Abstract: One approach to assess neural networks underlying the cognitive processes is to study Electroencephalography (EEG). It is relevant to detect various mental states and characterize the physiological changes that help to discriminate two situations. That is why an EEG (amplitude, synchrony) classification procedure is described, validated. The two situations are "eyes closed" and "eyes opened" in order to study the "alpha blocking response" phenomenon in the occipital area. The good classification rate between the two situations is 92.1 % (SD = 3.5%) The spatial distribution of a part of amplitude features that helps to discriminate the two situations are located in the occipital regions that permit to validate the localization method. Moreover amplitude features in frontal areas, "short distant" synchrony in frontal areas and "long distant" synchrony between frontal and occipital area also help to discriminate between the two situations. This procedure will be used for mental fatigue detection.
Abstract: the cursive nature of the Arabic writing makes it
difficult to accurately segment characters or even deal with the whole
word efficiently. Therefore, in this paper, a printed Arabic sub-word
recognition system is proposed. The suggested algorithm utilizes
geometrical moments as descriptors for the separated sub-words.
Three types of moments are investigated and applied to the printed
sub-word images after dividing each image into multiple parts using
windowing. Since moments are global descriptors, the windowing
mechanism allows the moments to be applied to local regions of the
sub-word. The local-global mixture of the proposed scheme increases
the discrimination power of the moments while keeping the
simplicity and ease of use of moments.
Abstract: This study compares family communication patterns in association with family socio-cultural status, especially marriage and family pattern, and couples- socio-economic status between Muslim and Santal communities in rural Bangladesh. A total of 288 couples, 145 couples from the Muslim and 143 couples from the Santal were randomly selected through cluster sampling procedure from Kalna village situated in Tanore Upazila of Rajshahi district of Bangladesh, where both the communities dwell as neighbors. In order to collect data from the selected samples, interview method with semistructural questionnaire schedule was applied. The responses given by the respondents were analyzed by Pearson-s chi-squire test and bivariate correlation techniques. The results of Pearson-s chi-squire test revealed that family communication patterns (X2= 25. 90, df= 2, p0.05) were significantly different between the Muslim and Santal communities. In addition, Spearman-s bivariate correlation coefficients suggested that among the exogenous factors, family type (rs=.135, p
Abstract: We introduce a new interactive 3D simulator of ocular motion and expressions suitable for: (1) character animation applications to game design, film production, HCI (Human Computer Interface), conversational animated agents, and virtual reality; (2) medical applications (ophthalmic neurological and muscular pathologies: research and education); and (3) real time simulation of unconscious cognitive and emotional responses (for use, e.g., in psychological research). Using state-of-the-art computer animation technology we have modeled and rigged a physiologically accurate 3D model of the eyes, eyelids, and eyebrow regions and we have 'optimized' it for use with an interactive and web deliverable platform. In addition, we have realized a prototype device for realtime control of eye motions and expressions, including unconsciously produced expressions, for application as in (1), (2), and (3) above. The 3D simulator of eye motion and ocular expression is, to our knowledge, the most advanced/realistic available so far for applications in character animation and medical pedagogy.
Abstract: the current study presents a modeling framework to determine the torsion strength of an induction hardened splined shaft by considering geometry and material aspects with the aim to optimize the static torsion strength by selection of spline geometry and hardness depth. Six different spline geometries and seven different hardness profiles including non-hardened and throughhardened shafts have been considered. The results reveal that the torque that causes initial yielding of the induction hardened splined shaft is strongly dependent on the hardness depth and the geometry of the spline teeth. Guidelines for selection of the appropriate hardness depth and spline geometry are given such that an optimum static torsion strength of the component can be achieved.
Abstract: Flow-shop scheduling problem (FSP) deals with the
scheduling of a set of jobs that visit a set of machines in the same
order. The FSP is NP-hard, which means that an efficient algorithm
for solving the problem to optimality is unavailable. To meet the
requirements on time and to minimize the make-span performance of
large permutation flow-shop scheduling problems in which there are
sequence dependent setup times on each machine, this paper
develops one hybrid genetic algorithms (HGA). Proposed HGA
apply a modified approach to generate population of initial
chromosomes and also use an improved heuristic called the iterated
swap procedure to improve initial solutions. Also the author uses
three genetic operators to make good new offspring. The results are
compared to some recently developed heuristics and computational
experimental results show that the proposed HGA performs very
competitively with respect to accuracy and efficiency of solution.
Abstract: This paper proposes a modeling method of the laws controlling manufacturing systems with temporal and non temporal constraints. A methodology of robust control construction generating the margins of passive and active robustness is being elaborated. Indeed, two paramount models are presented in this paper. The first utilizes the P-time Petri Nets which is used to manage the flow type disturbances. The second, the quality model, exploits the Intervals Constrained Petri Nets (ICPN) tool which allows the system to preserve its quality specificities. The redundancy of the robustness of the elementary parameters between passive and active is also used. The final model built allows the correlation of temporal and non temporal criteria by putting two paramount models in interaction. To do so, a set of definitions and theorems are employed and affirmed by applicator examples.
Abstract: In this survey the process of crack propagation at the
toe of concrete gravity dam is investigated by applying principals
and criteria of linear elastic fracture mechanic. Simulating process of
earthquake conditions for three models of dam with different
geometrical condition, in empty reservoir under plain stress is
calculated through special fracture mechanic software FRANNC2D
[1] for determining fracture mechanic criteria. The outcomes showed
that in spite of the primary expectations, the simultaneous existence
of fillet in both toe and heel area (model 3), the rate of maximum
principal stress has not been decreased; however, even the maximum
principal stress has increased, so it caused stress intensity factors
increase which is undesirable. On the other hand, the dam with heel
fillet has shown the best attitude and it is because of items like
decreasing the rates of maximum and minimum principal stresses and
also is related to decreasing the rates of stress intensity factors for 1st
& 2nd modes of the model.
Abstract: This paper presents the design, implementation and
results related to the storage system of medical information
associated to the ECG (Electrocardiography) signal. The system
includes the signal acquisition modules, the preprocessing and signal
processing, followed by a module of transmission and reception of
the signal, along with the storage and web display system of the
medical platform. The tests were initially performed with this signal,
with the purpose to include more biosignal under the same system in
the future.
Abstract: Business and IT alignment has continued as a
top concern for business and IT executives for almost three
decades. Many researchers have conducted empirical studies on
the relationship between business-IT alignment and performance.
Yet, these approaches, lacking a social perspective, have had little
impact on sustaining performance and competitive advantage. In
addition to the limited alignment literature that explores
organisational learning that is represented in shared understanding,
communication, cognitive maps and experiences.
Hence, this paper proposes an integrated process that enables
social and intellectual dimensions through the concept of
organisational learning. In particular, the feedback and feedforward
process which provide a value creation across dynamic
multilevel of learning. This mechanism enables on-going
effectiveness through development of individuals, groups and
organisations, which improves the quality of business and IT
strategies and drives to performance.
Abstract: The mixture formation prior to the ignition process
plays as a key element in the diesel combustion. Parametric studies of
mixture formation and ignition process in various injection parameter
has received considerable attention in potential for reducing
emissions. Purpose of this study is to clarify the effects of injection
pressure on mixture formation and ignition especially during ignition
delay period, which have to be significantly influences throughout the
combustion process and exhaust emissions. This study investigated
the effects of injection pressure on diesel combustion fundamentally
using rapid compression machine. The detail behavior of mixture
formation during ignition delay period was investigated using the
schlieren photography system with a high speed camera. This method
can capture spray evaporation, spray interference, mixture formation
and flame development clearly with real images. Ignition process and
flame development were investigated by direct photography method
using a light sensitive high-speed color digital video camera. The
injection pressure and air motion are important variable that strongly
affect to the fuel evaporation, endothermic and prolysis process
during ignition delay. An increased injection pressure makes spray tip
penetration longer and promotes a greater amount of fuel-air mixing
occurs during ignition delay. A greater quantity of fuel prepared
during ignition delay period thus predominantly promotes more rapid
heat release.
Abstract: Corner detection and optical flow are common techniques for feature-based video stabilization. However, these algorithms are computationally expensive and should be performed at a reasonable rate. This paper presents an algorithm for discarding irrelevant feature points and maintaining them for future use so as to improve the computational cost. The algorithm starts by initializing a maintained set. The feature points in the maintained set are examined against its accuracy for modeling. Corner detection is required only when the feature points are insufficiently accurate for future modeling. Then, optical flows are computed from the maintained feature points toward the consecutive frame. After that, a motion model is estimated based on the simplified affine motion model and least square method, with outliers belonging to moving objects presented. Studentized residuals are used to eliminate such outliers. The model estimation and elimination processes repeat until no more outliers are identified. Finally, the entire algorithm repeats along the video sequence with the points remaining from the previous iteration used as the maintained set. As a practical application, an efficient video stabilization can be achieved by exploiting the computed motion models. Our study shows that the number of times corner detection needs to perform is greatly reduced, thus significantly improving the computational cost. Moreover, optical flow vectors are computed for only the maintained feature points, not for outliers, thus also reducing the computational cost. In addition, the feature points after reduction can sufficiently be used for background objects tracking as demonstrated in the simple video stabilizer based on our proposed algorithm.
Abstract: The dynamic spectrum allocation solutions such as
cognitive radio networks have been proposed as a key technology to
exploit the frequency segments that are spectrally underutilized.
Cognitive radio users work as secondary users who need to
constantly and rapidly sense the presence of primary users or
licensees to utilize their frequency bands if they are inactive. Short
sensing cycles should be run by the secondary users to achieve
higher throughput rates as well as to provide low level of interference
to the primary users by immediately vacating their channels once
they have been detected. In this paper, the throughput-sensing time
relationship in local and cooperative spectrum sensing has been
investigated under two distinct scenarios, namely, constant primary
user protection (CPUP) and constant secondary user spectrum
usability (CSUSU) scenarios. The simulation results show that the
design of sensing slot duration is very critical and depends on the
number of cooperating users under CPUP scenario whereas under
CSUSU, cooperating more users has no effect if the sensing time
used exceeds 5% of the total frame duration.
Abstract: Identity verification of authentic persons by their multiview faces is a real valued problem in machine vision. Multiview faces are having difficulties due to non-linear representation in the feature space. This paper illustrates the usability of the generalization of LDA in the form of canonical covariate for face recognition to multiview faces. In the proposed work, the Gabor filter bank is used to extract facial features that characterized by spatial frequency, spatial locality and orientation. Gabor face representation captures substantial amount of variations of the face instances that often occurs due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images of rotated profile views produce Gabor faces with high dimensional features vectors. Canonical covariate is then used to Gabor faces to reduce the high dimensional feature spaces into low dimensional subspaces. Finally, support vector machines are trained with canonical sub-spaces that contain reduced set of features and perform recognition task. The proposed system is evaluated with UMIST face database. The experiment results demonstrate the efficiency and robustness of the proposed system with high recognition rates.
Abstract: This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.
Abstract: The purpose of this article is to briefly review the opportunities that social media present to counselors and psychologists. Particular attention was given to understanding some of the more important common risks inherent in social media and the potential ethical dilemmas which may arise for counselors and psychologists who embrace them in their practice. Key considerations of issues pertinent to an online presence such as multiple relationships, visibility and privacy, maintaining ethical principles and professional boundaries are being discussed.
Abstract: Because of increasing demands for security in today-s
society and also due to paying much more attention to machine
vision, biometric researches, pattern recognition and data retrieval in
color images, face detection has got more application. In this article
we present a scientific approach for modeling human skin color, and
also offer an algorithm that tries to detect faces within color images
by combination of skin features and determined threshold in the
model. Proposed model is based on statistical data in different color
spaces. Offered algorithm, using some specified color threshold, first,
divides image pixels into two groups: skin pixel group and non-skin
pixel group and then based on some geometric features of face
decides which area belongs to face.
Two main results that we received from this research are as follow:
first, proposed model can be applied easily on different databases and
color spaces to establish proper threshold. Second, our algorithm can
adapt itself with runtime condition and its results demonstrate
desirable progress in comparison with similar cases.
Abstract: Since the feasibility study of R&D programs have been
initiated for efficient public R&D investments, year 2008, feasibility
studies have improved in terms of precision. Although experience
related to these studies of R&D programs have increased to a certain
point, still methodological improvement is required. The feasibility
studies of R&D programs are consisted of various viewpoints, such as
technology, policy, and economics. This research is to provide
improvement methods to the economic perspective; especially the cost
estimation process of R&D activities. First of all, the fundamental
concept of cost estimation is reviewed. After the review, a statistical
and econometric analysis method is applied as empirical analysis.
Conclusively, limitations and further research directions are provided.
Abstract: Many studies have shown that parallelization decreases efficiency [1], [2]. There are many reasons for these decrements. This paper investigates those which appear in the context of parallel data integration. Integration processes generally cannot be allocated to packages of identical size (i. e. tasks of identical complexity). The reason for this is unknown heterogeneous input data which result in variable task lengths. Process delay is defined by the slowest processing node. It leads to a detrimental effect on the total processing time. With a real world example, this study will show that while process delay does initially increase with the introduction of more nodes it ultimately decreases again after a certain point. The example will make use of the cloud computing platform Hadoop and be run inside Amazon-s EC2 compute cloud. A stochastic model will be set up which can explain this effect.
Abstract: The Artificial immune systems algorithms are Meta
heuristic optimization method, which are used for clustering and
pattern recognition applications are abundantly. These algorithms in
multimodal optimization problems are more efficient than genetic
algorithms. A major drawback in these algorithms is their slow
convergence to global optimum and their weak stability can be
considered in various running of these algorithms. In this paper,
improved Artificial Immune System Algorithm is introduced for the
first time to overcome its problems of artificial immune system. That
use of the small size of a local search around the memory antibodies
is used for improving the algorithm efficiently. The credibility of the
proposed approach is evaluated by simulations, and it is shown that
the proposed approach achieves better results can be achieved
compared to the standard artificial immune system algorithms