Abstract: Efficient retrieval of multimedia objects has gained enormous focus in recent years. A number of techniques have been suggested for retrieval of textual information; however, relatively little has been suggested for efficient retrieval of multimedia objects. In this paper we have proposed a generic architecture for contextaware retrieval of multimedia objects. The proposed framework combines the well-known approaches of text-based retrieval and context-aware retrieval to formulate architecture for accurate retrieval of multimedia data.
Abstract: Today, any organization - regardless of the specific activity - must be prepared to face continuous radical changes, innovation thus becoming a condition of survival in a globalized market. Few managers have a wider vision that includes innovation, to enable better performance of the critical activities, namely the degree of novelty that it must submit an innovation to be considered as such. Companies need not only radical changes in the products or their services, but also to their business strategies. Not all managers have an overall view on the real size of necessary innovation potential. Unfortunately there is still no common understanding (and correct) of the term of innovation among managers. Moreover, not all managers are aware of the need for innovation. In these conditions, increasing the processes adaptability of firms (through innovation) to meet the needs and performance requirements is difficult without a systematic framework. To overcome this disadvantage, the authors propose a framework for designing an innovation management system,, to cover all the important aspects of a business system, to reach the actual performance of an organization.
Abstract: This paper presents an analytical framework for an
effective online personal knowledge management (PKM) of
knowledge workers. The development of this framework is prompted
by our qualitative research on the PKM processes and cognitive
enablers of knowledge workers in eight organisations selected from
three main industries in Malaysia. This multiple-case research
identifies the relationships between the effectiveness of four online
PKM processes: get/retrieve, understand/analyse, share, and connect.
It also establishes the importance of cognitive enablers that mediate
this relationship, namely, method, identify, decide and drive.
Qualitative analysis is presented as the findings, supported by the
preceded quantitative analysis on an exploratory questionnaire
survey.
Abstract: The recent trend has been using hybrid approach rather than using a single intelligent technique to solve the problems. In this paper, we describe and discuss a framework to develop enterprise solutions that are backed by intelligent techniques. The framework not only uses intelligent techniques themselves but it is a complete environment that includes various interfaces and components to develop the intelligent solutions. The framework is completely Web-based and uses XML extensively. It can work like shared plat-form to be accessed by multiple developers, users and decision makers.
Abstract: We propose a low-cost uniform analysis framework
allowing comparison of the strengths and weaknesses of the
bicycling experience within and between cities. A primary
component is an expedient, one-page mobility survey from which
mode share is calculated. The bicycle mode share of many cities
remains unknown, creating a serious barrier for both scientists and
policy makers aiming to understand and increase rates of bicycling.
Because of its low cost and expedience, this framework could be
replicated widely, uniformly filling the data gap. The framework has
been applied to 13 Central European cities with success. Data is
collected on multiple modes with specific questions regarding both
behavior and quality of travel experience. Individual preferences are
also collected, examining the conditions under which respondents
would change behavior to adopt more sustainable modes (bicycling
or public transportation). A broad analysis opportunity results,
intended to inform policy choices.
Abstract: Climate change has profound consequences for the agriculture of south-eastern Australia and its climate-induced water shortage in the Murray-Darling Basin. Post Keynesian Economics (PKE) macro-dynamics, along with Kaleckian investment and growth theory, are used to develop an ecological-economic system dynamics model of this complex nonlinear river basin system. The Murray- Darling Basin Simulation Model (MDB-SM) uses the principles of PKE to incorporate the fundamental uncertainty of economic behaviors of farmers regarding the investments they make and the climate change they face, particularly as regards water ecosystem services. MDB-SM provides a framework for macroeconomic policies, especially for long-term fiscal policy and for policy directed at the sustainability of agricultural water, as measured by socio-economic well-being considerations, which include sustainable consumption and investment in the river basin. The model can also reproduce other ecological and economic aspects and, for certain parameters and initial values, exhibit endogenous business cycles and ecological sustainability with realistic characteristics. Most importantly, MDBSM provides a platform for the analysis of alternative economic policy scenarios. These results reveal the importance of understanding water ecosystem adaptation under climate change by integrating a PKE macroeconomic analytical framework with the system dynamics modelling approach. Once parameterised and supplied with historical initial values, MDB-SM should prove to be a practical tool to provide alternative long-term policy simulations of agricultural water and socio-economic well-being.
Abstract: Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.
Abstract: Policy management in organizations became rising issue in the last decade. It’s because of today’s regulatory requirements in the organizations. To manage policies in large organizations is an imperative work. However, major challenges facing organizations in the last decade is managing all the policies in the organization and making them an active documents rather than simple (inactive) documents stored in computer hard drive or on a shelf. Because of this challenge, organizations need policy management program. This policy management program can be either manual or automated. This paper presents suggestions towards managing policies in organizations. As well as possible policy management solution or program to be utilized, manual or automated. The research first examines the models and frameworks used for managing policies from various perspectives in the literature of the research area/domain. At the end of this paper, a policy management framework is proposed for managing enterprise policies effectively and in a simplified manner.
Abstract: The rapid development of the BlackBerry games industry and its development goals were not just for entertainment, but also used for educational of students interactively. Unfortunately the development of adaptive educational games on BlackBerry in Indonesian language that interesting and entertaining for learning process is very limited. This paper shows the research of development of novel adaptive educational games for students who can adjust the difficulty level of games based on the ability of the user, so that it can motivate students to continue to play these games. We propose a method where these games can adjust the level of difficulty, based on the assessment of the results of previous problems using neural networks with three inputs in the form of percentage correct, the speed of answer and interest mode of games (animation / lessons) and 1 output. The experimental results are presented and show the adaptive games are running well on mobile devices based on BlackBerry platform
Abstract: Emotions are related with learning processes and
physiological signals can be used to detect them for the
personalization of learning resources and to control the pace of
instruction. A model of relevant emotions has been developed, where
specific combinations of emotions and cognition processes are
connected and integrated with the concept of 'flow', in order to
improve learning. The cardiac pulse is a reliable signal that carries
useful information about the subject-s emotional condition; it is
detected using a classroom chair adapted with non invasive EMFi
sensor and an acquisition system that generates a ballistocardiogram
(BCG), the signal is processed by an algorithm to obtain
characteristics that match a specific emotional condition. The
complete chair system is presented in this work, along with a
framework for the personalization of learning resources.
Abstract: As a result of the daily workflow in the design
development departments of companies, databases containing huge
numbers of 3D geometric models are generated. According to the
given problem engineers create CAD drawings based on their design
ideas and evaluate the performance of the resulting design, e.g. by
computational simulations. Usually, new geometries are built either
by utilizing and modifying sets of existing components or by adding
single newly designed parts to a more complex design.
The present paper addresses the two facets of acquiring
components from large design databases automatically and providing
a reasonable overview of the parts to the engineer. A unified
framework based on the topographic non-negative matrix
factorization (TNMF) is proposed which solves both aspects
simultaneously. First, on a given database meaningful components
are extracted into a parts-based representation in an unsupervised
manner. Second, the extracted components are organized and
visualized on square-lattice 2D maps. It is shown on the example of
turbine-like geometries that these maps efficiently provide a wellstructured
overview on the database content and, at the same time,
define a measure for spatial similarity allowing an easy access and
reuse of components in the process of design development.
Abstract: Cognitive Infocommunications (CogInfoCom) is a new
research direction which has emerged as the synergic convergence
of infocommunications and the cognitive sciences. In this paper,
we provide the definition of CogInfoCom, and propose an architectural
framework for the interaction-oriented design of CogInfoCom
systems. We provide the outlines of an application example of
the interaction-oriented architecture, and briefly discuss its main
characteristics.
Abstract: In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.
Abstract: Purpose:This paper aims to gain insights to the influential factors of ERM adoptions by public listed firms in Malaysia. Findings:The two factors of financial leverage and auditor type were found to be significant influential factors for ERM adoption. In other words the findings indicated that firms with higher financial leverage and with a Big Four auditor are more likely to have a form of ERM framework in place. Originality/Value:Since there are relatively few studies conducted in this area and specially in developing economies like Malaysia, this study will broaden the scope of literature by providing novel empirical evidence.
Abstract: We study the problem of decision making with Dempster-Shafer belief structure. We analyze the previous work developed by Yager about using the ordered weighted averaging (OWA) operator in the aggregation of the Dempster-Shafer decision process. We discuss the possibility of aggregating with an ascending order in the OWA operator for the cases where the smallest value is the best result. We suggest the introduction of the ordered weighted geometric (OWG) operator in the Dempster-Shafer framework. In this case, we also discuss the possibility of aggregating with an ascending order and we find that it is completely necessary as the OWG operator cannot aggregate negative numbers. Finally, we give an illustrative example where we can see the different results obtained by using the OWA, the Ascending OWA (AOWA), the OWG and the Ascending OWG (AOWG) operator.
Abstract: The purposes of this research were 1) to study
consumer-based equity of luxury brands, 2) to study consumers-
purchase intention for luxury brands, 3) to study direct factors
affecting purchase intention towards luxury brands, and 4) to study
indirect factors affecting purchase intention towards luxury brands
through brand consciousness and brand equity to analyze information
by descriptive statistic and hierarchical stepwise regression analysis.
The findings revealed that the eight variables of the framework which
were: need for uniqueness, normative susceptibility, status
consumption, brand consciousness, brand awareness, perceived
quality, brand association, and brand loyalty affected the purchase
intention of the luxury brands (at the significance of 0.05). Brand
Loyalty had the strongest direct effect while status consumption had
the strongest indirect effect affecting the purchase intention towards
luxury brands. Brand consciousness and brand equity had the
mediators through the purchase intention of the luxury brands (at the
significance of 0.05).
Abstract: This paper presents a novel method for prediction of
the mechanical behavior of proximal femur using the general
framework of the quantitative computed tomography (QCT)-based
finite element Analysis (FEA). A systematic imaging and modeling
procedure was developed for reliable correspondence between the
QCT-based FEA and the in-vitro mechanical testing. A speciallydesigned
holding frame was used to define and maintain a unique
geometrical reference system during the analysis and testing. The
QCT images were directly converted into voxel-based 3D finite
element models for linear and nonlinear analyses. The equivalent
plastic strain and the strain energy density measures were used to
identify the critical elements and predict the failure patterns. The
samples were destructively tested using a specially-designed gripping
fixture (with five degrees of freedom) mounted within a universal
mechanical testing machine. Very good agreements were found
between the experimental and the predicted failure patterns and the
associated load levels.
Abstract: This paper proposes a dual tree complex wavelet transform (DT-CWT) based directional interpolation scheme for noisy images. The problems of denoising and interpolation are modelled as to estimate the noiseless and missing samples under the same framework of optimal estimation. Initially, DT-CWT is used to decompose an input low-resolution noisy image into low and high frequency subbands. The high-frequency subband images are interpolated by linear minimum mean square estimation (LMMSE) based interpolation, which preserves the edges of the interpolated images. For each noisy LR image sample, we compute multiple estimates of it along different directions and then fuse those directional estimates for a more accurate denoised LR image. The estimation parameters calculated in the denoising processing can be readily used to interpolate the missing samples. The inverse DT-CWT is applied on the denoised input and interpolated high frequency subband images to obtain the high resolution image. Compared with the conventional schemes that perform denoising and interpolation in tandem, the proposed DT-CWT based noisy image interpolation method can reduce many noise-caused interpolation artifacts and preserve well the image edge structures. The visual and quantitative results show that the proposed technique outperforms many of the existing denoising and interpolation methods.
Abstract: With the tremendous growth of World Wide Web
(WWW) data, there is an emerging need for effective information
retrieval at the document level. Several query languages such as
XML-QL, XPath, XQL, Quilt and XQuery are proposed in recent
years to provide faster way of querying XML data, but they still lack of
generality and efficiency. Our approach towards evolving a framework
for querying semistructured documents is based on formal query
algebra. Two elements are introduced in the proposed framework:
first, a generic and flexible data model for logical representation of
semistructured data and second, a set of operators for the manipulation
of objects defined in the data model. In additional to accommodating
several peculiarities of semistructured data, our model offers novel
features such as bidirectional paths for navigational querying and
partitions for data transformation that are not available in other
proposals.
Abstract: A multimedia presentation system refers to the integration of a multimedia database with a presentation manager which has the functionality of content selection, organization and playout of multimedia presentations. It requires high performance of involved system components. Starting from multimedia information capture until the presentation delivery, high performance tools are required for accessing, manipulating, storing and retrieving these segments, for transferring and delivering them in a presentation terminal according to a playout order. The organization of presentations is a complex task in that the display order of presentation contents (in time and space) must be specified. A multimedia presentation contains audio, video, images and text media types. The critical decisions for presentation construction include what the contents are, how the contents are organized, and once the decision is made on the organization of the contents of the presentation, it must be conveyed to the end user in the correct organizational order and in a timely fashion. This paper introduces a framework for specification of multimedia presentations and describes the design of sample presentations using this framework from a multimedia database.