Abstract: Technological innovation capability (TIC) is
defined as a comprehensive set of characteristics of a firm that
facilities and supports its technological innovation strategies.
An audit to evaluate the TICs of a firm may trigger
improvement in its future practices. Such an audit can be used
by the firm for self assessment or third-party independent
assessment to identify problems of its capability status. This
paper attempts to develop such an auditing framework that
can help to determine the subtle links between innovation
capabilities and business performance; and to enable the
auditor to determine whether good practice is in place. The
seven TICs in this study include learning, R&D, resources
allocation, manufacturing, marketing, organization and
strategic planning capabilities. Empirical data was acquired
through a survey study of 200 manufacturing firms in the
Hong Kong/Pearl River Delta (HK/PRD) region. Structural
equation modelling was employed to examine the
relationships among TICs and various performance indicators:
sales performance, innovation performance, product
performance, and sales growth. The results revealed that
different TICs have different impacts on different
performance measures. Organization capability was found to
have the most influential impact. Hong Kong manufacturers
are now facing the challenge of high-mix-low-volume
customer orders. In order to cope with this change, good
capability in organizing different activities among various
departments is critical to the success of a company.
Abstract: The paper presents new results of a recent industry
supported research and development study in which an efficient
framework for evaluating practical and meaningful power system
reliability and quality indices was applied. The system-wide
integrated performance indices are capable of addressing and
revealing areas of deficiencies and bottlenecks as well as
redundancies in the composite generation-transmission-demand
structure of large-scale power grids. The technique utilizes a linear
programming formulation, which simulates practical operating
actions and offers a general and comprehensive framework to assess
the harmony and compatibility of generation, transmission and
demand in a power system. Practical applications to a reduced
system model as well as a portion of the Saudi power grid are also
presented in the paper for demonstration purposes.
Abstract: Multi-Agent Systems (MAS) emerged in the pursuit to improve our standard of living, and hence can manifest complex human behaviors such as communication, decision making, negotiation and self-organization. The Social Network Services (SNSs) have attracted millions of users, many of whom have integrated these sites into their daily practices. The domains of MAS and SNS have lots of similarities such as architecture, features and functions. Exploring social network users- behavior through multiagent model is therefore our research focus, in order to generate more accurate and meaningful information to SNS users. An application of MAS is the e-Auction and e-Rental services of the Universiti Cyber AgenT(UniCAT), a Social Network for students in Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia, built around the Belief- Desire-Intention (BDI) model. However, in spite of the various advantages of the BDI model, it has also been discovered to have some shortcomings. This paper therefore proposes a multi-agent framework utilizing a modified BDI model- Belief-Desire-Intention in Dynamic and Uncertain Situations (BDIDUS), using UniCAT system as a case study.
Abstract: This research elaborates decision models for product
innovation in the early phases, focusing on one of the most widely
implemented method in marketing research: conjoint analysis and the
related conjoint-based models with special focus on heuristics
programming techniques for the development of optimal product
innovation. The concept, potential, requirements and limitations of
conjoint analysis and its conjoint-based heuristics successors are
analysed and the development of conceptual framework of Genetic
Algorithm (GA) as one of the most widely implemented heuristic
methods for developing product innovations are discussed.
Abstract: Grid computing provides a virtual framework for
controlled sharing of resources across institutional boundaries.
Recently, trust has been recognised as an important factor for
selection of optimal resources in a grid. We introduce a new method
that provides a quantitative trust value, based on the past interactions
and present environment characteristics. This quantitative trust value
is used to select a suitable resource for a job and eliminates run time
failures arising from incompatible user-resource pairs. The proposed
work will act as a tool to calculate the trust values of the various
components of the grid and there by improves the success rate of the
jobs submitted to the resource on the grid. The access to a resource
not only depend on the identity and behaviour of the resource but
also upon its context of transaction, time of transaction, connectivity
bandwidth, availability of the resource and load on the resource. The
quality of the recommender is also evaluated based on the accuracy
of the feedback provided about a resource. The jobs are submitted for
execution to the selected resource after finding the overall trust value
of the resource. The overall trust value is computed with respect to
the subjective and objective parameters.
Abstract: One problem in evaluating recent computational models of human category learning is that there is no standardized method for systematically comparing the models' assumptions or hypotheses. In the present study, a flexible general model (called GECLE) is introduced that can be used as a framework to systematically manipulate and compare the effects and descriptive validities of a limited number of assumptions at a time. Two example simulation studies are presented to show how the GECLE framework can be useful in the field of human high-order cognition research.
Abstract: The aim of the present study was to evaluate the
mucoadhesion and the release of nicotinamide gel formulations using
in vitro methods. An agar plate technique was used to investigate the
adhesiveness of the gels whereas a diffusion apparatus was employed
to determine the release of nicotinamide from the gels. In this
respect, 10% w/w nicotinamide gels containing bioadhesive
polymers: Carbopol 934P (0.5-2% w/w), hydroxypropylmethyl
cellulose (HPMC) (4-10% w/w), sodium carboxymethyl cellulose
(SCMC) (4-6% w/w) and methylcellulose 4000 (MC) (3-5% w/w)
were prepared. The gel formulations had pH values in the range of
7.14 - 8.17, which were considered appropriate to oral mucosa
application. In general, the rank order of pH values appeared to be
SCMC > MC4000 > HPMC > Carbopol 934P. Types and
concentrations of polymers used somewhat affected the
adhesiveness. It was found that anionic polymers (Carbopol 934 and
SCMC) adhered more firmly to the agar plate than the neutral
polymers (HPMC and MC 4000). The formulation containing 0.5%
Carbopol 934P (F1) showed the highest release rate. With the
exception of the formulation F1, the neutral polymers tended to give
higher relate rates than the anionic polymers. For oral tissue
treatment, the optimum has to be balanced between the residence
time (adhesiveness) of the formulations and the release rate of the
drug. The formulations containing the anionic polymers: Carbopol
934P or SCMC possessed suitable physical properties (appearance,
pH and viscosity). In addition, for anionic polymer formulations,
justifiable mucoadhesive properties and reasonable release rates of
nicotinamide were achieved. Accordingly, these gel formulations
may be applied for the treatment of oral mucosal lesions.
Abstract: Magneto-rheological (MR) fluid damper is a semiactive
control device that has recently received more attention by the
vibration control community. But inherent hysteretic and highly
nonlinear dynamics of MR fluid damper is one of the challenging
aspects to employ its unique characteristics. The combination of
artificial neural network (ANN) and fuzzy logic system (FLS) have
been used to imitate more precisely the behavior of this device.
However, the derivative-based nature of adaptive networks causes
some deficiencies. Therefore, in this paper, a novel approach that
employ genetic algorithm, as a free-derivative algorithm, to enhance
the capability of fuzzy systems, is proposed. The proposed method
used to model MR damper. The results will be compared with
adaptive neuro-fuzzy inference system (ANFIS) model, which is one
of the well-known approaches in soft computing framework, and two
best parametric models of MR damper. Data are generated based on
benchmark program by applying a number of famous earthquake
records.
Abstract: Master plan is a tool to guide and manage the growth of cities in a planned manner. The soul of a master plan lies in its implementation framework. If not implemented, people are trapped in a mess of urban problems and laissez-faire development having serious long term repercussions. Unfortunately, Master Plans prepared for several major cities of Pakistan could not be fully implemented due to host of reasons and Lahore is no exception. Being the second largest city of Pakistan with a population of over 7 million people, Lahore holds the distinction that the first ever Master Plan in the country was prepared for this city in 1966. Recently in 2004, a new plan titled `Integrated Master Plan for Lahore-2021- has been approved for implementation. This paper provides a comprehensive account of the weaknesses and constraints in the plan preparation process and implementation strategies of Master Plans prepared for Lahore. It also critically reviews the new Master Plan particularly with respect to the proposed implementation framework. The paper discusses the prospects and pre-conditions for successful implementation of the new Plan in the light of historic analysis, interviews with stakeholders and the new institutional context under the devolution plan.
Abstract: The understanding of the system level of biological behavior and phenomenon variously needs some elements such as gene sequence, protein structure, gene functions and metabolic pathways. Challenging problems are representing, learning and reasoning about these biochemical reactions, gene and protein structure, genotype and relation between the phenotype, and expression system on those interactions. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this study an ontological meta-model for the knowledge representation of the genetic regulatory networks. Ontology in artificial intelligence means the fundamental categories and relations that provide a framework for knowledge models. Domain ontology's are now commonly used to enable heterogeneous information resources, such as knowledge-based systems, to communicate with each other. The interest of our model is to represent the spatial, temporal and spatio-temporal knowledge. We validated our propositions in the genetic regulatory network of the Aarbidosis thaliana flower
Abstract: This paper draws a methodological framework adopted within an internal Telecomitalia project aimed to identify, on a user centred base, the potential interest towards a technological scenario aimed to extend on a personal bubble the typical communication and media fruition home environment. The problem is that involving user in the early stage of the development of such disruptive technology scenario asking users opinions on something that users actually do not manage even in a rough manner could lead to wrong or distorted results. For that reason we chose an approach that indirectly aim to understand users hidden needs in order to obtain a meaningful picture of the possible interest for a technological proposition non yet easily understandable.
Abstract: This study empirically examines the long run equilibrium relationship between South Africa’s exports and imports using quarterly data from 1985 to 2012. The theoretical framework used for the study is based on Johansen’s Maximum Likelihood cointegration technique which tests for both the existence and number of cointegration vectors that exists. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant cointegrating relationship is found to exist between exports and imports. The study models this unique linear and lagged relationship using a Vector Error Correction Model (VECM). The findings of the study confirm the existence of a long run equilibrium relationship between exports and imports.
Abstract: In data mining, the association rules are used to find
for the associations between the different items of the transactions
database. As the data collected and stored, rules of value can be found
through association rules, which can be applied to help managers
execute marketing strategies and establish sound market frameworks.
This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth)
to derive from fuzzy association rules. At first, we apply fuzzy
partition methods and decide a membership function of quantitative
value for each transaction item. Next, we implement FFP-growth
to deal with the process of data mining. In addition, in order to
understand the impact of Apriori algorithm and FFP-growth algorithm
on the execution time and the number of generated association
rules, the experiment will be performed by using different sizes of
databases and thresholds. Lastly, the experiment results show FFPgrowth
algorithm is more efficient than other existing methods.
Abstract: In many countries, digital city or ubiquitous city
(u-City) projects have been initiated to provide digitalized economic
environments to cities. Recently in Korea, Kangwon Province has
started the u-Kangwon project to boost local economy with digitalized
tourism services. We analyze the limitations of the ubiquitous IT
approach through the u-Kangwon case. We have found that travelers
are more interested in quality over speed in access of information. For
improved service quality, we are looking to develop an
IT-convergence service design framework (ISDF). The ISDF is based
on the service engineering technique and composed of three parts:
Service Design, Service Simulation, and the Service Platform.
Abstract: the elastic scattering of protons, deuterons and 3He on 6Li at different incident energies have been analyzed in the framework of the optical model using ECIS88 as well as SPI GENOA codes. The potential parameters were extracted in the phenomenological treatment of measured by us angular distributions and literature data. A good agreement between theoretical and experimental differential cross sections was obtained in whole angular range. Parameters for real part of potential have been also calculated microscopically with singleand double-folding model for the p and d, 3He scattering, respectively, using DFPOT code. For best agreement with experiment the normalization factor N for the potential depth is obtained in the range of 0.7-0.9.
Abstract: This paper explores the social and political imperatives in the sphere of public policy relating to social justice. In India, the colonial legacy and post-colonial social and political pressures sustained the appropriation of 'caste' category in allocating public resources to the backward class of citizens. For several reasons, 'economic' category could not be placed in allocating resources. This paper examines the reasons behind the deliberative exercises and formulating policies and seeks an alternative framework in realizing social justice in terms of a unified category. This attempt can be viewed as a reconciliation of traditional and modern values for a viable alternative in public policy making.
Abstract: Segmentation of a color image composed of different
kinds of regions can be a hard problem, namely to compute for an
exact texture fields. The decision of the optimum number of
segmentation areas in an image when it contains similar and/or un
stationary texture fields. A novel neighborhood-based segmentation
approach is proposed. A genetic algorithm is used in the proposed
segment-pass optimization process. In this pass, an energy function,
which is defined based on Markov Random Fields, is minimized. In
this paper we use an adaptive threshold estimation method for image
thresholding in the wavelet domain based on the generalized
Gaussian distribution (GGD) modeling of sub band coefficients. This
method called Normal Shrink is computationally more efficient and
adaptive because the parameters required for estimating the threshold
depend on sub band data energy that used in the pre-stage of
segmentation. A quad tree is employed to implement the multi
resolution framework, which enables the use of different strategies at
different resolution levels, and hence, the computation can be
accelerated. The experimental results using the proposed
segmentation approach are very encouraging.
Abstract: Small and Medium Sized Enterprises (SMEs) play an important role in many economies. In New Zealand, for example, 97% of all manufacturing companies employ less than 100 staff, and generate the predominant part of this industry sector-s economic output. Manufacturing SMEs as a group also have a significant impact on the environment. This situation is similar in many developed economies, including the European Union. Sustainable economic development therefore needs to strongly consider the role of manufacturing SMEs, who generally find it challenging to move towards more environmentally friendly business practices. This paper presents a systems thinking approach to modelling and understanding the factors which have an influence on the successful uptake of environmental practices in small and medium sized manufacturing companies. It presents a number of causal loop diagrams which have been developed based on primary action research, and a thorough understanding of the literature in this area. The systems thinking model provides the basis for further development of a strategic framework for the successful uptake of environmental innovation in manufacturing SMEs.
Abstract: This study examines knowledge management in the public organizations in Iran. The purpose of this article is to provide a conceptual framework for application of knowledge management in public organizations. The study indicates that an increasing tendency for implementation of knowledge management in organizations is emerging. Nonetheless knowledge management in public organizations is toddler and little has been done to bring the subject to use in the public sector. The globalization of change and popularization of some values like participation, citizen-orientation and knowledge-orientation in the new theories of public administration requires that the knowledge management is considered and attend to in the public sector. This study holds that a knowledge management framework for public organizations is different from this in the public sector, because public sector is stakeholder-dependent while the private is shareholder-dependent. Based on the research, we provide a conceptual model. The model proposed involves three factors: Organizational, knowledge citizens and contextual factors. The study results indicate these factors affect on knowledge management in public organizations in Iran.
Abstract: To judge whether the memristor can be interpreted as
the fourth fundamental circuit element, we propose a variable-relation
criterion of fundamental circuit elements. According to the criterion,
we investigate the nature of three fundamental circuit elements and the
memristor. From the perspective of variables relation, the memristor
builds a direct relation between the voltage across it and the current
through it, instead of a direct relation between the magnetic flux and
the charge. Thus, it is better to characterize the memristor and the
resistor as two special cases of the same fundamental circuit element,
which is the memristive system in Chua-s new framework. Finally, the
definition of memristor is refined according to the difference between
the magnetic flux and the flux linkage.