Abstract: A novel adaptive fuzzy trajectory tracking algorithm of Stewart platform based motion platform is proposed to compensate path deviation and degradation of controller-s performance due to actuator torque limit. The algorithm can be divided into two parts: the real-time trajectory shaping part and the joint space adaptive fuzzy controller part. For a reference trajectory in task space whenever any of the actuators is saturated, the desired acceleration of the reference trajectory is modified on-line by using dynamic model of motion platform. Meanwhile an additional action with respect to the difference between the nominal and modified trajectories is utilized in the non-saturated region of actuators to reduce the path error. Using modified trajectory as input, the joint space controller incorporates compute torque controller, leg velocity observer and fuzzy disturbance observer with saturation compensation. It can ensure stability and tracking performance of controller in present of external disturbance and position only measurement. Simulation results verify the effectiveness of proposed control scheme.
Abstract: The study presents a brief and synthetic discussion of selected conclusions resulting from multidimensional and in-depth empirical studies. Its theoretical part presents the assumptions referring to social responsibility management from the perspective of the specific nature of small enterprise functioning, while the empirical part presents the selected dysfunctions and paradoxes in social responsibility management referring to this group of enterprises. The paper is summarized by a short list of the resulting recommendations.
Abstract: Unlike the best effort service provided by the internet
today, next-generation wireless networks will support real-time
applications. This paper proposes an adaptive early packet discard
(AEPD) policy to improve the performance of the real time TCP
traffic over ATM networks and avoid the fragmentation problem.
Three main aspects are incorporated in the proposed policy. First,
providing quality-of-service (QoS) guaranteed for real-time
applications by implementing a priority scheduling. Second,
resolving the partially corrupted packets problem by differentiating
the buffered cells of one packet from another. Third, adapting a
threshold dynamically using Fuzzy logic based on the traffic
behavior to maintain a high throughput under a variety of load
conditions. The simulation is run for two priority classes of the input
traffic: real time and non-real time classes. Simulation results show
that the proposed AEPD policy improves throughput and fairness
over that using static threshold under the same traffic conditions.
Abstract: The paper investigates parallel channel instabilities of
natural circulation boiling water reactor. A thermal-hydraulic model
is developed to simulate two-phase flow behavior in the natural circulation boiling water reactor (NCBWR) with the incorporation of
ex-core components and recirculation loop such as steam separator, down-comer, lower-horizontal section and upper-horizontal section
and then, numerical analysis is carried out for parallel channel
instabilities of the reactor undergoing both in-phase and out-of-phase
modes of oscillations. To analyze the relative effect on stability of the reactor due to inclusion of various ex-core components and
recirculation loop, marginal stable point is obtained at a particular inlet enthalpy of the reactor core without the inclusion of ex-core
components and recirculation loop and then with the inclusion of the
same. Numerical simulations are also conducted to determine the
relative dominance between two modes of oscillations i.e. in-phase and out-of-phase. Simulations are also carried out when the channels
are subjected to asymmetric power distribution keeping the inlet enthalpy same.
Abstract: Clustering unstructured text documents is an
important issue in data mining community and has a number of
applications such as document archive filtering, document
organization and topic detection and subject tracing. In the real
world, some of the already clustered documents may not be of
importance while new documents of more significance may evolve.
Most of the work done so far in clustering unstructured text
documents overlooks this aspect of clustering. This paper, addresses
this issue by using the Fading Function. The unstructured text
documents are clustered. And for each cluster a statistics structure
called Cluster Profile (CP) is implemented. The cluster profile
incorporates the Fading Function. This Fading Function keeps an
account of the time-dependent importance of the cluster. The work
proposes a novel algorithm Clustering n-ary Merge Algorithm
(CnMA) for unstructured text documents, that uses Cluster Profile
and Fading Function. Experimental results illustrating the
effectiveness of the proposed technique are also included.
Abstract: The purpose of this paper is to provide a practical
example to the Linear Quadratic Gaussian (LQG) controller. This
method includes a description and some discussion of the discrete
Kalman state estimator. One aspect of this optimality is that the
estimator incorporates all information that can be provided to it. It
processes all available measurements, regardless of their precision, to
estimate the current value of the variables of interest, with use of
knowledge of the system and measurement device dynamics, the
statistical description of the system noises, measurement errors, and
uncertainty in the dynamics models.
Since the time of its introduction, the Kalman filter has been the
subject of extensive research and application, particularly in the area
of autonomous or assisted navigation. For example, to determine the
velocity of an aircraft or sideslip angle, one could use a Doppler
radar, the velocity indications of an inertial navigation system, or the
relative wind information in the air data system. Rather than ignore
any of these outputs, a Kalman filter could be built to combine all of
this data and knowledge of the various systems- dynamics to
generate an overall best estimate of velocity and sideslip angle.
Abstract: This paper proposes a novel approach that combines statistical models and support vector machines. A hybrid scheme which appropriately incorporates the advantages of both the generative and discriminant model paradigms is described and evaluated. Support vector machines (SVMs) are trained to divide the whole speakers' space into small subsets of speakers within a hierarchical tree structure. During testing a speech token is assigned to its corresponding group and evaluation using gaussian mixture models (GMMs) is then processed. Experimental results show that the proposed method can significantly improve the performance of text independent speaker identification task. We report improvements of up to 50% reduction in identification error rate compared to the baseline statistical model.
Abstract: The recommendation of the committee on corporate
governance for public companies in Nigeria, that the position of the
CEO be separated from board chair has generated serious debate
among scholars and practitioners. They have questioned the
appropriateness of implementing corporate governance model that is
based on Anglo-Saxon agency problem characterized by dispersed
ownership structure; where markets for corporate control, legal
regulation, and contractual incentives are the key governance
mechanisms. This paper strives to resolve the argument by adopting
an institutional perspective in testing the agency theory on board
duality. The study developed a theoretical and empirical model to
better understand how ownership structure influences agency conflict
and how such affects firm performance. Hence, the study examines
the relationship between CEO duality and firm performance using
two institutional ownership structures – dispersed ownership and
concentrated ownership structures. The empirical results show that
CEO duality is negatively correlated with firm performance in
Nigeria irrespective of the firm-s ownership structure. The findings
give credence to the recommendation of the Peterside Commission
on the need to separate the position of CEO from board chair.
Abstract: Carriers scattering in the inversion channel of n-
MOSFET dominates the drain current. This paper presents an effective
electron mobility model for the pocket implanted nano scale
n-MOSFET. The model is developed by using two linear pocket
profiles at the source and drain edges. The channel is divided into
three regions at source, drain and central part of the channel region.
The total number of inversion layer charges is found for these three
regions by numerical integration from source to drain ends and the
number of depletion layer charges is found by using the effective
doping concentration including pocket doping effects. These two
charges are then used to find the effective normal electric field,
which is used to find the effective mobility model incorporating the
three scattering mechanisms, such as, Coulomb, phonon and surface
roughness scatterings as well as the ballistic phenomena for the
pocket implanted nano-scale n-MOSFET. The simulation results show
that the derived mobility model produces the same results as found
in the literatures.
Abstract: Home is important for Chinese people. Because the
information regarding the house attributes and surrounding
environments is incomplete in most real estate agency, most house
buyers are difficult to consider the overall factors effectively and only
can search candidates by sorting-based approach. This study aims to
develop a decision support system for housing purchasing, in which
surrounding facilities of each house are quantified. Then, all
considered house factors and customer preferences are incorporated
into Simple Multi-Attribute Ranking Technique (SMART) to support
the housing evaluation. To evaluate the validity of proposed approach,
an empirical study was conducted from a real estate agency. Based on
the customer requirement and preferences, the proposed approach can
identify better candidate house with consider the overall house
attributes and surrounding facilities.
Abstract: A phenomenological model for species spreading which incorporates the Allee effect, a species- maximum attainable growth rate, collective dispersal rate and dispersal adaptability is presented. This builds on a well-established reaction-diffusion model for spatial spreading of invading organisms. The model is phrased in terms of the “hostility" (which quantifies the Allee threshold in relation to environmental sustainability) and dispersal adaptability (which measures how a species is able to adapt its migratory response to environmental conditions). The species- invading/retreating speed and the sharpness of the invading boundary are explicitly characterised in terms of the fundamental parameters, and analysed in detail.
Abstract: Innovational development of regions in Russia is generally faced with the essential influence from federal and local authorities. The organization of effective mechanism of innovation development (and self-development) is impossible without establishment of defined institutional conditions in the analyzed field. Creative utilization of scientific concepts and information should merge, giving rise to continuing innovation and advanced production. The paper presents an analysis of institutional conditions in the field of creation and development of innovation activity infrastructure and transferring of knowledge and skills between different economic agents in Russia. Knowledge is mainly privately owned, developed through R&D investments and incorporated into technology or a product. Innovation infrastructure is a strong concentration mechanism of advanced facilities, which are mainly located inside large agglomerations or city-regions in order to benefit from scale effects in both input markets (human capital, private financial capital) and output markets (higher education services, research services). The empirical results of the paper show that in the presence of more efficient innovation and knowledge transfer and transcoding system and of a more open attitude of economic agents towards innovation, the innovation and knowledge capacity of regional economy is much higher.
Abstract: Platinum oxide nanoparticles were prepared by a
simple hydrothermal route and chemical reduction using
carbohydrates (Fructose and sucrose) as the reducing and
stabilizing agents. The crystallite size of these nanoparticles was
evaluated from X-ray diffraction (XRD), atomic force microscopy
(AFM) and transmission electron microscopy (TEM) and was
found to be 10 nm as shown in figure 1, which is the
demonstration of EM bright field and transmission electron
microscopy. The effect of carbohydrates on the morphology of the
nanoparticles was studied using TEM (Figure 1). The
nanoparticles (100 μg/ml) were administered to the Pseudomonas
Stutzeri and Lactobacillus cultures and the incubation was done at
35 oC for 24 hours. The nanocomposites exhibited interesting
inhibitory as well as bactericidal activity against P. Stutzeri and
and Lactobacillus species. Incorporation of nanoparticles also
increased the thermal stability of the carbohydrates.
Abstract: Modeling the behavior of the dialogue management in
the design of a spoken dialogue system using statistical methodologies
is currently a growing research area. This paper presents a work
on developing an adaptive learning approach to optimize dialogue
strategy. At the core of our system is a method formalizing dialogue
management as a sequential decision making under uncertainty whose
underlying probabilistic structure has a Markov Chain. Researchers
have mostly focused on model-free algorithms for automating the
design of dialogue management using machine learning techniques
such as reinforcement learning. But in model-free algorithms there
exist a dilemma in engaging the type of exploration versus exploitation.
Hence we present a model-based online policy learning
algorithm using interconnected learning automata for optimizing
dialogue strategy. The proposed algorithm is capable of deriving
an optimal policy that prescribes what action should be taken in
various states of conversation so as to maximize the expected total
reward to attain the goal and incorporates good exploration and
exploitation in its updates to improve the naturalness of humancomputer
interaction. We test the proposed approach using the most
sophisticated evaluation framework PARADISE for accessing to the
railway information system.
Abstract: In recent years, an increased competition and lower profit margins have necessitated a focus on improving the performance of the product development process, an area that traditionally have been excluded from detailed steering and evaluation. A systematic improvement requires a good understanding of the current performance, wherefore the interest for product development performance measurement has increased dramatically. This paper presents a case study that evaluates the performance of the product development performance measurement system used in a Swedish company that is a part of a global corporate group. The study is based on internal documentation and eighteen in-depth interviews with stakeholders involved in the product development process. The results from the case study includes a description of what metrics that are in use, how these are employed, and its affect on the quality of the performance measurement system. Especially, the importance of having a well-defined process proved to have a major impact on the quality of the performance measurement system in this particular case.
Abstract: For a variety of safety and economic reasons, engineering undergraduates in Australia have experienced diminishing access to the real hardware that is typically the embodiment of their theoretical studies. This trend will delay the development of practical competence, decrease the ability to model and design, and suppress motivation. The author has attempted to address this concern by creating a software tool that contains both photographic images of real machinery, and sets of graphical modeling 'tools'. Academics from a range of disciplines can use the software to set tutorial tasks, and incorporate feedback comments for a range of student responses. An evaluation of the software demonstrated that students who had solved modeling problems with the aid of the electronic tutor performed significantly better in formal examinations with similar problems. The 2-D graphical diagnostic routines in the Tutor have the potential to be used in a wider range of problem-solving tasks.
Abstract: It-s known that incorporating prior knowledge into support
vector regression (SVR) can help to improve the approximation
performance. Most of researches are concerned with the incorporation
of knowledge in form of numerical relationships. Little work,
however, has been done to incorporate the prior knowledge on the
structural relationships among the variables (referred as to Structural
Prior Knowledge, SPK). This paper explores the incorporation of SPK
in SVR by constructing appropriate admissible support vector kernel
(SV kernel) based on the properties of reproducing kernel (R.K).
Three-levels specifications of SPK are studies with the corresponding
sub-levels of prior knowledge that can be considered for the method.
These include Hierarchical SPK (HSPK), Interactional SPK (ISPK)
consisting of independence, global and local interaction, Functional
SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A
convenient tool for describing the SPK, namely Description Matrix
of SPK is introduced. Subsequently, a new SVR, namely Motivated
Support Vector Regression (MSVR) whose structure is motivated
in part by SPK, is proposed. Synthetic examples show that it is
possible to incorporate a wide variety of SPK and helpful to improve
the approximation performance in complex cases. The benefits of
MSVR are finally shown on a real-life military application, Air-toground
battle simulation, which shows great potential for MSVR to
the complex military applications.
Abstract: Nowadays, efficiency, effectiveness and economy are regarded as the main objectives of managers and the secret of the continuity of an organization in competing economy. In such competing settings, it is essential that the management of an organization has not been neglected and been obliged to identify quickly the opportunities for improving the operation of organization and remove the shortcomings of their managed system in order to use the opportunities for development. Operational auditing is a useful tool for system adjustment and leading an organization toward its objectives. Operational auditing is indeed a viewpoint which identifies the causes of insufficiencies, weaknesses and deficiencies of system and plans to eliminate them. Operational auditing is useful in the effectiveness and optimization of executive managers- decisions and increasing the efficiency and economy of their performance in the future and prevents the waste and incorrect use of resources. Evidence shows that operational auditing is used at a limited level in Iran. This matter raises some questions like the following ones in the minds. Why do a limited number of corporations use operational auditing? Which factors can guarantee its full implementation? What obstacles are there in its implementation? The purpose of this article is to determine executive objectives, the operation domain of operational auditing, the components of operational auditing and the executive obstacles to operational auditing in Iran.
Abstract: With the resource exhaustion, bad affections of human
activities and the awakening of the human rights, the corporate social
responsibility became popular corporate strategy achieving
sustainable development of both corporation and society. The issue of
Guideline of Chinese Corporate Social Responsibility Report
promotes greatly corporation to take social responsibility. This paper
built the index system according to this guideline and takes the textile
industry as an example, uses the analytical hierarchy process to
identify the weightings of different responsibilities of corporation to
guide the corporate social responsibility performance assessment.
Abstract: Calcium [Ca2+] dynamics is studied as a potential form
of neuron excitability that can control many irregular processes like
metabolism, secretion etc. Ca2+ ion enters presynaptic terminal and
increases the synaptic strength and thus triggers the neurotransmitter
release. The modeling and analysis of calcium dynamics in neuron
cell becomes necessary for deeper understanding of the processes
involved. A mathematical model has been developed for cylindrical
shaped neuron cell by incorporating physiological parameters like
buffer, diffusion coefficient, and association rate. Appropriate initial
and boundary conditions have been framed. The closed form solution
has been developed in terms of modified Bessel function. A computer
program has been developed in MATLAB 7.11 for the whole
approach.