Abstract: This paper proposes a solution to the motion planning
and control problem of car-like mobile robots which is required to
move safely to a designated target in a priori known workspace
cluttered with swarm of boids exhibiting collective emergent
behaviors. A generalized algorithm for target convergence and
swarm avoidance is proposed that will work for any number of
swarms. The control laws proposed in this paper also ensures
practical stability of the system. The effectiveness of the proposed
control laws are demonstrated via computer simulations of an
emergent behavior.
Abstract: Inventory decisional environment of short life-cycle
products is full of uncertainties arising from randomness and
fuzziness of input parameters like customer demand requiring
modeling under hybrid uncertainty. Prior inventory models
incorporating fuzzy demand have unfortunately ignored stochastic
variation of demand. This paper determines an unambiguous optimal
order quantity from a set of n fuzzy observations in a newsvendor
inventory setting in presence of fuzzy random variable demand
capturing both fuzzy perception and randomness of customer
demand. The stress of this paper is in providing solution procedure
that attains optimality in two steps with demand information
availability in linguistic phrases leading to fuzziness along with
stochastic variation. The first step of solution procedure identifies
and prefers one best fuzzy opinion out of all expert opinions and the
second step determines optimal order quantity from the selected
event that maximizes profit. The model and solution procedure is
illustrated with a numerical example.
Abstract: There are two paradigms proposed to provide QoS for Internet applications: Integrated service (IntServ) and Differentiated service (DiffServ).Intserv is not appropriate for large network like Internet. Because is very complex. Therefore, to reduce the complexity of QoS management, DiffServ was introduced to provide QoS within a domain using aggregation of flow and per- class service. In theses networks QoS between classes is constant and it allows low priority traffic to be effected from high priority traffic, which is not suitable. In this paper, we proposed a fuzzy controller, which reduced the effect of low priority class on higher priority ones. Our simulations shows that, our approach reduces the latency dependency of low priority class on higher priority ones, in an effective manner.
Abstract: In an open real-time system environment, the coexistence of different kinds of real-time and non real-time applications makes the system scheduling mechanism face new requirements and challenges. One two-level scheduling scheme of the open real-time systems is introduced, and points out that hard and soft real-time applications are scheduled non-distinctively as the same type real-time applications, the Quality of Service (QoS) cannot be guaranteed. It has two flaws: The first, it can not differentiate scheduling priorities of hard and soft real-time applications, that is to say, it neglects characteristic differences between hard real-time applications and soft ones, so it does not suit a more complex real-time environment. The second, the worst case execution time of soft real-time applications cannot be predicted exactly, so it is not worth while to cost much spending in order to assure all soft real-time applications not to miss their deadlines, and doing that may cause resource wasting. In order to solve this problem, a novel two-level real-time scheduling mechanism (including scheduling profile and scheduling algorithm) which adds the process of dealing with soft real-time applications is proposed. Finally, we verify real-time scheduling mechanism from two aspects of theory and experiment. The results indicate that our scheduling mechanism can achieve the following objectives. (1) It can reflect the difference of priority when scheduling hard and soft real-time applications. (2) It can ensure schedulability of hard real-time applications, that is, their rate of missing deadline is 0. (3) The overall rate of missing deadline of soft real-time applications can be less than 1. (4) The deadline of a non-real-time application is not set, whereas the scheduling algorithm that server 0 S uses can avoid the “starvation" of jobs and increase QOS. By doing that, our scheduling mechanism is more compatible with different types of applications and it will be applied more widely.
Abstract: The group mutual exclusion (GME) problem is an
interesting generalization of the mutual exclusion problem. Several
solutions of the GME problem have been proposed for message
passing distributed systems. However, none of these solutions is
suitable for real time distributed systems. In this paper, we propose a
token-based distributed algorithms for the GME problem in soft real
time distributed systems. The algorithm uses the concepts of priority
queue, dynamic request set and the process state. The algorithm uses
first come first serve approach in selecting the next session type
between the same priority levels and satisfies the concurrent
occupancy property. The algorithm allows all n processors to be
inside their CS provided they request for the same session. The
performance analysis and correctness proof of the algorithm has also
been included in the paper.
Abstract: In this paper an efficient incomplete factorization preconditioner is proposed for the Least Mean Squares (LMS) adaptive filter. The proposed preconditioner is approximated from a priori knowledge of the factors of input correlation matrix with an incomplete strategy, motivated by the sparsity patter of the upper triangular factor in the QRD-RLS algorithm. The convergence properties of IPLMS algorithm are comparable with those of transform domain LMS(TDLMS) algorithm. Simulation results show efficiency and robustness of the proposed algorithm with reduced computational complexity.
Abstract: Cluster analysis is the name given to a diverse collection of techniques that can be used to classify objects (e.g. individuals, quadrats, species etc). While Kohonen's Self-Organizing Feature Map (SOFM) or Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including speech recognition, image data compression, image or character recognition, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. SOM networks combine competitive learning with dimensionality reduction by smoothing the clusters with respect to an a priori grid and provide a powerful tool for data visualization. In this paper, SOM is used for creating a toroidal mapping of two-dimensional lattice to perform cluster analysis on results of a chemical analysis of wines produced in the same region in Italy but derived from three different cultivators, referred to as the “wine recognition data" located in the University of California-Irvine database. The results are encouraging and it is believed that SOM would make an appealing and powerful decision-support system tool for clustering tasks and for data visualization.
Abstract: The conventional production of biodiesel from crude
palm oil which contains large amounts of free fatty acids in the
presence of a homogeneous base catalyst confronts the problems of
soap formation and very low yield of biodiesel. To overcome these
problems, free fatty acids must be esterified to their esters in the
presence of an acid catalyst prior to alkaline-catalyzed
transesterification. Sulfated metal oxides are a promising group of
catalysts due to their very high acidity. In this research, aluminadoped
sulfated tin oxide (SO4
2-/Al2O3-SnO2) catalysts were prepared
and used for esterification of free fatty acids in crude palm oil in a
batch reactor. The SO4
2-/Al2O3-SnO2 catalysts were prepared from
different Al precursors. The results showed that different Al
precursors gave different activities of the SO4
2-/Al2O3-SnO2 catalysts.
The esterification of free fatty acids in crude palm oil with methanol
in the presence of SO4
2-/Al2O3-SnO2 catalysts followed first-order
kinetics.
Abstract: This article examines the emergence and development
of the Kazakhstan species of humanism. The biggest challenge for
Kazakhstan in terms of humanism is connected with advocating
human values in parallel to promoting national interests; preserving
the continuity of traditions in various spheres of life, business and
culture. This should be a common goal for the entire society, the
main direction for a national intelligence, and a platform for the state
policy. An idea worth considering is a formation of national humanist
tradition model; the challenges are adapting people to live in the
context of new industrial and innovative economic conditions,
keeping the balance during intensive economic development of the
country, and ensuring social harmony in the society.
Abstract: A subjectively influenced router for vehicles in a fourjunction
traffic system is presented. The router is based on a 3-layer
Backpropagation Neural Network (BPNN) and a greedy routing
procedure. The BPNN detects priorities of vehicles based on the
subjective criteria. The subjective criteria and the routing procedure
depend on the routing plan towards vehicles depending on the user.
The routing procedure selects vehicles from their junctions based on
their priorities and route them concurrently to the traffic system. That
is, when the router is provided with a desired vehicles selection
criteria and routing procedure, it routes vehicles with a reasonable
junction clearing time. The cost evaluation of the router determines
its efficiency. In the case of a routing conflict, the router will route
the vehicles in a consecutive order and quarantine faulty vehicles.
The simulations presented indicate that the presented approach is an
effective strategy of structuring a subjective vehicle router.
Abstract: With high speed vessels getting ever more sophisti-cated, travelling at higher and higher speeds and operating in With high speed vessels getting ever more sophisticated,
travelling at higher and higher speeds and operating in areas of
high maritime traffic density, training becomes of the highest priority
to ensure that safety levels are maintained, and risks are adequately
mitigated. Training onboard the actual craft on the actual route still
remains the most effective way for crews to gain experience. However,
operational experience and incidents during the last 10 years
demonstrate the need for supplementary training whether in the area
of simulation or man to man, man/ machine interaction. Training and
familiarisation of the crew is the most important aspect in preventing
incidents. The use of simulator, computer and web based training
systems in conjunction with onboard training focusing on critical
situations will improve the man machine interaction and thereby
reduce the risk of accidents. Today, both ship simulator and bridge
teamwork courses are now becoming the norm in order to improve
further emergency response and crisis management skills. One of the
main causes of accidents is the human factor. An efficient way to
reduce human errors is to provide high-quality training to the personnel
and to select the navigators carefully.areas of high maritime traffic density, training becomes of the highest priority to ensure that safety levels are maintained, and risks are adequately mitigated. Training onboard the actual craft on the actual route still remains the most effective way for crews to gain experience. How-ever, operational experience and incidents during the last 10 years demonstrate the need for supplementary training whether in the area of simulation or man to man, man/ machine interaction. Training and familiarisation of the crew is the most important aspect in preventing incidents. The use of simulator, computer and web based training systems in conjunction with onboard training focusing on critical situations will improve the man machine interaction and thereby reduce the risk of accidents. Today, both ship simulator and bridge teamwork courses are now becoming the norm in order to improve further emergency response and crisis management skills. One of the main causes of accidents is the human factor. An efficient way to reduce human errors is to provide high-quality training to the person-nel and to select the navigators carefully. KeywordsCBT - WBT systems, Human factors.
Abstract: In real-field applications, the correct determination of voice segments highly improves the overall system accuracy and minimises the total computation time. This paper presents reliable measures of speech compression by detcting the end points of the speech signals prior to compressing them. The two different compession schemes used are the Global threshold and the Level- Dependent threshold techniques. The performance of the proposed method is tested wirh the Signal to Noise Ratios, Peak Signal to Noise Ratios and Normalized Root Mean Square Error parameter measures.
Abstract: The need to have standards has always been a priority
of all the disciplines in the world. Today, standards such as XML and
USB are trying to create a universal interface for their respective
areas. The information regarding every family in the discipline
addressed, must have a lot in common, known as Metadata. A lot of
work has been done in specific domains such as IEEE LOM and
MPEG-7 but they do not appeal to the universality of creating
Metadata for all entities, where we take an entity (object) as, not
restricted to Software Terms. This paper tries to address this problem
of universal Metadata Definition which may lead to increase in
precision of search.
Abstract: The objective of this paper is to estimate realistic
principal extrusion process parameters by means of artificial neural
network. Conventionally, finite element analysis is used to derive
process parameters. However, the finite element analysis of the
extrusion model does not consider the manufacturing process
constraints in its modeling. Therefore, the process parameters
obtained through such an analysis remains highly theoretical.
Alternatively, process development in industrial extrusion is to a
great extent based on trial and error and often involves full-size
experiments, which are both expensive and time-consuming. The
artificial neural network-based estimation of the extrusion process
parameters prior to plant execution helps to make the actual extrusion
operation more efficient because more realistic parameters may be
obtained. And so, it bridges the gap between simulation and real
manufacturing execution system. In this work, a suitable neural
network is designed which is trained using an appropriate learning
algorithm. The network so trained is used to predict the
manufacturing process parameters.
Abstract: Prior to 1975, women in Laos suffered from having
reduced levels of power over decision-making in their families and in
their communities. This has had a negative impact on their ability to
develop their own identities. Their roles were identified as being
responsible for household activities and making preparations for their
marriage. Many women lost opportunities to get educated and access
the outdoor work that might have empowered them to improve their
situations. So far, no accurate figures of either emigrants or return
migrants have been compiled but it appears that most of them were
women, and it was women who most and more frequently remitted
money home. However, very few recent studies have addressed the
relationship between remittances and the roles of women in Laos.
This study, therefore, aims at redressing to some extent the
deficiencies in knowledge. Qualitative techniques were used to gather
data, including individual in-depth interviews and direct observation
in combination with the content analysis method. Forty women in
Vientiane Municipality and Savannakhet province were individually
interviewed. It was found that the monetary remittance was typically
used for family security and well-being; on fungible activities; on
economic and business activities; and on community development,
especially concerning hospitality and providing daily household
necessities. Remittances played important roles in improving many
respondents- livelihoods and positively changed their identities in
families and communities. Women became empowered as they were
able to start commercial businesses, rather than taking care of (just)
housework, children and elders. Interviews indicated that 92.5% of
the respondents their quality of lives improved, 90% felt happier in
their families and 82.5% felt conflicts in their families were reduced.
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: More and more governments around the world are
introducing e-government as a means of reducing costs, improving
services, saving time and increasing effectiveness and efficiency in
the public sector Therefore e-government has been identified as one
of the top priorities for Saudi government and all its agencies.
However, the adoption of e-government is facing many challenges
and barriers such as technological, cultural, organizational, and social
issues which must be considered and treated carefully by any
government contemplating its adoption. This paper reports on a pilot
study amongst online (e-ready) citizens to identify the challenges and
barriers that affect the adoption of e-government services especially
from their perspective in Saudi society. Based on the analysis of data
collected from an online survey the researcher was able to identify
some of the important barriers and challenges from the e-ready
citizen perspective. As a result, this study has generated a list of
possible strategies to move towards successful adoption of egovernment
services in Saudi Arabia.
Abstract: Problems on algebraical polynomials appear in many fields of mathematics and computer science. Especially the task of determining the roots of polynomials has been frequently investigated.Nonetheless, the task of locating the zeros of complex polynomials is still challenging. In this paper we deal with the location of zeros of univariate complex polynomials. We prove some novel upper bounds for the moduli of the zeros of complex polynomials. That means, we provide disks in the complex plane where all zeros of a complex polynomial are situated. Such bounds are extremely useful for obtaining a priori assertations regarding the location of zeros of polynomials. Based on the proven bounds and a test set of polynomials, we present an experimental study to examine which bound is optimal.
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: In this paper, five options of Iran’s gas flare recovery
have been compared via MCDM method. For developing the model,
the weighing factor of each indicator an AHP method is used via the
Expert-choice software. Several cases were considered in this
analysis. They are defined where the priorities were defined always
keeping one criterion in first position, while the priorities of the other
criteria were defined by ordinal information defining the mutual
relations of the criteria and the respective indicators. The results,
show that amongst these cases, priority is obtained for CHP usage
where availability indicator is highly weighted while the pipeline
usage is obtained where environmental indicator highly weighted and
the injection priority is obtained where economic indicator is highly
weighted and also when the weighing factor of all the criteria are the
same the Injection priority is obtained.