Search results for: Adaptive modulation and coding

Authors: Lakshmi Pujitha Dachuri, Nalini Uppala

Abstract:

In many applications retransmissions of lost packets are not permitted. OFDM is a multi-carrier modulation scheme having excellent performance which allows overlapping in frequency domain. With OFDM there is a simple way of dealing with multipath relatively simple DSP algorithms.

 In this paper, an image frame is compressed using DWT, and the compressed data is arranged in data vectors, each with equal number of coefficients. These vectors are quantized and binary coded to get the bit steams, which are then packetized and intelligently mapped to the OFDM system. Based on one-bit channel state information at the transmitter, the descriptions in order of descending priority are assigned to the currently good channels such that poorer sub-channels can only affect the lesser important data vectors. We consider only one-bit channel state information available at the transmitter, informing only about the sub-channels to be good or bad. For a good sub-channel, instantaneous received power should be greater than a threshold P_th. Otherwise, the sub-channel is in fading state and considered bad for that batch of coefficients. In order to reduce the system power consumption, the mapped descriptions onto the bad sub channels are dropped at the transmitter. The binary channel state information gives an opportunity to map the bit streams intelligently and to save a reasonable amount of power. By using MAT LAB simulation we can analysis the performance of our proposed scheme, in terms of system energy saving without compromising the received quality in terms of peak signal-noise ratio.

Keywords: Binary channel state, Channel state feedback, DWT-OFDM system, Energy saving, Fading broadcast channel.

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Authors: Inês Ramalhete, Hugo Farias, Rui da Silva Pinto

Abstract:

Adequate housing has been a widely discussed theme in academic circles related to low-cost housing, whereas its physical features are easy to deal with, overcrowding (related to social, cultural and economic aspects) is still ambiguous, particularly regarding the set of indicators that can accurately reflect and measure it. This paper develops research on low-cost housing models for developing countries and what is the best method to embed overcrowding as an important parameter for adaptability. A critical review of international overcrowding indicators and their application in two developing countries, Cape Verde and Angola, is presented. The several rationales and the constraints for an accurate assessment of overcrowding are considered, namely baseline data (statistics), which can induce misjudgments, as well as social and cultural factors (such as personal choices of residents). This paper proposes a way to tackle overcrowding through housing adaptability, considering factors such as physical flexibility, functional ambiguity, and incremental expansion schemes. Moreover, a case-study is presented to establish a framework for the theoretical application of the proposed approach.

Keywords: Adaptive housing, low-cost housing, overcrowding.

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Authors: S. Sarumathi, M. Vaishnavi, S. Geetha, P. Ranjetha

Abstract:

Machine learning is a new and exciting area of artificial intelligence nowadays. Machine learning is the most valuable, time, supervised, and cost-effective approach. It is not a narrow learning approach; it also includes a wide range of methods and techniques that can be applied to a wide range of complex realworld problems and time domains. Biological image classification, adaptive testing, computer vision, natural language processing, object detection, cancer detection, face recognition, handwriting recognition, speech recognition, and many other applications of machine learning are widely used in research, industry, and government. Every day, more data are generated, and conventional machine learning techniques are becoming obsolete as users move to distributed and real-time operations. By providing fundamental knowledge of machine learning tools and research opportunities in the field, the aim of this article is to serve as both a comprehensive overview and a guide. A diverse set of machine learning resources is demonstrated and contrasted with the key features in this survey.

Keywords: Artificial intelligence, machine learning, deep learning, machine learning algorithms, machine learning tools.

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Authors: A. Pedram, M. R. Jamali, T. Pedram, S. M. Fakhraie, C. Lucas

Abstract:

Local Linear Neuro-Fuzzy Models (LLNFM) like other neuro- fuzzy systems are adaptive networks and provide robust learning capabilities and are widely utilized in various applications such as pattern recognition, system identification, image processing and prediction. Local linear model tree (LOLIMOT) is a type of Takagi-Sugeno-Kang neuro fuzzy algorithm which has proven its efficiency compared with other neuro fuzzy networks in learning the nonlinear systems and pattern recognition. In this paper, a dedicated reconfigurable and parallel processing hardware for LOLIMOT algorithm and its applications are presented. This hardware realizes on-chip learning which gives it the capability to work as a standalone device in a system. The synthesis results on FPGA platforms show its potential to improve the speed at least 250 of times faster than software implemented algorithms.

Keywords: LOLIMOT, hardware, neurofuzzy systems, reconfigurable, parallel.

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Authors: O. S. Ebrahim, M. A. Badr, A. S. Elgendy, K. O. Shawky, P. K. Jain

Abstract:

This paper demonstrates an improved Loss Model Control (LMC) for a 3-phase induction motor (IM) driving pump load. Compared with other power loss reduction algorithms for IM, the presented one has the advantages of fast and smooth flux adaptation, high accuracy, and versatile implementation. The performance of LMC depends mainly on the accuracy of modeling the motor drive and losses. A loss-model for IM drive that considers the surplus power loss caused by inverter voltage harmonics using closed-form equations and also includes the magnetic saturation has been developed. Further, an Artificial Neural Network (ANN) controller is synthesized and trained offline to determine the optimal flux level that achieves maximum drive efficiency. The drive’s voltage and speed control loops are connecting via the stator frequency to avoid the possibility of excessive magnetization. Besides, the resistance change due to temperature is considered by a first-order thermal model. The obtained thermal information enhances motor protection and control. These together have the potential of making the proposed algorithm reliable. Simulation and experimental studies are performed on 5.5 kW test motor using the proposed control method. The test results are provided and compared with the fixed flux operation to validate the effectiveness.

Keywords: Artificial neural network, ANN, efficiency optimization, induction motor, IM, Pulse Width Modulated, PWM, harmonic losses.

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Authors: Shiuh-Jer Huang, Ming-Tien Su

Abstract:

Since the driving speed and control accuracy of commercial optical disk are increasing significantly, it needs an efficient controller to monitor the track seeking and following operations of the servo system for achieving the desired data extracting response. The nonlinear behaviors of the actuator and servo system of the optical disk drive will influence the laser spot positioning. Here, the model-free fuzzy control scheme is employed to design the track seeking servo controller for a d.c. motor driving optical disk drive system. In addition, the sliding model control strategy is introduced into the fuzzy control structure to construct a 1-D adaptive fuzzy rule intelligent controller for simplifying the implementation problem and improving the control performance. The experimental results show that the steady state error of the track seeking by using this fuzzy controller can maintain within the track width (1.6 μm ). It can be used in the track seeking and track following servo control operations.

Keywords: Fuzzy control, gain tuning and optical disk drive.

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Authors: Lu Yang, Meiyang Song, Xiang Yu, Wenhao Zhou, Chuntao Feng

Abstract:

To address the problem that the FM continuous-wave (FMCW) radar extracts human vital sign signals which are susceptible to noise interference and low reconstruction accuracy, a detection scheme for the sign signals is proposed. Firstly, an improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) algorithm is applied to decompose the radar-extracted thoracic signals to obtain several intrinsic modal functions (IMF) with different spatial scales, and then the IMF components are optimized by a backpropagation (BP) neural network improved by immune genetic algorithm (IGA). The simulation results show that this scheme can effectively separate the noise, accurately extract the respiratory and heartbeat signals and improve the reconstruction accuracy and signal to-noise ratio of the sign signals.

Keywords: Frequency modulated continuous wave radar, ICEEMDAN, BP Neural Network, vital signs signal.

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Authors: Sun-Ki Hong, Yong-Ho Cho, Ki-Seok Kim, Tae-Sam Kang

Abstract:

Piezoelectric actuator is treated as RC load when it is modeled electrically. For some piezoelectric actuator applications, arbitrary voltage is required to actuate. Especially for unidirectional arbitrary voltage driving like as sine wave, some special inverter with circuit that can charge and discharge the capacitive energy can be used. In this case, the difference between power supply level and the object voltage level for RC load is varied. Because the control gain is constant, the controlled output is not uniform according to the voltage difference. In this paper, for charge and discharge circuit for unidirectional arbitrary voltage driving for piezoelectric actuator, the controller gain is controlled according to the voltage difference. With the proposed simple idea, the load voltage can have controlled smoothly although the voltage difference is varied. The appropriateness is proved from the simulation of the proposed circuit.

Keywords: Analog voltage inverter, Capacitive load, Gain control, DC-DC converter, Piezoelectric, Voltage waveform.

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Authors: M. Polanský

Abstract:

This paper introduces a new method called ARPDC (Advanced Robust Parallel Distributed Compensation) for automatic control of nonlinear systems. This method improves a quality of robust control by interpolating of robust and optimal controller. The weight of each controller is determined by an original criteria function for model validity and disturbance appreciation. ARPDC method is based on nonlinear Takagi-Sugeno (T-S) fuzzy systems and Parallel Distributed Compensation (PDC) control scheme. The relaxed stability conditions of ARPDC control of nominal system have been derived. The advantages of presented method are demonstrated on the inverse pendulum benchmark problem. From comparison between three different controllers (robust, optimal and ARPDC) follows, that ARPDC control is almost optimal with the robustness close to the robust controller. The results indicate that ARPDC algorithm can be a good alternative not only for a robust control, but in some cases also to an adaptive control of nonlinear systems.

Keywords: Robust control, optimal control, Takagi–Sugeno (TS) fuzzy models, linear matrix inequality (LMI), observer, Advanced Robust Parallel Distributed Compensation (ARPDC).

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Authors: Zhongzhen Luo, Saeid Habibi, Martin v. Mohrenschildt

Abstract:

Self-driving vehicle require a high level of situational awareness in order to maneuver safely when driving in real world condition. This paper presents a LiDAR based real time perception system that is able to process sensor raw data for multiple target detection and tracking in dynamic environment. The proposed algorithm is nonparametric and deterministic that is no assumptions and priori knowledge are needed from the input data and no initializations are required. Additionally, the proposed method is working on the three-dimensional data directly generated by LiDAR while not scarifying the rich information contained in the domain of 3D. Moreover, a fast and efficient for real time clustering algorithm is applied based on a radially bounded nearest neighbor (RBNN). Hungarian algorithm procedure and adaptive Kalman filtering are used for data association and tracking algorithm. The proposed algorithm is able to run in real time with average run time of 70ms per frame.

Keywords: LiDAR, real-time system, clustering, tracking, data association.

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Authors: Seungsuk Ha, Youngjoon Han, Hernsoo Hahn

Abstract:

This paper proposes a method of adaptively generating a gait pattern of biped robot. The gait synthesis is based on human's gait pattern analysis. The proposed method can easily be applied to generate the natural and stable gait pattern of any biped robot. To analyze the human's gait pattern, sequential images of the human's gait on the sagittal plane are acquired from which the gait control values are extracted. The gait pattern of biped robot on the sagittal plane is adaptively generated by a genetic algorithm using the human's gait control values. However, gait trajectories of the biped robot on the sagittal plane are not enough to construct the complete gait pattern because the biped robot moves on 3-dimension space. Therefore, the gait pattern on the frontal plane, generated from Zero Moment Point (ZMP), is added to the gait one acquired on the sagittal plane. Consequently, the natural and stable walking pattern for the biped robot is obtained.

Keywords: Biped robot, gait pattern, genetic algorithm.

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Authors: J. Jenefa, E. A. Mary Anita

Abstract:

Vehicular Ad hoc NETwork (VANET) is a kind of Mobile Ad hoc NETwork (MANET). It allows the vehicles to communicate with one another as well as with nearby Road Side Units (RSU) and Regional Trusted Authorities (RTA). Vehicles communicate through On-Board Units (OBU) in which privacy has to be assured which will avoid the misuse of private data. A secure authentication framework for VANETs is proposed in which Public Key Cryptography (PKC) based adaptive pseudonym scheme is used to generate self-generated pseudonyms. Self-generated pseudonyms are used instead of real IDs for privacy preservation and non-repudiation. The ID-Based Signature (IBS) and ID-Based Online/Offline Signature (IBOOS) schemes are used for authentication. IBS is used to authenticate between vehicle and RSU whereas IBOOS provides authentication among vehicles. Security attacks like impersonation attack in the network are resolved and the attacking nodes are rejected from the network, thereby ensuring secure communication among the vehicles in the network. Simulation results shows that the proposed system provides better authentication in VANET environment.

Keywords: Non-repudiation, privacy preservation, public key cryptography, self- generated pseudonym.

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Authors: Amr Sayed, Y. Hiroshi, T. Goto, N. Enteria, M. M. Radwan, M. Abdelsamei Eid

Abstract:

Climate considerations are essential dimensions in the assessment of thermal comfort and indoor environments inside Egyptian housing. The primary aim of this paper is to analyze the indoor environment of new housing in the new city of Assiut in the Southern Upper Egypt zone, in order to evaluate its thermal environment and determine the acceptable indoor operative temperatures. The psychrometric charts for ASHRAE Standard 55 and ACS used in this study would facilitate an overall representation of the climate in one of the hottest months in the summer season. This study helps to understand and deal with this problem and work on a passive cooling ventilation strategy in these contexts in future studies. The results that demonstrated the indoor temperature is too high, ranges between 31°C to 40°C in different natural ventilation strategies. This causes the indoor environment to be far from the optimum comfort operative temperature of ACS except when using air conditioners. Finally, this study is considered a base for developing a new system using natural ventilation with passive cooling strategies.

Keywords: Adaptive comfort standard (ACS), indoor environment, thermal comfort, ventilation.

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Authors: Zongyou He, Bashu Tsai, Chinhung Ko, Tainchi Lu

Abstract:

A procedural-animation-based approach which rapidly synthesize the adaptive locomotion for quadruped characters that they can walk or run in any directions on an uneven terrain within a dynamic environment was proposed. We devise practical motion models of the quadruped animals for adapting to a varied terrain in a real-time manner. While synthesizing locomotion, we choose the corresponding motion models by means of the footstep prediction of the current state in the dynamic environment, adjust the key-frames of the motion models relying on the terrain-s attributes, calculate the collision-free legs- trajectories, and interpolate the key-frames according to the legs- trajectories. Finally, we apply dynamic time warping to each part of motion for seamlessly concatenating all desired transition motions to complete the whole locomotion. We reduce the time cost of producing the locomotion and takes virtual characters to fit in with dynamic environments no matter when the environments are changed by users.

Keywords: Dynamic environment, motion synthesis, procedural animation, quadruped locomotion

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Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

Abstract:

Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: Diabetic retinopathy, fundus, CHT, exudates, hemorrhages.

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Authors: Mohd. Israil, M. Salim Beg

Abstract:

In order to accommodate various multimedia services, next generation wireless networks are characterized by very high transmission bit rates. Thus, in such systems and networks, the received signal is not only limited by noise but - especially with increasing symbols rate often more significantly by the intersymbol interference (ISI) caused by the time dispersive radio channels such as those are used in this work. This paper deals with the study of the performance of detector for high bit rate transmission on some worst case models of frequency selective fading channels for outdoor mobile radio environments. This paper deals with a number of different wireless channels with different power profiles and different number of resolvable paths. All the radio channels generated in this paper are for outdoor vehicular environments with Doppler spread of 100 Hz. A carrier frequency of 1800 MHz is used and all the channels used in this work are such that they are useful for next generation wireless systems. Schemes for mitigation of ISI with adaptive equalizers of different types have been investigated and their performances have been investigated in terms of BER measured as a function of SNR.

Keywords: Mobile channels, Rayleigh Fading, Equalization, NMLD.

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Authors: Emilija Miletic, Milos Krstic, Maxim Piz, Michael Methfessel

Abstract:

In this work we present a solution for DAGC (Digital Automatic Gain Control) in WLAN receivers compatible to IEEE 802.11a/g standard. Those standards define communication in 5/2.4 GHz band using Orthogonal Frequency Division Multiplexing OFDM modulation scheme. WLAN Transceiver that we have used enables gain control over Low Noise Amplifier (LNA) and a Variable Gain Amplifier (VGA). The control over those signals is performed in our digital baseband processor using dedicated hardware block DAGC. DAGC in this process is used to automatically control the VGA and LNA in order to achieve better signal-to-noise ratio, decrease FER (Frame Error Rate) and hold the average power of the baseband signal close to the desired set point. DAGC function in baseband processor is done in few steps: measuring power levels of baseband samples of an RF signal,accumulating the differences between the measured power level and actual gain setting, adjusting a gain factor of the accumulation, and applying the adjusted gain factor the baseband values. Based on the measurement results of RSSI signal dependence to input power we have concluded that this digital AGC can be implemented applying the simple linearization of the RSSI. This solution is very simple but also effective and reduces complexity and power consumption of the DAGC. This DAGC is implemented and tested both in FPGA and in ASIC as a part of our WLAN baseband processor. Finally, we have integrated this circuit in a compact WLAN PCMCIA board based on MAC and baseband ASIC chips designed from us.

Keywords: WLAN, AGC, RSSI, baseband processor

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Authors: Srinivasan Chandrasekaran, Manda Hari Venkata Ramachandra Rao

Abstract:

Increase in the oil and gas exploration in ultra deep-water demands an adaptive structural form of the platform. Triceratops has superior motion characteristics compared to that of the Tension Leg Platform and Single Point Anchor Reservoir platforms, which is well established in the literature. Buoyant legs that support the deck are position-restrained to the sea bed using tethers with high axial pretension. Environmental forces that act on the platform induce dynamic tension variations in the tethers, causing the failure of tethers. The present study investigates the dynamic response behavior of the restraining system of the platform under the failure of a single tether of each buoyant leg in high sea states. Using the rain-flow counting algorithm and the Goodman diagram, fatigue damage caused to the tethers is estimated, and the fatigue life is predicted. Results shows that under failure conditions, the fatigue life of the remaining tethers is quite alarmingly low.

Keywords: Fatigue life, Failure analysis, PM spectrum, rain flow counting, triceratops.

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Authors: Cemil Turan, Mohammad Shukri Salman

Abstract:

The convergence rate of the least-mean-square (LMS) algorithm deteriorates if the input signal to the filter is correlated. In a system identification problem, this convergence rate can be improved if the signal is white and/or if the system is sparse. We recently proposed a sparse transform domain LMS-type algorithm that uses a variable step-size for a sparse system identification. The proposed algorithm provided high performance even if the input signal is highly correlated. In this work, we investigate the performance of the proposed TD-LMS algorithm for a large number of filter tap which is also a critical issue for standard LMS algorithm. Additionally, the optimum value of the most important parameter is calculated for all experiments. Moreover, the convergence analysis of the proposed algorithm is provided. The performance of the proposed algorithm has been compared to different algorithms in a sparse system identification setting of different sparsity levels and different number of filter taps. Simulations have shown that the proposed algorithm has prominent performance compared to the other algorithms.

Keywords: Adaptive filtering, sparse system identification, VSSLMS algorithm, TD-LMS algorithm.

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Authors: Karunakar A K, Manohara Pai M M

Abstract:

In 3D-wavelet video coding framework temporal filtering is done along the trajectory of motion using Motion Compensated Temporal Filtering (MCTF). Hence computationally efficient motion estimation technique is the need of MCTF. In this paper a predictive technique is proposed in order to reduce the computational complexity of the MCTF framework, by exploiting the high correlation among the frames in a Group Of Picture (GOP). The proposed technique applies coarse and fine searches of any fast block based motion estimation, only to the first pair of frames in a GOP. The generated motion vectors are supplied to the next consecutive frames, even to subsequent temporal levels and only fine search is carried out around those predicted motion vectors. Hence coarse search is skipped for all the motion estimation in a GOP except for the first pair of frames. The technique has been tested for different fast block based motion estimation algorithms over different standard test sequences using MC-EZBC, a state-of-the-art scalable video coder. The simulation result reveals substantial reduction (i.e. 20.75% to 38.24%) in the number of search points during motion estimation, without compromising the quality of the reconstructed video compared to non-predictive techniques. Since the motion vectors of all the pair of frames in a GOP except the first pair will have value ±1 around the motion vectors of the previous pair of frames, the number of bits required for motion vectors is also reduced by 50%.

Keywords: Motion Compensated Temporal Filtering, predictivemotion estimation, lifted wavelet transform, motion vector

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Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin

Abstract:

This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of singleparameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.

Keywords: Hybrid fault diagnosis, Dynamic neural networks, Nonlinear systems.

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Authors: Prasan Pitiranggon, Nunthika Benjathepanun, Somsri Banditvilai, Veera Boonjing

Abstract:

Our study proposes an alternative method in building Fuzzy Rule-Based System (FRB) from Support Vector Machine (SVM). The first set of fuzzy IF-THEN rules is obtained through an equivalence of the SVM decision network and the zero-ordered Sugeno FRB type of the Adaptive Network Fuzzy Inference System (ANFIS). The second set of rules is generated by combining the first set based on strength of firing signals of support vectors using Gaussian kernel. The final set of rules is then obtained from the second set through input scatter partitioning. A distinctive advantage of our method is the guarantee that the number of final fuzzy IFTHEN rules is not more than the number of support vectors in the trained SVM. The final FRB system obtained is capable of performing classification with results comparable to its SVM counterpart, but it has an advantage over the black-boxed SVM in that it may reveal human comprehensible patterns.

Keywords: Fuzzy Rule Base, Rule Extraction, Rule Generation, Support Vector Machine.

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Authors: Eduardo F. Mello, Peter H. Bauer

Abstract:

The primary focus of this paper is the generation of energy-optimal speed trajectories for heterogeneous electric vehicle platoons in urban driving conditions. Optimal speed trajectories are generated for individual vehicles and for an entire platoon under the assumption that they can be executed without errors, as would be the case for self-driving vehicles. It is then shown that the optimization for the “average vehicle in the platoon” generates similar transportation energy savings to optimizing speed trajectories for each vehicle individually. The introduced approach only requires the lead vehicle to run the optimization software while the remaining vehicles are only required to have adaptive cruise control capability. The achieved energy savings are typically between 30% and 50% for stop-to-stop segments in cities. The prime motivation of urban platooning comes from the fact that urban platoons efficiently utilize the available space and the minimization of transportation energy in cities is important for many reasons, i.e., for environmental, power, and range considerations.

Keywords: Electric vehicles, energy efficiency, optimization, platooning, self-driving vehicles, urban traffic.

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Authors: Awadhesh Kumar Singh

Abstract:

Checkpointing is one of the commonly used techniques to provide fault-tolerance in distributed systems so that the system can operate even if one or more components have failed. However, mobile computing systems are constrained by low bandwidth, mobility, lack of stable storage, frequent disconnections and limited battery life. Hence, checkpointing protocols having lesser number of synchronization messages and fewer checkpoints are preferred in mobile environment. There are two different approaches, although not orthogonal, to checkpoint mobile computing systems namely, time-based and index-based. Our protocol is a fusion of these two approaches, though not first of its kind. In the present exposition, an index-based checkpointing protocol has been developed, which uses time to indirectly coordinate the creation of consistent global checkpoints for mobile computing systems. The proposed algorithm is non-blocking, adaptive, and does not use any control message. Compared to other contemporary checkpointing algorithms, it is computationally more efficient because it takes lesser number of checkpoints and does not need to compute dependency relationships. A brief account of important and relevant works in both the fields, time-based and index-based, has also been included in the presentation.

Keywords: Checkpointing, forced checkpoint, mobile computing, recovery, time-coordinated.

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Authors: M. A. M. El-Bendary, A. E. Abu El-Azm, N. A. El-Fishawy, F. Shawky, F. E. El-Samie

Abstract:

With increasing utilization of the wireless devices in different fields such as medical devices and industrial fields, the paper presents a method for simplify the Bluetooth packets with throughput enhancing. The paper studies a vital issue in wireless communications, which is the throughput of data over wireless networks. In fact, the Bluetooth and ZigBee are a Wireless Personal Area Network (WPAN). With taking these two systems competition consideration, the paper proposes different schemes for improve the throughput of Bluetooth network over a reliable channel. The proposition depends on the Channel Quality Driven Data Rate (CQDDR) rules, which determines the suitable packet in the transmission process according to the channel conditions. The proposed packet is studied over additive White Gaussian Noise (AWGN) and fading channels. The Experimental results reveal the capability of extension of the PL length by 8, 16, 24 bytes for classic and EDR packets, respectively. Also, the proposed method is suitable for the low throughput Bluetooth.

Keywords: Bluetooth, throughput, adaptive packets, EDRpackets, CQDDR, low latency. Channel condition

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Authors: Hani Baek, Gwang Min Sun, Chansun Shin, Sung Ho Ahn

Abstract:

Fast neutron irradiation using nuclear reactors is an effective method to improve switching loss and short circuit durability of power semiconductor (insulated gate bipolar transistors (IGBT) and insulated gate transistors (IGT), etc.). However, not only fast neutrons but also thermal neutrons, epithermal neutrons and gamma exist in the nuclear reactor. And the electrical properties of the IGBT may be deteriorated by the irradiation of gamma. Gamma irradiation damages are known to be caused by Total Ionizing Dose (TID) effect and Single Event Effect (SEE), Displacement Damage. Especially, the TID effect deteriorated the electrical properties such as leakage current and threshold voltage of a power semiconductor. This work can confirm the effect of the gamma irradiation on the electrical properties of 600 V NPT-IGBT. Irradiation of gamma forms lattice defects in the gate oxide and Si-SiO₂ interface of the IGBT. It was confirmed that this lattice defect acts on the center of the trap and affects the threshold voltage, thereby negatively shifted the threshold voltage according to TID. In addition to the change in the carrier mobility, the conductivity modulation decreases in the n-drift region, indicating a negative influence that the forward voltage drop decreases. The turn-off delay time of the device before irradiation was 212 ns. Those of 2.5, 10, 30, 70 and 100 kRad(Si) were 225, 258, 311, 328, and 350 ns, respectively. The gamma irradiation increased the turn-off delay time of the IGBT by approximately 65%, and the switching characteristics deteriorated.

Keywords: NPT-IGBT, gamma irradiation, switching, turn-off delay time, recombination, trap center.

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Authors: A. Allirani, M. Suganthi

Abstract:

Data gathering is an essential operation in wireless sensor network applications. So it requires energy efficiency techniques to increase the lifetime of the network. Similarly, clustering is also an effective technique to improve the energy efficiency and network lifetime of wireless sensor networks. In this paper, an energy efficient cluster formation protocol is proposed with the objective of achieving low energy dissipation and latency without sacrificing application specific quality. The objective is achieved by applying randomized, adaptive, self-configuring cluster formation and localized control for data transfers. It involves application - specific data processing, such as data aggregation or compression. The cluster formation algorithm allows each node to make independent decisions, so as to generate good clusters as the end. Simulation results show that the proposed protocol utilizes minimum energy and latency for cluster formation, there by reducing the overhead of the protocol.

Keywords: Sensor networks, Low latency, Energy sorting protocol, data processing, Cluster formation.

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Authors: Devdutt

Abstract:

In this paper, vibration control response of passenger seat in quarter car model having three degrees of freedom is studied. Three different control strategies are taken into account using Adaptive Neuro Fuzzy Inference System (ANFIS) controller. In first case, ANFIS controller is applied in main suspension of active quarter car model. In second case, passenger seat suspension is assembled with ANFIS controller. Finally, both main and passenger seat suspensions are integrated with ANFIS controller. Simulation work under random road excitations is performed using passive and controlled quarter car models for performance comparison of passenger ride comfort. Ride comfort analysis is also compared as per ISO 2631-1 criterion. The obtained simulation responses are compared taking passenger seat acceleration and displacement response in time and frequency domain for the selection of best control strategy in designed quarter car model.

Keywords: Active suspension system, ANFIS controller, passenger ride comfort, quarter car model.

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Authors: S. A. Mohamed, A. S. Zayed, O. A. Abolaeha

Abstract:

A new Feed-Forward/Feedback Generalized Minimum Variance Pole-placement Controller to incorporate the robustness of classical pole-placement into the flexibility of generalized minimum variance self-tuning controller for Single-Input Single-Output (SISO) has been proposed in this paper. The design, which provides the user with an adaptive mechanism, which ensures that the closed loop poles are, located at their pre-specified positions. In addition, the controller design which has a feed-forward/feedback structure overcomes the certain limitations existing in similar poleplacement control designs whilst retaining the simplicity of adaptation mechanisms used in other designs. It tracks set-point changes with the desired speed of response, penalizes excessive control action, and can be applied to non-minimum phase systems. Besides, at steady state, the controller has the ability to regulate the constant load disturbance to zero. Example simulation results using both simulated and real plant models demonstrate the effectiveness of the proposed controller.

Keywords: Pole-placement, Minimum variance control, self-tuning control and feedforward control.

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Authors: Ming-Lun Chiang, Hsi-Chia Chen, Chieh Wu, Yu-Ting Tseng, Ming-Ju Chen

Abstract:

In this study, three strains of Vibrio parahaemolyticus (690, BCRC 13023 and BCRC 13025) were subjected to acid adaptation at pH 5.5 for 90 min. The survival of acid-adapted and non-adapted V. parahaemolyticus strains under simulated gastric condition and their protein expression profiles were investigated. Results showed that acid adaptation increased the survival of the test V. parahaemolyticus strains after exposure to simulated gastric juice (pH 3). Additionally, acid adaptation also affected the protein expression in these V. parahaemolyticus strains. Nine proteins, identified as atpA, atpB, DnaK, GroEL, OmpU, enolase, fructose-bisphosphate aldolase, phosphoglycerate kinase and triosephosphate isomerase, were induced by acid adaptation in two or three of the test strains. These acid-adaptive proteins may play important regulatory roles in the acid tolerance response (ATR) of V. parahaemolyticus.

Keywords: Acid adaptation, protein expression, simulated gastric juice, Vibrio parahaemolyticus

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