Abstract: We consider a Principal-Agent model with the
Principal being a seller who does not know perfectly how much the
buyer (the Agent) is willing to pay for the good. The buyer-s
preferences are hence his private information. The model corresponds
to the nonlinear pricing problem of Maskin and Riley. We assume
there are three types of Agents. The model is solved using
“informational rents" as variables. In the last section we present the
main characteristics of the optimal contracts in asymmetric
information and some possible extensions of the model.
Abstract: Automated operations based on voice commands will become more and more important in many applications, including robotics, maintenance operations, etc. However, voice command recognition rates drop quite a lot under non-stationary and chaotic noise environments. In this paper, we tried to significantly improve the speech recognition rates under non-stationary noise environments. First, 298 Navy acronyms have been selected for automatic speech recognition. Data sets were collected under 4 types of noisy environments: factory, buccaneer jet, babble noise in a canteen, and destroyer. Within each noisy environment, 4 levels (5 dB, 15 dB, 25 dB, and clean) of Signal-to-Noise Ratio (SNR) were introduced to corrupt the speech. Second, a new algorithm to estimate speech or no speech regions has been developed, implemented, and evaluated. Third, extensive simulations were carried out. It was found that the combination of the new algorithm, the proper selection of language model and a customized training of the speech recognizer based on clean speech yielded very high recognition rates, which are between 80% and 90% for the four different noisy conditions. Fourth, extensive comparative studies have also been carried out.
Abstract: Information and communication service providers
(ICSP) that are significant in size and provide Internet-based services
take administrative, technical, and physical protection measures via
the information security check service (ISCS). These protection
measures are the minimum action necessary to secure the stability and
continuity of the information and communication services (ICS) that
they provide. Thus, information assets are essential to providing ICS,
and deciding the relative importance of target assets for protection is a
critical procedure. The risk analysis model designed to decide the
relative importance of information assets, which is described in this
study, evaluates information assets from many angles, in order to
choose which ones should be given priority when it comes to
protection. Many-sided risk analysis (MSRS) grades the importance of
information assets, based on evaluation of major security check items,
evaluation of the dependency on the information and communication
facility (ICF) and influence on potential incidents, and evaluation of
major items according to their service classification, in order to
identify the ISCS target. MSRS could be an efficient risk analysis
model to help ICSPs to identify their core information assets and take
information protection measures first, so that stability of the ICS can
be ensured.
Abstract: Problem solving has traditionally been one of the principal research areas for artificial intelligence. Yet, although artificial intelligence reasoning techniques have been employed in several product support systems, the benefit of integrating product support, knowledge engineering, and problem solving, is still unclear. This paper studies the synergy of these areas and proposes a knowledge engineering framework that integrates product support systems and artificial intelligence techniques. The framework includes four spaces; the data, problem, hypothesis, and solution ones. The data space incorporates the knowledge needed for structured reasoning to take place, the problem space contains representations of problems, and the hypothesis space utilizes a multimodal reasoning approach to produce appropriate solutions in the form of virtual documents. The solution space is used as the gateway between the system and the user. The proposed framework enables the development of product support systems in terms of smaller, more manageable steps while the combination of different reasoning techniques provides a way to overcome the lack of documentation resources.
Abstract: Tourism industry is an important sector in Malaysia economy and this motivates the examination of long-run relationships between tourist arrivals from three selected European countries in Malaysia and four possible determinants; relative prices, exchange rates, transportation cost and relative prices of substitute destination. The study utilizes data from January 1999 to September 2008 and employs standard econometric techniques that include unit root test and cointegration test. The estimated demand model indicates that depreciation of local currency and increases in prices at substitute destination have positive impact on tourist arrivals while increase in transportation cost has negative impact on tourist arrivals. In addition, the model suggests that higher rate of increase in local prices relative to prices at tourist country of origin may not deter tourists from coming to Malaysia
Abstract: Business Process Modeling (BPM) is the first and
most important step in business process management lifecycle. Graph
based formalism and rule based formalism are the two most
predominant formalisms on which process modeling languages are
developed. BPM technology continues to face challenges in coping
with dynamic business environments where requirements and goals
are constantly changing at the execution time. Graph based
formalisms incur problems to react to dynamic changes in Business
Process (BP) at the runtime instances. In this research, an adaptive
and flexible framework based on the integration between Object
Oriented diagramming technique and Petri Net modeling language is
proposed in order to support change management techniques for
BPM and increase the representation capability for Object Oriented
modeling for the dynamic changes in the runtime instances. The
proposed framework is applied in a higher education environment to
achieve flexible, updatable and dynamic BP.
Abstract: This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a multirate neural control of an AUV trajectory for a nontrivial mid-small size AUV “r2D4" stochastic model. This control system has been demonstrated and evaluated by simulation of diving maneuvers using software package Simulink. From the simulation results it can be seen that the chosen AUV model is stable in the presence of noises, and also can be concluded that the proposed research technique will be useful for fast SA of similar AUV systems in real-time search-and-rescue operations.
Abstract: In order to derive important parameters concerning
mobile subscriber MS with ongoing calls in Low Earth Orbit Mobile
Satellite Systems LEO MSSs, a positioning system had to be
integrated into MSS in order to localize mobile subscribers MSs and
track them during the connection. Such integration is regarded as a
complex implementation.
We propose in this paper a novel method based on advantages of
mobility model of Low Earth Orbit Mobile Satellite System LEO
MSS called Evaluation Parameters Method EPM which allows for
such systems the evaluation of different information concerning a
MS with a call in progress even if its location is unknown.
Abstract: Here are many methods for designing and
implementation of virtual laboratories, because of their special
features. The most famous architectural designs are based on
the events. This model of architecting is so efficient for virtual
laboratories implemented on a local network. Later, serviceoriented
architecture, gave the remote access ability to them
and Peer-To-Peer architecture, hired to exchanging data with
higher quality and more speed. Other methods, such as Agent-
Based architecting, are trying to solve the problems of
distributed processing in a complicated laboratory system.
This study, at first, reviews the general principles of
designing a virtual laboratory, and then compares the different
methods based on EDA, SOA and Agent-Based architecting
to present weaknesses and strengths of each method. At the
end, we make the best choice for design, based on existing
conditions and requirements.
Abstract: The process parameters, temperature, pH and
substrate concentration, were optimized for the production of
gentamicin using Micromonouspora echinospora. Experiments were
carried out according to central composite design in response surface
method. The optimum conditions for the maximum production of
gentamicin were found to be: temperature – 31.7oC, pH – 6.8 and
substrate concentration – 3%. At these optimized conditions the
production of gentamicin was found to be – 1040 mg/L. The R2 value
of 0.9465 indicates a good fitness of the model.
Abstract: The Model for Knowledge Base of Computational Objects
(KBCO model) has been successfully applied to represent the
knowledge of human like Plane Geometry, Physical, Calculus. However,
the original model cannot easyly apply in inorganic chemistry
field because of the knowledge specific problems. So, the aim of
this article is to introduce how we extend the Computional Object
(Com-Object) in KBCO model, kinds of fact, problems model, and
inference algorithms to develop a program for solving problems
in inorganic chemistry. Our purpose is to develop the application
that can help students in their study inorganic chemistry at schools.
This application was built successful by using Maple, C# and WPF
technology. It can solve automatically problems and give human
readable solution agree with those writting by students and teachers.
Abstract: Knowledge of an organization does not merely reside
in structured form of information and data; it is also embedded in
unstructured form. The discovery of such knowledge is particularly
difficult as the characteristic is dynamic, scattered, massive and
multiplying at high speed. Conventional methods of managing
unstructured information are considered too resource demanding and
time consuming to cope with the rapid information growth.
In this paper, a Multi-faceted and Automatic Knowledge
Elicitation System (MAKES) is introduced for the purpose of
discovery and capture of organizational knowledge. A trial
implementation has been conducted in a public organization to
achieve the objective of decision capture and navigation from a
number of meeting minutes which are autonomously organized,
classified and presented in a multi-faceted taxonomy map in both
document and content level. Key concepts such as critical decision
made, key knowledge workers, knowledge flow and the relationship
among them are elicited and displayed in predefined knowledge
model and maps. Hence, the structured knowledge can be retained,
shared and reused.
Conducting Knowledge Management with MAKES reduces work
in searching and retrieving the target decision, saves a great deal of
time and manpower, and also enables an organization to keep pace
with the knowledge life cycle. This is particularly important when
the amount of unstructured information and data grows extremely
quickly. This system approach of knowledge management can
accelerate value extraction and creation cycles of organizations.
Abstract: This paper considers the control of the longitudinal
flight dynamics of an F-16 aircraft. The primary design objective
is model-following of the pitch rate q, which is the preferred
system for aircraft approach and landing. Regulation of the aircraft
velocity V (or the Mach-hold autopilot) is also considered, but
as a secondary objective. The problem is challenging because the
system is nonlinear, and also non-affine in the input. A sliding
mode controller is designed for the pitch rate, that exploits the
modal decomposition of the linearized dynamics into its short-period
and phugoid approximations. The inherent robustness of the SMC
design provides a convenient way to design controllers without gain
scheduling, with a steady-state response that is comparable to that
of a conventional polynomial based gain-scheduled approach with
integral control, but with improved transient performance. Integral
action is introduced in the sliding mode design using the recently
developed technique of “conditional integrators", and it is shown that
robust regulation is achieved with asymptotically constant exogenous
signals, without degrading the transient response. Through extensive
simulation on the nonlinear multiple-input multiple-output (MIMO)
longitudinal model of the F-16 aircraft, it is shown that the conditional
integrator design outperforms the one based on the conventional linear
control, without requiring any scheduling.
Abstract: The main purpose of this study is to analyze the
feelings of tourists for the service quality of the bikeway. In addition,
this study also analyzed the causal relationship between service
quality and satisfaction to visitor-s lane loyalty. In this study, the Ya
Tam San bikeway visitor-s subjects, using the designated convenience
sampling carried out the survey, a total of 651 questionnaires were
validly. Valid questionnaires after statistical analysis, the following
findings: 1. Visitor-s lane highest quality of service project: the routes
through the region weather pleasant. Lane "with health and sports," the
highest satisfaction various factors of service quality and satisfaction,
loyal between correlations exist. 4. Guided tours of bikeways, the
quality of the environment, and modeling imagery can effectively
predict visitor satisfaction. 5. Quality of bikeway, public facilities,
guided tours, and modeling imagery can effectively predict visitor
loyalty. According to the above results, the study not only makes
recommendations to the government units and the bicycle industry,
also asked the research direction for future researchers.
Abstract: Missing data is a persistent problem in almost all
areas of empirical research. The missing data must be treated very
carefully, as data plays a fundamental role in every analysis.
Improper treatment can distort the analysis or generate biased results.
In this paper, we compare and contrast various imputation techniques
on missing data sets and make an empirical evaluation of these
methods so as to construct quality software models. Our empirical
study is based on NASA-s two public dataset. KC4 and KC1. The
actual data sets of 125 cases and 2107 cases respectively, without
any missing values were considered. The data set is used to create
Missing at Random (MAR) data Listwise Deletion(LD), Mean
Substitution(MS), Interpolation, Regression with an error term and
Expectation-Maximization (EM) approaches were used to compare
the effects of the various techniques.
Abstract: Water quality is a subject of ongoing concern.
Deterioration of water quality has initiated serious management
efforts in many countries. This study endeavors to automatically
classify water quality. The water quality classes are evaluated using 6
factor indices. These factors are pH value (pH), Dissolved Oxygen
(DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen
(NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (TColiform).
The methodology involves applying data mining
techniques using multilayer perceptron (MLP) neural network
models. The data consisted of 11 sites of canals in Dusit district in
Bangkok, Thailand. The data is obtained from the Department of
Drainage and Sewerage Bangkok Metropolitan Administration
during 2007-2011. The results of multilayer perceptron neural
network exhibit a high accuracy multilayer perception rate at 96.52%
in classifying the water quality of Dusit district canal in Bangkok
Subsequently, this encouraging result could be applied with plan and
management source of water quality.
Abstract: The paper presents a modelling methodology for
small scale multi-source renewable energy systems. Using historical
site-specific weather data, the relationships of cost, availability and
energy form are visualised as a function of the sizing of photovoltaic
arrays, wind turbines, and battery capacity. The specific dependency
of each site on its own particular weather patterns show that unique
solutions exist for each site. It is shown that in certain cases the
capital component cost can be halved if the desired theoretical
demand availability is reduced from 100% to 99%.
Abstract: A new analytical model is developed which provides
close-formed solutions for both transient indoor and envelope
temperature changes in buildings. Time-dependent boundary
temperature is presented as Fourier series which can approximate real
weather conditions. The final close-formed solutions are simple,
concise, and comprehensive. The model was compared with
numerical results and good accuracy was obtained. The model can
be used as design and control guidelines in engineering applications
for analysing mechanical heat transfer properties for buildings.
Abstract: Present wireless communication demands compact and intelligent devices with multitasking capabilities at affordable cost. The focus in the presented paper is on a dual band antenna for wireless communication with the capability of operating at two frequency bands with same structure. Two resonance frequencies are observed with the second operation band at 4.2GHz approximately three times the first resonance frequency at 1.5GHz. Structure is simple loop of microstrip line with characteristic impedance 50 ohms. The proposed antenna is designed using defective ground structure (DGS) and shows the nearly one third reductions in size as compared to without DGS. This antenna was simulated on electromagnetic (EM) simulation software and fabricated using microwave integrated circuit technique on RT-Duroid dielectric substrate (εr= 2.22) of thickness (H=15 mils). The designed antenna was tested on automatic network analyzer and shows the good agreement with simulated results. The proposed structure is modeled into an equivalent electrical circuit and simulated on circuit simulator. Subsequently, theoretical analysis was carried out and simulated. The simulated, measured, equivalent circuit response, and theoretical results shows good resemblance. The bands of operation draw many potential applications in today’s wireless communication.
Abstract: In biological and biomedical research motif finding tools are important in locating regulatory elements in DNA sequences. There are many such motif finding tools available, which often yield position weight matrices and significance indicators. These indicators, p-values and E-values, describe the likelihood that a motif alignment is generated by the background process, and the expected number of occurrences of the motif in the data set, respectively. The various tools often estimate these indicators differently, making them not directly comparable. One approach for comparing motifs from different tools, is computing the E-value as the product of the p-value and the number of possible alignments in the data set. In this paper we explore the combinatorics of the motif alignment models OOPS, ZOOPS, and ANR, and propose a generic algorithm for computing the number of possible combinations accurately. We also show that using the wrong alignment model can give E-values that significantly diverge from their true values.