Search results for: Shared Memory Parallel Computing

Authors: Mona Soliman Habib

Abstract:

This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.

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Authors: Masahiro Taketa, Masaki Ito, Takao Kawamura, Kazunori Sugahara

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We develop a new interface for Bus-Net which is optimized for a smartphone. We are continuing to develop the shortest path planning system of public transportation called "Bus-Net" in Tottori prefecture as web application to improve the usability of public transportation. Recent trend of computing platform, however has shifted to an advanced mobile device called a smartphone such as iPhone and Android in Japan. A smartphone has different characters with existing feature phone in terms of OS, large touche panel, and several other features. We derive a guideline to design the new interface for a smartphone to full use of the functionality. The guideline is about simplicity of user-s operation, location awareness and usability. We developed the new interface for “Bus-Net" on iPhone referring to the guideline. Due to the evaluation, the application interface we developed is better than the existing web-based interface in terms of the usability.

Keywords: Path Planning, Public Transportation, Smartphone, User Interface

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Authors: Sevil Yildiz

Abstract:

In parallel, broadcasting has changed rapidly with the changing of the world at the same area. Broadcasting is also influenced and reshaped in terms of the emergence of new communication technologies. These developments have resulted a lot of economic and social consequences. The most important consequences of these results are those of the powers of the governments to control over the means of communication and control mechanisms related to the descriptions of the new issues. For this purpose, autonomous and independent regulatory bodies have been established by the state. One of these regulatory bodies is the Radio and Television Supreme Council, which to be established in 1994, with the Code no 3984. Today’s Radio and Television Supreme Council which is responsible for the regulation of the radio and television broadcasts all across Turkey has an important and effective position as autonomous and independent regulatory body. The Radio and Television Supreme Council acts as being a remarkable organizer for a sensitive area of radio and television broadcasting on one hand, and the area of democratic, liberal and keep in mind the concept of the public interest by putting certain principles for the functioning of the Board control, in the context of media policy as one of the central organs, on the other hand. In this study, the role of the Radio and Television Supreme Council is examined in accordance with the Code no 3894 in order to control over the communication and control mechanisms as well as the examination of the changes in the duties of the Code No. 6112, dated 2011.

Keywords: Regulatory Boards, Radio and Television Supreme Council.

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Authors: Azze-Eddine Maredj, Nourredine Tonkin

Abstract:

The recent developments in computing and communication technology permit to users to access multimedia documents with variety of devices (PCs, PDAs, mobile phones...) having heterogeneous capabilities. This diversification of supports has trained the need to adapt multimedia documents according to their execution contexts. A semantic framework for multimedia document adaptation based on the conceptual neighborhood graphs was proposed. In this framework, adapting consists on finding another specification that satisfies the target constraints and which is as close as possible from the initial document. In this paper, we propose a new way of building the conceptual neighborhood graphs to best preserve the proximity between the adapted and the original documents and to deal with more elaborated relations models by integrating the relations relaxation graphs that permit to handle the delays and the distances defined within the relations.

Keywords: Conceptual Neighborhood Graph, Relaxation Graphs, Relations with Delays, Semantic Adaptation of Multimedia Documents.

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Authors: Gaoyong Luo

Abstract:

The approach based on the wavelet transform has been widely used for image denoising due to its multi-resolution nature, its ability to produce high levels of noise reduction and the low level of distortion introduced. However, by removing noise, high frequency components belonging to edges are also removed, which leads to blurring the signal features. This paper proposes a new method of image noise reduction based on local variance and edge analysis. The analysis is performed by dividing an image into 32 x 32 pixel blocks, and transforming the data into wavelet domain. Fast lifting wavelet spatial-frequency decomposition and reconstruction is developed with the advantages of being computationally efficient and boundary effects minimized. The adaptive thresholding by local variance estimation and edge strength measurement can effectively reduce image noise while preserve the features of the original image corresponding to the boundaries of the objects. Experimental results demonstrate that the method performs well for images contaminated by natural and artificial noise, and is suitable to be adapted for different class of images and type of noises. The proposed algorithm provides a potential solution with parallel computation for real time or embedded system application.

Keywords: Edge strength, Fast lifting wavelet, Image denoising, Local variance.

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Authors: B. S. Raghavendra, D. Narayana Dutt

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In this paper, we have developed a method to compute fractal dimension (FD) of discrete time signals, in the time domain, by modifying the box-counting method. The size of the box is dependent on the sampling frequency of the signal. The number of boxes required to completely cover the signal are obtained at multiple time resolutions. The time resolutions are made coarse by decimating the signal. The loglog plot of total number of boxes required to cover the curve versus size of the box used appears to be a straight line, whose slope is taken as an estimate of FD of the signal. The results are provided to demonstrate the performance of the proposed method using parametric fractal signals. The estimation accuracy of the method is compared with that of Katz, Sevcik, and Higuchi methods. In addition, some properties of the FD are discussed.

Keywords: Box-counting, Fractal dimension, Higuchi method, Katz method, Parametric fractal signals, Sevcik method.

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Authors: Kyung-Jung Lee, Hyun-Sik Ahn

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This paper suggests a design methodology for the hardware and software of the electronic control unit (ECU) of safety-critical vehicle applications such as braking and steering. The architecture of the hardware is a high integrity system such thatit incorporates a high performance 32-bit CPU and a separate peripheral controlprocessor (PCP) together with an external watchdog CPU. Communication between the main CPU and the PCP is executed via a common area of RAM and events on either processor which are invoked by interrupts. Safety-related software is also implemented to provide a reliable, self-testing computing environment for safety critical and high integrity applications. The validity of the design approach is shown by using the hardware-in-the-loop simulation (HILS)for electric power steering(EPS) systemswhich consists of the EPS mechanism, the designed ECU, and monitoring tools.

Keywords: Electronic control unit, electric power steering, functional safety, hardware-in-the-loop simulation.

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Authors: Ali Shatnawi

Abstract:

Signal processing applications which are iterative in nature are best represented by data flow graphs (DFG). In these applications, the maximum sampling frequency is dependent on the topology of the DFG, the cyclic dependencies in particular. The determination of the iteration bound, which is the reciprocal of the maximum sampling frequency, is critical in the process of hardware implementation of signal processing applications. In this paper, a novel technique to compute the iteration bound is proposed. This technique is different from all previously proposed techniques, in the sense that it is based on the natural flow of tokens into the DFG rather than the topology of the graph. The proposed algorithm has lower run-time complexity than all known algorithms. The performance of the proposed algorithm is illustrated through analytical analysis of the time complexity, as well as through simulation of some benchmark problems.

Keywords: Data flow graph, Iteration period bound, Rateoptimalscheduling, Recursive DSP algorithms.

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Authors: Alexander A. Muravyov

Abstract:

A minimal complexity version of component mode synthesis is presented that requires simplified computer programming, but still provides adequate accuracy for modeling lower eigenproperties of large structures and their transient responses. The novelty is that a structural separation into components is done along a plane/surface that exhibits rigid-like behavior, thus only normal modes of each component is sufficient to use, without computing any constraint, attachment, or residual-attachment modes. The approach requires only such input information as a few (lower) natural frequencies and corresponding undamped normal modes of each component. A novel technique is shown for formulation of equations of motion, where a double transformation to generalized coordinates is employed and formulation of nonproportional damping matrix in generalized coordinates is shown.

Keywords: component mode synthesis, finite element models, transient response, nonproportional damping

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Authors: Dejan Tanikić, Jelena Đoković, Saša Kalinović, Miodrag Manić, Saša Ranđelović

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This paper deals with measuring and modelling of the quality of the machined surface of the metal machining process. The average surface roughness (R_a) which represents the quality of the machined part was measured during the dry turning of the AISI 4140 steel. A large number of factors with the unknown relations among them influences this parameter, and that is why mathematical modelling is extremely complicated. Different values of cutting speed, feed rate, depth of cut (cutting regime) and workpiece hardness causes different surface roughness values. Modelling with soft computing techniques may be very useful in such cases. This paper presents the usage of the fuzzy logic-based system for determining metal machining process parameter in order to find the proper values of cutting regimes.

Keywords: Metal machining, surface roughness, fuzzy logic, process modelling.

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Authors: Sheng-Hsiu Kuo, Pao-Hsiung Chiu, Reui-Kuo Lin, Yan-Ting Lin

Abstract:

A one-step conservative level set method, combined with a global mass correction method, is developed in this study to simulate the incompressible two-phase flows. The present framework do not need to solve the conservative level set scheme at two separated steps, and the global mass can be exactly conserved. The present method is then more efficient than two-step conservative level set scheme. The dispersion-relation-preserving schemes are utilized for the advection terms. The pressure Poisson equation solver is applied to GPU computation using the pCDR library developed by National Center for High-Performance Computing, Taiwan. The SMP parallelization is used to accelerate the rest of calculations. Three benchmark problems were done for the performance evaluation. Good agreements with the referenced solutions are demonstrated for all the investigated problems.

Keywords: Conservative level set method, two-phase flow, dispersion-relation-preserving, graphics processing unit (GPU), multi-threading.

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Authors: San Nah Sze, Wei King Tiong

Abstract:

The multiple traveling salesman problem (mTSP) can be used to model many practical problems. The mTSP is more complicated than the traveling salesman problem (TSP) because it requires determining which cities to assign to each salesman, as well as the optimal ordering of the cities within each salesman's tour. Previous studies proposed that Genetic Algorithm (GA), Integer Programming (IP) and several neural network (NN) approaches could be used to solve mTSP. This paper compared the results for mTSP, solved with Genetic Algorithm (GA) and Nearest Neighbor Algorithm (NNA). The number of cities is clustered into a few groups using k-means clustering technique. The number of groups depends on the number of salesman. Then, each group is solved with NNA and GA as an independent TSP. It is found that k-means clustering and NNA are superior to GA in terms of performance (evaluated by fitness function) and computing time.

Keywords: Multiple Traveling Salesman Problem, GeneticAlgorithm, Nearest Neighbor Algorithm, k-Means Clustering.

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Authors: Mohamad Izuddin Nordin, Azween Abdullah, Mahamat Issa Hassan

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In this paper, cloud resource broker using goalbased request in medical application is proposed. To handle recent huge production of digital images and data in medical informatics application, the cloud resource broker could be used by medical practitioner for proper process in discovering and selecting correct information and application. This paper summarizes several reviewed articles to relate medical informatics application with current broker technology and presents a research work in applying goal-based request in cloud resource broker to optimize the use of resources in cloud environment. The objective of proposing a new kind of resource broker is to enhance the current resource scheduling, discovery, and selection procedures. We believed that it could help to maximize resources allocation in medical informatics application.

Keywords: Broker, Cloud Computing, Medical Informatics, Resources Discovery, Resource Selection.

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Authors: Hasanifard Goran, Habib Nejad Korayem Moharam, Nikoobin Amin

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A new robust nonlinear control scheme of a manipulator is proposed in this paper which is robust against modeling errors and unknown disturbances. It is based on the principle of variable structure control, with sliding mode control (SMC) method. The variable structure control method is a robust method that appears to be well suited for robotic manipulators because it requers only bounds on the robotic arm parameters. But there is no single systematic procedure that is guaranteed to produce a suitable control law. Also, to reduce chattring of the control signal, we replaced the sgn function in the control law by a continuous approximation such as tangant function. We can compute the maximum load with regard to applied torque into joints. The effectivness of the proposed approach has been evaluated analitically demonstrated through computer simulations for the cases of variable load and robot arm parameters.

Keywords: Variable structure control, robust control, switching surface, robot manipulator.

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Authors: Yung-Chuan Lee, Shahram Rahimi, Bidyut Gupta

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In this paper, we introduce an mobile agent framework with proactive load balancing for ambient intelligence (AmI) environments. One of the main obstacles of AmI is the scalability in which the openness of AmI environment introduces dynamic resource requirements on agencies. To mediate this scalability problem, our framework proposes a load balancing module to proactively analyze the resource consumption of network bandwidth and preferred agencies to suggest the optimal communication method to its user. The framework generally formulates an AmI environment that consists of three main components: (1) mobile devices, (2) hosts or agencies, and (3) directory service center (DSC). A preliminary implementation was conducted with NetLogo and the experimental results show that the proposed approach provides enhanced system performance by minimizing the network utilization to provide users with responsive services.

Keywords: Ambient intelligence, load balancing, multiagent systems, ubiquitous computing.

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Authors: Azian Hariri, M. Z. M Yusof, A. M. Leman

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Experimental study was conducted to assess personal welding fumes exposure toward welders during an aluminum metal inert gas (MIG) process. The welding process was carried out by a welding machine attached to a Computer Numerical Control (CNC) workbench. A dummy welder was used to replicate welder during welding works and was attached with sampling pumps and filter cassettes for welding fumes sampling. Direct reading instruments to measure air velocity, humidity, temperature and particulate matter with diameter size 10µm or less (PM₁₀) were located behind the dummy welder and parallel to the neck collar level to make sure the measured welding fumes exposure were not being influenced by other factors. Welding fumes exposure during standing and sitting position with and without the usage of local exhaust ventilation (LEV) was investigated. Welding fume samples were then digested and analyzed by using inductively coupled plasma mass spectroscopy (ICP-MS) according to ASTM D7439-08 method. The results of the study showed the welding fume exposure during sitting was lower compared to standing position. LEV helped reduce aluminum and lead exposure to acceptable levels during standing position. However during sitting position reduction of exposure was smaller. It can be concluded that welder position and the correct positioning of LEV should be implemented for effective exposure reduction. 

Keywords: ICP-MS, MIG process, personal sampling, welding fumes exposure.

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: Anomaly detection, autoencoder, data centers, deep learning.

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Authors: T. Vigneswari, M. A. Maluk Mohamed

Abstract:

Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foraging behaviour of bees. This work proposes a modified ABC algorithm, Cluster Heterogeneous Earliest First Min- Min Artificial Bee Colony (CHMM-ABC), to optimally schedule jobs for the available resources. The proposed model utilizes a novel Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm along with Min-Min algorithm to identify the initial food source. Simulation results show the performance improvement of the proposed algorithm over other swarm intelligence techniques.

Keywords: Grid Computing, Grid Scheduling, Heterogeneous Earliest Finish Time (HEFT), Artificial Bee colony (ABC) Algorithm, Resource Management.

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Authors: Dana Kristalova, Jan Mazal

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This article deals with geographical conditions in terrain and their effect on the movement of vehicles, their effect on speed and safety of movement of people and vehicles. Finding of the optimal routes outside the communication is studied in the Army environment, but it occur in civilian as well, primarily in crisis situation, or by the provision of assistance when natural disasters such as floods, fires, storms etc., have happened. These movements require the optimization of routes when effects of geographical factors should be included. The most important factor is the surface of a terrain. It is based on several geographical factors as are slopes, soil conditions, micro-relief, a type of surface and meteorological conditions. Their mutual impact has been given by coefficient of deceleration. This coefficient can be used for the commander`s decision. New approaches and methods of terrain testing, mathematical computing, mathematical statistics or cartometric investigation are necessary parts of this evaluation.

Keywords: Movement in a terrain, geographical factors, surface of a field, mathematical evaluation, optimization and searching paths.

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Authors: Rima Grati, Khouloud Boukadi, Hanene Ben-Abdallah

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Due to the dynamic nature of the Cloud, continuous monitoring of QoS requirements is necessary to manage the Cloud computing environment. The process of QoS monitoring and SLA violation detection consists of: collecting low and high level information pertinent to the service, analyzing the collected information, and taking corrective actions when SLA violations are detected. In this paper, we detail the architecture and the implementation of the first step of this process. More specifically, we propose an event-based approach to obtain run time information of services developed as BPEL processes. By catching particular events (i.e., the low level information), our approach recognizes the run-time execution path of a monitored service and uses the BPEL execution patterns to compute QoS of the composite service (i.e., the high level information).

Keywords: Monitoring of Web service composition, Cloud environment, Run-time extraction of execution path of BPEL.

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Authors: Robiul Islam, Monjurul Hasan, Rezaul Karim, M. F. M. Zain

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Coal fly ash, an industrial by product of coal combustion thermal power plants is considered as a hazardous material and its improper disposal has become an environmental issue. On the other hand, manufacturing conventional clay bricks involves on consumption of large amount of clay and leads substantial depletion of topsoil. This paper unveils the possibility of using fly ash as a partial replacement of clay for brick manufacturing considering the local technology practiced in Bangladesh. The effect of fly ash with different replacing ratio (0%, 20%, 30%, 40%, and 50% by volume) of clay on properties of bricks was studied. Bricks were made in the field parallel to ordinary bricks marked with specific number for different percentage to identify them at time of testing. No physical distortion is observed in fly ash brick after burning in the kiln. Results from laboratory test show that compressive strength of brick is decreased with the increase of fly ash and maximum compressive strength is found to be 19.6 MPa at 20% of fly ash. In addition, water absorption of fly ash brick is increased with the increase of fly ash. The abrasion value and Specific gravity of coarse aggregate prepared from brick with fly ash also studied and the results of this study suggests that 20% fly ash can be considered as the optimum fly ash content for producing good quality bricks utilizing present practiced technology.

Keywords: Bangladesh brick, fly ash, clay brick, physical properties, compressive strength.

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

Abstract:

2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: Artificial Intelligence, machine learning, deep learning, convolutional neural networks.

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Authors: Jeffrey A. Dunne, Kevin Ligozio

Abstract:

In many applications there is a broad variety of information relevant to a focal “object" of interest, and the fusion of such heterogeneous data types is desirable for classification and categorization. While these various data types can sometimes be treated as orthogonal (such as the hull number, superstructure color, and speed of an oil tanker), there are instances where the inference and the correlation between quantities can provide improved fusion capabilities (such as the height, weight, and gender of a person). A service-oriented architecture has been designed and prototyped to support the fusion of information for such “object-centric" situations. It is modular, scalable, and flexible, and designed to support new data sources, fusion algorithms, and computational resources without affecting existing services. The architecture is designed to simplify the incorporation of legacy systems, support exact and probabilistic entity disambiguation, recognize and utilize multiple types of uncertainties, and minimize network bandwidth requirements.

Keywords: Data fusion, distributed computing, service-oriented architecture, SOA

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Authors: Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang

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In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

Keywords: Deep learning, convolutional neural network, LSTM, housing prediction.

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Authors: Kang-Gyu Park, Sun-Jong Park, Hong Jae Yim, Hyo-Gyung Kwak

Abstract:

This paper attempts to evaluate the effect of fire damage on concrete by using nonlinear resonance vibration method, one of the nonlinear nondestructive method. Concrete exhibits not only nonlinear stress-strain relation but also hysteresis and discrete memory effect which are contained in consolidated materials. Hysteretic materials typically show the linear resonance frequency shift. Also, the shift of resonance frequency is changed according to the degree of micro damage. The degree of the shift can be obtained through nonlinear resonance vibration method. Five exposure scenarios were considered in order to make different internal micro damage. Also, the effect of post-fire-curing on fire-damaged concrete was taken into account to conform the change in internal damage. Hysteretic nonlinearity parameter was obtained by amplitudedependent resonance frequency shift after specific curing periods. In addition, splitting tensile strength was measured on each sample to characterize the variation of residual strength. Then, a correlation between the hysteretic nonlinearity parameter and residual strength was proposed from each test result.

Keywords: Fire damaged concrete, nonlinear resonance vibration method, nonlinearity parameter, post-fire-curing, splitting tensile strength.

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Authors: Prakash G L, Thejaswini M, S H Manjula, K R Venugopal, L M Patnaik

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Computing and maintaining network structures for efficient data aggregation incurs high overhead for dynamic events where the set of nodes sensing an event changes with time. Moreover, structured approaches are sensitive to the waiting time that is used by nodes to wait for packets from their children before forwarding the packet to the sink. An optimal routing and data aggregation scheme for wireless sensor networks is proposed in this paper. We propose Tree on DAG (ToD), a semistructured approach that uses Dynamic Forwarding on an implicitly constructed structure composed of multiple shortest path trees to support network scalability. The key principle behind ToD is that adjacent nodes in a graph will have low stretch in one of these trees in ToD, thus resulting in early aggregation of packets. Based on simulations on a 2,000-node Mica2- based network, we conclude that efficient aggregation in large-scale networks can be achieved by our semistructured approach.

Keywords: Aggregation, Packet Merging, Query Processing.

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Authors: F. Vallée, J-F. Toubeau, Z. De Grève, J. Lobry

Abstract:

When evaluating the capacity of a generation park to cover the load in transmission systems, traditional Loss of Load Expectation (LOLE) and Expected Energy not Served (EENS) indices can be used. If those indices allow computing the annual duration and severity of load non covering situations, they do not take into account the fact that the load excess is generally shifted from one penury state (hour or quarter of an hour) to the following one. In this paper, a sequential Monte Carlo framework is introduced in order to compute adjusted LOLE and EENS indices. Practically, those adapted indices permit to consider the effect of load excess transfer on the global adequacy of a generation park, providing thus a more accurate evaluation of this quantity.

Keywords: Expected Energy not Served, Loss of Load Expectation, Monte Carlo simulation, reliability, wind generation.

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Authors: Erfan Asghari Fesaghandis, Reza Ghaffari Adli, Abbas Kianvash, Hossein Aghajani, Homa Homaie

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NiTi alloys possess magnificent superelastic, shape memory, high strength and biocompatible properties. For improving mechanical properties, foremost, superelasticity behavior, heat treatment process is carried out. In this paper, two different heat treatment methods were undertaken: (1) solid solution, and (2) aging. The effect of each treatment in a constant time is investigated. Five samples were prepared to study the structure and optimize mechanical properties under different time and temperature. For measuring the upper plateau stress, lower plateau stress and residual strain, tensile test is carried out. The samples were aged at two different temperatures to see difference between aging temperatures. The sample aged at 500 °C has a bigger crystallite size and lower amount of Ni which causes the mentioned sample to possess poor pseudo elasticity behaviour than the other aged sample. The sample aged at 460 °C has shown remarkable superelastic properties. The mentioned sample’s higher plateau is 580 MPa with the lowest residual strain (0.17%) while other samples have possessed higher residual strains. X-ray diffraction was used to investigate the produced phases.

Keywords: Heat treatment, phase transformation, superelasticity, NiTi alloy.

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Authors: Jia-Shiun Chen, Hsiu-Ying Hwang

Abstract:

Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.

Keywords: Hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control.

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Authors: Rudolf Egger

Abstract:

This paper explores the relationships between the basic learning processes of leading trade union workers and their methods for coping with the changes in the life-courses of societies today. It will discuss the fragile discourse on lifelong learning in trade unions and the “production of self-techniques” to get in touch with the new economic forms. On the basis of an empirical project, different processes of the socialization of leading trade union workers will be analysed to discover the consequences of the lifelong learning discourse. The results show what competences they need to develop for the “wider benefits of negotiations”. The main challenge remains to make visible how deeply intertwined trade union learning and education are with development in an ongoing dynamic economic process, rather than a quick-fix injection of skills and information. There is a complex relationship existing between the three ‘partners’, work, learning and society forming. The author suggests that contemporary trade unions could be trendsetters who make their own learning agendas by drawing less on formal education and more on informal and non-formal learning contexts. This is in parallel with growing political and scientific consciousness of the need to arrive at new educational/vocational policies and practices.

Keywords: Lifelong learning, Trade unions, Non-formal learning, Educational/vocational policies.

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