Abstract: With the development of ubiquitous computing,
current user interaction approaches with keyboard, mouse and pen
are not sufficient. Due to the limitation of these devices the useable
command set is also limited. Direct use of hands as an input device is
an attractive method for providing natural Human Computer
Interaction which has evolved from text-based interfaces through 2D
graphical-based interfaces, multimedia-supported interfaces, to fully
fledged multi-participant Virtual Environment (VE) systems.
Imagine the human-computer interaction of the future: A 3Dapplication
where you can move and rotate objects simply by moving
and rotating your hand - all without touching any input device. In this
paper a review of vision based hand gesture recognition is presented.
The existing approaches are categorized into 3D model based
approaches and appearance based approaches, highlighting their
advantages and shortcomings and identifying the open issues.
Abstract: Maximal Ratio Combining (MRC) is considered the most complex combining technique as it requires channel coefficients estimation. It results in the lowest bit error rate (BER) compared to all other combining techniques. However the BER starts to deteriorate as errors are introduced in the channel coefficients estimation. A novel combining technique, termed Generalized Maximal Ratio Combining (GMRC) with a polynomial kernel, yields an identical BER as MRC with perfect channel estimation and a lower BER in the presence of channel estimation errors. We show that GMRC outperforms the optimal MRC scheme in general and we hereinafter introduce it to the scientific community as a new “supraoptimal" algorithm. Since diversity combining is especially effective in small femto- and pico-cells, internet-associated wireless peripheral systems are to benefit most from GMRC. As a result, many spinoff applications can be made to IP-based 4th generation networks.
Abstract: The work presented in this paper focus on Knowledge Management services enabling CSCW (Computer Supported Cooperative Work) applications to provide an appropriate adaptation to the user and the situation in which the user is working. In this paper, we explain how a knowledge management system can be designed to support users in different situations exploiting contextual data, users' preferences, and profiles of involved artifacts (e.g., documents, multimedia files, mockups...). The presented work roots in the experience we had in the MILK project and early steps made in the MAIS project.
Abstract: this paper aims to provide an approach to predict the
performance of the product produced after multi-stages of
manufacturing processes, as well as the assembly. Such approach
aims to control and subsequently identify the relationship between
the process inputs and outputs so that a process engineer can more
accurately predict how the process output shall perform based on the
system inputs. The approach is guided by a six-sigma methodology to
obtain improved performance.
In this paper a case study of the manufacture of a hermetic
reciprocating compressor is presented. The application of artificial
neural networks (ANNs) technique is introduced to improve
performance prediction within this manufacturing environment. The
results demonstrate that the approach predicts accurately and
effectively.
Abstract: Today, Genetic Algorithm has been used to solve
wide range of optimization problems. Some researches conduct on
applying Genetic Algorithm to text classification, summarization
and information retrieval system in text mining process. This
researches show a better performance due to the nature of Genetic
Algorithm. In this paper a new algorithm for using Genetic
Algorithm in concept weighting and topic identification, based on
concept standard deviation will be explored.
Abstract: Texture information plays increasingly an important
role in remotely sensed imagery classification and many pattern
recognition applications. However, the selection of relevant textural
features to improve this classification accuracy is not a straightforward
task. This work investigates the effectiveness of two Mutual
Information Feature Selector (MIFS) algorithms to select salient
textural features that contain highly discriminatory information for
multispectral imagery classification. The input candidate features are
extracted from a SPOT High Resolution Visible(HRV) image using
Wavelet Transform (WT) at levels (l = 1,2).
The experimental results show that the selected textural features
according to MIFS algorithms make the largest contribution to
improve the classification accuracy than classical approaches such
as Principal Components Analysis (PCA) and Linear Discriminant
Analysis (LDA).
Abstract: The Emergency Department of a medical center in
Taiwan cooperated to conduct the research. A predictive model of
triage system is contracted from the contract procedure, selection of
parameters to sample screening. 2,000 pieces of data needed for the
patients is chosen randomly by the computer. After three
categorizations of data mining (Multi-group Discriminant Analysis,
Multinomial Logistic Regression, Back-propagation Neural
Networks), it is found that Back-propagation Neural Networks can
best distinguish the patients- extent of emergency, and the accuracy
rate can reach to as high as 95.1%. The Back-propagation Neural
Networks that has the highest accuracy rate is simulated into the triage
acuity expert system in this research. Data mining applied to the
predictive model of the triage acuity expert system can be updated
regularly for both the improvement of the system and for education
training, and will not be affected by subjective factors.
Abstract: In this study, effects of EGR on CO and HC emissions
of a dual fuel HCCI-DI engine are investigated. Tests were
conducted on a single-cylinder variable compression ratio (VCR)
diesel engine with compression ratio of 17.5. Premixed gasoline is
provided by a carburetor connected to intake manifold and equipped
with a screw to adjust premixed air-fuel ratio, and diesel fuel is
injected directly into the cylinder through an injector at pressure of
250 bars. A heater placed at inlet manifold is used to control the
intake charge temperature. Optimal intake charge temperature was
110-115ºC due to better formation of a homogeneous mixture
causing HCCI combustion. Timing of diesel fuel injection has a great
effect on stratification of in-cylinder charge in HCCI combustion.
Experiments indicated 35 BTDC as the optimum injection timing.
Coolant temperature was maintained 50ºC during the tests. Results
show that increasing engine speed at a constant EGR rate leads to
increase in CO and UHC emissions due to the incomplete
combustion caused by shorter combustion duration and less
homogeneous mixture. Results also show that increasing EGR
reduces the amount of oxygen and leads to incomplete combustion
and therefore increases CO emission due to lower combustion
temperature. HC emission also increases as a result of lower
combustion temperatures.
Abstract: This paper presents the design, fabrication and
evaluation of magneto-rheological damper. Semi-active control
devices have received significant attention in recent years because
they offer the adaptability of active control devices without requiring
the associated large power sources. Magneto-Rheological (MR)
dampers are semi- active control devices that use MR fluids to
produce controllable dampers. They potentially offer highly reliable
operation and can be viewed as fail-safe in that they become passive
dampers if the control hardware malfunction. The advantage of MR
dampers over conventional dampers are that they are simple in
construction, compromise between high frequency isolation and
natural frequency isolation, they offer semi-active control, use very
little power, have very quick response, has few moving parts, have a
relax tolerances and direct interfacing with electronics. Magneto-
Rheological (MR) fluids are Controllable fluids belonging to the
class of active materials that have the unique ability to change
dynamic yield stress when acted upon by an electric or magnetic
field, while maintaining viscosity relatively constant. This property
can be utilized in MR damper where the damping force is changed by
changing the rheological properties of the fluid magnetically. MR
fluids have a dynamic yield stress over Electro-Rheological fluids
(ER) and a broader operational temperature range. The objective of
this papert was to study the application of an MR damper to vibration
control, design the vibration damper using MR fluids, test and
evaluate its performance. In this paper the Rheology and the theory
behind MR fluids and their use on vibration control were studied.
Then a MR vibration damper suitable for vehicle suspension was
designed and fabricated using the MR fluid. The MR damper was
tested using a dynamic test rig and the results were obtained in the
form of force vs velocity and the force vs displacement plots. The
results were encouraging and greatly inspire further research on the
topic.
Abstract: Nowadays, without the awareness of consumer
behavior and correct understanding of it, it is not possible for organizations to take appropriate measures to meet the consumer
needs and demands. The aim of this paper is the identification and
prioritization of the factors affecting the consumer behavior based on
the product value. The population of the study includes all the
consumers of furniture producing firms in East Azarbaijan province,
Iran. The research sample includes 93 people selected by the sampling formula in unlimited population. The data collection
instrument was a questionnaire, the validity of which was confirmed
through face validity and the reliability of which was determined,
using Cronbach's alpha coefficient. The Kolmogorov-Smironov test
was used to test data normality, the t-test for identification of factors
affecting the product value, and Friedman test for prioritizing the
factors. The results show that quality, satisfaction, styling, price, finishing operation, performance, safety, worth, shape, use, and
excellence are placed from 1 to 11 priorities, respectively.
Abstract: Universities have an important role in social education in many aspects. In terms of creating awareness and convincing public about social issues, universities take a leading position for public. The best way to provide public support for social education is to develop public communication campaigns. The aim of this study is to present a public communication model which will be guided in social education practices. The study titled “Importance of public communication campaigns and art activities in Social Education “is based on the following topics: Effects of public communication campaigns on social education, Public relations techniques for education, communication strategies, Steps of public relations campaigns in social education, making persuasive messages for public communication campaigns, developing artistic messages and organizing art activities in social education. In addition to these topics, media planning for social education, forming a team as campaign managers, dialogues with opinion leaders in education and preparing creative communication models for social education will be taken into consideration. This study also aims to criticize social education Case studies in Turkey. At the same time, some communicative methods and principles will be given in the light of communication campaigns within the context of this notice.
Abstract: In metal cutting industries, mathematical/statistical
models are typically used to predict tool replacement time. These
off-line methods usually result in less than optimum replacement
time thereby either wasting resources or causing quality problems.
The few online real-time methods proposed use indirect measurement
techniques and are prone to similar errors. Our idea is based on
identifying the optimal replacement time using an electronic nose to
detect the airborne compounds released when the tool wear reaches
to a chemical substrate doped into tool material during the
fabrication. The study investigates the feasibility of the idea, possible
doping materials and methods along with data stream mining
techniques for detection and monitoring different phases of tool
wear.
Abstract: Due to availability of powerful image processing software
and improvement of human computer knowledge, it becomes
easy to tamper images. Manipulation of digital images in different
fields like court of law and medical imaging create a serious problem
nowadays. Copy-move forgery is one of the most common types
of forgery which copies some part of the image and pastes it to
another part of the same image to cover an important scene. In
this paper, a copy-move forgery detection method proposed based
on Fourier transform to detect forgeries. Firstly, image is divided to
same size blocks and Fourier transform is performed on each block.
Similarity in the Fourier transform between different blocks provides
an indication of the copy-move operation. The experimental results
prove that the proposed method works on reasonable time and works
well for gray scale and colour images. Computational complexity
reduced by using Fourier transform in this method.
Abstract: This paper describes part of a project about Learningby-
Modeling (LbM). Studying complex systems is increasingly
important in teaching and learning many science domains. Many
features of complex systems make it difficult for students to develop
deep understanding. Previous research indicates that involvement
with modeling scientific phenomena and complex systems can play a
powerful role in science learning. Some researchers argue with this
view indicating that models and modeling do not contribute to
understanding complexity concepts, since these increases the
cognitive load on students. This study will investigate the effect of
different modes of involvement in exploring scientific phenomena
using computer simulation tools, on students- mental model from the
perspective of structure, behavior and function. Quantitative and
qualitative methods are used to report about 121 freshmen students
that engaged in participatory simulations about complex phenomena,
showing emergent, self-organized and decentralized patterns. Results
show that LbM plays a major role in students' concept formation
about complexity concepts.
Abstract: The main objective of the paper has been represented
by the identification of the changes that occurred in the competitive
environment and their impact on the strategic marketing management
of companies in B2B market. At Romania-s level there has not yet
been done a similar research that studies change management in
crises on business to business field. In order to answer to the paper-s
objectives, a qualitative marketing research (in-depth structured
interview) was conducted, within the top management of 27
companies in Romanian business to business field. The main results
of the research highlight the necessity of a management of change, as
a result of the crises, as follows: changes in the corporate objectives
(from development objectives to maintaining objectives), changes
market segmentation and in competitive advantages, changes at the
level of market strategies and of the marketing mix.
Abstract: Shadows add great amount of realism to a scene and
many algorithms exists to generate shadows. Recently, Shadow
volumes (SVs) have made great achievements to place a valuable
position in the gaming industries. Looking at this, we concentrate on
simple but valuable initial partial steps for further optimization in SV
generation, i.e.; model simplification and silhouette edge detection
and tracking. Shadow volumes (SVs) usually takes time in generating
boundary silhouettes of the object and if the object is complex then
the generation of edges become much harder and slower in process.
The challenge gets stiffer when real time shadow generation and
rendering is demanded. We investigated a way to use the real time
silhouette edge detection method, which takes the advantage of
spatial and temporal coherence, and exploit the level-of-details
(LOD) technique for reducing silhouette edges of the model to use
the simplified version of the model for shadow generation speeding
up the running time. These steps highly reduce the execution time of
shadow volume generations in real-time and are easily flexible to any
of the recently proposed SV techniques. Our main focus is to exploit
the LOD and silhouette edge detection technique, adopting them to
further enhance the shadow volume generations for real time
rendering.
Abstract: A typical definition of the Computer Aided Diagnosis
(CAD), found in literature, can be: A diagnosis made by a radiologist
using the output of a computerized scheme for automated image
analysis as a diagnostic aid. Often it is possible to find the expression
Computer Aided Detection (CAD or CADe): this definition
emphasizes the intent of CAD to support rather than substitute the
human observer in the analysis of radiographic images. In this article
we will illustrate the application of CAD systems and the aim of
these definitions.
Commercially available CAD systems use computerized
algorithms for identifying suspicious regions of interest. In this paper
are described the general CAD systems as an expert system
constituted of the following components: segmentation / detection,
feature extraction, and classification / decision making.
As example, in this work is shown the realization of a Computer-
Aided Detection system that is able to assist the radiologist in
identifying types of mammary tumor lesions. Furthermore this
prototype of station uses a GRID configuration to work on a large
distributed database of digitized mammographic images.
Abstract: Pressures for urban redevelopment are intensifying in
all large cities. A new logic for urban development is required –
green urbanism – that provides a spatial framework for directing
population and investment inwards to brownfields and greyfields
precincts, rather than outwards to the greenfields. This represents
both a major opportunity and a major challenge for city planners in
pluralist liberal democracies. However, plans for more compact
forms of urban redevelopment are stalling in the face of community
resistance. A new paradigm and spatial planning platform is required
that will support timely multi-level and multi-actor stakeholder
engagement, resulting in the emergence of consensus plans for
precinct-level urban regeneration capable of more rapid
implementation. Using Melbourne, Australia as a case study, this
paper addresses two of the urban intervention challenges – where and
how – via the application of a 21st century planning tool ENVISION
created for this purpose.
Abstract: Conflicts identification among non-functional requirements is often identified intuitively which impairs conflict analysis practices. This paper proposes a new model to identify conflicts among non-functional requirements. The proposed model uses the matrix mechanism to identify the quality based conflicts among non-functional requirements. The potential conflicts are identified through the mapping of low level conflicting quality attributes to low level functionalities using the matrices. The proposed model achieves the identification of conflicts among product and process requirements, identifies false conflicts, decreases the documentation overhead, and maintains transparency of identified conflicts. The attributes are not concomitantly taken into account by current models in practice.
Abstract: The main goal of the study is to analyze all relevant properties of the electro hydraulic systems and based on that to make a proper choice of the neural network control strategy that may be used for the control of the mechatronic system. A combination of electronic and hydraulic systems is widely used since it combines the advantages of both. Hydraulic systems are widely spread because of their properties as accuracy, flexibility, high horsepower-to-weight ratio, fast starting, stopping and reversal with smoothness and precision, and simplicity of operations. On the other hand, the modern control of hydraulic systems is based on control of the circuit fed to the inductive solenoid that controls the position of the hydraulic valve. Since this circuit may be easily handled by PWM (Pulse Width Modulation) signal with a proper frequency, the combination of electrical and hydraulic systems became very fruitful and usable in specific areas as airplane and military industry. The study shows and discusses the experimental results obtained by the control strategy of neural network control using MATLAB and SIMULINK [1]. Finally, the special attention was paid to the possibility of neuro-controller design and its application to control of electro-hydraulic systems and to make comparative with other kinds of control.