Search results for: Software modeling.

Authors: N. Mantalay, N. Chakpitak, W. Janchai, P. Sureepong

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Work-life balance has been acknowledged and promoted for the sake of employee retention. It is essential for a manager to realize the human resources situation within a company to help employees work happily and perform at their best. This paper suggests knowledge management and critical thinking are useful to motivate employees to think about their work-life balance. A qualitative case study is presented, which aimed to discover the meaning of work-life balance-s meaning from the perspective of Thai knowledge workers and how it affects their decision-making towards work resignation. Results found three types of work-life balance dimensions; a work- life balance including a workplace and a private life setting, an organizational working life balance only, and a worklife balance only in a private life setting. These aspects all influenced the decision-making of the employees. Factors within a theme of an organizational work-life balance were involved with systematic administration, fair treatment, employee recognition, challenging assignments to gain working experience, assignment engagement, teamwork, relationship with superiors, and working environment, while factors concerning private life settings were about personal demands such as an increasing their salary or starting their own business.

Keywords: knowledge management, work-life balance, knowledge workers, decision-making, critical thinking, diverse workforce

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Authors: Dima Stopel, Zvi Boger, Robert Moskovitch, Yuval Shahar, Yuval Elovici

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Computer worm detection is commonly performed by antivirus software tools that rely on prior explicit knowledge of the worm-s code (detection based on code signatures). We present an approach for detection of the presence of computer worms based on Artificial Neural Networks (ANN) using the computer's behavioral measures. Identification of significant features, which describe the activity of a worm within a host, is commonly acquired from security experts. We suggest acquiring these features by applying feature selection methods. We compare three different feature selection techniques for the dimensionality reduction and identification of the most prominent features to capture efficiently the computer behavior in the context of worm activity. Additionally, we explore three different temporal representation techniques for the most prominent features. In order to evaluate the different techniques, several computers were infected with five different worms and 323 different features of the infected computers were measured. We evaluated each technique by preprocessing the dataset according to each one and training the ANN model with the preprocessed data. We then evaluated the ability of the model to detect the presence of a new computer worm, in particular, during heavy user activity on the infected computers.

Keywords: Artificial Neural Networks, Feature Selection, Temporal Analysis, Worm Detection.

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Authors: Babak Dizangian, Mohammad Reza Ghasemi, Akram Ghalandari

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Moment frames have considerable ductility against cyclic lateral loads and displacements; however, if this feature causes the relative displacement to exceed the permissible limit, it can impose unfavorable hysteretic behavior on the frame. Therefore, adding a bracing system with the capability of preserving the capacity of high energy absorption and controlling displacements without a considerable increase in the stiffness is quite important. This paper investigates the retrofitting of a single storey steel moment frame through a delayed wire-rope bracing system using a middle steel plate. In this model, the steel plate lies where the wire ropes meet, and the model geometry is such that the cables are continuously under tension so that they can take the most advantage of the inherent potential they have in tolerating tensile stress. Using the steel plate also reduces the system stiffness considerably compared to cross bracing systems and preserves the ductile frame’s energy absorption capacity. In this research, the software models of delayed wire-rope bracing system have been studied, validated, and compared with other researchers’ laboratory test results.

Keywords: Ductile moment frame, delayed wire rope bracing, cyclic loading, hysteresis curve, energy absorption.

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Authors: J. Modu, J. F. Georgin, L. Briançon, E. Antoinet

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Wind turbine gravity foundations are designed to resist overturning failure through gravitational forces resulting from their masses. Owing to the relatively high volume of the cementitious material present, the foundations tend to suffer thermal strains and internal cracking due to high temperatures and temperature gradients depending on factors such as geometry, mix design and level of restraint. This is a result of a fully coupled mechanism commonly known as THMC (Thermo- Hygro - Mechanical - Chemical) coupling whose kinetics peak during the early age of concrete. The focus of this paper is therefore to present and offer a discussion on the temperature and humidity evolutions occurring in mass pours such as wind turbine gravity foundations based on sensor results obtained from the monitoring of an actual wind turbine foundation. To offer prediction of the evolutions, the formulation of a 3D Thermal-Hydro-Chemical (THC) model that is mainly derived from classical fundamental physical laws is also presented and discussed. The THC model can be mathematically fully coupled in Finite Element analyses. In the current study, COMSOL Multi-physics software was used to simulate the 3D THC coupling that occurred in the monitored wind turbine foundation to predict the temperature evolution at five different points within the foundation from time of casting.

Keywords: Early age behavior, reinforced concrete, THC 3D models, wind turbines.

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Authors: Mofid Gorjibandpy, Mehdi Kazemi Sangsereki

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In a bi-fuel diesel engine, the carburetor plays a vital role in switching from fuel gas to petrol mode operation and viceversa. The carburetor is the most important part of the fuel system of a diesel engine. All diesel engines carry variable venturi mixer carburetors. The basic operation of the carburetor mainly depends on the restriction barrel called the venturi. When air flows through the venturi, its speed increases and its pressure decreases. The main challenge focuses on designing a mixing device which mixes the supplied gas is the incoming air at an optimum ratio. In order to surmount the identified problems, the way fuel gas and air flow in the mixer have to be analyzed. In this case, the Computational Fluid Dynamics or CFD approach is applied in design of the prototype mixer. The present work is aimed at further understanding of the air and fuel flow structure by performing CFD studies using a software code. In this study for mixing air and gas in the condition that has been mentioned in continuance, some mixers have been designed. Then using of computational fluid dynamics, the optimum mixer has been selected. The results indicated that mixer with 12 holes can produce a homogenous mixture than those of 8-holes and 6-holes mixer. Also the result showed that if inlet convergency was smoother than outlet divergency, the mixture get more homogenous, the reason of that is in increasing turbulence in outlet divergency.

Keywords: Computational Fluid Dynamics, Venturi mixer, Air-fuel ratio, Turbulence.

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Authors: Mi Sook Lee

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The number of the companies accepting RFID in Korea has been increased continuously due to the domestic development of information technology. The acceptance of RFID by companies in Korea enabled them to do business with many global enterprises in a much more efficient and effective way. According to a survey[33, p76], many companies in Korea have used RFID for inventory or distribution manages. But, the use of RFID in the companies in Korea is in the early stages and its potential value hasn-t fully been realized yet. At this time, it would be very important to investigate the factors that affect RFID acceptance. For this study, many previous studies were referenced and some RFID experts were interviewed. Through the pilot test, four factors were selected - Security Trust, Employee Knowledge, Partner Influence, Service Provider Trust - affecting RFID acceptance and an extended technology acceptance model(e-TAM) was presented with those factors. The proposed model was empirically tested using data collected from employees in companies or public enterprises. In order to analyze some relationships between exogenous variables and four variables in TAM, structural equation modeling(SEM) was developed and SPSS12.0 and AMOS 7.0 were used for analyses. The results are summarized as follows: 1) security trust perceived by employees positively influences on perceived usefulness and perceived ease of use; 2) employee-s knowledge on RFID positively influences on only perceived ease of use; 3) a partner-s influence for RFID acceptance positively influences on only perceived usefulness; 4) service provider trust very positively influences on perceived usefulness and perceived ease of use 5) the relationships between TAM variables are the same as the previous studies.

Keywords: RFID, TAM, Security Trust, Employee Knowledge, Partner Influence, Service Provider Trust.

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Authors: Andrew Hwang

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The average American worker sits for thirteen hours a day, often with poor posture and infrequent breaks, which can lead to health issues and back problems. The Smart Cushion was created to alert individuals of their poor postures, and may potentially alleviate back problems and correct poor posture. The Smart Cushion is a portable, rectangular, foam cushion, with five strategically placed pressure sensors, that utilizes an Arduino Uno circuit board and specifically designed software, allowing it to collect data from the five pressure sensors and store the data on an SD card. The data is then compiled into graphs and compared to controlled postures. Before volunteers sat on the cushion, their levels of back pain were recorded on a scale from 1-10. Data was recorded for an hour during sitting, and then a new, corrected posture was suggested. After using the suggested posture for an hour, the volunteers described their level of discomfort on a scale from 1-10. Different patterns of sitting postures were generated that were able to serve as early warnings of potential back problems. By using the Smart Cushion, the areas where different volunteers were applying the most pressure while sitting could be identified, and the sitting postures could be corrected. Further studies regarding the relationships between posture and specific regions of the body are necessary to better understand the origins of back pain; however, the Smart Cushion is sufficient for correcting sitting posture and preventing the development of additional back pain.

Keywords: Arduino Sketch Algorithm, biomedical technology, pressure sensors, Smart Cushion.

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Authors: Zohreh Orshesh

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In this study, a 3D combustion chamber was simulated using FLUENT 6.32. Aims to obtain accurate information about the profile of the combustion in the furnace and also check the effect of oxygen enrichment on the combustion process. Oxygen enrichment is an effective way to reduce combustion pollutant. The flow rate of air to fuel ratio is varied as 1.3, 3.2 and 5.1 and the oxygen enriched flow rates are 28, 54 and 68 lit/min. Combustion simulations typically involve the solution of the turbulent flows with heat transfer, species transport and chemical reactions. It is common to use the Reynolds-averaged form of the governing equation in conjunction with a suitable turbulence model. The 3D Reynolds Averaged Navier Stokes (RANS) equations with standard k-ε turbulence model are solved together by Fluent 6.3 software. First order upwind scheme is used to model governing equations and the SIMPLE algorithm is used as pressure velocity coupling. Species mass fractions at the wall are assumed to have zero normal gradients.Results show that minimum mole fraction of CO2 happens when the flow rate ratio of air to fuel is 5.1. Additionally, in a fixed oxygen enrichment condition, increasing the air to fuel ratio will increase the temperature peak. As a result, oxygen-enrichment can reduce the CO2 emission at this kind of furnace in high air to fuel rates.

Keywords: Combustion chamber, Oxygen enrichment, Reynolds Averaged Navier- Stokes, CO2 emission

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Authors: Moustafa Osman Mohammed

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This paper will explore formation of HCl aerosol at atmospheric boundary layers and encourages the uptake of environmental modeling systems (EMSs) as a practice evaluation of gaseous emissions (“framework measures”) from small and medium-sized enterprises (SMEs). The conceptual model predicts greenhouse gas emissions to ecological points beyond landfill site operations. It focuses on incorporation traditional knowledge into baseline information for both measurement data and the mathematical results, regarding parameters influence model variable inputs. The paper has simplified parameters of aerosol processes based on the more complex aerosol process computations. The simple model can be implemented to both Gaussian and Eulerian rural dispersion models. Aerosol processes considered in this study were (i) the coagulation of particles, (ii) the condensation and evaporation of organic vapors, and (iii) dry deposition. The chemical transformation of gas-phase compounds is taken into account photochemical formulation with exposure effects according to HCl concentrations as starting point of risk assessment. The discussion set out distinctly aspect of sustainability in reflection inputs, outputs, and modes of impact on the environment. Thereby, models incorporate abiotic and biotic species to broaden the scope of integration for both quantification impact and assessment risks. The later environmental obligations suggest either a recommendation or a decision of what is a legislative should be achieved for mitigation measures of landfill gas (LFG) ultimately.

Keywords: Air dispersion model, landfill management, spatial analysis, environmental impact and risk assessment.

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Authors: Jasim. A. Ghaeb

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A high performance computer includes a fast processor and millions bytes of memory. During the data processing, huge amount of information are shuffled between the memory and processor. Because of its small size and its effectiveness speed, cache has become a common feature of high performance computers. Enhancing cache performance proved to be essential in the speed up of cache-based computers. Most enhancement approaches can be classified as either software based or hardware controlled. The performance of the cache is quantified in terms of hit ratio or miss ratio. In this paper, we are optimizing the cache performance based on enhancing the cache hit ratio. The optimum cache performance is obtained by focusing on the cache hardware modification in the way to make a quick rejection to the missed line's tags from the hit-or miss comparison stage, and thus a low hit time for the wanted line in the cache is achieved. In the proposed technique which we called Even- Odd Tabulation (EOT), the cache lines come from the main memory into cache are classified in two types; even line's tags and odd line's tags depending on their Least Significant Bit (LSB). This division is exploited by EOT technique to reject the miss match line's tags in very low time compared to the time spent by the main comparator in the cache, giving an optimum hitting time for the wanted cache line. The high performance of EOT technique against the familiar mapping technique FAM is shown in the simulated results.

Keywords: Caches, Cache performance, Hit time, Cache hit ratio, Cache mapping, Cache memory.

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Authors: Tasneem Halawani, Yamen Khateeb

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With customers’ ever-increasing expectations for fast services provisioning for all their business needs, information technology (IT) organizations, as business partners, have to cope with this demanding environment and deliver their services in the most effective and efficient way. The purpose of this paper is to identify optimization and automation opportunities for the top requested IT services in a heterogenic digital environment and widely spread customer base. In collaboration with systems, processes, and subject matter experts (SMEs), the processes in scope were approached by analyzing four-year related historical data, identifying and surveying stakeholders, modeling the as-is processes, and studying systems integration/automation capabilities. This effort resulted in identifying several pain areas, including standardization, unnecessary customer and IT involvement, manual steps, systems integration, and performance measurement. These pain areas were addressed by standardizing the top five requested IT services, eliminating/automating 43 steps, and utilizing a single platform for end-to-end process execution. In conclusion, the optimization of IT service request processes in a heterogenic digital environment and widely spread customer base is challenging, yet achievable without compromising the service quality and customers’ added value. Further studies can focus on measuring the value of the eliminated/automated process steps to quantify the enhancement impact. Moreover, a similar approach can be utilized to optimize other IT service requests, with a focus on business criticality.

Keywords: Automation, customer value, heterogenic, integration, IT services, optimization, processes.

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: Conditional Generative Adversarial Net, market and credit risk management, neural network, time series.

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Authors: Eun Mi Ryu, Ah Young An, Ji Yeon Kang, Yeong Soo Shin, Hee Sun Kim

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When high strength reinforced concrete is exposed to high temperature due to a fire, deteriorations occur such as loss in strength and elastic modulus, cracking and spalling of the concrete. Therefore, it is important to understand risk of structural safety in building structures by studying structural behaviors and rehabilitation of fire damaged high strength concrete structures. This paper aims at investigating rehabilitation effect on fire damaged high strength concrete beams using experimental and analytical methods. In the experiments, flexural specimens with high strength concrete are exposed to high temperatures according to ISO 834 standard time temperature curve. From four-point loading test, results show that maximum loads of the rehabilitated beams are similar to or higher than those of the non-fire damaged RC beam. In addition, structural analyses are performed using ABAQUS 6.10-3 with same conditions as experiments to provide accurate predictions on structural and mechanical behaviors of rehabilitated RC beams. The parameters are the fire cover thickness and strengths of repairing mortar. Analytical results show good rehabilitation effects, when the results predicted from the rehabilitated models are compared to structural behaviors of the non-damaged RC beams. In this study, fire damaged high strength concrete beams are rehabilitated using polymeric cement mortar. The predictions from the finite element (FE) models show good agreements with the experimental results and the modeling approaches can be used to investigate applicability of various rehabilitation methods for further study.

Keywords: Fire, High strength concrete, Rehabilitation, Reinforced concrete beam.

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Authors: Amri Yusoff, Shahrizuan Shafiril, Ashardi Abas, Norma Che Yusoff

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Nowadays, illegal logging has been causing many effects including flash flood, avalanche, global warming, and etc. The purpose of this study was to maintain the earth ecosystem by keeping and regulate Malaysia’s treasurable rainforest by utilizing a new technology that will assist in real-time alert and give faster response to the authority to act on these illegal activities. The methodology of this research consisted of design stages that have been conducted as well as the system model and system architecture of the prototype in addition to the proposed hardware and software that have been mainly used such as microcontroller, sensor with the implementation of GSM, and GPS integrated system. This prototype was deployed at Royal Belum forest in December 2014 for phase 1 and April 2015 for phase 2 at 21 pinpoint locations. The findings of this research were the capture of data in real-time such as temperature, humidity, gaseous, fire, and rain detection which indicate the current natural state and habitat in the forest. Besides, this device location can be detected via GPS of its current location and then transmitted by SMS via GSM system. All of its readings were sent in real-time for further analysis. The data that were compared to meteorological department showed that the precision of this device was about 95% and these findings proved that the system is acceptable and suitable to be used in the field.

Keywords: Remote monitoring system, forest data, GSM, GPS, wireless sensor.

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Authors: Jeong-Woo Seo, Jin-Seung Choi, Dong-Won Kang, Jae-Hyuk Bae, Gye-Rae Tack

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To achieve accurate and precise results of finite element analysis (FEA) of bones, it is important to represent the load/boundary conditions as identical as possible to the human body such as the bone properties, the type and force of the muscles, the contact force of the joints, and the location of the muscle attachment. In this study, the difference in the Von-Mises stress and the total deformation was compared by classifying them into Case 1, which shows the actual anatomical form of the muscle attached to the femur when the same muscle force was applied, and Case 2, which gives a simplified representation of the attached location. An inverse dynamical musculoskeletal model was simulated using data from an actual walking experiment to complement the accuracy of the muscular force, the input value of FEA. The FEA method using the results of the muscular force that were calculated through the simulation showed that the maximum Von-Mises stress and the maximum total deformation in Case 2 were underestimated by 8.42% and 6.29%, respectively, compared to Case 1. The torsion energy and bending moment at each location of the femur occurred via the stress ingredient. Due to the geometrical/morphological feature of the femur of having a long bone shape when the stress distribution is wide, as shown in Case 1, a greater Von-Mises stress and total deformation are expected from the sum of the stress ingredients. More accurate results can be achieved only when the muscular strength and the attachment location in the FEA of the bones and the attachment form are the same as those in the actual anatomical condition under the various moving conditions of the human body.

Keywords: Musculoskeletal modeling, Finite element analysis, Von-Mises stress, Deformation, Muscle attachment.

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Authors: Amira Kheriji Abbes, Faouzi Bouani, Mekki Ksouri

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Model Predictive Control (MPC) is an established control technique in a wide range of process industries. The reason for this success is its ability to handle multivariable systems and systems having input, output or state constraints. Neverthless comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprisers as well as a transformer of organizations and markets. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In this paper, we propose an efficient firmware for the implementation of constrained MPC in the performed STM32 microcontroller using interior point method. Indeed, performances study shows good execution speed and low computational burden. These results encourage to develop predictive control algorithms to be programmed in industrial standard processes. The PID anti windup controller was also implemented in the STM32 in order to make a performance comparison with the MPC. The main features of the proposed constrained MPC framework are illustrated through two examples.

Keywords: Embedded software, microcontroller, constrainedModel Predictive Control, interior point method, PID antiwindup, Keil tool, C/Cµ language.

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Authors: R. Bharanidaran, B. T. Ramesh

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High precision in motion is required to manipulate the micro objects in precision industries for micro assembly, cell manipulation etc. Precision manipulation is achieved based on the appropriate mechanism design of micro devices such as microgrippers. Design of a compliant based mechanism is the better option to achieve a highly precised and controlled motion. This research article highlights the method of designing a compliant based three fingered microgripper suitable for holding asymmetric objects. Topological optimization technique, a systematic method is implemented in this research work to arrive a topologically optimized design of the mechanism needed to perform the required micro motion of the gripper. Optimization technique has a drawback of generating senseless regions such as node to node connectivity and staircase effect at the boundaries. Hence, it is required to have post processing of the design to make it manufacturable. To reduce the effect of post processing stage and to preserve the edges of the image, a cubic spline interpolation technique is introduced in the MATLAB program. Structural performance of the topologically developed mechanism design is tested using finite element method (FEM) software. Further the microgripper structure is examined to find its fatigue life and vibration characteristics.

Keywords: Compliant mechanism, Cubic spline interpolation, FEM, Topology optimization.

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Authors: Abilio Avila, Orestis Terzidis

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A fundamental principle of Grounded Theory (GT) is to prevent the formation of preconceived theories. This implies the need to start a research study with an open mind and to avoid being absorbed by the existing literature. However, to start a new study without an understanding of the research domain and its context can be extremely challenging. This paper presents a research approach that simultaneously supports a researcher to identify and to focus on critical areas of a research project and prevent the formation of prejudiced concepts by the current body of literature. This approach comprises of four stages: Selection of secondary case studies, analysis of secondary case studies, development of an initial conceptual framework, development of an initial interview guide. The analysis of secondary case studies as a starting point for a research project allows a researcher to create a first understanding of a research area based on real-world cases without being influenced by the existing body of theory. It enables a researcher to develop through a structured course of actions a firm guide that establishes a solid starting point for further investigations. Thus, the described approach may have significant implications for GT researchers who aim to start a study within a given research area.

Keywords: Grounded theory, qualitative research, secondary case studies, secondary data analysis, interview guide.

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Authors: Sandu L., Topală F., Porojan S.

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Restoration of endodontically treated teeth is a common problem in dentistry, related to the fractures occurring in such teeth and to concentration of forces little information regarding variation of basic preparation guidelines in stress distribution has been available. To date, there is still no agreement in the literature about which material or technique can optimally restore endodontically treated teeth. The aim of the present study was to evaluate the influence of the core height and restoration materials on corono-radicular restored upper first premolar. The first step of the study was to achieve 3D models in order to analyze teeth, dowel and core restorations and overlying full ceramic crowns. The FEM model was obtained by importing the solid model into ANSYS finite element analysis software. An occlusal load of 100 N was conducted, and stresses occurring in the restorations, and teeth structures were calculated. Numerical simulations provide a biomechanical explanation for stress distribution in prosthetic restored teeth. Within the limitations of the present study, it was found that the core height has no important influence on the stress generated in coronoradicular restored premolars. It can be drawn that the cervical regions of the teeth and restorations were subjected to the highest stress concentrations.

Keywords: 3D models, finite element analysis, dowel and core restoration, full ceramic crown, premolars, structural simulations.

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Authors: Karchung, S. Ruangsinchaiwanich

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This paper presents open-loop vector control method of induction motor with space vector pulse width modulation (SVPWM) technique. Normally, the closed loop speed control is preferred and is believed to be more accurate. However, it requires a position sensor to track the rotor position which is not desirable to use it for certain workspace applications. This paper exhibits the performance of three-phase induction motor with the simplest control algorithm without the use of a position sensor nor an estimation block to estimate rotor position for sensorless control. The motor stator currents are measured and are transformed to synchronously rotating (d-q-axis) frame by use of Clarke and Park transformation. The actual control happens in this frame where the measured currents are compared with the reference currents. The error signal is fed to a conventional PI controller, and the corrected d-q voltage is generated. The controller outputs are transformed back to three phase voltages and are fed to SVPWM block which generates PWM signal for the voltage source inverter. The open loop vector control model along with SVPWM algorithm is modeled in MATLAB/Simulink software and is experimented and validated in TMS320F28335 DSP board.

Keywords: Electric drive, induction motor, open-loop vector control, space vector pulse width modulation technique.

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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, Production planning, Demand Uncertainty.

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Authors: A. Zaidi, F. Khelifi, R. Masmoudi, M. Bouhicha

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5

In order to eradicate the degradation of reinforced concrete structures due to the steel corrosion, professionals in constructions suggest using fiber reinforced polymers (FRP) for their excellent properties. Nevertheless, high temperatures may affect the bond between FRP bar and concrete, and consequently the serviceability of FRP-reinforced concrete structures. This paper presents a nonlinear numerical investigation using ADINA software to investigate the effect of the spacing between glass FRP (GFRP) bars embedded in concrete on circumferential thermal deformations and the distribution of radial thermal cracks in reinforced concrete beams submitted to high temperature variations up to 60 °C for asymmetrical problems. The thermal deformations predicted from nonlinear finite elements model, at the FRP bar/concrete interface and at the external surface of concrete cover, were established as a function of the ratio of concrete cover thickness to FRP bar diameter (c/d_b) and the ratio of spacing between FRP bars in concrete to FRP bar diameter (e/d_b). Numerical results show that the circumferential thermal deformations at the external surface of concrete cover are linear until cracking thermal load varied from 32 to 55 °C corresponding to the ratio of e/d_b varied from 1.3 to 2.3, respectively. However, for ratios e/d_b >2.3 and c/d_b >1.6, the thermal deformations at the external surface of concrete cover exhibit linear behavior without any cracks observed on the specified surface. The numerical results are compared to those obtained from analytical models validated by experimental tests.

Keywords: Concrete beam, FRP bars, spacing effect, thermal deformation.

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Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

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A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme Gradient Boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impairment, multiclass classification, ADNI, support vector machine, random forest.

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Authors: Anjan Kumar Kakati, M. Chandrasekaran, Amitava Mandal, Amit Kumar Singh

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End milling process is one of the common metal cutting operations used for machining parts in manufacturing industry. It is usually performed at the final stage in manufacturing a product and surface roughness of the produced job plays an important role. In general, the surface roughness affects wear resistance, ductility, tensile, fatigue strength, etc., for machined parts and cannot be neglected in design. In the present work an experimental investigation of end milling of aluminium alloy with carbide tool is carried out and the effect of different cutting parameters on the response are studied with three-dimensional surface plots. An artificial neural network (ANN) is used to establish the relationship between the surface roughness and the input cutting parameters (i.e., spindle speed, feed, and depth of cut). The Matlab ANN toolbox works on feed forward back propagation algorithm is used for modeling purpose. 3-12-1 network structure having minimum average prediction error found as best network architecture for predicting surface roughness value. The network predicts surface roughness for unseen data and found that the result/prediction is better. For desired surface finish of the component to be produced there are many different combination of cutting parameters are available. The optimum cutting parameter for obtaining desired surface finish, to maximize tool life is predicted. The methodology is demonstrated, number of problems are solved and algorithm is coded in Matlab®.

Keywords: End milling, Surface roughness, Neural networks.

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Authors: Nicolò Vaiana, Giorgio Serino

Abstract:

In this paper, a one-dimensional (1d) Parallel Elasto- Plastic Model (PEPM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement, is presented. The parallel modeling concept is applied to discretize the continuously decreasing tangent stiffness function, thus allowing to simulate the dynamic behavior of seismic isolation bearings by putting linear elastic and nonlinear elastic-perfectly plastic elements in parallel. The mathematical model has been validated by comparing the experimental force-displacement hysteresis loops, obtained testing a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted numerically. Good agreement between the simulated and experimental results shows that the proposed model can be an effective numerical tool to predict the forcedisplacement relationship of seismic isolators within relatively large displacements. Compared to the widely used Bouc-Wen model, the proposed one allows to avoid the numerical solution of a first order ordinary nonlinear differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort, and requires the evaluation of only three model parameters from experimental tests, namely the initial tangent stiffness, the asymptotic tangent stiffness, and a parameter defining the transition from the initial to the asymptotic tangent stiffness.

Keywords: Base isolation, earthquake engineering, parallel elasto-plastic model, seismic isolators, softening hysteresis loops.

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Authors: U. Yerlikaya, R. T. Balkan

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In this research, a method is developed to obtain high-dimensional configuration space for path planning problems. In typical cases, the path planning problems are solved directly in the 3-dimensional (D) workspace. However, this method is inefficient in handling the robots with various geometrical and mechanical restrictions. To overcome these difficulties, path planning may be formalized and solved in a new space which is called configuration space. The number of dimensions of the configuration space comes from the degree of freedoms of the system of interest. The method can be applied in two ways. In the first way, the point clouds of all the bodies of the system and interaction of them are used. The second way is performed via using the clearance function of simulation software where the minimum distances between surfaces of bodies are simultaneously measured. A double-turret system is held in the scope of this study. The 4-D configuration space of a double-turret system is obtained in these two ways. As a result, the difference between these two methods is around 1%, depending on the density of the point cloud. The disparity between the two forms steadily decreases as the point cloud density increases. At the end of the study, in order to verify 4-D configuration space obtained, 4-D path planning problem was realized as 2-D + 2-D and a sample path planning is carried out with using A* algorithm. Then, the accuracy of the configuration space is proved using the obtained paths on the simulation model of the double-turret system.

Keywords: A* Algorithm, autonomous turrets, high-dimensional C-Space, manifold C-Space, point clouds.

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Authors: M. Alqhatani, S. Bajwa, S. Setunge

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Metropolitan areas have suffered from traffic problems, which have steadily increased in many monocentric cities. Urban expansion, population growth, and road network development have resulted in a structural shift toward urban sprawl, increasing commuters’ dependence on private modes of transport. This paper aims to model the influence of socioeconomic and land-use factors on mode choice using a multinomial and nested logit model. Land-use patterns—such as residential, commercial, retail, educational and employment related—affect the choice of mode and destination in the short and medium term. Socioeconomic factors—such as age, gender, income, household size, and house type—also affect choice, while residential location is affected in the long term. Riyadh in Saudi Arabia and Melbourne in Australia were chosen as case studies. Riyadh is a car-dependent city with limited public transport, whereas Melbourne has good public transport but an increase in car dependence. Aggregate level land-use data and disaggregate level individual, household, and journey-to-work data are used to determine the effects of land use and socioeconomic factors on mode choice. The model results determined that urban sprawl is the main factor that affects mode choice, income, and house type.

Keywords: Socioeconomic, land use, mode choice, multinomial logit and nested logit.

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Authors: Mahnaz Hosseinzadeh, Shaghayegh Rezaee Amiri

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This paper presents a methodology for serial production planning problem in wire and cable manufacturing process that addresses the problem of input-output imbalance in different consecutive stations, hoping to minimize the halt of machines in each stage. To this end, a linear Goal Programming (GP) model is developed, in which four main categories of constraints as per the number of runs per machine, machines’ sequences, acceptable inventories of machines at the end of each period, and the necessity of fulfillment of the customers’ orders are considered. The model is formulated based upon on the real data obtained from IKO TAK Company, an important supplier of wire and cable for oil and gas and automotive industries in Iran. By solving the model in GAMS software the optimal number of runs, end-of-period inventories, and the possible minimum idle time for each machine are calculated. The application of the numerical results in the target company has shown the efficiency of the proposed model and the solution in decreasing the lead time of the end product delivery to the customers by 20%. Accordingly, the developed model could be easily applied in wire and cable companies for the aim of optimal production planning to reduce the halt of machines in manufacturing stages.

Keywords: Serial manufacturing process, production planning, wire and cable industry, goal programming approach.

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Authors: Ehi E. Aimiuwu

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As of 2017, many online learning professionals, institutions, and journals are still wondering how instructors can keep student engaged in the online learning environment to facilitate active learning effectively. The purpose of this qualitative single-case and narrative research is to explore whether online professors understand their role as mentors and facilitators of students’ academic success by keeping students engaged in active learning based on personalized experience in the field. Data collection tools that were used in the study included an NVivo 12 Plus qualitative software, an interview protocol, a digital audiotape, an observation sheet, and a transcription. Seven online professors in the United States from LinkedIn and residencies were interviewed for this study. Eleven online teaching techniques from previous research were used as the study framework. Data analysis process, member checking, and key themes were used to achieve saturation. About 85.7% of professors agreed on rubric as the preferred online grading technique. About 57.1% agreed on professors logging in daily, students logging in about 2-5 times weekly, knowing students to increase accountability, email as preferred communication tool, and computer access for adequate online learning. About 42.9% agreed on syllabus for clear class expectations, participation to show what has been learned, and energizing students for creativity.

Keywords: Class facilitation, class management, online teaching, online education, pedagogy.

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Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

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As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the CPU, RAM, and ROM memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles.

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