Abstract: Business Processes (BPs) are the key instrument to
understand how companies operate at an organizational level, taking
an as-is view of the workflow, and how to address their issues by
identifying a to-be model. In last year’s, the BP Model and Notation
(BPMN) has become a de-facto standard for modeling processes.
However, this standard does not incorporate explicitly the Problem-
Solving (PS) knowledge in the Process Modeling (PM) results. Thus,
such knowledge cannot be shared or reused. To narrow this gap is
today a challenging research area. In this paper we present a
framework able to capture the PS knowledge and to improve a
workflow. This framework extends the BPMN specification by
incorporating new general-purpose elements. A pilot scenario is also
presented and discussed.
Abstract: Medical Image fusion plays a vital role in medical
field to diagnose the brain tumors which can be classified as benign
or malignant. It is the process of integrating multiple images of the
same scene into a single fused image to reduce uncertainty and
minimizing redundancy while extracting all the useful information
from the source images. Fuzzy logic is used to fuse two brain MRI
images with different vision. The fused image will be more
informative than the source images. The texture and wavelet features
are extracted from the fused image. The multilevel Adaptive Neuro
Fuzzy Classifier classifies the brain tumors based on trained and
tested features. The proposed method achieved 80.48% sensitivity,
99.9% specificity and 99.69% accuracy. Experimental results
obtained from fusion process prove that the use of the proposed
image fusion approach shows better performance while compared
with conventional fusion methodologies.
Abstract: A dual tiered network model is designed to overcome the problem of energy alert and fault tolerance. This model minimizes the delay time and overcome failure of links. Performance analysis of the dual tiered network model is studied in this paper where the CA and LS schemes are compared with DEO optimal. We then evaluate the Integrated Network Topological Control and Key Management (INTK) Schemes, which was proposed to add security features of the wireless sensor networks. Clustering efficiency, level of protections, the time complexity is some of the parameters of INTK scheme that were analyzed. We then evaluate the Cluster based Energy Competent n-coverage scheme (CEC n-coverage scheme) to ensure area coverage for wireless sensor networks.
Abstract: In this paper, a new method for multi criteria decision making is represented whichspecifies a trajectory satisfying desired criteria including minimization of time. A rescue robot is defined to perform certain tasks before the arrival of rescue team, including evaluation of the probability of explosion in the area, detecting human-beings, and providing preliminary aidsin case of identifying signs of life, so that the security of the surroundings will have enhanced significantly for the individuals inside the disaster zone as well as the rescue team. The main idea behind our technique is using the Program Evaluation and Review Technique analysis along with Critical Path Method and use the Multi Criteria Decision Making (MCDM) method to decidewhich set of activities must be performed first. Since the disastrous event in one area may be well contagious to others, it is one of the robot's priorities to evaluate the relative adversity of the situation, using the above methods and prioritize its mission.
Abstract: Homemade HPC clusters are widely used in many small labs, because they are easy to build and cost-effective. Even though incremental growth is an advantage of clusters, it results in heterogeneous systems anyhow. Instead of adding new nodes to the cluster, we can extend clusters to include some other Internet servers working independently on the same LAN, so that we can make use of their idle times, especially during the night. However extension across a firewall raises some security problems with NFS. In this paper, we propose a method to solve such a problem using SSH tunneling, and suggest a modified structure of the cluster that implements it.
Abstract: The amount of energy the world uses doubles every 20 years. Green homes play an important role in reducing the residential energy demand. This paper presents a platform that is intended to learn the behavior of home residents and build a profile about their habits and actions. The proposed resident aware home controller intervenes in the operation of home appliances in order to save energy without compromising the convenience of the residents. The presented platform can be used to simulate the actions and movements happening inside a home. The paper includes several optimization techniques that are meant to save energy in the home. In addition, several test scenarios are presented that show how the controller works. Moreover, this paper shows the computed actual savings when each of the presented techniques is implemented in a typical home. The test scenarios have validated that the techniques developed are capable of effectively saving energy at homes.
Abstract: In this paper, we present a recommendation library application on Android system. The objective of this system is to support and advice user to use library resources based on mobile application. We describe the design approaches and functional components of this system. The system was developed based on under association rules, Apriori algorithm. In this project, it was divided the result by the research purposes into 2 parts: developing the Mobile application for online library service and testing and evaluating the system. Questionnaires were used to measure user satisfaction with system usability by specialists and users. The results were satisfactory both specialists and users.
Abstract: Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.
Abstract: In Knowledge and Data Engineering field, relational
database is the best repository to store data in a real world. It has
been using around the world more than eight decades. Normalization
is the most important process for the analysis and design of relational
databases. It aims at creating a set of relational tables with minimum
data redundancy that preserve consistency and facilitate correct
insertion, deletion, and modification. Normalization is a major task in
the design of relational databases. Despite its importance, very few
algorithms have been developed to be used in the design of
commercial automatic normalization tools. It is also rare technique to
do it automatically rather manually. Moreover, for a large and
complex database as of now, it make even harder to do it manually.
This paper presents a new complete automated relational database
normalization method. It produces the directed graph and spanning
tree, first. It then proceeds with generating the 2NF, 3NF and also
BCNF normal forms. The benefit of this new algorithm is that it can
cope with a large set of complex function dependencies.
Abstract: We describe a relationship between integral images and
differential images. First, we derive a simple difference filter from
conventional integral image. In the derivation, we show that an
integral image and the corresponding differential image are related
to each other by simultaneous linear equations, where the numbers
of unknowns and equations are the same, and therefore, we can
execute the integration and differentiation by solving the simultaneous
equations. We applied the relationship to an image fusion problem,
and experimentally verified the effectiveness of the proposed method.
Abstract: Shifted polynomial basis (SPB) is a variation of
polynomial basis representation. SPB has potential for efficient
bit level and digi -level implementations of multiplication over
binary extension fields with subquadratic space complexity. For
efficient implementation of pairing computation with large finite
fields, this paper presents a new SPB multiplication algorithm based
on Karatsuba schemes, and used that to derive a novel scalable
multiplier architecture. Analytical results show that the proposed
multiplier provides a trade-off between space and time complexities.
Our proposed multiplier is modular, regular, and suitable for very
large scale integration (VLSI) implementations. It involves less
area complexity compared to the multipliers based on traditional
decomposition methods. It is therefore, more suitable for efficient
hardware implementation of pairing based cryptography and elliptic
curve cryptography (ECC) in constraint driven applications.
Abstract: Let maxζG(m) denote the maximum number of edges in a subgraph of graph G induced by m nodes. The n-dimensional augmented cube, denoted as AQn, a variation of the hypercube, possesses some properties superior to those of the hypercube. We study the cases when G is the augmented cube AQn.
Abstract: Optical Burst Switching (OBS) is a promising technology for the future generation Internet. Control architecture and Contention resolution are the main issues faced by the Optical Burst Switching networks. In this paper we are only taking care of the Contention problem and to overcome this issue we propose Pre-Deflection Routing with Control Packet Signal Scheme for Contention Resolution in Optical Burst Switch Networks. In this paper Pre-deflection routing approach has been proposed in which routing is carried out in two ways, Shortest Path First (SPF) and Least Hop First (LHF) Routing to forward the clusters and canoes respectively. Hereafter Burst Offset Time Control Algorithm has been proposed where a forward control packet (FCP) collects the congestion price and contention price along its paths. Thereafter a reverse-direction control packet (RCP) sent by destination node which delivers the information of FCP to the source node, and source node uses this information to revise its offset time and burst length.
Abstract: This paper designs an intelligent guidance system, based on wireless sensor networks, for efficient parking in parking lots. The proposed system consists of a parking space allocation subsystem, a parking space monitoring subsystem, a driving guidance subsystem, and a vehicle detection subsystem. In the system, we propose a novel and effective virtual coordinate system for sensing and displaying devices to determine the proper vacant parking space and provide the precise guidance to the driver. This study constructs a ZigBee-based wireless sensor network on Arduino platform and implements the prototype of the proposed system using Arduino-based complements. Experimental results confirm that the proposed prototype can not only work well, but also provide drivers the correct parking information.
Abstract: Diabetic retinopathy is characterized by the development of retinal microaneurysms. The damage can be prevented if disease is treated in its early stages. In this paper, we are comparing Support Vector Machine (SVM) and Naïve Bayes (NB) classifiers for automatic microaneurysm detection in images acquired through non-dilated pupils. The Nearest Neighbor classifier is used as a baseline for comparison. Detected microaneurysms are validated with expert ophthalmologists’ hand-drawn ground-truths. The sensitivity, specificity, precision and accuracy of each method are also compared.
Abstract: In this paper, a multi-focus image fusion method using Spatial Frequency Measurements (SFM) and Wavelet Packet was proposed. The proposed fusion approach, firstly, the two fused images were transformed and decomposed into sixteen subbands using Wavelet packet. Next, each subband was partitioned into sub-blocks and each block was identified the clearer regions by using the Spatial Frequency Measurement (SFM). Finally, the recovered fused image was reconstructed by performing the Inverse Wavelet Transform. From the experimental results, it was found that the proposed method outperformed the traditional SFM based methods in terms of objective and subjective assessments.
Abstract: We present a method for dehazing images. A dark
envelope image is derived with the bilateral minimum filter and a
bright envelope is derived with the bilateral maximum filter. The
ambient light and transmission of the scene are estimated from these
two envelope images. An image without haze is reconstructed from
the estimated ambient light and transmission.
Abstract: The paper focuses on the problem of the point
correspondence matching in stereo images. The proposed matching
algorithm is based on the combination of simpler methods such as
normalized sum of squared differences (NSSD) and a more complex
phase correlation based approach, by considering the noise and other
factors, as well. The speed of NSSD and the preciseness of the
phase correlation together yield an efficient approach to find the best
candidate point with sub-pixel accuracy in stereo image pairs. The
task of the NSSD in this case is to approach the candidate pixel
roughly. Afterwards the location of the candidate is refined by an
enhanced phase correlation based method which in contrast to the
NSSD has to run only once for each selected pixel.
Abstract: The spread of Web 2.0 has caused user-generated content explosion. Users can tag resources to describe and organize
them. Tag clouds provide rough impression of relative importance of
each tag within overall cloud in order to facilitate browsing among
numerous tags and resources. The goal of our paper is to enrich
visualization of tag clouds. A font distribution algorithm has been
proposed to calculate a novel metric based on frequency and content,
and to classify among classes from this metric based on power
law distribution and percentages. The suggested algorithm has been
validated and verified on the tag cloud of a real-world thesis portal.
Abstract: The proliferation of multimedia technology and services in today’s world provide ample research scope in the frontiers of visual signal processing. Wide spread usage of video based applications in heterogeneous environment needs viable methods of Video Quality Assessment (VQA). The evaluation of video quality not only depends on high QoS requirements but also emphasis the need of novel term ‘QoE’ (Quality of Experience) that perceive video quality as user centric. This paper discusses two vital video quality assessment methods namely, subjective and objective assessment methods. The evolution of various video quality metrics, their classification models and applications are reviewed in this work. The Mean Opinion Score (MOS) based subjective measurements and algorithm based objective metrics are discussed and their challenges are outlined. Further, this paper explores the recent progress of VQA in emerging technologies such as mobile video and 3D video.