Abstract:
Innovation is becoming more and more important in
modern society. There are a lot of researches on different kinds of
innovation but marketing innovation is one kind of innovation that
has not been studied frequently before. Marketing innovation is
defined as a new way in which companies can market themselves to
potential or existing customers.
The study shows some key elements for marketing innovation that
are worth paying attention to when implementing marketing
innovation projects. Examples of such key elements are: paying
attention to the neglected market, suitable market segmentatio
reliable market information, public relationship, increased customer
value, combination of market factors, explore different marketing
channels and the use of technology in combination with what? Beside
the key elements for marketing innovation, we also present some
risks that may occur, such as cost, market uncertainty, information
leakage, imitation and overdependence on experience.
By proposing a set of indicators to measure marketing innovation,
the article offers solutions for marketing innovation implementation
so that any organization can achieve optimal results.
Abstract: The paper compares different channel models used for
modeling Broadband Power-Line Communication (BPLC) system.
The models compared are Zimmermann and Dostert, Philipps,
Anatory et al and Anatory et al generalized Transmission Line (TL)
model. The validity of each model was compared in time domain
with ATP-EMTP software which uses transmission line approach. It
is found that for a power-line network with minimum number of
branches all the models give similar signal/pulse time responses
compared with ATP-EMTP software; however, Zimmermann and
Dostert model indicates the same amplitude but different time delay.
It is observed that when the numbers of branches are increased only
generalized TL theory approach results are comparable with ATPEMTP
results. Also the Multi-Carrier Spread Spectrum (MC-SS)
system was applied to check the implication of such behavior on the
modulation schemes. It is observed that using Philipps on the
underground cable can predict the performance up to 25dB better
than other channel models which can misread the actual performance
of the system. Also modified Zimmermann and Dostert under
multipath can predict a better performance of about 5dB better than
the actual predicted by Generalized TL theory. It is therefore
suggested for a realistic BPLC system design and analyses the model
based on generalized TL theory be used.
Abstract: Estimation of natural frequency of structures is very
important and isn-t usually calculated simply and sometimes
complicated. Lack of knowledge about that caused hard damage and
hazardous effects.
In this paper, with using from two different models in FEM
method and based on hydrodynamic mass of fluids, natural frequency
of an especial bearing (Fig. 1) in an electric field (or, a periodic
force) is calculated in different stiffness and different geometric. In
final, the results of two models and analytical solution are compared.
Abstract: In recent years, copulas have become very popular in
financial research and actuarial science as they are more flexible in
modelling the co-movements and relationships of risk factors as compared
to the conventional linear correlation coefficient by Pearson.
However, a precise estimation of the copula parameters is vital in
order to correctly capture the (possibly nonlinear) dependence structure
and joint tail events. In this study, we employ two optimization
heuristics, namely Differential Evolution and Threshold Accepting to
tackle the parameter estimation of multivariate t distribution models
in the EML approach. Since the evolutionary optimizer does not rely
on gradient search, the EML approach can be applied to estimation of
more complicated copula models such as high-dimensional copulas.
Our experimental study shows that the proposed method provides
more robust and more accurate estimates as compared to the IFM
approach.
Abstract: In this paper, we present a robust and secure
algorithm for watermarking, the watermark is first transformed into
the frequency domain using the discrete wavelet transform (DWT).
Then the entire DWT coefficient except the LL (Band) discarded,
these coefficients are permuted and encrypted by specific mixing.
The encrypted coefficients are inserted into the most significant
spectral components of the stego-image using a chaotic system. This
technique makes our watermark non-vulnerable to the attack (like
compression, and geometric distortion) of an active intruder, or due
to noise in the transmission link.
Abstract: The paper deals with the most important changes that have occurred in business because of social media and its impact on organisations and leadership in recent years. It seeks to synthesize existing research, theories and concepts, in order to understand "social destinations", and to provide a bridge from past research to future success. Becoming a "social destination" is a strategic and tactical leadership and management issue and the paper will present the importance of destination leadership in choosing the way towards a social destination and some organisational models. It also presents some social media tools that can be used in transforming a destination into a social one. Adapting organisations to the twentyfirst century means adopting social media as a way of life and a way of business.
Abstract: This paper discusses the design characteristics management accounting systems should have to be useful for strategic planning and control and provides brief introductions to strategic variance analysis, profit-linked performance measurement models and balanced scorecard. It shows two multi-period, multiproduct models are specified, can be related to Porter's strategy framework and cost and revenue drivers, and can be used to support strategic planning, control and cost management.
Abstract: Almost all Libyan industries (both private and public) have struggled with many difficulties during the past three decades due to many problems. These problems have created a strongly negative impact on the productivity and utilization of many companies within Libya. This paper studies the current awareness and implementation levels of Just-In-Time (JIT) within the Libyan Textile private industry. A survey has been applied in this study using an intensive detailed questionnaire. Based on the analysis of the survey responses, the results show that the management body within the surveyed companies has a modest strategy towards most of the areas that are considered as being very crucial in any successful implementation of JIT. The results also show a variation within the implementation levels of the JIT elements as these varies between Low and Acceptable levels. The paper has also identified limitations within the investigated areas within this industry, and has pointed to areas where senior managers within the Libyan textile industry should take immediate actions in order to achieve effective implementation of JIT within their companies.
Abstract: We proposed a technique to identify road traffic
congestion levels from velocity of mobile sensors with high accuracy
and consistent with motorists- judgments. The data collection utilized
a GPS device, a webcam, and an opinion survey. Human perceptions
were used to rate the traffic congestion levels into three levels: light,
heavy, and jam. Then the ratings and velocity were fed into a
decision tree learning model (J48). We successfully extracted vehicle
movement patterns to feed into the learning model using a sliding
windows technique. The parameters capturing the vehicle moving
patterns and the windows size were heuristically optimized. The
model achieved accuracy as high as 99.68%. By implementing the
model on the existing traffic report systems, the reports will cover
comprehensive areas. The proposed method can be applied to any
parts of the world.
Abstract: The structure of retinal vessels is a prominent feature,
that reveals information on the state of disease that are reflected in
the form of measurable abnormalities in thickness and colour.
Vascular structures of retina, for implementation of clinical diabetic
retinopathy decision making system is presented in this paper.
Retinal Vascular structure is with thin blood vessel, whose accuracy
is highly dependent upon the vessel segmentation. In this paper the
blood vessel thickness is automatically detected using preprocessing
techniques and vessel segmentation algorithm. First the capture
image is binarized to get the blood vessel structure clearly, then it is
skeletonised to get the overall structure of all the terminal and
branching nodes of the blood vessels. By identifying the terminal
node and the branching points automatically, the main and branching
blood vessel thickness is estimated. Results are presented and
compared with those provided by clinical classification on 50 vessels
collected from Bejan Singh Eye hospital..
Abstract: In this paper an algorithm is used to detect the color defects of ceramic tiles. First the image of a normal tile is clustered using GCMA; Genetic C-means Clustering Algorithm; those results in best cluster centers. C-means is a common clustering algorithm which optimizes an objective function, based on a measure between data points and the cluster centers in the data space. Here the objective function describes the mean square error. After finding the best centers, each pixel of the image is assigned to the cluster with closest cluster center. Then, the maximum errors of clusters are computed. For each cluster, max error is the maximum distance between its center and all the pixels which belong to it. After computing errors all the pixels of defected tile image are clustered based on the centers obtained from normal tile image in previous stage. Pixels which their distance from their cluster center is more than the maximum error of that cluster are considered as defected pixels.
Abstract: Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of medical ultrasound images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to clinical ultrasound images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected ultrasound images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (detection hypotheses) in the original images.
Abstract: Importance of software quality is increasing leading to development of new sophisticated techniques, which can be used in constructing models for predicting quality attributes. One such technique is Artificial Neural Network (ANN). This paper examined the application of ANN for software quality prediction using Object- Oriented (OO) metrics. Quality estimation includes estimating maintainability of software. The dependent variable in our study was maintenance effort. The independent variables were principal components of eight OO metrics. The results showed that the Mean Absolute Relative Error (MARE) was 0.265 of ANN model. Thus we found that ANN method was useful in constructing software quality model.
Abstract: The quest for alternatefuels for a CI engine has
become all the more imperative considering its importance in the
economy of a nation and from the standpoint of preserving the environment. Reported in this paper are the combustion performance and P-θ characteristics of a CI engine operating on B20 biodiesel fuel derived from Jatropha oil.Itis observed that the twin effect of advancing the injection timing and increasing the injector opening pressure (IOP) up to 220 barhas resulted in minimum brake specific
energy consumption and higherpeak pressure. It is also observed that
the crank angle of occurrence of peak pressure progressestowards top
dead center (TDC) as the timing is advanced and IOP is increased.
Abstract: IP multicasting is a key technology for many existing and emerging applications on the Internet. Furthermore, with increasing popularity of wireless devices and mobile equipment, it is necessary to determine the best way to provide this service in a wireless environment. IETF Mobile IP, that provides mobility for hosts in IP networks, proposes two approaches for mobile multicasting, namely, remote subscription (MIP-RS) and bi-directional tunneling (MIP-BT). In MIP-RS, a mobile host re-subscribes to the multicast groups each time it moves to a new foreign network. MIP-RS suffers from serious packet losses while mobile host handoff occurs. In MIP-BT, mobile hosts send and receive multicast packets by way of their home agents (HAs), using Mobile IP tunnels. Therefore, it suffers from inefficient routing and wastage of system resources. In this paper, we propose a protocol called Mobile Multicast support using Old Foreign Agent (MMOFA) for Mobile Hosts. MMOFA is derived from MIP-RS and with the assistance of Mobile host's Old foreign agent, routes the missing datagrams due to handoff in adjacent network via tunneling. Also, we studied the performance of the proposed protocol by simulation under ns-2.27. The results demonstrate that MMOFA has optimal routing efficiency and low delivery cost, as compared to other approaches.
Abstract: The problem of estimating time-varying regression is
inevitably concerned with the necessity to choose the appropriate
level of model volatility - ranging from the full stationarity of instant
regression models to their absolute independence of each other. In the
stationary case the number of regression coefficients to be estimated
equals that of regressors, whereas the absence of any smoothness
assumptions augments the dimension of the unknown vector by the
factor of the time-series length. The Akaike Information Criterion
is a commonly adopted means of adjusting a model to the given
data set within a succession of nested parametric model classes,
but its crucial restriction is that the classes are rigidly defined by
the growing integer-valued dimension of the unknown vector. To
make the Kullback information maximization principle underlying the
classical AIC applicable to the problem of time-varying regression
estimation, we extend it onto a wider class of data models in which
the dimension of the parameter is fixed, but the freedom of its values
is softly constrained by a family of continuously nested a priori
probability distributions.
Abstract: The purpose of this paper is to perform a multidisciplinary design and analysis (MDA) of honeycomb panels used in the satellites structural design. All the analysis is based on clamped-free boundary conditions. In the present work, detailed finite element models for honeycomb panels are developed and analysed. Experimental tests were carried out on a honeycomb specimen of which the goal is to compare the previous modal analysis made by the finite element method as well as the existing equivalent approaches. The obtained results show a good agreement between the finite element analysis, equivalent and tests results; the difference in the first two frequencies is less than 4% and less than 10% for the third frequency. The results of the equivalent model presented in this analysis are obtained with a good accuracy. Moreover, investigations carried out in this research relate to the honeycomb plate modal analysis under several aspects including the structural geometrical variation by studying the various influences of the dimension parameters on the modal frequency, the variation of core and skin material of the honeycomb. The various results obtained in this paper are promising and show that the geometry parameters and the type of material have an effect on the value of the honeycomb plate modal frequency.
Abstract: Automatic segmentation of skin lesions is the first step
towards development of a computer-aided diagnosis of melanoma.
Although numerous segmentation methods have been developed,
few studies have focused on determining the most discriminative
and effective color space for melanoma application. This paper
proposes a novel automatic segmentation algorithm using color space
analysis and clustering-based histogram thresholding, which is able to
determine the optimal color channel for segmentation of skin lesions.
To demonstrate the validity of the algorithm, it is tested on a set of 30
high resolution dermoscopy images and a comprehensive evaluation
of the results is provided, where borders manually drawn by four
dermatologists, are compared to automated borders detected by the
proposed algorithm. The evaluation is carried out by applying three
previously used metrics of accuracy, sensitivity, and specificity and
a new metric of similarity. Through ROC analysis and ranking the
metrics, it is shown that the best results are obtained with the X and
XoYoR color channels which results in an accuracy of approximately
97%. The proposed method is also compared with two state-ofthe-
art skin lesion segmentation methods, which demonstrates the
effectiveness and superiority of the proposed segmentation method.
Abstract: Several models have been introduced so far for single
electron box, SEB, which all of them were restricted to DC response
and or low temperature limit. In this paper we introduce a new time
dependent, high temperature analytical model for SEB for the first
time. DC behavior of the introduced model will be verified against
SIMON software and its time behavior will be verified against a
newly published paper regarding step response of SEB.
Abstract: In this paper the design of maximally flat linear phase
finite impulse response (FIR) filters is considered. The problem is
handled with totally two different approaches. The first one is
completely deterministic numerical approach where the problem is
formulated as a Linear Complementarity Problem (LCP). The other
one is based on a combination of Markov Random Fields (MRF's)
approach with messy genetic algorithm (MGA). Markov Random
Fields (MRFs) are a class of probabilistic models that have been
applied for many years to the analysis of visual patterns or textures.
Our objective is to establish MRFs as an interesting approach to
modeling messy genetic algorithms. We establish a theoretical result
that every genetic algorithm problem can be characterized in terms of
a MRF model. This allows us to construct an explicit probabilistic
model of the MGA fitness function and introduce the Ising MGA.
Experimentations done with Ising MGA are less costly than those
done with standard MGA since much less computations are involved.
The least computations of all is for the LCP. Results of the LCP,
random search, random seeded search, MGA, and Ising MGA are
discussed.