms of the theoretical contribution, it predicts that the integrated models from the UTAUT theory and the service quality will provide new insights to understand factors that influence the guests’ satisfaction and intention to revisit smart hotels. After this study identifies influential factors, smart hotel practitioners could understand which factors may significantly influence smart hotel guests’ satisfaction and intention to revisit. In addition, smart hotel practitioners could also provide outstanding guests experience by improving their service quality based on the identified dimensions from the service quality measurement. Thus, it will be beneficial to the sustainability of the smart hotels business.

Keywords: intention to revisit, guest satisfaction, qualitative interviews, smart hotels

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Authors: Boukhris Lahouari

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Simulation of solar dryers with ANSYS has revolutionized the way in which drying processes are optimized and analyzed in various industries. This advanced software allows engineers and researchers to simulate the behavior of a solar dryer under different conditions, helping to improve efficiency and reduce energy consumption. This work presents a numerical study of a direct solar dryer, which uses radiation and natural convection to dry agricultural products. The simulations were made in order to determine the dynamic and thermal fields under the influence of the variation in the size of the inlet and outlet opening. The conservation equations based on the standard k-ε turbulence model are solved by the finite volume method using the ANSYS-Fluent commercial code.

Keywords: solar dryer, CFD, solar radiation, natural convection, turbulent flow

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Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

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This paper deals with different modeling aspects of masonry infill: no infill model, Layered shell infill model, and strut infill model. These models consider the complicated behavior of the in-filled plane frames under lateral load similar to an earthquake load. Three strut infill models are used: NBCC (2005) strut infill model, ASCE/SEI 41-06 strut infill model and proposed strut infill model based on modification to Canadian, NBCC (2005) strut infill model. Pushover and modal analyses of a masonry infill concrete frame with a single storey and an existing 5-storey RC building have been carried out by using different models for masonry infill. The corresponding hinge status, the value of base shear at target displacement as well as their dynamic characteristics have been determined and compared. A validation of the structural numerical models for the existing 5-storey RC building has been achieved by comparing the experimentally measured and the analytically estimated natural frequencies and their mode shapes. This study shows that ASCE/SEI 41-06 equation underestimates the values for the equivalent properties of the diagonal strut while Canadian, NBCC (2005) equation gives realistic values for the equivalent properties. The results indicate that both ASCE/SEI 41-06 and Canadian, NBCC (2005) equations for strut infill model give over estimated values for dynamic characteristic of the building. Proposed modification to Canadian, NBCC (2005) equation shows that the fundamental dynamic characteristic values of the building are nearly similar to the corresponding values using layered shell elements as well as measured field results.

Keywords: masonry infill, framed structures, RC buildings, non-structural elements

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Authors: Nattabhorn Leamcharaskul

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This study aims to examine determining factors of the dynamics of poverty in Thailand by using panel data of 3,567 households in 2007-2017. Four techniques of estimation are employed to analyze the situation of poverty across households and time periods: the multinomial logit model, the sequential logit model, the quantile regression model, and the difference in difference model. Households are categorized based on their experiences into 5 groups, namely chronically poor, falling into poverty, re-entering into poverty, exiting from poverty and never poor households. Estimation results emphasize the effects of demographic and socioeconomic factors as well as unexpected events on the economic status of a household. It is found that remittances have positive impact on household’s economic status in that they are likely to lower the probability of falling into poverty or trapping in poverty while they tend to increase the probability of exiting from poverty. In addition, not only receiving a secondary source of household income can raise the probability of being a never poor household, but it also significantly increases household income per capita of the chronically poor and falling into poverty households. Public work programs are recommended as an important tool to relieve household financial burden and uncertainty and thus consequently increase a chance for households to escape from poverty.

Keywords: difference in difference, dynamic, multinomial logit model, panel data, poverty, quantile regression, remittance, sequential logit model, Thailand, transfer

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Authors: Van-Thanh Ho, Jaiyoung Ryu

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In soft robotics, the optimization of fluid dynamics through pneumatic methods plays a pivotal role in enhancing operational efficiency and reducing energy loss. This is particularly crucial when replacing conventional techniques such as cable-driven electromechanical systems. The pneumatic model employed in this study represents a sophisticated framework designed to efficiently channel pressure from a high-pressure reservoir to various muscle locations on the robot's body. This intricate network involves a branching system of tubes. The study introduces a comprehensive pneumatic model, encompassing the components of a reservoir, tubes, and Pneumatically Actuated Muscles (PAM). The development of this model is rooted in the principles of shock tube theory. Notably, the study leverages experimental data to enhance the understanding of the interplay between the PAM structure and the surrounding fluid. This improved interactive approach involves the use of morphing motion, guided by a contraction function. The study's findings demonstrate a high degree of accuracy in predicting pressure distribution within the PAM. The model's predictive capabilities ensure that the error in comparison to experimental data remains below a threshold of 10%. Additionally, the research employs a machine learning model, specifically a surrogate model based on the Kriging method, to assess and quantify uncertainty factors related to the initial reservoir pressure and tube diameter. This comprehensive approach enhances our understanding of pneumatic soft robotics and its potential for improved operational efficiency.

Keywords: pneumatic artificial muscles, pressure drop, morhing motion, branched network, surrogate model

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Authors: A. Jomartov, A. Tuleshov, B. Tultaev

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One of the main tasks in the development of textile machinery is to increase the rapidity of automatic looms, and consequently, their productivity. With increasing automatic loom speeds, the dynamic loads on their separate mechanisms and moving joints sharply increase. Dynamic research allows us to determine the weakest mechanisms of the automatic loom. The modern automatic loom consists of a large number of structurally different mechanisms. These are cam, lever, gear, friction and combined cyclic mechanisms. The modern automatic loom contains various mechatronic devices: A device for the automatic removal of faulty weft, electromechanical drive warp yarns, electronic controllers, servos, etc. In the paper, we consider the multibody dynamic model of the automatic loom on the software complex SimulationX. SimulationX is multidisciplinary software for modeling complex physical and technical facilities and systems. The multibody dynamic model of the automatic loom allows consideration of: The transition processes, backlash at the joints and nodes, the force of resistance and electric motor performance.

Keywords: automatic loom, dynamics, model, multibody, SimulationX

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Authors: Samia Ait Ali Yahia

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Several steles with Libyan inscriptions were discovered in Grande Kabylia (Algeria), but very few researchers were interested in these inscriptions. Our work is to list, if possible all these steles in order to do a descriptive study of the corpus. The steles analysis will be focused on the iconographic and epigraphic level and on the different forms of Libyan characters in order to highlight the alphabet used by the Grande Kabylia.

Keywords: epigraphy, stele, Libyan inscription, Grande Kabylia

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Authors: Arellano Karina, Diego Avila-Pesántez, Leticia Vaca-Cárdenas, Alberto Arellano, Carmen Mantilla

Abstract:

Nowadays, security threats in Voice over IP (VoIP) systems are an essential and latent concern for people in charge of security in a corporate network, because, every day, new Denial-of-Service (DoS) attacks are developed. These affect the business continuity of an organization, regarding confidentiality, availability, and integrity of services, causing frequent losses of both information and money. The purpose of this study is to establish the necessary measures to mitigate DoS threats, which affect the availability of VoIP systems, based on the Session Initiation Protocol (SIP). A Security Model called MS-DoS-SIP is proposed, which is based on two approaches. The first one analyzes the recommendations of international security standards. The second approach takes into account weaknesses and threats. The implementation of this model in a VoIP simulated system allowed to minimize the present vulnerabilities in 92% and increase the availability time of the VoIP service into an organization.

Keywords: Denial-of-Service SIP attacks, MS-DoS-SIP, security model, VoIP-SIP vulnerabilities

Procedia PDF Downloads 203

Authors: Pawel Skruch, Marek Dlugosz

Abstract:

The paper starts with a general model of the temperature dynamics in buildings. The modelling approach relies on thermodynamics, in particular heat transfer, principles. The model considers heat loses by conduction and ventilation and internal heat gains. The parameters of the model can be determined uniquely from the geometry of the building and from thermal properties of construction materials. The model is presented using state space notation and this form is used in the control design procedure. A sliding surface is defined by the system output and the desired trajectory. The control law is designed to force the trajectory of the system from any initial condition to the sliding surface in finite time. The trajectory of the system after reaching the sliding surface remains on it. A simulation example is included to verify the approach and to demonstrate the achievable performance improvement by the proposed solution in the temperature control in buildings.

Keywords: modelling, building, temperature dynamics, sliding-mode control, sliding surface

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Authors: Tracy Smith-Carrier

Abstract:

In 1995, the World Health Organization declared that poverty was the biggest killer and the greatest cause of suffering in the world. Income is certainly a key social determinant of health, the lack of which causes innumerable health and mental health conditions. In seeking to provide relief from financial hardship for residents within their populace, states in the Global North have largely turned to the non-profit and charitable sector. The stigma and shame of accessing charity is a significant barrier for many, but what is more problematic is that the embrace of the charitable model has let governments off the hook from responding to their international human rights obligations. Although states are signatories to various human rights treaties and conventions internationally, many of these laws have not been implemented domestically. This presentation explores the limits of the charitable model in addressing poverty in countries of the Global North. Unlike in the ages passed, when poverty was thought to be an individual problem, we now know that poverty is largely systemic in nature. In this presentation, we will identify the structural determinants of poverty, outline why people are reticent to access charitable programs and services and how income security is reproduced through the charitable model, and discuss evidence-informed solutions, such as a basic income guarantee, to move beyond the charitable model in favour of a rights-based justice model. To move beyond charity, we must demand that governments recognize our fundamental human rights and address poverty and hunger using a justice model based on substantive human rights.

Keywords: basic income, charity, poverty, income security, hunger, food security, social justice, human rights

Procedia PDF Downloads 117