Abstract: The importance of happiness understanding research is caused by cardinal changes experiences in system of people values in the post-Soviet countries territory. «The time of changes», which characterized with destruction of old values and not creativeness of new, stimulating experiences by the person of existential vacuum. The given research is actual not only in connection with sense formation, but also in connection with necessity creatively to adapt in integrative space. According to numerous works [1,2,3], we define happiness as the peak experience connected with satisfaction correlated system of needs, dependent on style of subject's coping behavior.
Abstract: Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.
Abstract: Some believe that stigma is the worst side effect of the
people who have mental illness. Mental illness researchers have
focused on the influence of mass media on the stigmatization of the
people with mental illness. However, no studies have investigated the
effects of the interactive media, such as blogs, on the stigmatization
of mentally ill people, even though the media have a significant
influence on people in all areas of life. The purpose of this study is to
investigate the use of interactivity in destigmatization of the mentally
ill and the moderating effect of self-construal (independent versus
interdependent self-construal) on the relation between interactivity
and destigmatization. The findings suggested that people in the
human-human interaction condition had less social distance toward
people with mental illness. Additionally, participants with higher
independence showed more favorable affection and less social
distance toward mentally ill people. Finally, direct contact with
mentally ill people increased a person-s positive affect toward people
with mental illness. The current study should provide insights for
mental health practitioners by suggesting how they can use
interactive media to approach the public that stigmatizes the mentally
ill.
Abstract: Physiological control of a left ventricle assist device (LVAD) is generally a complicated task due to diverse operating environments and patient variability. In this work, a tracking control algorithm based on sliding mode and feed forward control for a class of discrete-time single input single output (SISO) nonlinear uncertain systems is presented. The controller was developed to track the reference trajectory to a set operating point without inducing suction in the ventricle. The controller regulates the estimated mean pulsatile flow Qp and mean pulsatility index of pump rotational speed PIω that was generated from a model of the assist device. We recall the principle of the sliding mode control theory then we combine the feed-forward control design with the sliding mode control technique to follow the reference trajectory. The uncertainty is replaced by its upper and lower boundary. The controller was tested in a computer simulation covering two scenarios (preload and ventricular contractility). The simulation results prove the effectiveness and the robustness of the proposed controller
Abstract: Automatic keyphrase extraction is useful in efficiently
locating specific documents in online databases. While several
techniques have been introduced over the years, improvement on
accuracy rate is minimal. This research examines attribute scores for
author-supplied keyphrases to better understand how the scores affect
the accuracy rate of automatic keyphrase extraction. Five attributes
are chosen for examination: Term Frequency, First Occurrence, Last
Occurrence, Phrase Position in Sentences, and Term Cohesion
Degree. The results show that First Occurrence is the most reliable
attribute. Term Frequency, Last Occurrence and Term Cohesion
Degree display a wide range of variation but are still usable with
suggested tweaks. Only Phrase Position in Sentences shows a totally
unpredictable pattern. The results imply that the commonly used
ranking approach which directly extracts top ranked potential phrases
from candidate keyphrase list as the keyphrases may not be reliable.
Abstract: Building conservation work generally involves complex and non-standard work different from new building construction processes. In preparing tenders for building conservation projects, therefore, the quantity surveyor must carefully consider the specificity of non-standard items and demarcate the scope of unique conservation work. While the quantity surveyor must appreciate the full range of works to prepare a good tender document, he typically manages many unfamiliar elements, including practical construction methods, restoration techniques and work sequences. Only by fulfilling the demanding requirements of building conservation work can the quantity surveyor enhance his professionalism an area of growing cultural value and economic importance. By discussing several issues crucial to tender preparations for building conservation projects in Malaysia, this paper seeks a deeper understanding of how quantity surveying can better standardize tender preparation work and more successfully manage building conservation processes.
Abstract: Control of complex systems is one of important files in complex systems, that not only relies on the essence of complex systems which is denoted by the core concept – emergence, but also embodies the elementary concept in control theory. Aiming at giving a clear and self-contained description of emergence, the paper introduces a formal way to completely describe the formation and dynamics of emergence in complex systems. Consequently, this paper indicates the Emergence-Oriented Control methodology that contains three kinds of basic control schemes: the direct control, the system re-structuring and the system calibration. As a universal ontology, the Emergence-Oriented Control provides a powerful tool for identifying and resolving control problems in specific systems.
Abstract: Nowadays, web-based technologies influence in
people-s daily life such as in education, business and others.
Therefore, many web developers are too eager to develop their web
applications with fully animation graphics and forgetting its
accessibility to its users. Their purpose is to make their web
applications look impressive. Thus, this paper would highlight on the
usability and accessibility of a voice recognition browser as a tool to
facilitate the visually impaired and blind learners in accessing virtual
learning environment. More specifically, the objectives of the study
are (i) to explore the challenges faced by the visually impaired
learners in accessing virtual learning environment (ii) to determine
the suitable guidelines for developing a voice recognition browser
that is accessible to the visually impaired. Furthermore, this study
was prepared based on an observation conducted with the Malaysian
visually impaired learners. Finally, the result of this study would
underline on the development of an accessible voice recognition
browser for the visually impaired.
Abstract: The development and extension of large cities induced
a need for shallow tunnel in soft ground of building areas. Estimation
of ground settlement caused by the tunnel excavation is important
engineering point. In this paper, prediction of surface subsidence
caused by tunneling in one section of seventh line of Tehran subway
is considered. On the basis of studied geotechnical conditions of the
region, tunnel with the length of 26.9km has been excavated applying
a mechanized method using an EPB-TBM with a diameter of 9.14m.
In this regard, settlement is estimated utilizing both analytical and
numerical finite element method. The numerical method shows that
the value of settlement in this section is 5cm. Besides, the analytical
consequences (Bobet and Loganathan-Polous) are 5.29 and 12.36cm,
respectively. According to results of this study, due tosaturation of
this section, there are good agreement between Bobet and numerical
methods. Therefore, tunneling processes in this section needs a
special consolidation measurement and support system before the
passage of tunnel boring machine.
Abstract: In this paper, we propose a novel limited feedback scheme for task planning with service robots. Instead of sending the full service robot state information for the task planning, the proposed scheme send the best-M indices of service robots with a indicator. With the indicator, the proposed scheme significantly reduces the communication overhead for task planning as well as mitigates the system performance degradation in terms of the utility. In addition, we analyze the system performance of the proposed scheme and compare the proposed scheme with the other schemes.
Abstract: In two studies we tested the hypothesis that the
appropriate linguistic formulation of a deontic rule – i.e. the
formulation which clarifies the monadic nature of deontic operators
- should produce more correct responses than the conditional
formulation in Wason selection task. We tested this assumption by
presenting a prescription rule and a prohibition rule in conditional
vs. proper deontic formulation. We contrasted this hypothesis with
two other hypotheses derived from social contract theory and
relevance theory. According to the first theory, a deontic rule
expressed in terms of cost-benefit should elicit a cheater detection
module, sensible to mental states attributions and thus able to
discriminate intentional rule violations from accidental rule
violations. We tested this prevision by distinguishing the two types
of violations. According to relevance theory, performance in
selection task should improve by increasing cognitive effect and
decreasing cognitive effort. We tested this prevision by focusing
experimental instructions on the rule vs. the action covered by the
rule. In study 1, in which 480 undergraduates participated, we
tested these predictions through a 2 x 2 x 2 x 2 (type of the rule x
rule formulation x type of violation x experimental instructions)
between-subjects design. In study 2 – carried out by means of a 2 x
2 (rule formulation x type of violation) between-subjects design -
we retested the hypothesis of rule formulation vs. the cheaterdetection
hypothesis through a new version of selection task in
which intentional vs. accidental rule violations were better
discriminated. 240 undergraduates participated in this study.
Results corroborate our hypothesis and challenge the contrasting
assumptions. However, they show that the conditional formulation
of deontic rules produces a lower performance than what is
reported in literature.
Abstract: The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.
Abstract: Current tools for data migration between documentoriented
and relational databases have several disadvantages. We
propose a new approach for data migration between documentoriented
and relational databases. During data migration the relational
schema of the target (relational database) is automatically created
from collection of XML documents. Proposed approach is verified on
data migration between document-oriented database IBM Lotus/
Notes Domino and relational database implemented in relational
database management system (RDBMS) MySQL.
Abstract: The Beijing road traffic system, as a typical huge
urban traffic system, provides a platform for analyzing the complex
characteristics and the evolving mechanisms of urban traffic systems.
Based on dynamic network theory, we construct the dynamic model
of the Beijing road traffic system in which the dynamical properties
are described completely. Furthermore, we come into the conclusion
that urban traffic systems can be viewed as static networks, stochastic
networks and complex networks at different system phases by
analyzing the structural randomness. As well as, we demonstrate the
evolving process of the Beijing road traffic network based on real
traffic data, validate the stochastic characteristics and the scale-free
property of the network at different phases
Abstract: This paper describes the challenges on the requirements engineering for developing an enterprise applications in higher
education environment. The development activities include software implementation, maintenance, and enhancement and support for online
transaction processing and overnight batch processing.
Generally, an enterprise application for higher education environment
may include Student Information System (SIS), HR/Payroll system,
Financial Systems etc. By the way, there are so many challenges in
requirement engineering phases in order to provide two distinctive
services that are production processing support and systems
development.
Abstract: In the article the historical formation of interethnic and
interconfessional agreement policy in Kazakhstan and their
developing features at present time will be analyzed.
The successfully pursued by Kazakhstan at the present in the
direction of ethnic and confessional policy is regarded as a major
factor in promoting stability for the country.
Abstract: Since DVB-RCS has been successively implemented, the mobile communication on the multi-beam satellite communication is attractive attention. And the DVB-RCS standard sets up to support mobility of a RCST. In the case of the spot-beam satellite system, the received signal strength does not differ largely between the center and the boundary of the beam. Thus, the RSS based handoff detection algorithm is not benefit to the satellite system as a terrestrial system. Therefore we propose an Adaptive handoff detection algorithm based on RCST mobility information. Our handoff detection algorithm not only can be used as centralized handoff detection algorithm but also removes uncertainties of handoff due to the variation of RSS. Performances were compared with RSS based handoff algorithm. Simulation results show that the proposed handoff detection algorithm not only achieved better handoff and link degradation rate, but also achieved better forward link spectral efficiency.
Abstract: This paper presents a constrained valley detection
algorithm. The intent is to find valleys in the map for the path planning
that enables a robot or a vehicle to move safely. The constraint to the
valley is a desired width and a desired depth to ensure the space for
movement when a vehicle passes through the valley. We propose an
algorithm to find valleys satisfying these 2 dimensional constraints.
The merit of our algorithm is that the pre-processing and the
post-processing are not necessary to eliminate undesired small valleys.
The algorithm is validated through simulation using digitized
elevation data.
Abstract: Multiple sequence alignment is a fundamental part in
many bioinformatics applications such as phylogenetic analysis.
Many alignment methods have been proposed. Each method gives a
different result for the same data set, and consequently generates a
different phylogenetic tree. Hence, the chosen alignment method
affects the resulting tree. However in the literature, there is no
evaluation of multiple alignment methods based on the comparison of
their phylogenetic trees. This work evaluates the following eight
aligners: ClustalX, T-Coffee, SAGA, MUSCLE, MAFFT, DIALIGN,
ProbCons and Align-m, based on their phylogenetic trees (test trees)
produced on a given data set. The Neighbor-Joining method is used
to estimate trees. Three criteria, namely, the dNNI, the dRF and the
Id_Tree are established to test the ability of different alignment
methods to produce closer test tree compared to the reference one
(true tree). Results show that the method which produces the most
accurate alignment gives the nearest test tree to the reference tree.
MUSCLE outperforms all aligners with respect to the three criteria
and for all datasets, performing particularly better when sequence
identities are within 10-20%. It is followed by T-Coffee at lower
sequence identity (30%), trees scores of all methods
become similar.
Abstract: We consider a two-way relay network where two sources exchange information. A relay helps the two sources exchange information using the decode-and-XOR-forward protocol. We investigate the power minimization problem with minimum rate constraints. The system needs two time slots and in each time slot the required rate pair should be achievable. The power consumption is minimized in each time slot and we obtained the closed form solution. The simulation results confirm that the proposed power allocation scheme consumes lower total power than the conventional schemes.