Abstract: The paper explores the development of an optimization of method and apparatus for retrieving extended high dynamic range from digital negative image. Architectural photo imaging can benefit from high dynamic range imaging (HDRI) technique for preserving and presenting sufficient luminance in the shadow and highlight clipping image areas. The HDRI technique that requires multiple exposure images as the source of HDRI rendering may not be effective in terms of time efficiency during the acquisition process and post-processing stage, considering it has numerous potential imaging variables and technical limitations during the multiple exposure process. This paper explores an experimental method and apparatus that aims to expand the dynamic range from digital negative image in HDRI environment. The method and apparatus explored is based on a single source of RAW image acquisition for the use of HDRI post-processing. It will cater the optimization in order to avoid and minimize the conventional HDRI photographic errors caused by different physical conditions during the photographing process and the misalignment of multiple exposed image sequences. The study observes the characteristics and capabilities of RAW image format as digital negative used for the retrieval of extended high dynamic range process in HDRI environment.
Abstract: Many research works are carried out on the analysis of
traces in a digital learning environment. These studies produce large
volumes of usage tracks from the various actions performed by a
user. However, to exploit these data, compare and improve
performance, several issues are raised. To remedy this, several works
deal with this problem seen recently. This research studied a series of
questions about format and description of the data to be shared. Our
goal is to share thoughts on these issues by presenting our experience
in the analysis of trace-based log files, comparing several approaches
used in automatic classification applied to e-learning platforms.
Finally, the obtained results are discussed.
Abstract: In 2011, Debiao et al. pointed out that S-3PAKE protocol proposed by Lu and Cao for password-authenticated key exchange in the three-party setting is vulnerable to an off-line dictionary attack. Then, they proposed some countermeasures to eliminate the security vulnerability of the S-3PAKE. Nevertheless, this paper points out their enhanced S-3PAKE protocol is still vulnerable to undetectable on-line dictionary attacks unlike their claim.
Abstract: In order to guarantee secure communication for wireless sensor networks (WSNs), many user authentication schemes have successfully drawn researchers- attention and been studied widely. In 2012, He et al. proposed a robust biometric-based user authentication scheme for WSNs. However, this paper demonstrates that He et al.-s scheme has some drawbacks: poor reparability problem, user impersonation attack, and sensor node impersonate attack.
Abstract: Beta-spline is built on G2 continuity which guarantees
smoothness of generated curves and surfaces using it. This curve is
preferred to be used in object design rather than reconstruction. This
study however, employs the Beta-spline in reconstructing a 3-
dimensional G2 image of the Stanford Rabbit. The original data
consists of multi-slice binary images of the rabbit. The result is then
compared with related works using other techniques.
Abstract: The Address Resolution Protocol (ARP) is used by
computers to map logical addresses (IP) to physical addresses
(MAC). However ARP is an all trusting protocol and is stateless
which makes it vulnerable to many ARP cache poisoning attacks
such as Man-in-the-Middle (MITM) and Denial of service (DoS)
attacks. These flaws result in security breaches thus weakening the
appeal of the computer for exchange of sensitive data. In this paper
we describe ARP, outline several possible ARP cache poisoning
attacks and give the detailed of some attack scenarios in network
having both wired and wireless hosts. We have analyzed each of
proposed solutions, identify their strengths and limitations. Finally
get that no solution offers a feasible solution. Hence, this paper
presents an efficient and secure version of ARP that is able to cope
up with all these types of attacks and is also a feasible solution. It is a
stateful protocol, by storing the information of the Request frame in
the ARP cache, to reduce the chances of various types of attacks in
ARP. It is more efficient and secure by broadcasting ARP Reply
frame in the network and storing related entries in the ARP cache
each time when communication take place.
Abstract: The purpose of this research aims to discover the
knowledge for analysis student motivation behavior on e-Learning
based on Data Mining Techniques, in case of the Information
Technology for Communication and Learning Course at Suan
Sunandha Rajabhat University. The data mining techniques was
applied in this research including association rules, classification
techniques. The results showed that using data mining technique can
indicate the important variables that influence the student motivation
behavior on e-Learning.
Abstract: Recent developments in automotive technology are focused on economy, comfort and safety. Vehicle tracking and collision detection systems are attracting attention of many investigators focused on safety of driving in the field of automotive mechatronics. In this paper, a vision-based vehicle detection system is presented. Developed system is intended to be used in collision detection and driver alert. The system uses RGB images captured by a camera in a car driven in the highway. Images captured by the moving camera are used to detect the moving vehicles in the image. A vehicle ahead of the camera is detected in daylight conditions. The proposed method detects moving vehicles by subtracting successive images. Plate height of the vehicle is determined by using a plate recognition algorithm. Distance of the moving object is calculated by using the plate height. After determination of the distance of the moving vehicle relative speed of the vehicle and Time-to-Collision are calculated by using distances measured in successive images. Results obtained in road tests are discussed in order to validate the use of the proposed method.
Abstract: In this paper, a novel corner detection method is
presented to stably extract geometrically important corners.
Intensity-based corner detectors such as the Harris corner can detect
corners in noisy environments but has inaccurate corner position and
misses the corners of obtuse angles. Edge-based corner detectors such
as Curvature Scale Space can detect structural corners but show
unstable corner detection due to incomplete edge detection in noisy
environments. The proposed image-based direct curvature estimation
can overcome limitations in both inaccurate structural corner detection
of the Harris corner detector (intensity-based) and the unstable corner
detection of Curvature Scale Space caused by incomplete edge
detection. Various experimental results validate the robustness of the
proposed method.
Abstract: The use of human hand as a natural interface for humancomputer interaction (HCI) serves as the motivation for research in hand gesture recognition. Vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. In this paper, we use the concept of object-based video abstraction for segmenting the frames into video object planes (VOPs), as used in MPEG-4, with each VOP corresponding to one semantically meaningful hand position. Next, the key VOPs are selected on the basis of the amount of change in hand shape – for a given key frame in the sequence the next key frame is the one in which the hand changes its shape significantly. Thus, an entire video clip is transformed into a small number of representative frames that are sufficient to represent a gesture sequence. Subsequently, we model a particular gesture as a sequence of key frames each bearing information about its duration. These constitute a finite state machine. For recognition, the states of the incoming gesture sequence are matched with the states of all different FSMs contained in the database of gesture vocabulary. The core idea of our proposed representation is that redundant frames of the gesture video sequence bear only the temporal information of a gesture and hence discarded for computational efficiency. Experimental results obtained demonstrate the effectiveness of our proposed scheme for key frame extraction, subsequent gesture summarization and finally gesture recognition.
Abstract: With the rapid development of wireless mobile communication, applications for mobile devices must focus on network security. In 2008, Chang-Chang proposed security improvements on the Lu et al.-s elliptic curve authentication key agreement protocol for wireless mobile networks. However, this paper shows that Chang- Chang-s improved protocol is still vulnerable to off-line password guessing attacks unlike their claims.
Abstract: In this paper, we present two new ranking and unranking
algorithms for k-ary trees represented by x-sequences in Gray
code order. These algorithms are based on a gray code generation algorithm
developed by Ahrabian et al.. In mentioned paper, a recursive
backtracking generation algorithm for x-sequences corresponding to
k-ary trees in Gray code was presented. This generation algorithm
is based on Vajnovszki-s algorithm for generating binary trees in
Gray code ordering. Up to our knowledge no ranking and unranking
algorithms were given for x-sequences in this ordering. we present
ranking and unranking algorithms with O(kn2) time complexity for
x-sequences in this Gray code ordering
Abstract: In this paper, we focused primarily on Istanbul data
that is gathered by using intelligent transportation systems (ITS), and
considered the developments in traffic information delivery and
future applications that are being planned for implementation. Since
traffic congestion is increasing and travel times are becoming less
consistent and less predictable, traffic information delivery has
become a critical issue. Considering the fuel consumption and wasted
time in traffic, advanced traffic information systems are becoming
increasingly valuable which enables travelers to plan their trips more
accurately and easily.
Abstract: In this paper we describe a hybrid technique of Minimax search and aggregate Mahalanobis distance function synthesis to evolve Awale game player. The hybrid technique helps to suggest a move in a short amount of time without looking into endgame database. However, the effectiveness of the technique is heavily dependent on the training dataset of the Awale strategies utilized. The evolved player was tested against Awale shareware program and the result is appealing.
Abstract: In this paper, we propose ablock-wise watermarking scheme for color image authentication to resist malicious tampering of digital media. The thresholding technique is incorporated into the scheme such that the tampered region of the color image can be recovered with high quality while the proofing result is obtained. The watermark for each block consists of its dual authentication data and the corresponding feature information. The feature information for recovery iscomputed bythe thresholding technique. In the proofing process, we propose a dual-option parity check method to proof the validity of image blocks. In the recovery process, the feature information of each block embedded into the color image is rebuilt for high quality recovery. The simulation results show that the proposed watermarking scheme can effectively proof the tempered region with high detection rate and can recover the tempered region with high quality.
Abstract: In this paper a unified approach via block-pulse functions (BPFs) or shifted Legendre polynomials (SLPs) is presented to solve the linear-quadratic-Gaussian (LQG) control problem. Also a recursive algorithm is proposed to solve the above problem via BPFs. By using the elegant operational properties of orthogonal functions (BPFs or SLPs) these computationally attractive algorithms are developed. To demonstrate the validity of the proposed approaches a numerical example is included.
Abstract: Acoustic Imaging based sound localization using microphone
array is a challenging task in digital-signal processing.
Discrete Fourier transform (DFT) based near-field acoustical holography
(NAH) is an important acoustical technique for sound source
localization and provide an efficient solution to the ill-posed problem.
However, in practice, due to the usage of small curtailed aperture
and its consequence of significant spectral leakage, the DFT could
not reconstruct the active-region-of-sound (AROS) effectively, especially
near the edges of aperture. In this paper, we emphasize the
fundamental problems of DFT-based NAH, provide a solution to
spectral leakage effect by the extrapolation based on linear predictive
coding and 2D Tukey windowing. This approach has been tested to
localize the single and multi-point sound sources. We observe that
incorporating extrapolation technique increases the spatial resolution,
localization accuracy and reduces spectral leakage when small curtail
aperture with a lower number of sensors accounts.
Abstract: In this paper a combined feature selection method is
proposed which takes advantages of sample domain filtering,
resampling and feature subset evaluation methods to reduce
dimensions of huge datasets and select reliable features. This method
utilizes both feature space and sample domain to improve the process
of feature selection and uses a combination of Chi squared with
Consistency attribute evaluation methods to seek reliable features.
This method consists of two phases. The first phase filters and
resamples the sample domain and the second phase adopts a hybrid
procedure to find the optimal feature space by applying Chi squared,
Consistency subset evaluation methods and genetic search.
Experiments on various sized datasets from UCI Repository of
Machine Learning databases show that the performance of five
classifiers (Naïve Bayes, Logistic, Multilayer Perceptron, Best First
Decision Tree and JRIP) improves simultaneously and the
classification error for these classifiers decreases considerably. The
experiments also show that this method outperforms other feature
selection methods.
Abstract: This paper presents a design and prototype
implementation of new home automation system that uses WiFi
technology as a network infrastructure connecting its parts. The
proposed system consists of two main components; the first part is
the server (web server), which presents system core that manages,
controls, and monitors users- home. Users and system administrator
can locally (LAN) or remotely (internet) manage and control system
code. Second part is hardware interface module, which provides
appropriate interface to sensors and actuator of home automation
system. Unlike most of available home automation system in the
market the proposed system is scalable that one server can manage
many hardware interface modules as long as it exists on WiFi
network coverage. System supports a wide range of home
automation devices like power management components, and
security components. The proposed system is better from the
scalability and flexibility point of view than the commercially
available home automation systems.
Abstract: In recent years there has been renewal of interest in the
relation between Green IT and Cloud Computing. The growing use of
computers in cloud platform has caused marked energy consumption,
putting negative pressure on electricity cost of cloud data center. This
paper proposes an effective mechanism to reduce energy utilization in
cloud computing environments. We present initial work on the
integration of resource and power management that aims at reducing
power consumption. Our mechanism relies on recalling virtualization
services dynamically according to user-s virtualization request and
temporarily shutting down the physical machines after finish in order
to conserve energy. Given the estimated energy consumption, this
proposed effort has the potential to positively impact power
consumption. The results from the experiment concluded that energy
indeed can be saved by powering off the idling physical machines in
cloud platforms.