Search results for: adaptive speed observer

Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

A self tuning PID control strategy using reinforcement learning is proposed in this paper to deal with the control of wind energy conversion systems (WECS). Actor-Critic learning is used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency, a single RBF neural network is used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for WECS and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.

Keywords: Wind energy conversion systems, reinforcementlearning; Actor-Critic learning; adaptive PID control; RBF network.

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Authors: Halim Djerroud, Arab Ali Cherif

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We assume that conscious functions are implemented automatically. In other words that consciousness as well as the non-consciousness aspect of human thought, planning and perception, are produced by biologically adaptive algorithms. We propose that the mechanisms of consciousness can be produced using similar adaptive algorithms to those executed by the mechanism. In this paper, we present a computational model of consciousness, the ”Global Abstraction Workspace” which is an internal environmental modelling perceived as a multi-agent system. This system is able to evolve and generate new data and processes as well as actions in the environment.

Keywords: Artificial consciousness, cognitive architecture, global abstraction workspace, mutli-agents system.

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Authors: Imron Rosyadi, Ridha A. Djemal, Saleh A. Alshebeili

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Design and implementation of a novel B-ACOSD CFAR algorithm is presented in this paper. It is proposed for detecting radar target in log-normal distribution environment. The BACOSD detector is capable to detect automatically the number interference target in the reference cells and detect the real target by an adaptive threshold. The detector is implemented as a System on Chip on FPGA Altera Stratix II using parallelism and pipelining technique. For a reference window of length 16 cells, the experimental results showed that the processor works properly with a processing speed up to 115.13MHz and processing time0.29 ┬Ás, thus meets real-time requirement for a typical radar system.

Keywords: CFAR, FPGA, radar.

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Authors: M. Umabharathi, S. Vijayabaskar

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Evolutionary Fuzzy PID Speed Controller for Permanent Magnet Synchronous Motor (PMSM) is developed to achieve the Speed control of PMSM in Closed Loop operation and to deal with the existence of transients. Consider a Fuzzy PID control design problem, based on common control Engineering Knowledge. If the transient error is big, that Good transient performance can be obtained by increasing the P and I gains and decreasing the D gains. To autotune the control parameters of the Fuzzy PID controller, the Evolutionary Algorithms (EA) are developed. EA based Fuzzy PID controller provides better speed control and guarantees the closed loop stability. The Evolutionary Fuzzy PID controller can be implemented in real time Applications without any concern about instabilities that leads to system failure or damage.

Keywords: Evolutionary Algorithm (EA), Fuzzy system, Genetic Algorithm (GA), Membership, Permanent Magnet Synchronous Motor (PMSM).

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Authors: Grzegorz Ulacha, Ryszard Stasiński

Abstract:

In the paper an effective context based lossless coding technique is presented. Three principal and few auxiliary contexts are defined. The predictor adaptation technique is an improved CoBALP algorithm, denoted CoBALP+. Cumulated predictor error combining 8 bias estimators is calculated. It is shown experimentally that indeed, the new technique is time-effective while it outperforms the well known methods having reasonable time complexity, and is inferior only to extremely computationally complex ones.

Keywords: Adaptive prediction, context coding, image losslesscoding, prediction error bias correction.

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Authors: Shiv Shankar Mishra, S. Wairya, R. K. Nagaria, S. Tiwari

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New methodologies for XOR-XNOR circuits are proposed to improve the speed and power as these circuits are basic building blocks of many arithmetic circuits. This paper evaluates and compares the performance of various XOR-XNOR circuits. The performance of the XOR-XNOR circuits based on TSMC 0.18μm process models at all range of the supply voltage starting from 0.6V to 3.3V is evaluated by the comparison of the simulation results obtained from HSPICE. Simulation results reveal that the proposed circuit exhibit lower PDP and EDP, more power efficient and faster when compared with best available XOR-XNOR circuits in the literature.

Keywords: Exclusive-OR (XOR), Exclusive-NOR (XNOR), High speed, Low power, Arithmetic Circuits.

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Authors: Armansyah, I. P. Almanar, M. Saiful Bahari Shaari, M. Shamil Jaffarullah, Nur’amirah Busu, M. Arif Fadzleen Zainal Abidin, M. Amlie A. Kasim

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During welding, the amount of heat present in weld zones determines the quality of weldment produced. Thus, the heat distribution characteristics and its magnitude in weld zones with respect to process variables such as tool pin-shoulder rotational and traveling speed during welding is analyzed using thermal finite element analyses method. For this purpose, transient thermal finite element analyses are performed to model the temperatures distribution and its quantities in weld-zones with respect to process variables such as rotational speed and traveling speed during welding. Commercially available software Altair HyperWork is used to model three-dimensional tool pin-shoulder vs. workpieces and to simulate the friction stir process. The results show that increasing tool rotational speed, at a constant traveling speed, will increase the amount of heat generated in weld-zones. In contrary, increasing traveling speed, at constant tool pin-shoulder rotational speeds, will reduce the amount of heat generated in weld zones.

Keywords: Frictions Stir Welding, Temperature Distribution, Finite Element Method, Altair Hyperwork.

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Authors: Mohd Fikri Azli bin Abdullah, Khairul Anwar bin Kamarul Hatta, Esther Jeganathan

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WiFi has become an essential technology that is widely used nowadays. It is famous due to its convenience to be used with mobile devices. This is especially true for Internet users worldwide that use WiFi connections. There are many location based services that are available nowadays which uses Wireless Fidelity (WiFi) signal fingerprinting. A common example that is gaining popularity in this era would be Foursquare. In this work, the WiFi signal would be used to estimate the user or client’s location. Similar to GPS, fingerprinting method needs a floor plan to increase the accuracy of location estimation. Still, the factor of inconsistent WiFi signal makes the estimation defer at different time intervals. Given so, an adaptive method is needed to obtain the most accurate signal at all times. WiFi signals are heavily distorted by external factors such as physical objects, radio frequency interference, electrical interference, and environmental factors to name a few. Due to these factors, this work uses a method of reducing the signal noise and estimation using the Nearest Neighbour based on past activities of the signal to increase the signal accuracy up to more than 80%. The repository yet increases the accuracy by using Artificial Neural Network (ANN) pattern matching. The repository acts as the server cum support of the client side application decision. Numerous previous works has adapted the methods of collecting signal strengths in the repository over the years, but mostly were just static. In this work, proposed solutions on how the adaptive method is done to match the signal received to the data in the repository are highlighted. With the said approach, location estimation can be done more accurately. Adaptive update allows the latest location fingerprint to be stored in the repository. Furthermore, any redundant location fingerprints are removed and only the updated version of the fingerprint is stored in the repository. How the location estimation of the user can be predicted would be highlighted more in the proposed solution section. After some studies on previous works, it is found that the Artificial Neural Network is the most feasible method to deploy in updating the repository and making it adaptive. The Artificial Neural Network functions are to do the pattern matching of the WiFi signal to the existing data available in the repository.

Keywords: Adaptive Repository, Artificial Neural Network, Location Estimation, Nearest Neighbour Euclidean Distance, WiFi RSSI Fingerprinting.

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Authors: Péter Restás, Andrea Czibor, Zsolt Péter Szabó

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Purpose: This article aims to rethink the phenomena of employee behavior as a product of a system. Both organizational culture and Complex Adaptive Systems (CAS) theory emphasize that individual behavior depends on the specific system and the unique organizational culture. These two major theories are both represented in the field of organizational studies; however, they are rarely used together for the comprehensive understanding of workplace behavior. Methodology: By reviewing the literature we use key concepts stemming from organizational culture and CAS theory in order to show the similarities between these theories and create an enriched understanding of employee behavior. Findings: a) Workplace behavior is defined here as social cognition issue. b) Organizations are discussed here as complex systems, and cultures which drive and dictate the cognitive processes of agents in the system. c) Culture gives CAS theory a context which lets us see organizations not just as ever-changing and unpredictable, but as such systems that aim to create and maintain stability by recurring behavior. Conclusion: Applying the knowledge from culture and CAS theory sheds light on our present understanding of employee behavior, also emphasizes the importance of novel ways in organizational research and management.

Keywords: Complex adaptive systems theory, employee behavior, organizational culture, stability.

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Authors: Yuichi Masukake, Yoshihisa Ishida

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In this paper, we proposed a method to design a model-following adaptive controller for linear/nonlinear plants. Radial basis function neural networks (RBF-NNs), which are known for their stable learning capability and fast training, are used to identify linear/nonlinear plants. Simulation results show that the proposed method is effective in controlling both linear and nonlinear plants with disturbance in the plant input.

Keywords: Linear/nonlinear plants, neural networks, radial basisfunction networks.

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Authors: M. Chaoui, M-T. Laskri

Abstract:

The evolution of information and communication technology has made a very powerful support for the improvement of online learning platforms in creation of courses. This paper presents a study that attempts to explore new web architecture for creating an adaptive online learning system to profiles of learners, using the Web as a source for the automatic creation of courses for the online training platform. This architecture will reduce the time and decrease the effort performed by the drafters of the current e-learning platform, and direct adaptation of the Web content will greatly enrich the quality of online training courses.

Keywords: Web Content, e-Learning, Educational Content, LMS, Profiles of Learners

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Authors: Pankaj, Sonia R. Bansal

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Stresses for the elastic-plastic transition and fully plastic state have been derived for a thin rotating disc with inclusion and results have been discussed numerically and depicted graphically. It has been observed that the rotating disc with inclusion and made of compressible material requires lesser angular speed to yield at the internal surface whereas it requires higher percentage increase in angular speed to become fully plastic as compare to disc made of incompressible material.

Keywords: Angular speed, Elastic-Plastic, Inclusion, Rotatingdisc, Stress, Transition.

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Authors: Neeraj K. Chasta

Abstract:

This paper presents an idea for analog current comparison which compares input signal and reference currents with high speed and accuracy. Proposed circuit utilizes amplification properties of common gate configuration, where voltage variations of input current are amplified and a compared output voltage is developed. Cascaded inverter stages are used to generate final CMOS compatible output voltage. Power consumption of circuit can be controlled by the applied gate bias voltage. The comparator is designed and studied at 180nm CMOS process technology for a supply voltage of 3V.

Keywords: Current Mode, Comparator, High Resolution, High Speed.

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: Big data, k-NN, machine learning, traffic speed prediction.

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Authors: A. Chandrashekar, H. N. Reddappa, B. S. Ajaykumar

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A Friction stir welding tool is a critical component to the success of the process. The tool typically consists of a rotating round shoulder and a threaded cylindrical pin that heats the work piece, mostly by friction, and moves the softened alloy around it to form the joint. In this research work, an attempt has been made to investigate the relationship between FSW variables mainly tool profile, rotating speed, welding speed and the mechanical properties (tensile strength, yield strength, percentage elongation, and micro hardness) of friction stir welded aluminum alloy 5083 joints. From the experimental details, it can be assessed that the joint produced by using Triflute profile tool has contribute superior mechanical and structural properties as compared to Tapered unthreaded & Threaded tool for 1000rpm.

Keywords: Friction stir welding, Tool profile, Rotating speed, Strength, Speed ratio.

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Authors: Hyun-Chool Shin

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In this paper we propose a simple adaptive algorithm iteratively solving the unit-norm constrained optimization problem. Instead of conventional parameter norm based normalization, the proposed algorithm incorporates scalar normalization which is computationally much simpler. The analysis of stationary point is presented to show that the proposed algorithm indeed solves the constrained optimization problem. The simulation results illustrate that the proposed algorithm performs as good as conventional ones while being computationally simpler.

Keywords: constrained optimization, unit-norm, LMS, principle component analysis.

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Authors: M.O. Makhmalbaf, F. Mohajeri Nav, M. Zabihi Samani

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The recent drive for use of performance-based methodologies in design and assessment of structures in seismic areas has significantly increased the demand for the development of reliable nonlinear inelastic static pushover analysis tools. As a result, the adaptive pushover methods have been developed during the last decade, which unlike their conventional pushover counterparts, feature the ability to account for the effect that higher modes of vibration and progressive stiffness degradation might have on the distribution of seismic storey forces. Even in advanced pushover methods, little attention has been paid to the Unsymmetric structures. This study evaluates the seismic demands for three dimensional Unsymmetric-Plan buildings determined by the Displacement-based Adaptive Pushover (DAP) analysis, which has been introduced by Antoniou and Pinho [2004]. The capability of DAP procedure in capturing the torsional effects due to the irregularities of the structures, is investigated by comparing its estimates to the exact results, obtained from Incremental Dynamic Analysis (IDA). Also the capability of the procedure in prediction the seismic behaviour of the structure is discussed.

Keywords: Nonlinear static procedures, Unsymmetric-PlanBuildings, Torsional effects, IDA.

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Authors: Saeid Nahi, Seyed Mohammad Hossein Nabavi

Abstract:

Nowadays, power systems, energy generation by wind has been very important. Noting that the production of electrical energy by wind turbines on site to several factors (such as wind speed and profile site for the turbines, especially off the wind input speed, wind rated speed and wind output speed disconnect) is dependent. On the other hand, several different types of turbines in the market there. Therefore, selecting a turbine that its capacity could also answer the need for electric consumers the efficiency is high something is important and necessary. In this context, calculating the amount of wind power to help optimize overall network, system operation, in determining the parameters of wind power is very important. In this article, to help calculate the amount of wind power plant, connected to the national network in the region Manjil wind, selecting the best type of turbine and power delivery profile appropriate to the network using Monte Carlo method has been. In this paper, wind speed data from the wind site in Manjil, as minute and during the year has been. Necessary simulations based on Random Numbers Simulation method and repeat, using the software MATLAB and Excel has been done.

Keywords: wind turbine, efficiency, wind turbine work points, Random Numbers, reliability

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Authors: Yusuke Onoue, Seiji Fujino, Norimasa Nakashima

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The IDR(s) method based on an extended IDR theorem was proposed by Sonneveld and van Gijzen. The original IDR(s) method has excellent property compared with the conventional iterative methods in terms of efficiency and small amount of memory. IDR(s) method, however, has unexpected property that relative residual 2-norm stagnates at the level of less than 10-12. In this paper, an effective strategy for stagnation detection, stagnation avoidance using adaptively information of parameter s and improvement of convergence rate itself of IDR(s) method are proposed in order to gain high accuracy of the approximated solution of IDR(s) method. Through numerical experiments, effectiveness of adaptive tuning IDR(s) method is verified and demonstrated.

Keywords: Krylov subspace methods, IDR(s), adaptive tuning, stagnation of relative residual.

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Authors: Qun-Feng Zhang, Pan-Pan Yan, Jun Li, Jun-Qing Lei

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Numerical investigation of hammershock propagation in the S-bend intake caused by engine surge has been conducted by using Improved Delayed Detach-Eddy Simulation (IDDES). The effects of surge signatures on hammershock characteristics are obtained. It was shown that once the hammershock is produced, it moves upward to the intake entrance quickly with constant speed, however, the strength of hammershock keeps increasing. Meanwhile, being influenced by the centrifugal force, the hammershock strength on the larger radius side is much larger. Hammershock propagation speed and strength are sensitive to the ramp upgradient of surge signature. A larger ramp up gradient results in higher propagation speed and greater strength. Nevertheless, ramp down profile of surge signature have no obvious effect on the propagation speed and strength of hammershock. Increasing the maximum value of surge signature leads to enhance in the intensity of hammershock, they approximately match quadratic function distribution law.

Keywords: Hammershock, IDDES, S-bend, surge signature.

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Authors: Sally Naji, Julie Gwilliam

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Climate change remains a challenging matter for the human and the built environment in the 21st century, where the need to consider adaptation to climate change in the development process is paramount. However, there remains a lack of information regarding how we should prepare responses to this issue, such as through developing organized and sophisticated tools enabling the adaptation process. This study aims to build a systematic framework approach to investigate the potentials that Neighborhood Sustainability Assessment tools (NSA) might offer in enabling both the analysis of the emerging adaptive capacity to climate change. The analysis of the framework presented in this paper aims to discuss this issue in three main phases. The first part attempts to link sustainability and climate change, in the context of adaptive capacity. It is argued that in deciding to promote sustainability in the context of climate change, both the resilience and vulnerability processes become central. However, there is still a gap in the current literature regarding how the sustainable development process can respond to climate change. As well as how the resilience of practical strategies might be evaluated. It is suggested that the integration of the sustainability assessment processes with both the resilience thinking process, and vulnerability might provide important components for addressing the adaptive capacity to climate change. A critical review of existing literature is presented illustrating the current lack of work in this field, integrating these three concepts in the context of addressing the adaptive capacity to climate change. The second part aims to identify the most appropriate scale at which to address the built environment for the climate change adaptation. It is suggested that the neighborhood scale can be considered as more suitable than either the building or urban scales. It then presents the example of NSAs, and discusses the need to explore their potential role in promoting the adaptive capacity to climate change. The third part of the framework presents a comparison among three example NSAs, BREEAM Communities, LEED-ND, and CASBEE-UD. These three tools have been selected as the most developed and comprehensive assessment tools that are currently available for the neighborhood scale. This study concludes that NSAs are likely to present the basis for an organized framework to address the practical process for analyzing and yet promoting Adaptive Capacity to Climate Change. It is further argued that vulnerability (exposure & sensitivity) and resilience (Interdependence & Recovery) form essential aspects to be addressed in the future assessment of NSA’s capability to adapt to both short and long term climate change impacts. Finally, it is acknowledged that further work is now required to understand impact assessment in terms of the range of physical sectors (Water, Energy, Transportation, Building, Land Use and Ecosystems), Actor and stakeholder engagement as well as a detailed evaluation of the NSA indicators, together with a barriers diagnosis process.

Keywords: Adaptive capacity, climate change, NSA tools, resilience, vulnerability.

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Authors: M.M. Namazi, S.M. Saghaiannejad, A. Rashidi

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In this paper by using the port-controlled Hamiltonian (PCH) systems theory, a full-order nonlinear controlled model is first developed. Then a nonlinear passivity-based robust adaptive control (PBRAC) of switched reluctance motor in the presence of external disturbances for the purpose of torque ripple reduction and characteristic improvement is presented. The proposed controller design is separated into the inner loop and the outer loop controller. In the inner loop, passivity-based control is employed by using energy shaping techniques to produce the proper switching function. The outer loop control is employed by robust adaptive controller to determine the appropriate Torque command. It can also overcome the inherent nonlinear characteristics of the system and make the whole system robust to uncertainties and bounded disturbances. A 4KW 8/6 SRM with experimental characteristics that takes magnetic saturation into account is modeled, simulation results show that the proposed scheme has good performance and practical application prospects.

Keywords: Switched Reluctance Motor, Port HamiltonianSystem, Passivity-Based Control, Torque Ripple Minimization

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Authors: Walid Chakroun, Sorour Alotaibi, Nesreen Ghaddar, Kamel Ghali

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This study aims at determining the extent to which occupant control of microenvironment influences, improves thermal sensation and comfort, and saves energy in spaces equipped with ceiling personalized ventilation (CPV) system assisted by chair fans (CF) and desk fans (DF) in 2 experiments in a climatic chamber equipped with two-station CPV systems, one that allows control of fan flow rate and the other is set to the fan speed of the selected participant in control. Each experiment included two participants each entering the cooled space from transitional environment at a conventional mixed ventilation (MV) at 24 °C. For CPV diffuser, fresh air was delivered at a rate of 20 Cubic feet per minute (CFM) and a temperature of 16 °C while the recirculated air was delivered at the same temperature but at a flow rate 150 CFM. The macroclimate air of the space was at 26 °C. The full speed flow rates for both the CFs and DFs were at 5 CFM and 20 CFM, respectively. Occupant 1 was allowed to operate the CFs or the DFs at (1/3 of the full speed, 2/3 of the full speed, and the full speed) while occupant 2 had no control on the fan speed and their fan speed was selected by occupant 1. Furthermore, a parametric study was conducted to study the effect of increasing the fresh air flow rate on the occupants’ thermal comfort and whole body sensations. The results showed that most occupants in the CPV+CFs, who did not control the CF flow rate, felt comfortable 6 minutes. The participants, who controlled the CF speeds, felt comfortable in around 24 minutes because they were preoccupied with the CFs. For the DF speed control experiments, most participants who did not control the DFs felt comfortable within the first 8 minutes. Similarly to the CPV+CFs, the participants who controlled the DF flow rates felt comfortable at around 26 minutes. When the CPV system was either supported by CFs or DFs, 93% of participants in both cases reached thermal comfort. Participants in the parametric study felt more comfortable when the fresh air flow rate was low, and felt cold when as the flow rate increased.

Keywords: Thermal comfort, thermal sensation, predicted mean vote, thermal environment.

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Authors: Shafaf Ibrahim, Noor Elaiza Abdul Khalid, Mazani Manaf

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Segmentation of Magnetic Resonance Imaging (MRI) images is the most challenging problems in medical imaging. This paper compares the performances of Seed-Based Region Growing (SBRG), Adaptive Network-Based Fuzzy Inference System (ANFIS) and Fuzzy c-Means (FCM) in brain abnormalities segmentation. Controlled experimental data is used, which designed in such a way that prior knowledge of the size of the abnormalities are known. This is done by cutting various sizes of abnormalities and pasting it onto normal brain tissues. The normal tissues or the background are divided into three different categories. The segmentation is done with fifty seven data of each category. The knowledge of the size of the abnormalities by the number of pixels are then compared with segmentation results of three techniques proposed. It was proven that the ANFIS returns the best segmentation performances in light abnormalities, whereas the SBRG on the other hand performed well in dark abnormalities segmentation.

Keywords: Seed-Based Region Growing (SBRG), Adaptive Network-Based Fuzzy Inference System (ANFIS), Fuzzy c-Means (FCM), Brain segmentation.

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Authors: Azhar Hussain, Kashif Shahzad, Chunming Tang

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this paper gives a novel approach towards real-time speed estimation of multiple traffic vehicles using fuzzy logic and image processing techniques with proper arrangement of camera parameters. The described algorithm consists of several important steps. First, the background is estimated by computing median over time window of specific frames. Second, the foreground is extracted using fuzzy similarity approach (FSA) between estimated background pixels and the current frame pixels containing foreground and background. Third, the traffic lanes are divided into two parts for both direction vehicles for parallel processing. Finally, the speeds of vehicles are estimated by Maximum a Posterior Probability (MAP) estimator. True ground speed is determined by utilizing infrared sensors for three different vehicles and the results are compared to the proposed algorithm with an accuracy of ± 0.74 kmph.

Keywords: Defuzzification, Fuzzy similarity approach, lane cropping, Maximum a Posterior Probability (MAP) estimator, Speed estimation

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Authors: Wann-Ming Wey

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In today's popularity and progress of information technology, the big data set and its analysis are no longer a major conundrum. Now, we could not only use the relevant big data to analysis and emulate the possible status of urban development in the near future, but also provide more comprehensive and reasonable policy implementation basis for government units or decision-makers via the analysis and emulation results as mentioned above. In this research, we set Taipei City as the research scope, and use the relevant big data variables (e.g., population, facility utilization and related social policy ratings) and Analytic Network Process (ANP) approach to implement in-depth research and discussion for the possible reduction of land use in primary and secondary schools of Taipei City. In addition to enhance the prosperous urban activities for the urban public facility utilization, the final results of this research could help improve the efficiency of urban land use in the future. Furthermore, the assessment model and research framework established in this research also provide a good reference for schools or other public facilities land use and adaptive reuse strategies in the future.

Keywords: Adaptive reuse, analytic network process, big data, land use strategy.

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Authors: H. Baseri, G. Alinejad

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The objective of this study is to design an adaptive neuro-fuzzy inference system (ANFIS) for estimation of surface roughness in grinding process. The Used data have been generated from experimental observations when the wheel has been dressed using a rotary diamond disc dresser. The input parameters of model are dressing speed ratio, dressing depth and dresser cross-feed rate and output parameter is surface roughness. In the experimental procedure the grinding conditions are constant and only the dressing conditions are varied. The comparison of the predicted values and the experimental data indicates that the ANFIS model has a better performance with respect to back-propagation neural network (BPNN) model which has been presented by the authors in previous work for estimation of the surface roughness.

Keywords: Grinding, ANFIS, Neural network, Disc dressing.

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Authors: Rawinun Praserttaweelap, Somyot Kiatwanidvilai

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Obstacle avoidance is the one key for the robot system in unknown environment. The robots should be able to know their position and safety region. This research starts on the path planning which are SLAM and AMCL in ROS system. In addition, the best parameters of the obstacle avoidance function are required. In situation on Hard Disk Drive Manufacturing, the distance between robots and obstacles are very serious due to the manufacturing constraint. The simulations are accomplished by the SLAM and AMCL with adaptive velocity and safety region calculation.

Keywords: Obstacle avoidance, simultaneous localization and mapping, adaptive Monte Carlo localization, KLD sampling.

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Authors: Fu Hao, Sun Gang, Tang Laiying, Cui Junfeng

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To solve the quick and accurate level-adjusting problem in the process of spacecraft precise mating, automatic leveling and equalizing hoist device for spacecraft is developed. Based on lifting point adjustment by utilizing XY-workbench, the leveling and equalizing controller by a self-adaptive control algorithm is proposed. By simulation analysis and lifting test using engineering prototype, validity and reliability of the hoist device is verified, which can meet the precision mating requirements of practical applications for spacecraft.

Keywords: automatic leveling and equalizing, hoist device, lifting point adjustment, self-adaptive control

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Authors: J. Ritonja

Abstract:

The biochemical technology has been developing extremely fast since the middle of the last century. The main reason for such development represents a requirement for large production of high-quality biologically manufactured products such as pharmaceuticals, foods, and beverages. The impact of the biochemical industry on the world economy is enormous. The great importance of this industry also results in intensive development in scientific disciplines relevant to the development of biochemical technology. In addition to developments in the fields of biology and chemistry, which enable to understand complex biochemical processes, development in the field of control theory and applications is also very important. In the paper, the control for the biochemical reactor for the milk fermentation was studied. During the fermentation process, the biophysical quantities must be precisely controlled to obtain the high-quality product. To control these quantities, the bioreactor’s stirring drive and/or heating system can be used. Available commercial biochemical reactors are equipped with open loop or conventional linear closed loop control system. Due to the outstanding parameters variations and the partial nonlinearity of the biochemical process, the results obtained with these control systems are not satisfactory. To improve the fermentation process, the self-tuning adaptive control system was proposed. The use of the self-tuning adaptive control is suggested because the parameters’ variations of the studied biochemical process are very slow in most cases. To determine the linearized mathematical model of the fermentation process, the recursive least square identification method was used. Based on the obtained mathematical model the linear quadratic regulator was tuned. The parameters’ identification and the controller’s synthesis are executed on-line and adapt the controller’s parameters to the fermentation process’ dynamics during the operation. The use of the proposed combination represents the original solution for the control of the milk fermentation process. The purpose of the paper is to contribute to the progress of the control systems for the biochemical reactors. The proposed adaptive control system was tested thoroughly. From the obtained results it is obvious that the proposed adaptive control system assures much better following of the reference signal as a conventional linear control system with fixed control parameters.

Keywords: Adaptive control, biochemical reactor, linear quadratic regulator, recursive least square identification.

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