Abstract: In illumination variant face recognition, existing
methods extracting face albedo as light normalized image may lead to
loss of extensive facial details, with light template discarded. To
improve that, a novel approach for realistic facial texture
reconstruction by combining original image and albedo image is
proposed. First, light subspaces of different identities are established
from the given reference face images; then by projecting the original
and albedo image into each light subspace respectively, texture
reference images with corresponding lighting are reconstructed and
two texture subspaces are formed. According to the projections in
texture subspaces, facial texture with normal light can be synthesized.
Due to the combination of original image, facial details can be
preserved with face albedo. In addition, image partition is applied to
improve the synthesization performance. Experiments on Yale B and
CMUPIE databases demonstrate that this algorithm outperforms the
others both in image representation and in face recognition.
Abstract: Phylogenies ; The evolutionary histories of groups of
species are one of the most widely used tools throughout the life
sciences, as well as objects of research with in systematic,
evolutionary biology. In every phylogenetic analysis reconstruction
produces trees. These trees represent the evolutionary histories of
many groups of organisms, bacteria due to horizontal gene transfer
and plants due to process of hybridization. The process of gene
transfer in bacteria and hybridization in plants lead to reticulate
networks, therefore, the methods of constructing trees fail in
constructing reticulate networks. In this paper a model has been
employed to reconstruct phylogenetic network in honey bee. This
network represents reticulate evolution in honey bee. The maximum
parsimony approach has been used to obtain this reticulate network.
Abstract: User-Centered Design (UCD), Usability Engineering (UE) and Participatory Design (PD) are the common Human- Computer Interaction (HCI) approaches that are practiced in the software development process, focusing towards issues and matters concerning user involvement. It overlooks the organizational perspective of HCI integration within the software development organization. The Management Information Systems (MIS) perspective of HCI takes a managerial and organizational context to view the effectiveness of integrating HCI in the software development process. The Human-Centered Design (HCD) which encompasses all of the human aspects including aesthetic and ergonomic, is claimed as to provide a better approach in strengthening the HCI approaches to strengthen the software development process. In determining the effectiveness of HCD in the software development process, this paper presents the findings of a content analysis of HCI approaches by viewing those approaches as a technology which integrates user requirements, ranging from the top management to other stake holder in the software development process. The findings obtained show that HCD approach is a technology that emphasizes on human, tools and knowledge in strengthening the HCI approaches to strengthen the software development process in the quest to produce a sustainable, usable and useful software product.
Abstract: In many applications, it is a priori known that the
target function should satisfy certain constraints imposed by, for
example, economic theory or a human-decision maker. Here we
consider partially monotone problems, where the target variable
depends monotonically on some of the predictor variables but not all.
We propose an approach to build partially monotone models based
on the convolution of monotone neural networks and kernel
functions. The results from simulations and a real case study on
house pricing show that our approach has significantly better
performance than partially monotone linear models. Furthermore, the
incorporation of partial monotonicity constraints not only leads to
models that are in accordance with the decision maker's expertise,
but also reduces considerably the model variance in comparison to
standard neural networks with weight decay.
Abstract: Various models have been derived by studying large number of completed software projects from various organizations and applications to explore how project sizes mapped into project effort. But, still there is a need to prediction accuracy of the models. As Neuro-fuzzy based system is able to approximate the non-linear function with more precision. So, Neuro-Fuzzy system is used as a soft computing approach to generate model by formulating the relationship based on its training. In this paper, Neuro-Fuzzy technique is used for software estimation modeling of on NASA software project data and performance of the developed models are compared with the Halstead, Walston-Felix, Bailey-Basili and Doty Models mentioned in the literature.
Abstract: Nowadays, quick technological changes force companies
to develop innovative products in an increasingly competitive
environment. Therefore, how to enhance the time of new product
development is very important. This design problem often lacks
the exact formula for getting it, and highly depends upon human
designers- past experiences. For these reasons, in this work, a Casebased
reasoning (CBR) system to assist in new product development
is proposed. When a case is recovered from the case base, the system
will take into account not only the attribute-s specific value and
how important it is. It will also take into account if the attribute
has a positive influence over the product development. Hence the
manufacturing time will be improved. This information will be
introduced as a new concept called “adaptability". An application to
this method for hearing instrument new design illustrates the proposed
approach.
Abstract: This paper presents a solution for the behavioural animation of autonomous virtual agent navigation in virtual environments. We focus on using Dempster-Shafer-s Theory of Evidence in developing visual sensor for virtual agent. The role of the visual sensor is to capture the information about the virtual environment or identifie which part of an obstacle can be seen from the position of the virtual agent. This information is require for vitual agent to coordinate navigation in virtual environment. The virual agent uses fuzzy controller as a navigation system and Fuzzy α - level for the action selection method. The result clearly demonstrates the path produced is reasonably smooth even though there is some sharp turn and also still not diverted too far from the potential shortest path. This had indicated the benefit of our method, where more reliable and accurate paths produced during navigation task.
Abstract: Optical flow is a research topic of interest for many
years. It has, until recently, been largely inapplicable to real-time
applications due to its computationally expensive nature. This paper
presents a new reliable flow technique which is combined with a
motion detection algorithm, from stationary camera image streams,
to allow flow-based analyses of moving entities, such as rigidity, in
real-time. The combination of the optical flow analysis with motion
detection technique greatly reduces the expensive computation of
flow vectors as compared with standard approaches, rendering the
method to be applicable in real-time implementation. This paper
describes also the hardware implementation of a proposed pipelined
system to estimate the flow vectors from image sequences in real
time. This design can process 768 x 576 images at a very high frame
rate that reaches to 156 fps in a single low cost FPGA chip, which is
adequate for most real-time vision applications.
Abstract: In this paper, we propose an adaptation of the Patricia-Tree for sparse datasets to generate non redundant rule associations. Using this adaptation, we can generate frequent closed itemsets that are more compact than frequent itemsets used in Apriori approach. This adaptation has been experimented on a set of datasets benchmarks.
Abstract: In this paper a new approach to face recognition is presented that achieves double dimension reduction making the system computationally efficient with better recognition results. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results improve with increase in face image resolution and levels off when arriving at a certain resolution level. In the proposed model of face recognition, first image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to better computational speed and feature extraction potential of Discrete Cosine Transform (DCT) it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A trade of between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL database, Yale database and a color database. The proposed technique has performed much better compared to other techniques. The significance of the model is two fold: (1) dimension reduction up to an effective and suitable face image resolution (2) appropriate DCT coefficients are retained to achieve best recognition results with varying image poses, intensity and illumination level.
Abstract: Bond graph models of an electrical transformer including
the nonlinear saturation are presented. The transformer
using electrical and magnetic circuits are modelled. These models
determine the relation between self and mutual inductances, and
the leakage and magnetizing inductances of power transformers
with two windings using the properties of a bond graph. The
equivalence between electrical and magnetic variables is given.
The modelling and analysis using this methodology to three phase
power transformers can be extended.
Abstract: The human friendly interaction is the key function of a human-centered system. Over the years, it has received much attention to develop the convenient interaction through intention recognition. Intention recognition processes multimodal inputs including speech, face images, and body gestures. In this paper, we suggest a novel approach of intention recognition using a graph representation called Intention Graph. A concept of valid intention is proposed, as a target of intention recognition. Our approach has two phases: goal recognition phase and intention recognition phase. In the goal recognition phase, we generate an action graph based on the observed actions, and then the candidate goals and their plans are recognized. In the intention recognition phase, the intention is recognized with relevant goals and user profile. We show that the algorithm has polynomial time complexity. The intention graph is applied to a simple briefcase domain to test our model.
Abstract: In this era of competitiveness, there is a growing need for supply chains also to become competitive enough to handle pressures like varying customer’s expectations, low cost high quality products to be delivered at the minimum time and the most important is throat cutting competition at world wide scale. In the recent years, supply chain competitiveness has been, therefore, accepted as one of the most important philosophies in the supply chain literature. Various researchers and practitioners have tried to identify and implement strategies in supply chains which can bring competitiveness in the supply chains i.e. supply chain competitiveness. The purpose of this paper is to suggest select strategies for supply chain competitiveness in the Indian manufacturing sector using an integrated approach of literature review and exploratory interviews with eminent professionals from the supply chain area in various industries, academia and research. The aim of the paper is to highlight the important area of competitiveness in the supply chain and to suggest recommendations to the industry and managers of manufacturing sector.
Abstract: Most of the losses in a power system relate to
the distribution sector which always has been considered.
From the important factors which contribute to increase losses
in the distribution system is the existence of radioactive flows.
The most common way to compensate the radioactive power
in the system is the power to use parallel capacitors. In
addition to reducing the losses, the advantages of capacitor
placement are the reduction of the losses in the release peak of
network capacity and improving the voltage profile. The point
which should be considered in capacitor placement is the
optimal placement and specification of the amount of the
capacitor in order to maximize the advantages of capacitor
placement.
In this paper, a new technique has been offered for the
placement and the specification of the amount of the constant
capacitors in the radius distribution network on the basis of
Genetic Algorithm (GA). The existing optimal methods for
capacitor placement are mostly including those which reduce
the losses and voltage profile simultaneously. But the
retaliation cost and load changes have not been considered as
influential UN the target function .In this article, a holistic
approach has been considered for the optimal response to this
problem which includes all the parameters in the distribution
network: The price of the phase voltage and load changes. So,
a vast inquiry is required for all the possible responses. So, in
this article, we use Genetic Algorithm (GA) as the most
powerful method for optimal inquiry.
Abstract: The background estimation approach using a small
window median filter is presented on the bases of analyzing IR point
target, noise and clutter model. After simplifying the two-dimensional
filter, a simple method of adopting one-dimensional median filter is
illustrated to make estimations of background according to the
characteristics of IR scanning system. The adaptive threshold is used
to segment canceled image in the background. Experimental results
show that the algorithm achieved good performance and satisfy the
requirement of big size image-s real-time processing.
Abstract: Spatial and mobile computing evolves. This paper
describes a smart modeling platform called “GeoSEMA". This
approach tends to model multidimensional GeoSpatial Evolutionary
and Mobile Agents. Instead of 3D and location-based issues, there
are some other dimensions that may characterize spatial agents, e.g.
discrete-continuous time, agent behaviors. GeoSEMA is seen as a
devoted design pattern motivating temporal geographic-based
applications; it is a firm foundation for multipurpose and
multidimensional special-based applications. It deals with
multipurpose smart objects (buildings, shapes, missiles, etc.) by
stimulating geospatial agents.
Formally, GeoSEMA refers to geospatial, spatio-evolutive and
mobile space constituents where a conceptual geospatial space model
is given in this paper. In addition to modeling and categorizing
geospatial agents, the model incorporates the concept of inter-agents
event-based protocols. Finally, a rapid software-architecture
prototyping GeoSEMA platform is also given. It will be
implemented/ validated in the next phase of our work.
Abstract: Generator of hypotheses is a new method for data mining. It makes possible to classify the source data automatically and produces a particular enumeration of patterns. Pattern is an expression (in a certain language) describing facts in a subset of facts. The goal is to describe the source data via patterns and/or IF...THEN rules. Used evaluation criteria are deterministic (not probabilistic). The search results are trees - form that is easy to comprehend and interpret. Generator of hypotheses uses very effective algorithm based on the theory of monotone systems (MS) named MONSA (MONotone System Algorithm).
Abstract: Quantitative Investigation of impact of the factors' contribution towards measuring the reusability of software components could be helpful in evaluating the quality of developed or developing reusable software components and in identification of reusable component from existing legacy systems; that can save cost of developing the software from scratch. But the issue of the relative significance of contributing factors has remained relatively unexplored. In this paper, we have use the Taguchi's approach in analyzing the significance of different structural attributes or factors in deciding the reusability level of a particular component. The results obtained shows that the complexity is the most important factor in deciding the better Reusability of a function oriented Software. In case of Object Oriented Software, Coupling and Complexity collectively play significant role in high reusability.
Abstract: Shear walls are used in most of the tall buildings for
carrying the lateral load. When openings for doors or windows are
necessary to be existed in the shear walls, a special type of the shear
walls is used called "coupled shear walls" which in some cases is
stiffened by specific beams and so, called "stiffened coupled shear
walls".
In this paper, a mathematical method for geometrically nonlinear
analysis of the stiffened coupled shear walls has been presented.
Then, a suitable formulation for determining the critical load of the
stiffened coupled shear walls under gravity force has been proposed.
The governing differential equations for equilibrium and deformation
of the stiffened coupled shear walls have been obtained by setting up
the equilibrium equations and the moment-curvature relationships for
each wall. Because of the complexity of the differential equation, the
energy method has been adopted for approximate solution of the
equations.
Abstract: Encrypted messages sending frequently draws the attention
of third parties, perhaps causing attempts to break and
reveal the original messages. Steganography is introduced to hide
the existence of the communication by concealing a secret message
in an appropriate carrier like text, image, audio or video. Quantum
steganography where the sender (Alice) embeds her steganographic
information into the cover and sends it to the receiver (Bob) over a
communication channel. Alice and Bob share an algorithm and hide
quantum information in the cover. An eavesdropper (Eve) without
access to the algorithm can-t find out the existence of the quantum
message. In this paper, a text quantum steganography technique based
on the use of indefinite articles (a) or (an) in conjunction with the nonspecific
or non-particular nouns in English language and quantum
gate truth table have been proposed. The authors also introduced a
new code representation technique (SSCE - Secret Steganography
Code for Embedding) at both ends in order to achieve high level of
security. Before the embedding operation each character of the secret
message has been converted to SSCE Value and then embeds to cover
text. Finally stego text is formed and transmits to the receiver side.
At the receiver side different reverse operation has been carried out
to get back the original information.