Abstract: In this paper, Fabless Prototyping Methodology is
introduced for the design and analysis of MEMS devices.
Conventionally Finite Element Analysis (FEA) is performed before
system level simulation. In our proposed methodology, system level
simulation is performed earlier than FEA as it is computationally less
extensive and low cost. System level simulations are based on
equivalent behavioral models of MEMS device. Electrostatic
actuation based MEMS Microgripper is chosen as case study to
implement this methodology. This paper addresses the behavioral
model development and simulation of actuator part of an
electrostatically actuated Microgripper. Simulation results show that
the actuator part of Microgripper works efficiently for a voltage range
of 0-45V with the corresponding jaw displacement of 0-4.5425μm.
With some minor changes in design, this range can be enhanced to
15μm at 85V.
Abstract: This study proposes novel hybrid social network analysis and collaborative filtering approach to enhance the performance of recommender systems. The proposed model selects subgroups of users in Internet community through social network analysis (SNA), and then performs clustering analysis using the information about subgroups. Finally, it makes recommendations using cluster-indexing CF based on the clustering results. This study tries to use the cores in subgroups as an initial seed for a conventional clustering algorithm. This model chooses five cores which have the highest value of degree centrality from SNA, and then performs clustering analysis by using the cores as initial centroids (cluster centers). Then, the model amplifies the impact of friends in social network in the process of cluster-indexing CF.
Abstract: Incremental forming is a complex forming process with
continuously local cumulative deformation taking place during its
process, and springback that forming quality affected by would occur.
The springback evaluation method based on forming error
compensation also was proposed, which it can be defined as the
difference between theory and the actual amount of compensation
along the measured direction. According to forming error
compensation evaluation method, experiments was designed and
implemented. And from the results that obtained it can be show, the
magnitude of springback average (δE) of formed parts was very small,
and the forming precision could be significantly improved by adopting
compensation method. Based on double tensile stress state in the main
deformation area, a hypothesis that there is little springback be arisen
by bending behavior on the formed parts that was proposed.
Abstract: This paper mainly proposes an efficient modified
particle swarm optimization (MPSO) method, to identify a slidercrank
mechanism driven by a field-oriented PM synchronous motor.
In system identification, we adopt the MPSO method to find
parameters of the slider-crank mechanism. This new algorithm is
added with “distance" term in the traditional PSO-s fitness function to
avoid converging to a local optimum. It is found that the comparisons
of numerical simulations and experimental results prove that the
MPSO identification method for the slider-crank mechanism is
feasible.
Abstract: In this paper, a new Genetic Algorithm (GA) based
methodology is proposed to optimize the Degree of Hybridization
(DOH) in a passenger parallel hybrid car. At first step, target
parameters for the vehicle are decided and then using ADvanced
VehIcle SimulatOR (ADVISOR) software, the variation pattern of
these target parameters, across the different DOHs, is extracted. At
the next step, a suitable cost function is defined and is optimized
using GA. In this paper, also a new technique has been proposed for
deciding the number of battery modules for each DOH, which leads
to a great improvement in the vehicle performance. The proposed
methodology is so simple, fast and at the same time, so efficient.
Abstract: Data mining and knowledge engineering have become a tough task due to the availability of large amount of data in the web nowadays. Validity and reliability of data also become a main debate in knowledge acquisition. Besides, acquiring knowledge from different languages has become another concern. There are many language translators and corpora developed but the function of these translators and corpora are usually limited to certain languages and domains. Furthermore, search results from engines with traditional 'keyword' approach are no longer satisfying. More intelligent knowledge engineering agents are needed. To address to these problems, a system known as Multilingual Word Semantic Network is proposed. This system adapted semantic network to organize words according to concepts and relations. The system also uses open source as the development philosophy to enable the native language speakers and experts to contribute their knowledge to the system. The contributed words are then defined and linked using lexical and semantic relations. Thus, related words and derivatives can be identified and linked. From the outcome of the system implementation, it contributes to the development of semantic web and knowledge engineering.
Abstract: This study attempts to investigate the relationship
between internal CSR practices and organizational commitment
based on the social exchange theory (SET). Specifically, we examine
the impact of five dimensions of internal CSR practices on
organizational commitment: health and safety, human rights, training
and education, work life balance and workplace diversity. The
proposed model was tested on a sample of 336 frontline employees
within the banking sector in Jordan. Results showed that all internal
CSR dimensions are significantly and positively related to affective
and normative commitment. In addition, the findings of this study
indicate that all internal CSR dimensions did not have a significant
relationship with continuance commitment. Limitations of the study,
directions for future research, and implications of the findings are
discussed.
Abstract: Detecting object in video sequence is a challenging
mission for identifying, tracking moving objects. Background
removal considered as a basic step in detected moving objects tasks.
Dual static cameras placed in front and rear moving platform
gathered information which is used to detect objects. Background
change regarding with speed and direction moving platform, so
moving objects distinguished become complicated. In this paper, we
propose framework allows detection moving object with variety of
speed and direction dynamically. Object detection technique built on
two levels the first level apply background removal and edge
detection to generate moving areas. The second level apply Moving
Areas Filter (MAF) then calculate Correlation Score (CS) for
adjusted moving area. Merging moving areas with closer CS and
marked as moving object. Experiment result is prepared on real scene
acquired by dual static cameras without overlap in sense. Results
showing accuracy in detecting objects compared with optical flow
and Mixture Module Gaussian (MMG), Accurate ratio produced to
measure accurate detection moving object.
Abstract: This study discusses the effect of uncertainty on
production levels of a petrochemical complex. Uncertainly or
variations in some model parameters, such as prices, supply and
demand of materials, can affect the optimality or the efficiency of any
chemical process. For any petrochemical complex with many plants,
there are many sources of uncertainty and frequent variations which
require more attention. Many optimization approaches are proposed
in the literature to incorporate uncertainty within the model in order
to obtain a robust solution. In this work, a stability analysis approach
is applied to a deterministic LP model of a petrochemical complex
consists of ten plants to investigate the effect of such variations on
the obtained optimal production levels. The proposed approach can
determinate the allowable variation ranges of some parameters,
mainly objective or RHS coefficients, before the system lose its
optimality. Parameters with relatively narrow range of variations, i.e.
stability limits, are classified as sensitive parameters or constraints
that need accurate estimate or intensive monitoring. These stability
limits offer easy-to-use information to the decision maker and help in
understanding the interaction between some model parameters and
deciding when the system need to be re-optimize. The study shows
that maximum production of ethylene and the prices of intermediate
products are the most sensitive factors that affect the stability of the
optimum solution
Abstract: The purpose of this research study is to investigate the manner in which various loads affect the mechanical properties of the formed mild steel plates. The investigation focuses on examining the cross-sectional area of the metal plate at the centre of the formed mild steel plate. Six mild steel plates were deformed with different loads. The loads applied on the plates had a magnitude of 5 kg, 10 kg, 15 kg, 20 kg, 25 kg and 30 kg. The radius of the punching die was 120 mm and the loads were applied at room temperature. The investigations established that the applied load causes the Vickers microhardness at the cross-sectional area of the plate to increase due to strain hardening. Hence, the percentage increase of the hardness due to the load was found to be directly proportional to the increase in the load. Furthermore, the tensile test results for the parent material showed that the average Ultimate Tensile Strength (UTS) for the three samples was 308 MPa while the average Yield Strength and Percentage Elongation were 227 MPa and 38 % respectively. Similarly, the UTS of the formed components increased after the deformation of the plate, as such it can be concluded that the forming loads alter the mechanical properties of the materials by improving and strengthening the material properties.
Abstract: In the present paper, we present a modification of the
New Iterative Method (NIM) proposed by Daftardar-Gejji and Jafari
[J. Math. Anal. Appl. 2006;316:753–763] and use it for solving
systems of nonlinear functional equations. This modification yields
a series with faster convergence. Illustrative examples are presented
to demonstrate the method.
Abstract: Chitosan is a biopolymer composed of glucosamine
and N-acetyl glucosamine. Solubility and viscosity pose problems in
some applications. These problems can be overcome with unique
modifications. In this study, firstly, chitosan was modified by caffeic
acid and thioglycolic acid, separately. Then, growing effects of these
modified polymers was observed in U937 cell line. Caffeic acid is a
phenolic compound and its modifications act carcinogenic inhibitors
in drugs. Thiolated chitosans are commonly being used for drugdelivery
systems in various routes, because of enhancing
mucoadhesiveness property. U937 cell line was used model cell for
leukaemia. Modifications were achieved by 1 – 15 % binding range.
Increasing binding ratios showed higher radical-scavenging activity
and reducing cell growth, in compared to native chitosan. Caffeic
acid modifications showed higher radical-scavenging activity than
thiolated chitosans at the same concentrations. Caffeic acid and
thioglycolic acid modifications inhibited growth of U937, effectively.
Abstract: The current speech interfaces in many military
applications may be adequate for native speakers. However,
the recognition rate drops quite a lot for non-native speakers
(people with foreign accents). This is mainly because the nonnative
speakers have large temporal and intra-phoneme
variations when they pronounce the same words. This
problem is also complicated by the presence of large
environmental noise such as tank noise, helicopter noise, etc.
In this paper, we proposed a novel continuous acoustic feature
adaptation algorithm for on-line accent and environmental
adaptation. Implemented by incremental singular value
decomposition (SVD), the algorithm captures local acoustic
variation and runs in real-time. This feature-based adaptation
method is then integrated with conventional model-based
maximum likelihood linear regression (MLLR) algorithm.
Extensive experiments have been performed on the NATO
non-native speech corpus with baseline acoustic model trained
on native American English. The proposed feature-based
adaptation algorithm improved the average recognition
accuracy by 15%, while the MLLR model based adaptation
achieved 11% improvement. The corresponding word error
rate (WER) reduction was 25.8% and 2.73%, as compared to
that without adaptation. The combined adaptation achieved
overall recognition accuracy improvement of 29.5%, and
WER reduction of 31.8%, as compared to that without
adaptation.
Abstract: Providing Services at Home has become over the last
few years a very dynamic and promising technological domain. It is
likely to enable wide dissemination of secure and automated living
environments. We propose a methodology for identifying threats to
Services at Home Delivery systems, as well as a threat analysis
of a multi-provider Home Gateway architecture. This methodology
is based on a dichotomous positive/preventive study of the target
system: it aims at identifying both what the system must do, and
what it must not do. This approach completes existing methods with
a synthetic view of potential security flaws, thus enabling suitable
measures to be taken into account. Security implications of the
evolution of a given system become easier to deal with. A prototype
is built based on the conclusions of this analysis.
Abstract: In this study, we present an advanced detection
technique for mass type breast cancer based on texture information
of organs. The proposed method detects the cancer areas in three
stages. In the first stage, the midpoints of mass area are determined
based on AHE (Adaptive Histogram Equalization). In the second
stage, we set the threshold coefficient of homogeneity by using
MLE (Maximum Likelihood Estimation) to compute the uniformity
of texture. Finally, mass type cancer tissues are extracted from the
original image. As a result, it was observed that the proposed
method shows an improved detection performance on dense breast
tissues of Korean women compared with the existing methods. It is
expected that the proposed method may provide additional
diagnostic information for detection of mass-type breast cancer.
Abstract: The hydrodynamic processes in bubbly liquid flowing
in tubes and nozzles are studied theoretically and numerically. The
principal regularities of non-stationary processes of boiling liquid
outflow are established under conditions of experiments when the
depressurization of a tube with high pressure inside occurs. The
steady-state solution of bubbly liquid flow in the nozzle of round
cross section with high pressure and temperature conditions inside
bubbles is studied accounting for phase transition and chemical
reactions.
Abstract: Recent research result has shown that two multidelay
feedback systems can synchronize each other under different
schemes, i.e. lag, projective-lag, anticipating, or projectiveanticipating
synchronization. There, the driving signal is significantly
complex due that it is constituted by multiple nonlinear transformations
of delayed state variable. In this paper, a secure communication
model is proposed based on synchronization of coupled multidelay
feedback systems, in which the plain signal is mixed with a complex
signal at the transmitter side and it is precisely retrieved at the receiver
side. The effectiveness of the proposed model is demonstrated and
verified in the specific example, where the message signal is masked
directly by the complex signal and security is examined under the
breaking method of power spectrum analysis.
Abstract: In this paper we developed the Improved Runge-Kutta Nystrom (IRKN) method for solving second order ordinary differential equations. The methods are two step in nature and require lower number of function evaluations per step compared with the existing Runge-Kutta Nystrom (RKN) methods. Therefore, the methods are computationally more efficient at achieving the higher order of local accuracy. Algebraic order conditions of the method are obtained and the third and fourth order method are derived with two and three stages respectively. The numerical results are given to illustrate the efficiency of the proposed method compared to the existing RKN methods.
Abstract: In this paper we proposed the use of Huffman
coding to reduce the PAR of an OFDM system as a distortionless
scrambling technique, and we utilize the amount saved in the
total bit rate by the Huffman coding to send the encoding table
for accurate decoding at the receiver without reducing the
effective throughput. We found that the use of Huffman coding
reduces the PAR by about 6 dB. Also we have investigated the
effect of PAR reduction due to Huffman coding through testing
the spectral spreading and the inband distortion due to HPA with
different IBO values. We found a complete match of our
expectation from the proposed solution with the obtained
simulation results.
Abstract: The density estimates considered in this paper comprise
a base density and an adjustment component consisting of a linear
combination of orthogonal polynomials. It is shown that, in the
context of density approximation, the coefficients of the linear combination
can be determined either from a moment-matching technique
or a weighted least-squares approach. A kernel representation of
the corresponding density estimates is obtained. Additionally, two
refinements of the Kronmal-Tarter stopping criterion are proposed
for determining the degree of the polynomial adjustment. By way of
illustration, the density estimation methodology advocated herein is
applied to two data sets.