Abstract: The evaluation of the question answering system is a major research area that needs much attention. Before the rise of domain-oriented question answering systems based on natural language understanding and reasoning, evaluation is never a problem as information retrieval-based metrics are readily available for use. However, when question answering systems began to be more domains specific, evaluation becomes a real issue. This is especially true when understanding and reasoning is required to cater for a wider variety of questions and at the same time achieve higher quality responses The research in this paper discusses the inappropriateness of the existing measure for response quality evaluation and in a later part, the call for new standard measures and the related considerations are brought forward. As a short-term solution for evaluating response quality of heterogeneous systems, and to demonstrate the challenges in evaluating systems of different nature, this research presents a black-box approach using observation, classification scheme and a scoring mechanism to assess and rank three example systems (i.e. AnswerBus, START and NaLURI).
Abstract: Paper deals with environmental metrics and assessment systems devoted to Small and Medium Sized Enterprises. Authors are presenting proposed assessment model which has an ability to discover current environmental strengths and weaknesses of Small and Middle Sized Enterprise. Suggested model has also an ambition to become a Sustainability Decision Tool. Model is able to identify "best environmental devision" in the company, and to quantify how this decision contributed into overall environmental improvement. Authors understand environmental improvements as environmental innovations (product, process and organizational). Suggested model is based on its own concept; however, authors are also utilizing already existing environmental assessment tools.
Abstract: This paper addresses the problem of source separation
in images. We propose a FastICA algorithm employing a modified
Gaussian contrast function for the Blind Source Separation.
Experimental result shows that the proposed Modified Gaussian
FastICA is effectively used for Blind Source Separation to obtain
better quality images. In this paper, a comparative study has been
made with other popular existing algorithms. The peak signal to
noise ratio (PSNR) and improved signal to noise ratio (ISNR) are
used as metrics for evaluating the quality of images. The ICA metric
Amari error is also used to measure the quality of separation.
Abstract: Internet Protocol version 4 (IPv4) address is decreasing and a rapid transition method to the next generation IP address (IPv6) should be established. This study aims to evaluate and select the best performance of the IPv6 address network transitionmechanisms, such as IPv4/IPv6 dual stack, transport Relay Translation (TRT) and Reverse Proxy with additional features. It is also aim to prove that faster access can be done while ensuring optimal usage of available resources used during the test and actual implementation. This study used two test methods such asInternet Control Message Protocol (ICMP)ping and ApacheBenchmark (AB) methodsto evaluate the performance.Performance metrics for this study include aspects ofaverageaccessin one second,time takenfor singleaccess,thedata transfer speed and the costof additional requirements.Reverse Proxy with Caching featureis the most efficientmechanism because of it simpler configurationandthe best performerfrom the test conducted.
Abstract: The abnormal increase in the number of applications available for download in Android markets is a good indication that they are being reused. However, little is known about their real reusability potential. A considerable amount of these applications is reported as having a poor quality or being malicious. Hence, in this paper, an approach to measure the reusability potential of classes in Android applications is proposed. The approach is not meant specifically for this particular type of applications. Rather, it is intended for Object-Oriented (OO) software systems in general and aims also to provide means to discard the classes of low quality and defect prone applications from being reused directly through inheritance and instantiation. An empirical investigation is conducted to measure and rank the reusability potential of the classes of randomly selected Android applications. The results obtained are thoroughly analyzed in order to understand the extent of this potential and the factors influencing it.
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: The automatic construction of large, high-resolution
image vistas (mosaics) is an active area of research in the fields of
photogrammetry [1,2], computer vision [1,4], medical image
processing [4], computer graphics [3] and biometrics [8]. Image
stitching is one of the possible options to get image mosaics. Vista
Creation in image processing is used to construct an image with a
large field of view than that could be obtained with a single
photograph. It refers to transforming and stitching multiple images
into a new aggregate image without any visible seam or distortion in
the overlapping areas. Vista creation process aligns two partial
images over each other and blends them together. Image mosaics
allow one to compensate for differences in viewing geometry. Thus
they can be used to simplify tasks by simulating the condition in
which the scene is viewed from a fixed position with single camera.
While obtaining partial images the geometric anomalies like rotation,
scaling are bound to happen. To nullify effect of rotation of partial
images on process of vista creation, we are proposing rotation
invariant vista creation algorithm in this paper. Rotation of partial
image parts in the proposed method of vista creation may introduce
some missing region in the vista. To correct this error, that is to fill
the missing region further we have used image inpainting method on
the created vista. This missing view regeneration method also
overcomes the problem of missing view [31] in vista due to cropping,
irregular boundaries of partial image parts and errors in digitization
[35]. The method of missing view regeneration generates the missing
view of vista using the information present in vista itself.
Abstract: Monitored 3-Dimensional (3D) video experience can be utilized as “feedback information” to fine tune the service parameters for providing a better service to the demanding 3D service customers. The 3D video experience which includes both video quality and depth perception is influenced by several contextual and content related factors (e.g., ambient illumination condition, content characteristics, etc) due to the complex nature of the 3D video. Therefore, effective factors on this experience should be utilized while assessing it. In this paper, structural information of the depth map sequences of the 3D video is considered as content related factor effective on the depth perception assessment. Cartoon-like filter is utilized to abstract the significant depth levels in the depth map sequences to determine the structural information. Moreover, subjective experiments are conducted using 3D videos associated with cartoon-like depth map sequences to investigate the effectiveness of ambient illumination condition, which is a contextual factor, on depth perception. Using the knowledge gained through this study, 3D video experience metrics can be developed to deliver better service to the 3D video service users.
Abstract: This paper investigates the fractals generated by the dynamical system of intuitionistic fuzzy contractions in the intuitionistic
fuzzy metric spaces by generalizing the Hutchinson-Barnsley theory. We prove some existence and uniqueness theorems of fractals in the
standard intuitionistic fuzzy metric spaces by using the intuitionistic fuzzy Banach contraction theorem. In addition to that, we analyze
some results on intuitionistic fuzzy fractals in the standard intuitionistic fuzzy metric spaces with respect to the Hausdorff intuitionistic
fuzzy metrics.
Abstract: In this paper, we propose an approach for the classification of fingerprint databases. It is based on the fact that a fingerprint image is composed of regular texture regions that can be successfully represented by co-occurrence matrices. So, we first extract the features based on certain characteristics of the cooccurrence matrix and then we use these features to train a neural network for classifying fingerprints into four common classes. The obtained results compared with the existing approaches demonstrate the superior performance of our proposed approach.
Abstract: In recent years, an increased competition and lower profit margins have necessitated a focus on improving the performance of the product development process, an area that traditionally have been excluded from detailed steering and evaluation. A systematic improvement requires a good understanding of the current performance, wherefore the interest for product development performance measurement has increased dramatically. This paper presents a case study that evaluates the performance of the product development performance measurement system used in a Swedish company that is a part of a global corporate group. The study is based on internal documentation and eighteen in-depth interviews with stakeholders involved in the product development process. The results from the case study includes a description of what metrics that are in use, how these are employed, and its affect on the quality of the performance measurement system. Especially, the importance of having a well-defined process proved to have a major impact on the quality of the performance measurement system in this particular case.
Abstract: Software development is moving towards agility with use cases and scenarios being used for requirements stories. Estimates of software costs are becoming even more important than before as effects of delays is much larger in successive short releases context of agile development. Thus, this paper reports on the development of new linear use case based software cost estimation model applicable in the very early stages of software development being based on simple metric. Evaluation showed that accuracy of estimates varies between 43% and 55% of actual effort of historical test projects. These results outperformed those of wellknown models when applied in the same context. Further work is being carried out to improve the performance of the proposed model when considering the effect of non-functional requirements.
Abstract: In this paper the multi-mode resource-constrained project scheduling problem with discounted cash flows is considered. Minimizing the makespan and maximization the net present value (NPV) are the two common objectives that have been investigated in the literature. We apply one evolutionary algorithm named multiobjective particle swarm optimization (MOPSO) to find Pareto front solutions. We used standard sets of instances from the project scheduling problem library (PSPLIB). The results are computationally compared respect to different metrics taken from the literature on evolutionary multi-objective optimization.
Abstract: In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.
Abstract: In this paper we propose a novel approach for ascertaining human identity based on fusion of profile face and gait biometric cues The identification approach based on feature learning in PCA-LDA subspace, and classification using multivariate Bayesian classifiers allows significant improvement in recognition accuracy for low resolution surveillance video scenarios. The experimental evaluation of the proposed identification scheme on a publicly available database [2] showed that the fusion of face and gait cues in joint PCA-LDA space turns out to be a powerful method for capturing the inherent multimodality in walking gait patterns, and at the same time discriminating the person identity..
Abstract: Design patterns describe good solutions to common
and reoccurring problems in program design. Applying design
patterns in software design and implementation have significant
effects on software quality metrics such as flexibility, usability,
reusability, scalability and robustness. There is no standard rule for
using design patterns. There are some situations that a pattern is
applied for a specific problem and this pattern uses another pattern.
In this paper, we study the effect of using chain of patterns on
software quality metrics.
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: Cryptography provides the secure manner of
information transmission over the insecure channel. It authenticates
messages based on the key but not on the user. It requires a lengthy
key to encrypt and decrypt the sending and receiving the messages,
respectively. But these keys can be guessed or cracked. Moreover,
Maintaining and sharing lengthy, random keys in enciphering and
deciphering process is the critical problem in the cryptography
system. A new approach is described for generating a crypto key,
which is acquired from a person-s iris pattern. In the biometric field,
template created by the biometric algorithm can only be
authenticated with the same person. Among the biometric templates,
iris features can efficiently be distinguished with individuals and
produces less false positives in the larger population. This type of iris
code distribution provides merely less intra-class variability that aids
the cryptosystem to confidently decrypt messages with an exact
matching of iris pattern. In this proposed approach, the iris features
are extracted using multi resolution wavelets. It produces 135-bit iris
codes from each subject and is used for encrypting/decrypting the
messages. The autocorrelators are used to recall original messages
from the partially corrupted data produced by the decryption process.
It intends to resolve the repudiation and key management problems.
Results were analyzed in both conventional iris cryptography system
(CIC) and non-repudiation iris cryptography system (NRIC). It
shows that this new approach provides considerably high
authentication in enciphering and deciphering processes.
Abstract: An Ad hoc wireless network comprises of mobile
terminals linked and communicating with each other sans the aid of
traditional infrastructure. Optimized Link State Protocol (OLSR) is a
proactive routing protocol, in which routes are discovered/updated
continuously so that they are available when needed. Hello messages
generated by a node seeks information about its neighbor and if the
latter fails to respond to a specified number of hello messages
regulated by neighborhood hold time, the node is forced to assume
that the neighbor is not in range. This paper proposes to evaluate
OLSR routing protocol in a random mobility network having various
neighborhood hold time intervals. The throughput and delivery ratio
are also evaluated to learn about its efficiency for multimedia loads.
Abstract: Key management is a vital component in any modern security protocol. Due to scalability and practical implementation considerations automatic key management seems a natural choice in significantly large virtual private networks (VPNs). In this context IETF Internet Key Exchange (IKE) is the most promising protocol under permanent review. We have made a humble effort to pinpoint IKEv2 net gain over IKEv1 due to recent modifications in its original structure, along with a brief overview of salient improvements between the two versions. We have used US National Institute of Technology NIIST VPN simulator to get some comparisons of important performance metrics.