Abstract: Transmission network expansion planning (TNEP) is
a basic part of power system planning that determines where, when
and how many new transmission lines should be added to the
network. Up till now, various methods have been presented to solve
the static transmission network expansion planning (STNEP)
problem. But in all of these methods, transmission expansion
planning considering network adequacy restriction has not been
investigated. Thus, in this paper, STNEP problem is being studied
considering network adequacy restriction using discrete particle
swarm optimization (DPSO) algorithm. The goal of this paper is
obtaining a configuration for network expansion with lowest
expansion cost and a specific adequacy. The proposed idea has been
tested on the Garvers network and compared with the decimal
codification genetic algorithm (DCGA). The results show that the
network will possess maximum efficiency economically. Also, it is
shown that precision and convergence speed of the proposed DPSO
based method for the solution of the STNEP problem is more than
DCGA approach.
Abstract: In this paper we proposed multistage adaptive
ARQ/HARQ/HARQ scheme. This method combines pure ARQ
(Automatic Repeat reQuest) mode in low channel bit error rate and
hybrid ARQ method using two different Reed-Solomon codes in
middle and high error rate conditions. It follows, that our scheme has
three stages. The main goal is to increase number of states in adaptive
HARQ methods and be able to achieve maximum throughput for
every channel bit error rate. We will prove the proposal by
calculation and then with simulations in land mobile satellite channel
environment. Optimization of scheme system parameters is described
in order to maximize the throughput in the whole defined Signal-to-
Noise Ratio (SNR) range in selected channel environment.
Abstract: This paper presents a novel iris recognition system
using 1D log polar Gabor wavelet and Euler numbers. 1D log polar
Gabor wavelet is used to extract the textural features, and Euler
numbers are used to extract topological features of the iris. The
proposed decision strategy uses these features to authenticate an
individual-s identity while maintaining a low false rejection rate. The
algorithm was tested on CASIA iris image database and found to
perform better than existing approaches with an overall accuracy of
99.93%.
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: Many agricultural and especially greenhouse
applications like plant inspection, data gathering, spraying and
selective harvesting could be performed by robots. In this paper
multiple nonholonomic robots are used in order to create a desired
formation scheme for screening solar energy in a greenhouse through
data gathering. The formation consists from a leader and a team
member equipped with appropriate sensors. Each robot is dedicated
to its mission in the greenhouse that is predefined by the
requirements of the application. The feasibility of the proposed
application includes experimental results with three unmanned
ground vehicles (UGV).
Abstract: This paper presents the averaging model of a buck
converter derived from the generalized state-space averaging method.
The sliding mode control is used to regulate the output voltage of the
converter and taken into account in the model. The proposed model
requires the fast computational time compared with those of the full
topology model. The intensive time-domain simulations via the exact
topology model are used as the comparable model. The results show
that a good agreement between the proposed model and the switching
model is achieved in both transient and steady-state responses. The
reported model is suitable for the optimal controller design by using
the artificial intelligence techniques.
Abstract: The aim of this study was to screen for
microorganism that able to utilize 3-N-trimethylamino-1-propanol
(homocholine) as a sole source of carbon and nitrogen. The aerobic
degradation of homocholine has been found by a gram-positive
Rhodococcus sp. bacterium isolated from soil. The isolate was
identified as Rhodococcus sp. strain A4 based on the phenotypic
features, physiologic and biochemical characteristics, and
phylogenetic analysis. The cells of the isolated strain grown on both
basal-TMAP and nutrient agar medium displayed elementary
branching mycelia fragmented into irregular rod and coccoid
elements. Comparative 16S rDNA sequencing studies indicated that
the strain A4 falls into the Rhodococcus erythropolis subclade and
forms a monophyletic group with the type-strains of R. opacus, and
R. wratislaviensis. Metabolites analysis by capillary electrophoresis,
fast atom bombardment-mass spectrometry, and gas
chromatography- mass spectrometry, showed trimethylamine (TMA)
as the major metabolite beside β-alanine betaine and
trimethylaminopropionaldehyde. Therefore, the possible degradation
pathway of trimethylamino propanol in the isolated strain is through
consequence oxidation of alcohol group (-OH) to aldehyde (-CHO)
and acid (-COOH), and thereafter the cleavage of β-alanine betaine
C-N bonds yielded trimethylamine and alkyl chain.
Abstract: Safety instrumented systems (SISs) are becoming
increasingly complex and the proportion of programmable electronic
parts is growing. The IEC 61508 global standard was established to
ensure the functional safety of SISs, but it was expressed in highly
macroscopic terms. This study introduces an evaluation process for
hardware safety integrity levels through failure modes, effects, and
diagnostic analysis (FMEDA).FMEDA is widely used to evaluate
safety levels, and it provides the information on failure rates and
failure mode distributions necessary to calculate a diagnostic coverage
factor for a given component. In our evaluation process, the
components of the SIS subsystem are first defined in terms of failure
modes and effects. Then, the failure rate and failure mechanism
distribution are assigned to each component. The safety mode and
detectability of each failure mode are determined for each component.
Finally, the hardware safety integrity level is evaluated based on the
calculated results.
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: 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: Current advancements in nanotechnology are dependent on the capabilities that can enable nano-scientists to extend their eyes and hands into the nano-world. For this purpose, a haptics (devices capable of recreating tactile or force sensations) based system for AFM (Atomic Force Microscope) is proposed. The system enables the nano-scientists to touch and feel the sample surfaces, viewed through AFM, in order to provide them with better understanding of the physical properties of the surface, such as roughness, stiffness and shape of molecular architecture. At this stage, the proposed work uses of ine images produced using AFM and perform image analysis to create virtual surfaces suitable for haptics force analysis. The research work is in the process of extension from of ine to online process where interaction will be done directly on the material surface for realistic analysis.
Abstract: In this work, we present for the first time in our perception an efficient digital watermarking scheme for mpeg audio layer 3 files that operates directly in the compressed data domain, while manipulating the time and subband/channel domain. In addition, it does not need the original signal to detect the watermark. Our scheme was implemented taking special care for the efficient usage of the two limited resources of computer systems: time and space. It offers to the industrial user the capability of watermark embedding and detection in time immediately comparable to the real music time of the original audio file that depends on the mpeg compression, while the end user/audience does not face any artifacts or delays hearing the watermarked audio file. Furthermore, it overcomes the disadvantage of algorithms operating in the PCMData domain to be vulnerable to compression/recompression attacks, as it places the watermark in the scale factors domain and not in the digitized sound audio data. The strength of our scheme, that allows it to be used with success in both authentication and copyright protection, relies on the fact that it gives to the users the enhanced capability their ownership of the audio file not to be accomplished simply by detecting the bit pattern that comprises the watermark itself, but by showing that the legal owner knows a hard to compute property of the watermark.
Abstract: Multi-dimensional principal component analysis
(PCA) is the extension of the PCA, which is used widely as the
dimensionality reduction technique in multivariate data analysis, to
handle multi-dimensional data. To calculate the PCA the singular
value decomposition (SVD) is commonly employed by the reason of
its numerical stability. The multi-dimensional PCA can be calculated
by using the higher-order SVD (HOSVD), which is proposed by
Lathauwer et al., similarly with the case of ordinary PCA. In this
paper, we apply the multi-dimensional PCA to the multi-dimensional
medical data including the functional independence measure (FIM)
score, and describe the results of experimental analysis.
Abstract: The issue of scientific – technological parks has been
proposed in several countries of the world especially in western
countries since a few decades ago and its efficiency is under
examination. In our county Iran, some scientific – technological
parks have been established or are being established. This design
would evaluate the urban role and method of architecture of these
parks in order to criticize its efficiency and offer some suggestions,
as much as possible to improve its building methods in Iran. The
main problem of this design is that how much these parks in Iran do
meet the international measurements. So for this reason, one
scientific park in Iran and one from western countries would be
studied and compared with each other.
Abstract: Facility location problem involves locating a facility
to optimize some performance measures. Location of a public facility
to serve the community, such as a fire station, significantly affects its
service quality. Main objective in locating a fire station is to
minimize the response time, which is the time duration between
receiving a call and reaching the place of incident. In metropolitan
areas, fire vehicles need to cross highways and other traffic obstacles
through some obstacle-overcoming points which delay the response
time. In this paper, fire station location problem is analyzed.
Simulation models are developed for the location problems which
involve obstacles. Particular case problems are analyzed and the
results are presented.
Abstract: In this paper, we propose a novel frequency offset
estimation scheme for orthogonal frequency division multiplexing
(OFDM) systems. By correlating the OFDM signals within the coherence
phase bandwidth and employing a threshold in the frequency
offset estimation process, the proposed scheme is not only robust to
the timing offset but also has a reduced complexity compared with
that of the conventional scheme. Moreover, a timing offset estimation
scheme is also proposed as the next stage of the proposed frequency
offset estimation. Numerical results show that the proposed scheme
can estimate frequency offset with lower computational complexity
and does not require additional memory while maintaining the same
level of estimation performance.
Abstract: Eukaryotic protein-coding genes are interrupted by spliceosomal introns, which are removed from the RNA transcripts before translation into a protein. The exon-intron structures of different eukaryotic species are quite different from each other, and the evolution of such structures raises many questions. We try to address some of these questions using statistical analysis of whole genomes. We go through all the protein-coding genes in a genome and study correlations between the net length of all the exons in a gene, the number of the exons, and the average length of an exon. We also take average values of these features for each chromosome and study correlations between those averages on the chromosomal level. Our data show universal features of exon-intron structures common to animals, plants, and protists (specifically, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Cryptococcus neoformans, Homo sapiens, Mus musculus, Oryza sativa, and Plasmodium falciparum). We have verified linear correlation between the number of exons in a gene and the length of a protein coded by the gene, while the protein length increases in proportion to the number of exons. On the other hand, the average length of an exon always decreases with the number of exons. Finally, chromosome clustering based on average chromosome properties and parameters of linear regression between the number of exons in a gene and the net length of those exons demonstrates that these average chromosome properties are genome-specific features.
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 paper proposes a new method for analyzing textual data. The method deals with items of textual data, where each item is described based on various viewpoints. The method acquires 2- class classification models of the viewpoints by applying an inductive learning method to items with multiple viewpoints. The method infers whether the viewpoints are assigned to the new items or not by using the models. The method extracts expressions from the new items classified into the viewpoints and extracts characteristic expressions corresponding to the viewpoints by comparing the frequency of expressions among the viewpoints. This paper also applies the method to questionnaire data given by guests at a hotel and verifies its effect through numerical experiments.
Abstract: A high energy dual-wavelength extracavity KTA
optical parametric oscillator (OPO) with excellent stability and beam
quality, which is pumped by a Q-switched single-longitudinal-mode
Nd:YAG laser, has been demonstrated based on a type II noncritical
phase matching (NCPM) KTA crystal. The maximum pulse energy of
10.2 mJ with the output stability of better than 4.1% rms at 3.467 μm is
obtained at the repetition rate of 10 Hz and pulse width of 2 ns, and the
11.9 mJ of 1.535 μm radiation is obtained simultaneously. This
extracavity NCPM KTA OPO is very useful when high energy, high
beam quality and smooth time domain are needed.