Search results for: Critical control

Authors: H. R. Kazemi Nia, A. Yeganeh Fallah

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Without uncertainty by applying external loads on beams, bending is created. The created bending in I-beams, puts one of the flanges in tension and the other one in compression. With increasing of bending, compression flange buckled and beam in out of its plane direction twisted, this twisting well-known as Lateral Torsional Buckling. Providing bending moment varieties along the beam, the critical moment is greater than the case its under pure bending. In other words, the value of bending gradient coefficient is always greater than unite. In this article by the use of " ANSYS 10.0" software near 80 3-D finite element models developed for the propose of analyzing beams` lateral torsional buckling and surveying influence of slenderness on beams' bending gradient coefficient. Results show that, presented Cb coefficient via AISC is not correct for some of beams and value of this coefficient is smaller than what proposed by AISC. Therefore instead of using a constant Cb for each case of loading , a function with two criterion for calculation of Cb coefficient for some cases is proposed.

Keywords: Beams critical moment, Bending Gradient Coefficient, finite element, Lateral Torsional Buckling

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Authors: HaeNa Lee, Sun K. Yoo

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Volume rendering is widely used in medical CT image visualization. Applying 3D image visualization to diagnosis application can require accurate volume rendering with high resolution. Interpolation is important in medical image processing applications such as image compression or volume resampling. However, it can distort the original image data because of edge blurring or blocking effects when image enhancement procedures were applied. In this paper, we proposed adaptive tension control method exploiting gradient information to achieve high resolution medical image enhancement in volume visualization, where restored images are similar to original images as much as possible. The experimental results show that the proposed method can improve image quality associated with the adaptive tension control efficacy.

Keywords: Tension control, Interpolation, Ray-casting, Medical imaging analysis.

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Authors: P. Karimi, A. H. Khedmati Bazkiaei

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The main goal of this study is to test differential neural network as a controller of smart structure and is to enumerate its advantages and disadvantages in comparison with other controllers. In this study, the smart structure has been considered as a Euler Bernoulli cantilever beam and it has been tried that it be under control with the use of vibration neural network resulting from movement. Also, a linear observer has been considered as a reference controller and has been compared its results. The considered vibration charts and the controlled state have been recounted in the final part of this text. The obtained result show that neural observer has better performance in comparison to the implemented linear observer.

Keywords: Smart material, on-line differential artificial neural network, active control, finite element method.

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Authors: C. Kalamani, V. Abishek Karthick, S. Anitha, K. Kavin Kumar

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The fault tolerant system plays a crucial role in the critical applications which are being used in the present scenario. A fault may change the functionality of circuits. Aim of this paper is to design multiplier using fault tolerant hybrid full adder. Fault tolerant hybrid full adder is designed to check and repair any fault in the circuit using self-checking circuit and the self-repairing circuit. Further, the use of conventional logic circuits may result in more area, delay as well as power consumption. In order to reduce these parameters of the circuit, GDI (Gate Diffusion Input) techniques with less number of transistors are used compared to conventional full adder circuit. This reduces the area, delay and power consumption. The proposed method solves the major problems occurring in the most crucial and critical applications.

Keywords: Gate diffusion input, hybrid full adder, self-checking, fault tolerant.

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Authors: Ali Al-Zughaibi, Huw Davies

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The purpose of this paper is to present a modeling and control of a quarter-car active suspension system with unknown mass, unknown time-delay and road disturbance. The objective of designing the controller is to derive a control law to achieve stability of the system and convergence that can considerably improve ride comfort and road disturbance handling. This is accomplished by using Routh-Hurwitz criterion based on defined parameters. Mathematical proof is given to show the ability of the designed controller to ensure the target of design, implementation with the active suspension system and enhancement dispersion oscillation of the system despite these problems. Simulations were also performed to control quarter car suspension, where the results obtained from these simulations verify the validity of the proposed design.

Keywords: Active suspension system, disturbance rejection, dynamic uncertainty, time-delay.

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Authors: Patil Ashwini, Archana Thosar

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This paper addresses the mathematical model of wind energy system useful for designing fault tolerant control. To serve the demand of power, large capacity wind energy systems are vital. These systems are installed offshore where non planned service is very costly. Whenever there is a fault in between two planned services, the system may stop working abruptly. This might even lead to the complete failure of the system. To enhance the reliability, the availability and reduce the cost of maintenance of wind turbines, the fault tolerant control systems are very essential. For designing any control system, an appropriate mathematical model is always needed. In this paper, the two-mass model is modified by considering the frequent mechanical faults like misalignments in the drive train, gears and bearings faults. These faults are subject to a wear process and cause frictional losses. This paper addresses these faults in the mathematics of the wind energy system. Further, the work is extended to study the variations of the parameters namely generator inertia constant, spring constant, viscous friction coefficient and gear ratio; on the pole-zero plot which is related with the physical design of the wind turbine. Behavior of the wind turbine during drive train faults are simulated and briefly discussed.

Keywords: Mathematical model of wind energy system, stability analysis, shaft stiffness, viscous friction coefficient, gear ratio, generator inertia, fault tolerant control.

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Authors: Hazly Amir, Roime Puniran

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This paper will present the implementation of QoS policy based system by utilizing rules on Access Control List (ACL) over Layer 3 (L3) switch. Also presented is the architecture on that implementation; the tools being used and the result were gathered. The system architecture has an ability to control ACL rules which are installed inside an external L3 switch. ACL rules used to instruct the way of access control being executed, in order to entertain all traffics through that particular switch. The main advantage of using this approach is that the single point of failure could be prevented when there are any changes on ACL rules inside L3 switches. Another advantage is that the agent could instruct ACL rules automatically straight away based on the changes occur on policy database without configuring them one by one. Other than that, when QoS policy based system was implemented in distributed environment, the monitoring process can be synchronized easily due to the automate process running by agent over external policy devices.

Keywords: QOS, ACL, L3 Switch.

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Authors: Muhibul Haque Bhuyan

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In the current context, the engineering program educators need to think about how to develop the concepts and complex engineering problem-solving skills through various complex engineering activities by the undergraduate engineering students in various engineering courses. But most of them are facing challenges to assess and evaluate these skills of their students. In this study, detailed assessment and evaluation methods for the undergraduate Electrical and Electronic Engineering (EEE) program are stated using the Outcome-Based Education (OBE) approach. For this purpose, a final year course titled control systems has been selected. The assessment and evaluation approach, course contents, course objectives, course outcomes (COs), and their mapping to the program outcomes (POs) with complex engineering problems and activities via the knowledge profiles, performance indicators, rubrics of assessment, CO and PO attainment data, and other statistics, are reported for a student-cohort of control systems course registered by the students of BSc in EEE program in Spring 2021 Semester at the EEE Department of Southeast University (SEU). It is found that the target benchmark was achieved by the students of that course. Several recommendations for the continuous quality improvement (CQI) process are also provided.

Keywords: Complex engineering problem, knowledge profiles, OBE, control systems course, COs, PIs, POs, assessment rubrics.

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Authors: B. Dora Arul Selvi, .N. Kamaraj

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Transient Stability is an important issue in power systems planning, operation and extension. The objective of transient stability analysis problem is not satisfied with mere transient instability detection or evaluation and it is most important to complement it by defining fast and efficient control measures in order to ensure system security. This paper presents a new Fuzzy Support Vector Machines (FSVM) to investigate the stability status of power systems and a modified generation rescheduling scheme to bring back the identified unstable cases to a more economical and stable operating point. FSVM improves the traditional SVM (Support Vector Machines) by adding fuzzy membership to each training sample to indicate the degree of membership of this sample to different classes. The preventive control based on economic generator rescheduling avoids the instability of the power systems with minimum change in operating cost under disturbed conditions. Numerical results on the New England 39 bus test system show the effectiveness of the proposed method.

Keywords: Fuzzy Support Vector Machine (FSVM), Incremental Cost, Preventive Control, Transient stability

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Authors: H. Mansor, S. B. Mohd Noor

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This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. Nevertheless, usually there are large peaks in the deadbeat response. By integrating QFT specifications into deadbeat algorithm, the large peaks could be tolerated. On the other hand, emerging QFT with adaptive element will produce a robust controller with wider coverage of uncertainty. By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called selftuning QFT-based deadbeat controller could be achieved. The output response that is fast, robust and adaptive is expected. Using a grain dryer plant model as a pilot case-study, the performance of the proposed method has been evaluated and analyzed. Grain drying process is very complex with highly nonlinear behaviour, long delay, affected by environmental changes and affected by disturbances. Performance comparisons have been performed between the proposed self-tuning QFT-based deadbeat, standard QFT and standard dead-beat controllers. The efficiency of the self-tuning QFTbased dead-beat controller has been proven from the tests results in terms of controller’s parameters are updated online, less percentage of overshoot and settling time especially when there are variations in the plant.

Keywords: Deadbeat control, quantitative feedback theory (QFT), robust control, self-tuning control.

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Authors: Hadi Gholizadeh, Ali Tajdin

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To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.

Keywords: Goal programming, quality control, vague environment, disposable glasses’ optimization, fuzzy regression.

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Authors: M. Naserian, M. Jooshaki, M. Fotuhi-Firuzabad, M. Hossein Mohammadi Sanjani, A. Oraee

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In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a solution is presented to uncover consumers with high air conditioner demand among a large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.

Keywords: Data-driven analysis, demand response, direct load control, HVAC system.

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Authors: S. Yaman, S. Rostami

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In this study, a black box modeling of the coupled-tank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutionary computation method, genetic algorithm. All tuned controllers are applied to the fuzzy model of the coupled-tank experimental setup and analyzed under the different reference input values. According to the results, it is seen that function tuner method demonstrates better robust control performance and guarantees the closed loop stability.

Keywords: Function tuner method, fuzzy modeling, fuzzy PID controller, genetic algorithm.

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Authors: Feng Yang, Xuehai Zhou, Dalei Hu

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In this paper, we propose a general mandatory access framework for distributed systems. The framework can be applied into multiple operating systems and can handle multiple stakeholders. Despite considerable advancements in the area of mandatory access control, a certain approach to enforcing mandatory access control can only be applied in a specific operating system. Other than PC market in which windows captures the overwhelming shares, there are a number of popular operating systems in the emerging smart phone environment, i.e. Android, Windows mobile, Symbian, RIM. It should be noted that more and more stakeholders are involved in smartphone software, such as devices owners, service providers and application providers. Our framework includes three parts—local decision layer, the middle layer and the remote decision layer. The middle layer takes charge of managing security contexts, OS API, operations and policy combination. The design of the remote decision layer doesn’t depend on certain operating systems because of the middle layer’s existence. We implement the framework in windows, linux and other popular embedded systems.

Keywords: Mandatory Access Control, Distributed System, General Platform.

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Authors: Mert Turanli, Hakan Temeltas

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In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller.

Keywords: Adaptive control, Centroidal Voronoi Tessellations, composite adaptation, coordination.

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Authors: R.Vinodha S. Abraham Lincoln, J. Prakash

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Multi-loop (De-centralized) Proportional-Integral- Derivative (PID) controllers have been used extensively in process industries due to their simple structure for control of multivariable processes. The objective of this work is to design multiple-model adaptive multi-loop PID strategy (Multiple Model Adaptive-PID) and neural network based multi-loop PID strategy (Neural Net Adaptive-PID) for the control of multivariable system. The first method combines the output of multiple linear PID controllers, each describing process dynamics at a specific level of operation. The global output is an interpolation of the individual multi-loop PID controller outputs weighted based on the current value of the measured process variable. In the second method, neural network is used to calculate the PID controller parameters based on the scheduling variable that corresponds to major shift in the process dynamics. The proposed control schemes are simple in structure with less computational complexity. The effectiveness of the proposed control schemes have been demonstrated on the CSTR process, which exhibits dynamic non-linearity.

Keywords: Multiple-model Adaptive PID controller, Multivariableprocess, CSTR process.

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Authors: R. Prakash, B. Meenakshipriya, R. Kumaravelan

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Fresh water is one of the resources which is getting depleted day by day. A wise method to address this issue is by the application of renewable energy-sun irradiation and by means of decentralized, cheap, energetically self-sufficient, robust and simple to operate plants, distillates can be obtained from sea, river or even sewage. Solar desalination is a technique used to desalinate water using solar energy. The present work deals with the comprehensive design and simulation of solar tracking system using LabVIEW, temperature and mass flow rate control of the solar desalination plant using LabVIEW and also analysis of single phase inverter circuit with LC filters for solar pumping system in MATLAB. The main objective of this work is to improve the performance of solar desalination system using automatic tracking system, output control using temperature and mass flow rate control system and also to reduce the harmonic distortion in the solar pumping system by means of LC filters. The simulation of single phase inverter was carried out using MATLAB and the output waveforms were analyzed. Simulations were performed for optimum output temperature control, which in turn controls the mass flow rate of water in the thermal collectors. Solar tracking system was accomplished using LABVIEW and was tested successfully. The thermal collectors are tracked in accordance with the sun’s irradiance levels, thereby increasing the efficiency of the thermal collectors.

Keywords: Desalination, Electro dialysis, LabVIEW, MATLAB, PWM inverter, Reverse osmosis.

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Authors: Zhiguo Yang, Xiangan Yue, Minglu Shao, Yang Yue, Tianqi Yue

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In low permeability reservoirs, the reservoir pore throat is small and the micro heterogeneity is prominent. Conventional microsphere profile control agents generally have good injectability but poor plugging effect; however, profile control agents with good plugging effect generally have poor injectability, which makes it difficult for agent to realize deep profile control of reservoir. To solve this problem, styrene and acrylamide were used as monomers in the laboratory. Emulsion polymerization was used to prepare the Controllable Self-Aggregating Colloidal Particle (CSA), which was rich in amide group. The CSA microsphere dispersion solution with a particle diameter smaller than the pore throat diameter was injected into the reservoir to ensure that the profile control agent had good inject ability. After dispersing the CSA microsphere to the deep part of the reservoir, the CSA microspheres dispersed in static for a certain period of time will self-aggregate into large-sized particle clusters to achieve plugging of hypertonic channels. The CSA microsphere has the characteristics of low expansion and avoids shear fracture in the process of migration. It can be observed by transmission electron microscope that CSA microspheres still maintain regular and uniform spherical and core-shell heterogeneous structure after aging at 100 ºC for 35 days, and CSA microspheres have good thermal stability. The results of bottle test showed that with the increase of cation concentration, the aggregation time of CSA microspheres gradually shortened, and the influence of divalent cations was greater than that of monovalent ions. Physical simulation experiments show that CSA microspheres have good injectability, and the aggregated CSA particle clusters can produce effective plugging and migrate to the deep part of the reservoir for profile control.

Keywords: Heterogeneous reservoir, deep profile control, emulsion polymerization, colloidal particles, plugging characteristic.

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Authors: Mustafa Sahin, İlkay Yavrucuk

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This paper presents a wind turbine envelope protection control algorithm that protects Variable Speed Variable Pitch (VSVP) wind turbines from damage during operation throughout their below and above rated regions, i.e. from cut-in to cut-out wind speed. The proposed approach uses a neural network that can adapt to turbines and their operating points. An algorithm monitors instantaneous wind and turbine states, predicts a wind speed that would push the turbine to a pre-defined envelope limit and, when necessary, realizes an avoidance action. Simulations are realized using the MS Bladed Wind Turbine Simulation Model for the NREL 5 MW wind turbine equipped with baseline controllers. In all simulations, through the proposed algorithm, it is observed that the turbine operates safely within the allowable limit throughout the below and above rated regions. Two example cases, adaptations to turbine operating points for the below and above rated regions and protections are investigated in simulations to show the capability of the proposed envelope protection system (EPS) algorithm, which reduces excessive wind turbine loads and expectedly increases the turbine service life.

Keywords: Adaptive envelope protection control, limit detection and avoidance, neural networks, ultimate load reduction, wind turbine power control.

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Authors: P. Acharjee, S. K. Goswami

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Particle Swarm Optimization (PSO) with elite PSO parameters has been developed for power flow analysis under practical constrained situations. Multiple solutions of the power flow problem are useful in voltage stability assessment of power system. A method of determination of multiple power flow solutions is presented using a hybrid of Particle Swarm Optimization (PSO) and local search technique. The unique and innovative learning factors of the PSO algorithm are formulated depending upon the node power mismatch values to be highly adaptive with the power flow problems. The local search is applied on the pbest solution obtained by the PSO algorithm in each iteration. The proposed algorithm performs reliably and provides multiple solutions when applied on standard and illconditioned systems. The test results show that the performances of the proposed algorithm under critical conditions are better than the conventional methods.

Keywords: critical conditions, ill-conditioned systems, localsearch technique, multiple power flow solutions, particle swarmoptimization.

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Authors: Mohamad R. Khaldi, Christine S. Khoury, Guy M. Naim

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The steady-state operation of maintaining voltage stability is done by switching various controllers scattered all over the power network. When a contingency occurs, whether forced or unforced, the dispatcher is to alleviate the problem in a minimum time, cost, and effort. Persistent problem may lead to blackout. The dispatcher is to have the appropriate switching of controllers in terms of type, location, and size to remove the contingency and maintain voltage stability. Wrong switching may worsen the problem and that may lead to blackout. This work proposed and used a Fuzzy CMeans Clustering (FCMC) to assist the dispatcher in the decision making. The FCMC is used in the static voltage stability to map instantaneously a contingency to a set of controllers where the types, locations, and amount of switching are induced.

Keywords: Fuzzy logic, Power system control, Reactive power control, Voltage control

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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Authors: M. Zareiee, A. Dideban

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This paper addresses the problem of forbidden states in non safe Petri Nets. In the system, for preventing it from entering the forbidden states, some linear constraints can be assigned to them. Then these constraints can be enforced on the system using control places. But when the number of constraints in the system is large, a large number of control places must be added to the model of system. This concept complicates the model of system. There are some methods for reducing the number of constraints in safe Petri Nets. But there is no a systematic method for non safe Petri Nets. In this paper we propose a method for reducing the number of constraints in non safe Petri Nets which is based on solving an integer linear programming problem.

Keywords: discrete event system, Supervisory control, Petri Net, Constraint

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Authors: Waleed S. Alwaneen

Abstract:

In many countries, cow dung is used as farm manure and for biogas production. Several bacterial strains associated with cow dung such as Campylobacter, Salmonella sp. and Escherichia coli cause serious human diseases. The objective of the present study was to investigate the use of insect larvae including fruit beetle, waxworms and tiger worms to improve the breakdown of agricultural wastes and reduce their pathogen loads. Fresh cow faeces were collected from a cattle farm and distributed into plastic boxes (100 g/box). Each box was provided with 10 larvae of fruit beetle, Waxworms and Tiger worms, respectively. There were 3 replicates in each treatment including the control. Bacteria were isolated weekly from both control and cow faeces to which larvae were added to determine the bacterial populations. Results revealed that the bacterial load was higher in the cow faeces treated with fruit beetles than in the control, while the bacterial load was lower in the cow faeces treated with waxworms and tiger worms than in the control. The activities of the fruit beetle larvae led to the cow faeces being liquefied which provided a more conducive growing media for bacteria. Therefore, higher bacterial load in the cow faeces treated with fruit beetle might be attributed to the liquefaction of cow faeces.

Keywords: Fruit beetle, waxworms, tiger worms, waste conditioning, composting.

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Authors: A. P. Joshi, H. V. Warrior, J. P. Panda

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This paper is a continuation of the work carried out by various turbulence modelers in Oceanography on the topic of oceanic turbulent mixing. It evaluates the evolution of ocean water temperature and salinity by the appropriate modeling of turbulent mixing utilizing proper prescription of eddy viscosity. Many modelers in past have suggested including terms like shear, buoyancy and vorticity to be the parameters that decide the slow pressure strain correlation. We add to it the fact that dissipation anisotropy also modifies the correlation through eddy viscosity parameterization. This recalibrates the established correlation constants slightly and gives improved results. This anisotropization of dissipation implies that the critical Richardson’s number increases much beyond unity (to 1.66) to accommodate enhanced mixing, as is seen in reality. The model is run for a couple of test cases in the General Ocean Turbulence Model (GOTM) and the results are presented here.

Keywords: Anisotropy, GOTM, pressure-strain correlation, Richardson Critical number.

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Authors: M. Nikbakht, N. Choupani

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In this study the behavior of interlaminar fracture of carbon-epoxy thermoplastic laminated composite is investigated numerically and experimentally. Tests are performed with Arcan specimens. Testing with Arcan specimen gives the opportunity of utilizing just one kind of specimen for extracting fracture properties for mode I, mode II and different mixed mode ratios of materials with exerting load via different loading angles. Variation of loading angles in range of 0-90° made possible to achieve different mixed mode ratios. Correction factors for various conditions are obtained from ABAQUS 2D finite element models which demonstrate the finite shape of Arcan specimens used in this study. Finally, applying the correction factors to critical loads obtained experimentally, critical interlaminar fracture toughness of this type of carbon- epoxy composite has been attained.

Keywords: Fracture Mechanics, Mixed Mode, Arcan Specimen, Finite Element.

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Authors: M. Kassim, M. Ismail, K. Jumari, M.I Yusof

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this paper presented a survey analysis subjected on network bandwidth management from published papers referred in IEEE Explorer database in three years from 2009 to 2011. Network Bandwidth Management is discussed in today-s issues for computer engineering applications and systems. Detailed comparison is presented between published papers to look further in the IP based network critical research area for network bandwidth management. Important information such as the network focus area, a few modeling in the IP Based Network and filtering or scheduling used in the network applications layer is presented. Many researches on bandwidth management have been done in the broad network area but fewer are done in IP Based network specifically at the applications network layer. A few researches has contributed new scheme or enhanced modeling but still the issue of bandwidth management still arise at the applications network layer. This survey is taken as a basic research towards implementations of network bandwidth management technique, new framework model and scheduling scheme or algorithm in an IP Based network which will focus in a control bandwidth mechanism in prioritizing the network traffic the applications layer.

Keywords: Bandwidth Management (BM), IP Based network, modeling, algorithm, internet traffic, network Management, Quality of Service (QoS).

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Authors: Berardina De Carolis, Giovanni Cozzolongo

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In this paper, we present C@sa, a multiagent system aiming at modeling, controlling and simulating the behavior of an intelligent house. The developed system aims at providing to architects, designers and psychologists a simulation and control tool for understanding which is the impact of embedded and pervasive technology on people daily life. In this vision, the house is seen as an environment made up of independent and distributed devices, controlled by agents, interacting to support user's goals and tasks.

Keywords: Ambient intelligence, agent-based systems, influence diagrams.

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Authors: A. Ashfak, A. Saheed, K. K. Abdul Rasheed, J. Abdul Jaleel

Abstract:

This paper presents the design, fabrication and evaluation of magneto-rheological damper. Semi-active control devices have received significant attention in recent years because they offer the adaptability of active control devices without requiring the associated large power sources. Magneto-Rheological (MR) dampers are semi- active control devices that use MR fluids to produce controllable dampers. They potentially offer highly reliable operation and can be viewed as fail-safe in that they become passive dampers if the control hardware malfunction. The advantage of MR dampers over conventional dampers are that they are simple in construction, compromise between high frequency isolation and natural frequency isolation, they offer semi-active control, use very little power, have very quick response, has few moving parts, have a relax tolerances and direct interfacing with electronics. Magneto- Rheological (MR) fluids are Controllable fluids belonging to the class of active materials that have the unique ability to change dynamic yield stress when acted upon by an electric or magnetic field, while maintaining viscosity relatively constant. This property can be utilized in MR damper where the damping force is changed by changing the rheological properties of the fluid magnetically. MR fluids have a dynamic yield stress over Electro-Rheological fluids (ER) and a broader operational temperature range. The objective of this papert was to study the application of an MR damper to vibration control, design the vibration damper using MR fluids, test and evaluate its performance. In this paper the Rheology and the theory behind MR fluids and their use on vibration control were studied. Then a MR vibration damper suitable for vehicle suspension was designed and fabricated using the MR fluid. The MR damper was tested using a dynamic test rig and the results were obtained in the form of force vs velocity and the force vs displacement plots. The results were encouraging and greatly inspire further research on the topic.

Keywords: Magneto-rheological Fluid, MR Damper, Semiactive controller, Electro-rheological fluid.

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Authors: Bin Su

Abstract:

Auckland has a temperate climate with comfortable warm, dry summers and mild, wet winters. Auckland house design not only focus on winter thermal performance and indoor thermal condition, but also indoor moisture control, which is closely related to indirect health effects such as dust mites, fungi, etc. Most Auckland houses are designed to use temporary heating for winter indoor thermal comfort. Based on field study data of indoor microclimate conditions of two Auckland townhouses with a whole home mechanical ventilation system or a passive wind directional skylight vent, this study is to evaluate and compare indoor moisture conditions of two insulated townhouses only using temporary heating with different ventilation systems.

Keywords: House ventilation, house thermal design, indoor health condition, indoor moisture control.

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