Abstract: A novel concept to balance and tradeoff between
make-to-stock and make-to-order has been hybrid MTS/MTO production context. One of the most important decisions involved in
the hybrid MTS/MTO environment is determining whether a product
is manufactured to stock, to order, or hybrid MTS/MTO strategy. In this paper, a model based on analytic network process is developed to tackle the addressed decision. Since the regarded decision deals with
the uncertainty and ambiguity of data as well as experts- and
managers- linguistic judgments, the proposed model is equipped with
fuzzy sets theory. An important attribute of the model is its generality due to diverse decision factors which are elicited from the
literature and developed by the authors. Finally, the model is validated by applying to a real case study to reveal how the proposed
model can actually be implemented.
Abstract: Location-based services (LBS) exploit the known
location of a user to provide services dependent on their geographic
context and personalized needs [1].
The development and arrival of broadband mobile data networks
supported with mobile terminals equipped with new location
technologies like GPS have finally created opportunities for
implementation of LBS applications. But, from the other side,
collecting location information data in general raises privacy
concerns.
This paper presents results from two surveys of LBS acceptance in
Croatia. The first survey was administered on 181 students, and the
second extended survey involved pattern of 180 Croatian citizens.
We developed questionnaire which consists of descriptions of 15
different applications with scale which measures perceptions and
attitudes of users towards these applications.
We report the results to identify potential commercial applications
for LBS in B2C segment. Our findings suggest that some types of
applications like emergency&safety services and navigation have
significantly higher rate of acceptance than other types.
Abstract: Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.
Abstract: We provide a supervised speech-independent voice recognition technique in this paper. In the feature extraction stage we propose a mel-cepstral based approach. Our feature vector classification method uses a special nonlinear metric, derived from the Hausdorff distance for sets, and a minimum mean distance classifier.
Abstract: Food mileage is one of the important issues concerning environmental sustainability. In this research we have utilized a prototype platform with iterative user-centered testing. With these findings we successfully demonstrate the use of the context of persuasive methods to influence users- attitudes towards the sustainable concept.
Abstract: The velocity of a moving point in a general path is the vector quantity, which has both magnitude and direction. The magnitude or the direction of the velocity vector can change over time as a result of acceleration that the time rate of velocity changes. Acceleration analysis is important because inertial forces and inertial torques are proportional to rectilinear and angular accelerations accordingly. The loads must be determined in advance to ensure that a machine is adequately designed to handle these dynamic loads. For planar motion, the vector direction of acceleration is commonly separated into two elements: tangential and centripetal or radial components of a point on a rotating body. All textbooks in physics, kinematics and dynamics of machinery consider the magnitude of a radial acceleration at condition when a point rotates with a constant angular velocity and it means without acceleration. The magnitude of the tangential acceleration considered on a basis of acceleration for a rotating point. Such condition of presentation of magnitudes for two components of acceleration logically and mathematically is not correct and may cause further confusion in calculation. This paper presents new analytical expressions of the radial and absolute accelerations of a rotating point with acceleration and covers the gap in theoretical study of acceleration analysis.
Abstract: CIM is the standard formalism for modeling management
information developed by the Distributed Management Task
Force (DMTF) in the context of its WBEM proposal, designed to
provide a conceptual view of the managed environment. In this
paper, we propose the inclusion of formal knowledge representation
techniques, based on Description Logics (DLs) and the Web Ontology
Language (OWL), in CIM-based conceptual modeling, and then we
examine the benefits of such a decision. The proposal is specified
as a CIM metamodel level mapping to a highly expressive subset
of DLs capable of capturing all the semantics of the models. The
paper shows how the proposed mapping provides CIM diagrams with
precise semantics and can be used for automatic reasoning about the
management information models, as a design aid, by means of newgeneration
CASE tools, thanks to the use of state-of-the-art automatic
reasoning systems that support the proposed logic and use algorithms
that are sound and complete with respect to the semantics. Such a
CASE tool framework has been developed by the authors and its
architecture is also introduced. The proposed formalization is not
only useful at design time, but also at run time through the use of
rational autonomous agents, in response to a need recently recognized
by the DMTF.
Abstract: Cyber attacks pose a serious threat to all states. Therefore, states constantly seek for various methods to encounter those threats. In addition, recent changes in the nature of cyber attacks and their more complicated methods have created a new concept: active cyber defense (ACD). This article tries to answer firstly why ACD is important to NATO and find out the viewpoint of NATO towards ACD. Secondly, infrastructure protection is essential to cyber defense. Critical infrastructure protection with ACD means is even more important. It is assumed that by implementing active cyber defense, NATO may not only be able to repel the attacks but also be deterrent. Hence, the use of ACD has a direct positive effect in all international organizations’ future including NATO.
Abstract: Qualification of doctoral students- and the candidates for a scientific degree is evaluated by the ability to solve scientific ideas in an innovative way, consequently, being a potential of research and science they play a significant role in the sustainability context of the society. The article deals with the analysis of the results of the pilot project, the aim of which has been to study the structure of doctoral students- research competences in the sustainability context. With the existance of variety of theories on research competence development, their analysis focuses on the attained aim approach. Three competence groups have been identified in this study: informative, communicative and instrumental. Within the study the doctoral students and candidates for a scientific degree (N=64) made their self-assessment of research competences. The study results depict their present research competence development level and its dynamics according to the aim to attain.
Abstract: In the paper a method of modeling text for Polish is
discussed. The method is aimed at transforming continuous input text
into a text consisting of sentences in so called canonical form, whose
characteristic is, among others, a complete structure as well as no
anaphora or ellipses. The transformation is lossless as to the content
of text being transformed. The modeling method has been worked
out for the needs of the Thetos system, which translates Polish
written texts into the Polish sign language. We believe that the
method can be also used in various applications that deal with the
natural language, e.g. in a text summary generator for Polish.
Abstract: For the communication between human and computer
in an interactive computing environment, the gesture recognition is
studied vigorously. Therefore, a lot of studies have proposed efficient
methods about the recognition algorithm using 2D camera captured
images. However, there is a limitation to these methods, such as the
extracted features cannot fully represent the object in real world.
Although many studies used 3D features instead of 2D features for
more accurate gesture recognition, the problem, such as the processing
time to generate 3D objects, is still unsolved in related researches.
Therefore we propose a method to extract the 3D features combined
with the 3D object reconstruction. This method uses the modified
GPU-based visual hull generation algorithm which disables unnecessary
processes, such as the texture calculation to generate three kinds
of 3D projection maps as the 3D feature: a nearest boundary, a farthest
boundary, and a thickness of the object projected on the base-plane. In
the section of experimental results, we present results of proposed
method on eight human postures: T shape, both hands up, right hand
up, left hand up, hands front, stand, sit and bend, and compare the
computational time of the proposed method with that of the previous
methods.
Abstract: Nowadays there are lots of applications of power and
free conveyors in logistics. They are the most frequently used
conveyor systems worldwide. Overhead conveyor technologies like
power and free systems are used in the most intra-logistics
applications in trade and industry. The automotive, food, beverage
and textile industry as well as aeronautic catering or engineering are
among the applications. Power and free systems employ different
manufacturing intervals in manufacturing as well as in production as
temporary store and buffer. Depending on the application area, power
and free conveyors are equipped with target controls enabling
complex distribution-and sorting tasks. This article introduces a new
power and free conveyor design in intra-logistics and explains its
components. According to the explanation of the components, a
model is created by means of their technical characteristics. Through
the CAD software, the model is visualized. After that, the static
analysis is evaluated. This analysis helps the calculation of the
mandatory state of structures under force action. This powerful model
helps companies achieve lower development costs as well as quicker
market maturity.
Abstract: Atmospheric plasma is emerging as a promising
technology for many industrial sectors, because of its ecological and
economic advantages respect to the traditional production processes.
For textile industry, atmospheric plasma is becoming a valid
alternative to the conventional wet processes, but the plasma
machines realized so far do not allow the treatment of fibrous
mechanically weak material.
Novel atmospheric plasma machine for industrial applications,
developed by VenetoNanotech SCpA in collaboration with Italian
producer of corona equipment ME.RO SpA is presented. The main
feature of this pre-industrial scale machine is the possibility of the inline
plasma treatment of delicate fibrous substrates such as fibre
sleeves, for example wool tops, cotton fibres, polymeric tows,
mineral fibers and so on, avoiding burnings and disruption of the
faint materials.
Abstract: In the given article the creative arts is being
investigated in the modern era and from the aspect of the artistic
interrelationship, having created by the character of his personality
and as the viewer. A study in the identity formation terms, the
definition of its being unique, unity and similarity as a global issue of
the XXI century has been conducted by the analyzing the definitions
which characterize the human nature in the arts. Spiritual universality
and human existence have been considered in the art system as a
human who is a creator, as the man hero and as the character who is
the recipient as well as the analyses which have been conducted
along with the worldwide cultural and historical processes.
Abstract: This paper concerns a formal model to help the
simulation of agent societies where institutional roles and
institutional links can be specified operationally. That is, this paper
concerns institutional roles that can be specified in terms of a minimal behavioral capability that an agent should have in order to
enact that role and, thus, to perform the set of institutional functions that role is responsible for. Correspondingly, the paper concerns
institutional links that can be specified in terms of a minimal
interactional capability that two agents should have in order to, while
enacting the two institutional roles that are linked by that institutional
link, perform for each other the institutional functions supported by
that institutional link. The paper proposes a cognitive architecture
approach to institutional roles and institutional links, that is, an approach in which a institutional role is seen as an abstract cognitive
architecture that should be implemented by any concrete agent (or set of concrete agents) that enacts the institutional role, and in which
institutional links are seen as interactions between the two abstract
cognitive agents that model the two linked institutional roles. We
introduce a cognitive architecture for such purpose, called the
Institutional BCC (IBCC) model, which lifts Yoav Shoham-s BCC
(Beliefs-Capabilities-Commitments) agent architecture to social
contexts. We show how the resulting model can be taken as a means
for a cognitive architecture account of institutional roles and
institutional links of agent societies. Finally, we present an example
of a generic scheme for certain fragments of the social organization
of agent societies, where institutional roles and institutional links are
given in terms of the model.
Abstract: Optical Character Recognition (OCR) is a very old and of great interest in pattern recognition field. In this paper we introduce a very powerful approach to recognize Persian text. We have used morphological operators, especially Hit/Miss operator to descript each sub-word and by using a template matching approach we have tried to classify generated description. We used just one font in two different sizes to verify our approach. We achieved a very good rate, up to 99.9%.
Abstract: Currently WWW is the first solution for scholars in
finding information. But, analyzing and interpreting this volume of
information will lead to researchers overload in pursuing their
research.
Trend detection in scientific publication retrieval systems helps
scholars to find relevant, new and popular special areas by
visualizing the trend of input topic.
However, there are few researches on trend detection in scientific
corpora while their proposed models do not appear to be suitable.
Previous works lack of an appropriate representation scheme for
research topics.
This paper describes a method that combines Semantic Web and
ontology to support advance search functions such as trend detection
in the context of scholarly Semantic Web system (SSWeb).
Abstract: Requirements are critical to system validation as they guide all subsequent stages of systems development. Inadequately specified requirements generate systems that require major revisions or cause system failure entirely. Use Cases have become the main vehicle for requirements capture in many current Object Oriented (OO) development methodologies, and a means for developers to communicate with different stakeholders. In this paper we present the results of a laboratory experiment that explored whether different types of use case format are equally effective in facilitating high knowledge user-s understanding. Results showed that the provision of diagrams along with the textual use case descriptions significantly improved user comprehension of system requirements in both familiar and unfamiliar application domains. However, when comparing groups that received models of textual description accompanied with diagrams of different level of details (simple and detailed) we found no significant difference in performance.
Abstract: Echocardiography imaging is one of the most common diagnostic tests that are widely used for assessing the abnormalities of the regional heart ventricle function. The main goal of the image enhancement task in 2D-echocardiography (2DE) is to solve two major anatomical structure problems; speckle noise and low quality. Therefore, speckle noise reduction is one of the important steps that used as a pre-processing to reduce the distortion effects in 2DE image segmentation. In this paper, we present the common filters that based on some form of low-pass spatial smoothing filters such as Mean, Gaussian, and Median. The Laplacian filter was used as a high-pass sharpening filter. A comparative analysis was presented to test the effectiveness of these filters after being applied to original 2DE images of 4-chamber and 2-chamber views. Three statistical quantity measures: root mean square error (RMSE), peak signal-to-ratio (PSNR) and signal-tonoise ratio (SNR) are used to evaluate the filter performance quantitatively on the output enhanced image.
Abstract: In this paper, we propose a modified version of the
Constant Modulus Algorithm (CMA) tailored for blind Decision
Feedback Equalizer (DFE) of first order Markovian time varying
channels. The proposed NonStationary CMA (NSCMA) is designed
so that it explicitly takes into account the Markovian structure of
the channel nonstationarity. Hence, unlike the classical CMA, the
NSCMA is not blind with respect to the channel time variations.
This greatly helps the equalizer in the case of realistic channels, and
avoids frequent transmissions of training sequences.
This paper develops a theoretical analysis of the steady state
performance of the CMA and the NSCMA for DFEs within a time
varying context. Therefore, approximate expressions of the mean
square errors are derived. We prove that in the steady state, the
NSCMA exhibits better performance than the classical CMA. These
new results are confirmed by simulation.
Through an experimental study, we demonstrate that the Bit Error
Rate (BER) is reduced by the NSCMA-DFE, and the improvement
of the BER achieved by the NSCMA-DFE is as significant as the
channel time variations are severe.