Abstract: This paper presents the study of hardness profile of spur gear heated by induction heating process in function of the machine parameters, such as the power (kW), the heating time (s) and the generator frequency (kHz). The global work is realized by 3D finite-element simulation applied to the process by coupling and resolving the electromagnetic field and the heat transfer problems, and it was performed in three distinguished steps. First, a Comsol 3D model was built using an adequate formulation and taking into account the material properties and the machine parameters. Second, the convergence study was conducted to optimize the mesh. Then, the surface temperatures and the case depths were deeply analyzed in function of the initial current density and the heating time in medium frequency (MF) and high frequency (HF) heating modes and the edge effect were studied. Finally, the simulations results are validated using experimental tests.
Abstract: Parallel programming models exist as an abstraction
of hardware and memory architectures. There are several parallel
programming models in commonly use; they are shared memory
model, thread model, message passing model, data parallel model,
hybrid model, Flynn-s models, embarrassingly parallel computations
model, pipelined computations model. These models are not specific
to a particular type of machine or memory architecture. This paper
expresses the model program for concurrent approach to data parallel
model through java programming.
Abstract: This paper presents a compact thermoelectric power generator system based on temperature difference across the element. The system can transfer the burning heat energy to electric energy directly. The proposed system has a thermoelectric generator and a power control box. In the generator, there are 4 thermoelectric modules (TEMs), each of which uses 2 thermoelectric chips (TEs) and 2 cold sinks, 1 thermal absorber, and 1 thermal conduction flat board. In the power control box, there are 1 storing energy device, 1 converter, and 1 inverter. The total net generating power is about 11W. This system uses commercial portable gas stoves or burns timber or the coal as the heat source, which is easily obtained. It adopts solid-state thermoelectric chips as heat inverter parts. The system has the advantages of being light-weight, quite, and mobile, requiring no maintenance, and havng easily-supplied heat source. The system can be used a as long as burning is allowed. This system works well for highly-mobilized outdoors situations by providing a power for illumination, entertainment equipment or the wireless equipment at refuge. Under heavy storms such as typhoon, when the solar panels become ineffective and the wind-powered machines malfunction, the thermoelectric power generator can continue providing the vital power.
Abstract: Text categorization is the problem of classifying text
documents into a set of predefined classes. In this paper, we
investigated three approaches to build a meta-classifier in order to
increase the classification accuracy. The basic idea is to learn a metaclassifier
to optimally select the best component classifier for each
data point. The experimental results show that combining classifiers
can significantly improve the accuracy of classification and that our
meta-classification strategy gives better results than each individual
classifier. For 7083 Reuters text documents we obtained a
classification accuracies up to 92.04%.
Abstract: Sharing the manufacturing facility through remote
operation and monitoring of a machining process is challenge for
effective use the production facility. Several automation tools in term
of hardware and software are necessary for successfully remote
operation of a machine. This paper presents a prototype of workpiece
holding attachment for remote operation of milling process by self
configuration the workpiece setup. The prototype is designed with
mechanism to reorient the work surface into machining spindle
direction with high positioning accuracy. Variety of parts geometry
is hold by attachment to perform single setup machining. Pin type
with array pattern additionally clamps the workpiece surface from
two opposite directions for increasing the machining rigidity.
Optimum pins configuration for conforming the workpiece geometry
with minimum deformation is determined through hybrid algorithms,
Genetic Algorithms (GA) and Particle Swarm Optimization (PSO).
Prototype with intelligent optimization technique enables to hold
several variety of workpiece geometry which is suitable for
machining low of repetitive production in remote operation.
Abstract: A solar refrigeration system based on the adsorptiondesorption
phenomena is designed and analyzed. An annular tubular
generator filled with silica gel adsorbent and with a perforated inner
cylinder is integrated within a flat solar collector. The working fluid
in the refrigeration cycle is water. The thermodynamic analysis and
because of the temperature level that could be attained with a flat
solar collector it is required that the system operates under vacuum
conditions. In order to enhance the performance of the system and to
get uniform temperature in the silica gel and higher desorbed mass,
an apparatus for rotation of the generator is incorporated in the
system. Testing is carried out and measurements are taken on the
designed installation. The effect of rotation is checked on the
temperature distribution and on the performance of this machine and
compared to the flat solar collector with fixed generator.
Abstract: In this paper, we propose a robust scheme to work face alignment and recognition under various influences. For face representation, illumination influence and variable expressions are the important factors, especially the accuracy of facial localization and face recognition. In order to solve those of factors, we propose a robust approach to overcome these problems. This approach consists of two phases. One phase is preprocessed for face images by means of the proposed illumination normalization method. The location of facial features can fit more efficient and fast based on the proposed image blending. On the other hand, based on template matching, we further improve the active shape models (called as IASM) to locate the face shape more precise which can gain the recognized rate in the next phase. The other phase is to process feature extraction by using principal component analysis and face recognition by using support vector machine classifiers. The results show that this proposed method can obtain good facial localization and face recognition with varied illumination and local distortion.
Abstract: This paper reports the fatigue crack growth behaviour
of gas tungsten arc, electron beam and laser beam welded Ti-6Al-4V
titanium alloy. Centre cracked tensile specimens were prepared to
evaluate the fatigue crack growth behaviour. A 100kN servo
hydraulic controlled fatigue testing machine was used under constant
amplitude uniaxial tensile load (stress ratio of 0.1 and frequency of
10 Hz). Crack growth curves were plotted and crack growth
parameters (exponent and intercept) were evaluated. Critical and
threshold stress intensity factor ranges were also evaluated. Fatigue
crack growth behaviour of welds was correlated with mechanical
properties and microstructural characteristics of welds. Of the three
joints, the joint fabricated by laser beam welding exhibited higher
fatigue crack growth resistance due to the presence of fine lamellar
microstructure in the weld metal.
Abstract: This study aims to identify the current situation and
problems of environmental statement for major four home appliances
(refrigerators, washing machines, air conditioners and television
receivers) sold at online stores in Japan, and then to suggest how to
improve the situation, through a questionnaire survey conducted
among businesses that operate online stores and online malls with
multiple online stores. Results of the study boil down to:
(1) It is found out that environmental statement for the home
appliances at online stores have four problems; (i) less information
on “three Rs" and “chemical substances" than the one on “energy
conservation", (ii) cost for providing environmental statement, (iii)
issues associated with a label and mark placement, and (iv) issues
associated with energy conservation statement.
(2) Improvements are suggested for each of the four problems listed
above, and shown are (i) the effectiveness of, and need to promote, a
label and mark placement, (ii) cost burden on buyers, and (iii) need
of active efforts made by businesses and of dissemination of legal
regulations to businesses.
Abstract: A fusion classifier composed of two modules, one made by a hidden Markov model (HMM) and the other by a support vector machine (SVM), is proposed to recognize faces with pose variations in open-set recognition settings. The HMM module captures the evolution of facial features across a subject-s face using the subject-s facial images only, without referencing to the faces of others. Because of the captured evolutionary process of facial features, the HMM module retains certain robustness against pose variations, yielding low false rejection rates (FRR) for recognizing faces across poses. This is, however, on the price of poor false acceptance rates (FAR) when recognizing other faces because it is built upon withinclass samples only. The SVM module in the proposed model is developed following a special design able to substantially diminish the FAR and further lower down the FRR. The proposed fusion classifier has been evaluated in performance using the CMU PIE database, and proven effective for open-set face recognition with pose variations. Experiments have also shown that it outperforms the face classifier made by HMM or SVM alone.
Abstract: Bendability is constrained by maximum top roller
load imparting capacity of the machine. Maximum load is
encountered during the edge pre-bending stage of roller bending.
Capacity of 3-roller plate bending machine is specified by
maximum thickness and minimum shell diameter combinations that
can be pre-bend for given plate material of maximum width.
Commercially available plate width or width of the plate that can be
accommodated on machine decides the maximum rolling width.
Original equipment manufacturers (OEM) provide the machine
capacity chart based on reference material considering perfectly
plastic material model. Reported work shows the bendability analysis
of heavy duty 3-roller plate bending machine. The input variables for
the industry are plate thickness, shell diameter and material property
parameters, as it is fixed by the design. Analytical models of
equivalent thickness, equivalent width and maximum width based on
power law material model were derived to study the bendability.
Equation of maximum width provides bendability for designed
configuration i.e. material property, shell diameter and thickness
combinations within the machine limitations. Equivalent thicknesses
based on perfectly plastic and power law material model were
compared for four different materials grades of C-Mn steel in order
to predict the bend-ability. Effect of top roller offset on the
bendability at maximum top roller load imparting capacity is
reported.
Abstract: There are some existing Java benchmarks, application benchmarks as well as micro benchmarks or mixture both of them,such as: Java Grande, Spec98, CaffeMark, HBech, etc. But none of them deal with behaviors of multi tasks operating systems. As a result, the achieved outputs are not satisfied for performance evaluation engineers. Behaviors of multi tasks operating systems are based on a schedule management which is employed in these systems. Different processes can have different priority to share the same resources. The time is measured by estimating from applications started to it is finished does not reflect the real time value which the system need for running those programs. New approach to this problem should be done. Having said that, in this paper we present a new Java benchmark, named FHOJ benchmark, which directly deals with multi tasks behaviors of a system. Our study shows that in some cases, results from FHOJ benchmark are far more reliable in comparison with some existing Java benchmarks.
Abstract: It is important to predict yield in semiconductor test process in order to increase yield. In this study, yield prediction means finding out defective die, wafer or lot effectively. Semiconductor test process consists of some test steps and each test includes various test items. In other world, test data has a big and complicated characteristic. It also is disproportionably distributed as the number of data belonging to FAIL class is extremely low. For yield prediction, general data mining techniques have a limitation without any data preprocessing due to eigen properties of test data. Therefore, this study proposes an under-sampling method using support vector machine (SVM) to eliminate an imbalanced characteristic. For evaluating a performance, randomly under-sampling method is compared with the proposed method using actual semiconductor test data. As a result, sampling method using SVM is effective in generating robust model for yield prediction.
Abstract: This paper presents the optimum design for a double
stator, cup rotor machine; a novel type of BLDC PM Machine. The optimization approach is divided into two stages: the first stage is
calculating the machine configuration using Matlab, and the second stage is the optimization of the machine using Finite Element
Modeling (FEM). Under the design specifications, the machine
model will be selected from three pole numbers, namely, 8, 10 and 12 with an appropriate slot number. A double stator brushless DC
permanent magnet machine is designed to achieve low cogging torque; high electromagnetic torque and low ripple torque.
Abstract: Distant-talking voice-based HCI system suffers from
performance degradation due to mismatch between the acoustic
speech (runtime) and the acoustic model (training). Mismatch is
caused by the change in the power of the speech signal as observed at
the microphones. This change is greatly influenced by the change in
distance, affecting speech dynamics inside the room before reaching
the microphones. Moreover, as the speech signal is reflected, its
acoustical characteristic is also altered by the room properties. In
general, power mismatch due to distance is a complex problem. This
paper presents a novel approach in dealing with distance-induced
mismatch by intelligently sensing instantaneous voice power variation
and compensating model parameters. First, the distant-talking speech
signal is processed through microphone array processing, and the
corresponding distance information is extracted. Distance-sensitive
Gaussian Mixture Models (GMMs), pre-trained to capture both
speech power and room property are used to predict the optimal
distance of the speech source. Consequently, pre-computed statistic
priors corresponding to the optimal distance is selected to correct
the statistics of the generic model which was frozen during training.
Thus, model combinatorics are post-conditioned to match the power
of instantaneous speech acoustics at runtime. This results to an
improved likelihood in predicting the correct speech command at
farther distances. We experiment using real data recorded inside two
rooms. Experimental evaluation shows voice recognition performance
using our method is more robust to the change in distance compared
to the conventional approach. In our experiment, under the most
acoustically challenging environment (i.e., Room 2: 2.5 meters), our
method achieved 24.2% improvement in recognition performance
against the best-performing conventional method.
Abstract: Nowadays, with the emerging of the new applications
like robot control in image processing, artificial vision for visual
servoing is a rapidly growing discipline and Human-machine
interaction plays a significant role for controlling the robot. This
paper presents a new algorithm based on spatio-temporal volumes for
visual servoing aims to control robots. In this algorithm, after
applying necessary pre-processing on video frames, a spatio-temporal
volume is constructed for each gesture and feature vector is extracted.
These volumes are then analyzed for matching in two consecutive
stages. For hand gesture recognition and classification we tested
different classifiers including k-Nearest neighbor, learning vector
quantization and back propagation neural networks. We tested the
proposed algorithm with the collected data set and results showed the
correct gesture recognition rate of 99.58 percent. We also tested the
algorithm with noisy images and algorithm showed the correct
recognition rate of 97.92 percent in noisy images.
Abstract: In the context of computer numerical control (CNC) and computer aided manufacturing (CAM), the capabilities of programming languages such as symbolic and intuitive programming, program portability and geometrical portfolio have special importance. They allow to save time and to avoid errors during part programming and permit code re-usage. Our updated literature review indicates that the current state of art presents voids in parametric programming, program portability and programming flexibility. In response to this situation, this article presents a compiler implementation for EGCL (Extended G-code Language), a new, enriched CNC programming language which allows the use of descriptive variable names, geometrical functions and flow-control statements (if-then-else, while). Our compiler produces low-level generic, elementary ISO-compliant Gcode, thus allowing for flexibility in the choice of the executing CNC machine and in portability. Our results show that readable variable names and flow control statements allow a simplified and intuitive part programming and permit re-usage of the programs. Future work includes allowing the programmer to define own functions in terms of EGCL, in contrast to the current status of having them as library built-in functions.
Abstract: We address the balancing problem of transfer lines in
this paper to find the optimal line balancing that minimizes the nonproductive
time. We focus on the tool change time and face
orientation change time both of which influence the makespane. We
consider machine capacity limitations and technological constraints
associated with the manufacturing process of auto cylinder heads.
The problem is represented by a mixed integer programming model
that aims at distributing the design features to workstations and
sequencing the machining processes at a minimum non-productive
time. The proposed model is solved by an algorithm established using
linearization schemes and Benders- decomposition approach. The
experiments show the efficiency of the algorithm in reaching the
exact solution of small and medium problem instances at reasonable
time.
Abstract: This study aims at investigating factors in research
and development (R&D) growth and exploring the role of R&D
management in enhancing social innovation and productivity
improvement in Iran-s industrial sector. It basically explores the
common types of R&D activities and the industries which benefited
the most from active R&D units in Iran. The researchers generated
qualitative analyses obtained from primary and secondary data.
The primary data have been retrieved through interviews with five
key players (Managing Director, Internal Manager, General Manager,
Executive Manager, and Project Manager) in the industrial sector.
The secondary data acquired from an investigation on Mazandaran, a
province of northern Iran. The findings highlight Iran-s focuses of R
& D on cost reduction and upgrading productivity. Industries that
have benefited the most from active R&D units are metallic,
machinery and equipment design, and automotive.
We rank order the primary effects of R&D on productivity
improvement as follows, industry improvement, economic growth,
using professional human resources, generating productivity and
creativity culture, creating a competitive and innovative environment,
and increasing people-s knowledge.
Generally, low budget dedication and insufficient supply of highly
skilled scientists and engineers are two important obstacles for R&D
in Iran. Whereas, R&D has resulted in improvement in Iranian
society, transfer of contemporary knowledge into the international
market is still lacking.
Abstract: Real-time object tracking is a problem which involves extraction of critical information from complex and uncertain imagedata. In this paper, we present a comprehensive methodology to design an artificial neural network (ANN) for a real-time object tracking application. The object, which is tracked for the purpose of demonstration, is a specific airplane. However, the proposed ANN can be trained to track any other object of interest. The ANN has been simulated and tested on the training and testing datasets, as well as on a real-time streaming video. The tracking error is analyzed with post-regression analysis tool, which finds the correlation among the calculated coordinates and the correct coordinates of the object in the image. The encouraging results from the computer simulation and analysis show that the proposed ANN architecture is a good candidate solution to a real-time object tracking problem.