Search results for: Dynamic Memory Leak Detection (DMLD).
3758 Memory Leak Detection in Distributed System
Authors: Roohi Shabrin S., Devi Prasad B., Prabu D., Pallavi R. S., Revathi P.
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Due to memory leaks, often-valuable system memory gets wasted and denied for other processes thereby affecting the computational performance. If an application-s memory usage exceeds virtual memory size, it can leads to system crash. Current memory leak detection techniques for clusters are reactive and display the memory leak information after the execution of the process (they detect memory leak only after it occur). This paper presents a Dynamic Memory Monitoring Agent (DMMA) technique. DMMA framework is a dynamic memory leak detection, that detects the memory leak while application is in execution phase, when memory leak in any process in the cluster is identified by DMMA it gives information to the end users to enable them to take corrective actions and also DMMA submit the affected process to healthy node in the system. Thus provides reliable service to the user. DMMA maintains information about memory consumption of executing processes and based on this information and critical states, DMMA can improve reliability and efficaciousness of cluster computing.Keywords: Dynamic Memory Monitoring Agent (DMMA), Cluster Computing, Memory Leak, Fault Tolerant Framework, Dynamic Memory Leak Detection (DMLD).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22843757 Research and Design on a Portable Intravehicular Ultrasonic Leak Detector for Manned Spacecraft
Authors: Yan Rongxin, Sun Wei, Li Weidan
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Based on the acoustics cascade sound theory, the mechanism of air leak sound producing, transmitting and signal detecting has been analyzed. A formula of the sound power, leak size and air pressure in the spacecraft has been built, and the relationship between leak sound pressure and receiving direction and distance has been studied. The center frequency in millimeter diameter leak is more than 20 kHz. The situation of air leaking from spacecraft to space has been simulated and an experiment of different leak size and testing distance and direction has been done. The sound pressure is in direct proportion to the cosine of the angle of leak to sensor. The portable ultrasonic leak detector has been developed, whose minimal leak rate is 10-1 Pa·m3/s, the testing radius is longer than 20 mm, the mass is less than 1.0 kg, and the electric power is less than 2.2 W.
Keywords: Leak detection, manned spacecraft, ultrasonic, sound transmitting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9643756 On Leak Localization in the Main Branched and Simple Inclined Gas Pipelines
Authors: T. Davitashvili, G. Gubelidze
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In this paper two mathematical models for definition of gas accidental escape localization in the gas pipelines are suggested. The first model was created for leak localization in the horizontal branched pipeline and second one for leak detection in inclined section of the main gas pipeline. The algorithm of leak localization in the branched pipeline did not demand on knowledge of corresponding initial hydraulic parameters at entrance and ending points of each sections of pipeline. For detection of the damaged section and then leak localization in this section special functions and equations have been constructed. Some results of calculations for compound pipelines having two, four and five sections are presented. Also a method and formula for the leak localization in the simple inclined section of the main gas pipeline are suggested. Some results of numerical calculations defining localization of gas escape for the inclined pipeline are presented.
Keywords: Branched and inclined gas pipelines, leak detection, mathematical modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19013755 Non-Destructive Visual-Statistical Approach to Detect Leaks in Water Mains
Authors: Alaa Al Hawari, Mohammad Khader, Tarek Zayed, Osama Moselhi
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In this paper, an effective non-destructive, noninvasive approach for leak detection was proposed. The process relies on analyzing thermal images collected by an IR viewer device that captures thermo-grams. In this study a statistical analysis of the collected thermal images of the ground surface along the expected leak location followed by a visual inspection of the thermo-grams was performed in order to locate the leak. In order to verify the applicability of the proposed approach the predicted leak location from the developed approach was compared with the real leak location. The results showed that the expected leak location was successfully identified with an accuracy of more than 95%.
Keywords: Thermography, Leakage, Water pipelines, Thermograms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25283754 Comparison of Two-Phase Critical Flow Models for Estimation of Leak Flow Rate through Cracks
Authors: Tadashi Watanabe, Jinya Katsuyama, Akihiro Mano
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The estimation of leak flow rates through narrow cracks in structures is of importance for nuclear reactor safety, since the leak flow could be detected before occurrence of loss-of-coolant accidents. The two-phase critical leak flow rates are calculated using the system analysis code, and two representative non-homogeneous critical flow models, Henry-Fauske model and Ransom-Trapp model, are compared. The pressure decrease and vapor generation in the crack, and the leak flow rates are found to be larger for the Henry-Fauske model. It is shown that the leak flow rates are not affected by the structural temperature, but affected largely by the roughness of crack surface.
Keywords: Crack, critical flow, leak, roughness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8413753 Research on Hybrid Neural Network in Intrusion Detection System
Authors: Jianhua Wang, Yan Yu
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This paper presents an intrusion detection system of hybrid neural network model based on RBF and Elman. It is used for anomaly detection and misuse detection. This model has the memory function .It can detect discrete and related aggressive behavior effectively. RBF network is a real-time pattern classifier, and Elman network achieves the memory ability for former event. Based on the hybrid model intrusion detection system uses DARPA data set to do test evaluation. It uses ROC curve to display the test result intuitively. After the experiment it proves this hybrid model intrusion detection system can effectively improve the detection rate, and reduce the rate of false alarm and fail.
Keywords: RBF, Elman, anomaly detection, misuse detection, hybrid neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23273752 Fault Detection of Pipeline in Water Distribution Network System
Authors: Shin Je Lee, Go Bong Choi, Jeong Cheol Seo, Jong Min Lee, Gibaek Lee
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Water pipe network is installed underground and once equipped, it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate or pressure. The transient model describing water flow in pipelines is presented and simulated using MATLAB. The fault situations such as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the better fault detection performance.Keywords: fault detection, water pipeline model, fast Fourier transform, discrete wavelet transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23423751 Use of Hierarchical Temporal Memory Algorithm in Heart Attack Detection
Authors: Tesnim Charrad, Kaouther Nouira, Ahmed Ferchichi
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In order to reduce the number of deaths due to heart problems, we propose the use of Hierarchical Temporal Memory Algorithm (HTM) which is a real time anomaly detection algorithm. HTM is a cortical learning algorithm based on neocortex used for anomaly detection. In other words, it is based on a conceptual theory of how the human brain can work. It is powerful in predicting unusual patterns, anomaly detection and classification. In this paper, HTM have been implemented and tested on ECG datasets in order to detect cardiac anomalies. Experiments showed good performance in terms of specificity, sensitivity and execution time.Keywords: HTM, Real time anomaly detection, ECG, Cardiac Anomalies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7943750 Program Memories Error Detection and Correction On-Board Earth Observation Satellites
Authors: Y. Bentoutou
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Memory Errors Detection and Correction aim to secure the transaction of data between the central processing unit of a satellite onboard computer and its local memory. In this paper, the application of a double-bit error detection and correction method is described and implemented in Field Programmable Gate Array (FPGA) technology. The performance of the proposed EDAC method is measured and compared with two different EDAC devices, using the same FPGA technology. Statistical analysis of single-event upset (SEU) and multiple-bit upset (MBU) activity in commercial memories onboard the first Algerian microsatellite Alsat-1 is given.
Keywords: Error Detection and Correction, On-board computer, small satellite missions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22213749 Memory and Higher Cognition
Authors: A. Páchová
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Working memory (WM) can be defined as the system which actively holds information in the mind to do tasks in spite of the distraction. Contrary, short-term memory (STM) is a system that represents the capacity for the active storing of information without distraction. There has been accumulating evidence that these types of memory are related to higher cognition (HC). The aim of this study was to verify the relationship between HC and memory (visual STM and WM, auditory STM and WM). 59 primary school children were tested by intelligence test, mathematical tasks (HC) and memory subtests. We have shown that visual but not auditory memory is a significant predictor of higher cognition. The relevance of these results are discussed.Keywords: higher cognition, long-term memory, short-term memory, working memory
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15503748 Virtual Environment Design Guidelines for Elderly People in Early Detection of Dementia
Authors: Syadiah Nor Wan Shamsuddin, Valerie Lesk , Hassan Ugail
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Early detection of dementia by testing the spatial memory can be applied using a virtual environment. This paper presents guidelines on how to design a virtual environment specifically for elderly in early detection of dementia. The specific design needs to be considered because the effectiveness of the technology relies on the ability of the end user to use it. The primary goal of these guidelines is to promote accessibility. Based on these guidelines, a virtual simulation was developed and evaluated. The results on usability of acceptance and satisfaction that are tested on young (control group) and elderly participants indicate that these guidelines are reliable and useful for use with elderly people.Keywords: Virtual Environment, spatial memory, design, guidelines
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18483747 Inefficiency of Data Storing in Physical Memory
Authors: Kamaruddin Malik Mohamad, Sapiee Haji Jamel, Mustafa Mat Deris
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Memory forensic is important in digital investigation. The forensic is based on the data stored in physical memory that involve memory management and processing time. However, the current forensic tools do not consider the efficiency in terms of storage management and the processing time. This paper shows the high redundancy of data found in the physical memory that cause inefficiency in processing time and memory management. The experiment is done using Borland C compiler on Windows XP with 512 MB of physical memory.Keywords: Digital Evidence, Memory Forensics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20193746 Bandwidth, Area Efficient and Target Device Independent DDR SDRAM Controller
Authors: T. Mladenov, F. Mujahid, E. Jung, D. Har
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The application of the synchronous dynamic random access memory (SDRAM) has gone beyond the scope of personal computers for quite a long time. It comes into hand whenever a big amount of low price and still high speed memory is needed. Most of the newly developed stand alone embedded devices in the field of image, video and sound processing take more and more use of it. The big amount of low price memory has its trade off – the speed. In order to take use of the full potential of the memory, an efficient controller is needed. Efficient stands for maximum random accesses to the memory both for reading and writing and less area after implementation. This paper proposes a target device independent DDR SDRAM pipelined controller and provides performance comparison with available solutions.Keywords: DDR SDRAM, controller, effective implementation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15543745 The Application of Specialized Memory Manager in Interactive CAD Systems
Authors: Wei Song, Lian-he Yang
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Interactive CAD systems have to allocate and deallocate memory frequently. Frequent memory allocation and deallocation can play a significant role in degrading application performance. An application may use memory in a very specific way and pay a performance penalty for functionality it does not need. We could counter that by developing specialized memory managers.Keywords: Interactive CAD systems, Specialized Memory Manager.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13233744 Dynamic Variation in Nano-Scale CMOS SRAM Cells Due to LF/RTS Noise and Threshold Voltage
Authors: M. Fadlallah, G. Ghibaudo, C. G. Theodorou
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The dynamic variation in memory devices such as the Static Random Access Memory can give errors in read or write operations. In this paper, the effect of low-frequency and random telegraph noise on the dynamic variation of one SRAM cell is detailed. The effect on circuit noise, speed, and length of time of processing is examined, using the Supply Read Retention Voltage and the Read Static Noise Margin. New test run methods are also developed. The obtained results simulation shows the importance of noise caused by dynamic variation, and the impact of Random Telegraph noise on SRAM variability is examined by evaluating the statistical distributions of Random Telegraph noise amplitude in the pull-up, pull-down. The threshold voltage mismatch between neighboring cell transistors due to intrinsic fluctuations typically contributes to larger reductions in static noise margin. Also the contribution of each of the SRAM transistor to total dynamic variation has been identified.
Keywords: Low-frequency noise, Random Telegraph Noise, Dynamic Variation, SRRV.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7193743 Research on Development and Accuracy Improvement of an Explosion Proof Combustible Gas Leak Detector Using an IR Sensor
Authors: Gyoutae Park, Seungho Han, Byungduk Kim, Youngdo Jo, Yongsop Shim, Yeonjae Lee, Sangguk Ahn, Hiesik Kim, Jungil Park
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In this paper, we presented not only development technology of an explosion proof type and portable combustible gas leak detector but also algorithm to improve accuracy for measuring gas concentrations. The presented techniques are to apply the flame-proof enclosure and intrinsic safe explosion proof to an infrared gas leak detector at first in Korea and to improve accuracy using linearization recursion equation and Lagrange interpolation polynomial. Together, we tested sensor characteristics and calibrated suitable input gases and output voltages. Then, we advanced the performances of combustible gaseous detectors through reflecting demands of gas safety management fields. To check performances of two company's detectors, we achieved the measurement tests with eight standard gases made by Korea Gas Safety Corporation. We demonstrated our instruments better in detecting accuracy other than detectors through experimental results.
Keywords: Gas sensor, leak, detector, accuracy, interpolation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14013742 The Relationship between Representational Conflicts, Generalization, and Encoding Requirements in an Instance Memory Network
Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy
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This paper aims to provide an interpretation of artificial neural networks (ANNs) and explore some of its implications. The interpretation views ANNs as a memory which encodes instances of experience. An experiment explores the behavior of encoding and retrieval of instances from memory. A localised representation ANN is created that allows control over encoding and retrieved memory sample size and is experimented with using the MNIST digits dataset. The relationship between input familiarity, conflict within retrieved samples, and error rates is described and demonstrated to be an effective driver for memory encoding. Results indicate that selective encoding and retrieval samples that allow detection of memory conflicts produce optimal performance, and that error rates are normally distributed with input familiarity and conflict. By using input familiarity and sample consistency to guide memory encoding, the number of encoding trials on the dataset were reduced to 18.33% of the training data while maintaining good recognition performance on the test data.
Keywords: Artificial Neural Networks, ANNs, representation, memory, conflict monitoring, confidence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5063741 Liveness Detection for Embedded Face Recognition System
Authors: Hyung-Keun Jee, Sung-Uk Jung, Jang-Hee Yoo
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To increase reliability of face recognition system, the system must be able to distinguish real face from a copy of face such as a photograph. In this paper, we propose a fast and memory efficient method of live face detection for embedded face recognition system, based on the analysis of the movement of the eyes. We detect eyes in sequential input images and calculate variation of each eye region to determine whether the input face is a real face or not. Experimental results show that the proposed approach is competitive and promising for live face detection.Keywords: Liveness Detection, Eye detection, SQI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31813740 An Implementation of Data Reusable MPEG Video Coding Scheme
Authors: Vasily G. Moshnyaga
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This paper presents an optimized MPEG2 video codec implementation, which drastically reduces the number of computations and memory accesses required for video compression. Unlike traditional scheme, we reuse data stored in frame memory to omit unnecessary coding operations and memory read/writes for unchanged macroblocks. Due to dynamic memory sharing among reference frames, data-driven macroblock characterization and selective macroblock processing, we perform less than 15% of the total operations required by a conventional coder while maintaining high picture quality.
Keywords: Data reuse, adaptive processing, video coding, MPEG
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12663739 Distributed Detection and Optimal Traffic-blocking of Network Worms
Authors: Zoran Nikoloski, Narsingh Deo, Ludek Kucera
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Despite the recent surge of research in control of worm propagation, currently, there is no effective defense system against such cyber attacks. We first design a distributed detection architecture called Detection via Distributed Blackholes (DDBH). Our novel detection mechanism could be implemented via virtual honeypots or honeynets. Simulation results show that a worm can be detected with virtual honeypots on only 3% of the nodes. Moreover, the worm is detected when less than 1.5% of the nodes are infected. We then develop two control strategies: (1) optimal dynamic trafficblocking, for which we determine the condition that guarantees minimum number of removed nodes when the worm is contained and (2) predictive dynamic traffic-blocking–a realistic deployment of the optimal strategy on scale-free graphs. The predictive dynamic traffic-blocking, coupled with the DDBH, ensures that more than 40% of the network is unaffected by the propagation at the time when the worm is contained.Keywords: Network worms, distributed detection, optimaltraffic-blocking, individual-based simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14383738 Testing Loaded Programs Using Fault Injection Technique
Authors: S. Manaseer, F. A. Masooud, A. A. Sharieh
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Fault tolerance is critical in many of today's large computer systems. This paper focuses on improving fault tolerance through testing. Moreover, it concentrates on the memory faults: how to access the editable part of a process memory space and how this part is affected. A special Software Fault Injection Technique (SFIT) is proposed for this purpose. This is done by sequentially scanning the memory of the target process, and trying to edit maximum number of bytes inside that memory. The technique was implemented and tested on a group of programs in software packages such as jet-audio, Notepad, Microsoft Word, Microsoft Excel, and Microsoft Outlook. The results from the test sample process indicate that the size of the scanned area depends on several factors. These factors are: process size, process type, and virtual memory size of the machine under test. The results show that increasing the process size will increase the scanned memory space. They also show that input-output processes have more scanned area size than other processes. Increasing the virtual memory size will also affect the size of the scanned area but to a certain limit.Keywords: Complex software systems, Error detection, Fault tolerance, Injection and testing methodology, Memory faults, Process and virtual memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18863737 Analysis of Performance of 3T1D Dynamic Random-Access Memory Cell
Authors: Nawang Chhunid, Gagnesh Kumar
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On-chip memories consume a significant portion of the overall die space and power in modern microprocessors. On-chip caches depend on Static Random-Access Memory (SRAM) cells and scaling of technology occurring as per Moore’s law. Unfortunately, the scaling is affecting stability, performance, and leakage power which will become major problems for future SRAMs in aggressive nanoscale technologies due to increasing device mismatch and variations. 3T1D Dynamic Random-Access Memory (DRAM) cell is a non-destructive read DRAM cell with three transistors and a gated diode. In 3T1D DRAM cell gated diode (D1) acts as a storage device and also as an amplifier, which leads to fast read access. Due to its high tolerance to process variation, high density, and low cost of memory as compared to 6T SRAM cell, it is universally used by the advanced microprocessor for on chip data and program memory. In the present paper, it has been shown that 3T1D DRAM cell can perform better in terms of fast read access as compared to 6T, 4T, 3T SRAM cells, respectively.Keywords: DRAM cell, read access time, tanner EDA tool write access time and retention time, average power dissipation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13403736 Schmitt Trigger Based SRAM Using Finfet Technology- Shorted Gate Mode
Authors: Vasundara Patel K. S., Harsha N. Bhushan, Kiran G. Gadag, Nischal Prasad B. N., Mohmmed Haroon
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The most widely used semiconductor memory types are the Dynamic Random Access Memory (DRAM) and Static Random Access memory (SRAM). Competition among memory manufacturers drives the need to decrease power consumption and reduce the probability of read failure. A technology that is relatively new and has not been explored is the FinFET technology. In this paper, a single cell Schmitt Trigger Based Static RAM using FinFET technology is proposed and analyzed. The accuracy of the result is validated by means of HSPICE simulations with 32nm FinFET technology and the results are then compared with 6T SRAM using the same technology.
Keywords: Schmitt trigger based SRAM, FinFET, and Static Noise Margin.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28503735 Reduced Dynamic Time Warping for Handwriting Recognition Based on Multidimensional Time Series of a Novel Pen Device
Authors: Muzaffar Bashir, Jürgen Kempf
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The purpose of this paper is to present a Dynamic Time Warping technique which reduces significantly the data processing time and memory size of multi-dimensional time series sampled by the biometric smart pen device BiSP. The acquisition device is a novel ballpoint pen equipped with a diversity of sensors for monitoring the kinematics and dynamics of handwriting movement. The DTW algorithm has been applied for time series analysis of five different sensor channels providing pressure, acceleration and tilt data of the pen generated during handwriting on a paper pad. But the standard DTW has processing time and memory space problems which limit its practical use for online handwriting recognition. To face with this problem the DTW has been applied to the sum of the five sensor signals after an adequate down-sampling of the data. Preliminary results have shown that processing time and memory size could significantly be reduced without deterioration of performance in single character and word recognition. Further excellent accuracy in recognition was achieved which is mainly due to the reduced dynamic time warping RDTW technique and a novel pen device BiSP.Keywords: Biometric character recognition, biometric person authentication, biometric smart pen BiSP, dynamic time warping DTW, online-handwriting recognition, multidimensional time series.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24063734 Research and Development of a Biomorphic Robot Driven by Shape Memory Alloys
Authors: Y.J. Lai, H.Y. Peng, M.W. Wu, J. Shaw
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In this study, we used shape memory alloys as actuators to build a biomorphic robot which can imitate the motion of an earthworm. The robot can be used to explore in a narrow space. Therefore we chose shape memory alloys as actuators. Because of the small deformation of a wire shape memory alloy, spiral shape memory alloys are selected and installed both on the X axis and Y axis (each axis having two shape memory alloys) to enable the biomorphic robot to do reciprocating motion. By the mechanism we designed, the robot can increase the distance as it moves in a duty cycle. In addition, two shape memory alloys are added to the robot head for controlling right and left turns. By sending pulses through the I/O card from the controller, the signals are then amplified by a driver to heat the shape memory alloys in order to make the SMA shrink to pull the mechanism to move.Keywords: Biomorphic Robot, Shape Memory Alloy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16543733 Real-Time Episodic Memory Construction for Optimal Action Selection in Cognitive Robotics
Authors: Deon de Jager, Yahya Zweiri, Dimitrios Makris
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The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.
Keywords: Cognitive robotics, semantic memory, episodic memory, maximum entropy principle, particle swarm optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16353732 Simulation and Experimentation on the Contact Width of New Metal Gasket for Asbestos Substitution
Authors: Moch. Agus Choiron, Yoshihiro Kurata, Shigeyuki Haruyama, Ken Kaminishi
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The contact width is important design parameter for optimizing the design of new metal gasket for asbestos substitution gasket. The contact width is found have relationship with the helium leak quantity. In the increasing of axial load value, the helium leak quantity is decreasing and the contact width is increasing. This study provides validity method using simulation analysis and the result is compared to experimental using pressure sensitive paper. The results denote similar trend data between simulation and experimental result. Final evaluation is determined by helium leak quantity to check leakage performance of gasket design. Considering the phenomena of position change on the convex contact, it can be developed the optimization of gasket design by increasing contact width.Keywords: contact width, simulation, pressure sensitive paper.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19463731 Detecting and Tracking Vehicles in Airborne Videos
Authors: Hsu-Yung Cheng, Chih-Chang Yu
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In this work, we present an automatic vehicle detection system for airborne videos using combined features. We propose a pixel-wise classification method for vehicle detection using Dynamic Bayesian Networks. In spite of performing pixel-wise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. The main novelty of the detection scheme is that the extracted combined features comprise not only pixel-level information but also region-level information. Afterwards, tracking is performed on the detected vehicles. Tracking is performed using efficient Kalman filter with dynamic particle sampling. Experiments were conducted on a wide variety of airborne videos. We do not assume prior information of camera heights, orientation, and target object sizes in the proposed framework. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging dataset.Keywords: Vehicle Detection, Airborne Video, Tracking, Dynamic Bayesian Networks
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15873730 Applications of Prediction and Identification Using Adaptive DCMAC Neural Networks
Authors: Yu-Lin Liao, Ya-Fu Peng
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An adaptive dynamic cerebellar model articulation controller (DCMAC) neural network used for solving the prediction and identification problem is proposed in this paper. The proposed DCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) neural network in efficient learning mechanism, guaranteed system stability and dynamic response. The recurrent network is embedded in the DCMAC by adding feedback connections in the association memory space so that the DCMAC captures the dynamic response, where the feedback units act as memory elements. The dynamic gradient descent method is adopted to adjust DCMAC parameters on-line. Moreover, the analytical method based on a Lyapunov function is proposed to determine the learning-rates of DCMAC so that the variable optimal learning-rates are derived to achieve most rapid convergence of identifying error. Finally, the adaptive DCMAC is applied in two computer simulations. Simulation results show that accurate identifying response and superior dynamic performance can be obtained because of the powerful on-line learning capability of the proposed DCMAC.Keywords: adaptive, cerebellar model articulation controller, CMAC, prediction, identification
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14013729 The Characterisation of TLC NAND Flash Memory, Leading to a Definable Endurance/Retention Trade-Off
Authors: Sorcha Bennett, Joe Sullivan
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Triple-Level Cell (TLC) NAND Flash memory at, and below, 20nm (nanometer) is still largely unexplored by researchers, and with the ever more commonplace existence of Flash in consumer and enterprise applications there is a need for such gaps in knowledge to be filled. At the time of writing, there was little published data or literature on TLC, and more specifically reliability testing, with a further emphasis on both endurance and retention. This paper will give an introduction to NAND Flash memory, followed by an overview of the relevant current research on the reliability of Flash memory, along with the planned future work which will provide results to help characterise the reliability of TLC memory.Keywords: TLC NAND flash memory, reliability, endurance, retention, trade-off, raw flash, patterns.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3514