Abstract: In view of the present cloud security problem has increasingly become one of the major obstacles hindering the development of the cloud computing, put forward a kind of memory based on Xen cloud environment security isolation technology implementation. And based on Xen virtual machine monitor system, analysis of the model of memory virtualization is implemented, using Xen memory virtualization system mechanism of super calls and grant table, based on the virtual machine manager internal implementation of access control module (ACM) to design the security isolation system memory. Experiments show that, the system can effectively isolate different customer domain OS between illegal access to memory data.
Abstract: With the ubiquitous computing’s emergence and the evolution of enterprises’ needs, one of the main challenges is to build context-aware applications based on Web services. These applications have become particularly relevant in the pervasive computing domain. In this paper, we introduce our approach that optimizes the use of Web services with context notions when dealing with contextual environments. We focus particularly on making Web services autonomous and natively context-aware. We implement and evaluate the proposed approach with a pedagogical example of a context-aware Web service treating temperature values.
Abstract: A good web design is a prerequisite for a successful business nowadays, especially since the internet is the most common way for people to inform themselves. Web design includes the optical composition, the structure, and the user guidance of websites. The importance of each website leads to the question if there is a way to measure its usefulness. The aim of this paper is to suggest a methodology for the evaluation of web design. The desired outcome is to have an evaluation that is concentrated on a specific website and its target group.
Abstract: Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.
Abstract: Hidden Markov Model (HMM) has been used in prediction and determination of states that generate different neural activations as well as mental working conditions. This paper addresses two applications of HMM; one to determine the optimal sequence of states for two neural states: Active (AC) and Inactive (IA) for the three emission (observations) which are for No Working (NW), Waiting (WT) and Working (W) conditions of human beings. Another is for the determination of optimal sequence of intentionality i.e. Believe (B), Desire (D), and Intention (I) as the states and three observational sequences: NW, WT and W. The computational results are encouraging and useful.
Abstract: This paper presents a four-dimensional computational
model, k-neighborhood template A-type three-dimensional bounded
cellular acceptor (abbreviated as A-3BCA(k)), and discusses the
hierarchical properties. An A-3BCA(k) is a four-dimensional
automaton which consists of a pair of a converter and a
configuration-reader. The former converts the given four-dimensional
tape to the three- and two- dimensional configuration and
the latter determines the acceptance or nonacceptance of given
four-dimensional tape whether or not the derived two-dimensional
configuration is accepted. We mainly investigate the difference of the
accepting power based on the difference of the configuration-reader.
It is shown that the difference of the accepting power of the
configuration-reader tends to affect directly that of the A-3BCA(k)
for the case when the converter is deterministic. On the other hand,
results are not analogous for the nondeterministic case.
Abstract: In recent years, a multi-antenna system is actively used
to improve the performance of the communication. A MIMO-OFDM
system can provide multiplexing gain or diversity gain. These gains
are obtained in proportion to the increase of the number of antennas.
In order to provide the optimal gain of the MIMO-OFDM system,
various transmission and reception schemes are presented. This paper
aims to propose a hybrid scheme that base station provides both
diversity gain and multiplexing gain at the same time.
Abstract: Wireless Sensor Networks (WSNs) have many advantages. Their deployment is easier and faster than wired sensor networks or other wireless networks, as they do not need fixed infrastructure. Nodes are partitioned into many small groups named clusters to aggregate data through network organization. WSN clustering guarantees performance achievement of sensor nodes. Sensor nodes energy consumption is reduced by eliminating redundant energy use and balancing energy sensor nodes use over a network. The aim of such clustering protocols is to prolong network life. Low Energy Adaptive Clustering Hierarchy (LEACH) is a popular protocol in WSN. LEACH is a clustering protocol in which the random rotations of local cluster heads are utilized in order to distribute energy load among all sensor nodes in the network. This paper proposes Connected Dominant Set (CDS) based cluster formation. CDS aggregates data in a promising approach for reducing routing overhead since messages are transmitted only within virtual backbone by means of CDS and also data aggregating lowers the ratio of responding hosts to the hosts existing in virtual backbones. CDS tries to increase networks lifetime considering such parameters as sensors lifetime, remaining and consumption energies in order to have an almost optimal data aggregation within networks. Experimental results proved CDS outperformed LEACH regarding number of cluster formations, average packet loss rate, average end to end delay, life computation, and remaining energy computation.
Abstract: This paper presents a scheme for the protection of loop system from all type of faults using the direction of fault current. The presence of distributed generation in today’s system increases the complexity of fault detection as the power flow is bidirectional. Hence, protection scheme specific to this purpose needs to be developed. This paper shows a fast protection scheme using communication which can be fiber optic or wireless. In this paper, the possibility of wireless communication for protection is studied to exchange the information between the relays. The negative sequence and positive sequence directional elements are used to determine the direction of fault current. A PSCAD simulation is presented and validated using commercial SEL relays.
Abstract: Rough set theory is used to handle uncertainty and incomplete information by applying two accurate sets, Lower approximation and Upper approximation. In this paper, the rough clustering algorithms are improved by adopting the Similarity, Dissimilarity–Similarity and Entropy based initial centroids selection method on three different clustering algorithms namely Entropy based Rough K-Means (ERKM), Similarity based Rough K-Means (SRKM) and Dissimilarity-Similarity based Rough K-Means (DSRKM) were developed and executed by yeast dataset. The rough clustering algorithms are validated by cluster validity indexes namely Rand and Adjusted Rand indexes. An experimental result shows that the ERKM clustering algorithm perform effectively and delivers better results than other clustering methods. Outlier detection is an important task in data mining and very much different from the rest of the objects in the clusters. Entropy based Rough Outlier Factor (EROF) method is seemly to detect outlier effectively for yeast dataset. In rough K-Means method, by tuning the epsilon (ᶓ) value from 0.8 to 1.08 can detect outliers on boundary region and the RKM algorithm delivers better results, when choosing the value of epsilon (ᶓ) in the specified range. An experimental result shows that the EROF method on clustering algorithm performed very well and suitable for detecting outlier effectively for all datasets. Further, experimental readings show that the ERKM clustering method outperformed the other methods.
Abstract: The security of the medical images and its related data is the major research area which is to be concentrated in today’s era. Security in the medical image indicates that the physician may hide patients’ related data in the medical image and transfer it safely to a defined location using reversible watermarking. Many reversible watermarking methods had proposed over the decade. This paper enhances the security level in brain tumor images to hide the patient’s detail, which has to be conferred with other physician’s suggestions. The details or the information will be hidden in Non-ROI area of the image by using the block cipher algorithm. The block cipher uses different keys to extract the details that are difficult for the intruder to detect all the keys and to spot the details, which are the key advantage of this method. The ROI is the tumor area and Non-ROI is the area rest of ROI. The Non-ROI should not be spoiled in any cause and the details in the Non-ROI should be extracted correctly. The reversible watermarking method proposed in this paper performs well when compared to existing methods in the process of extraction of an original image and providing information security.
Abstract: This article discusses the passage of RDB to XML
documents (schema and data) based on metadata and semantic
enrichment, which makes the RDB under flattened shape and is
enriched by the object concept. The integration and exploitation of
the object concept in the XML uses a syntax allowing for the
verification of the conformity of the document XML during the
creation. The information extracted from the RDB is therefore
analyzed and filtered in order to adjust according to the structure of
the XML files and the associated object model. Those implemented
in the XML document through a SQL query are built dynamically. A
prototype was implemented to realize automatic migration, and so
proves the effectiveness of this particular approach.
Abstract: Health of a person plays a vital role in the collective
health of his community and hence the well-being of the society as a
whole. But, in today’s fast paced technology driven world, health
issues are increasingly being associated with human behaviors – their
lifestyle. Social networks have tremendous impact on the health
behavior of individuals. Many researchers have used social network
analysis to understand human behavior that implicates their social
and economic environments. It would be interesting to use a similar
analysis to understand human behaviors that have health
implications. This paper focuses on concepts of those behavioural
analyses that have health implications using social networks analysis
and provides possible algorithmic approaches. The results of these
approaches can be used by the governing authorities for rolling out
health plans, benefits and take preventive measures, while the
pharmaceutical companies can target specific markets, helping health
insurance companies to better model their insurance plans.
Abstract: This paper deals with the problem of management of
information resources in libraries of the public institution Sultan
Moulay Slimane University (SMSU) in order to analyze the
satisfaction of the readers, and allow university leaders to make better
strategic and instant decisions. For this, the integration of an
integrated management decision library system is a priority program
of higher education, as part of the Digital Morocco, which has a
proactive policy to develop the use of new technologies information
and communication in higher institutions. This operational
information system can provide better services to the students and for
the leaders. Our approach is to integrate the tools of business
intelligence (BI) in the library management by using power BI.
Abstract: This work is on decision tree-based classification for
the disbursement of scholarship. Tree-based data mining
classification technique is used in other to determine the generic rule
to be used to disburse the scholarship. The system based on the
defined rules from the tree is able to determine the class (status) to
which an applicant shall belong whether Granted or Not Granted. The
applicants that fall to the class of granted denote a successful
acquirement of scholarship while those in not granted class are
unsuccessful in the scheme. An algorithm that can be used to classify
the applicants based on the rules from tree-based classification was
also developed. The tree-based classification is adopted because of its
efficiency, effectiveness, and easy to comprehend features. The
system was tested with the data of National Information Technology
Development Agency (NITDA) Abuja, a Parastatal of Federal
Ministry of Communication Technology that is mandated to develop
and regulate information technology in Nigeria. The system was
found working according to the specification. It is therefore
recommended for all scholarship disbursement organizations.
Abstract: Computer aided diagnosis systems provide vital
opinion to radiologists in the detection of early signs of breast cancer
from mammogram images. Architectural distortions, masses and
microcalcifications are the major abnormalities. In this paper, a
computer aided diagnosis system has been proposed for
distinguishing abnormal mammograms with architectural distortion
from normal mammogram. Four types of texture features GLCM
texture, GLRLM texture, fractal texture and spectral texture features
for the regions of suspicion are extracted. Support vector machine
has been used as classifier in this study. The proposed system yielded
an overall sensitivity of 96.47% and an accuracy of 96% for
mammogram images collected from digital database for screening
mammography database.
Abstract: In this paper, we present a new segmentation approach
for focal liver lesions in contrast enhanced ultrasound imaging. This
approach, based on a two-cluster Fuzzy C-Means methodology,
considers type-II fuzzy sets to handle uncertainty due to the image
modality (presence of speckle noise, low contrast, etc.), and to
calculate the optimum inter-cluster threshold. Fine boundaries are
detected by a local recursive merging of ambiguous pixels. The
method has been tested on a representative database. Compared to
both Otsu and type-I Fuzzy C-Means techniques, the proposed
method significantly reduces the segmentation errors.
Abstract: In this article, we deal with a variant of the classical
course timetabling problem that has a practical application in many
areas of education. In particular, in this paper we are interested in
high schools remedial courses. The purpose of such courses is to
provide under-prepared students with the skills necessary to succeed
in their studies. In particular, a student might be under prepared in
an entire course, or only in a part of it. The limited availability
of funds, as well as the limited amount of time and teachers at
disposal, often requires schools to choose which courses and/or which
teaching units to activate. Thus, schools need to model the training
offer and the related timetabling, with the goal of ensuring the
highest possible teaching quality, by meeting the above-mentioned
financial, time and resources constraints. Moreover, there are some
prerequisites between the teaching units that must be satisfied. We
first present a Mixed-Integer Programming (MIP) model to solve
this problem to optimality. However, the presence of many peculiar
constraints contributes inevitably in increasing the complexity of
the mathematical model. Thus, solving it through a general-purpose
solver may be performed for small instances only, while solving
real-life-sized instances of such model requires specific techniques
or heuristic approaches. For this purpose, we also propose a heuristic
approach, in which we make use of a fast constructive procedure
to obtain a feasible solution. To assess our exact and heuristic
approaches we perform extensive computational results on both
real-life instances (obtained from a high school in Lecce, Italy) and
randomly generated instances. Our tests show that the MIP model is
never solved to optimality, with an average optimality gap of 57%.
On the other hand, the heuristic algorithm is much faster (in about the
50% of the considered instances it converges in approximately half of
the time limit) and in many cases allows achieving an improvement
on the objective function value obtained by the MIP model. Such an
improvement ranges between 18% and 66%.
Abstract: Localization of nodes is one of the key issues of
Wireless Sensor Network (WSN) that gained a wide attention in
recent years. The existing localization techniques can be generally
categorized into two types: range-based and range-free. Compared
with rang-based schemes, the range-free schemes are more costeffective,
because no additional ranging devices are needed. As a
result, we focus our research on the range-free schemes. In this paper
we study three types of range-free location algorithms to compare the
localization error and energy consumption of each one. Centroid
algorithm requires a normal node has at least three neighbor anchors,
while DV-hop algorithm doesn’t have this requirement. The third
studied algorithm is the amorphous algorithm similar to DV-Hop
algorithm, and the idea is to calculate the hop distance between two
nodes instead of the linear distance between them. The simulation
results show that the localization accuracy of the amorphous
algorithm is higher than that of other algorithms and the energy
consumption does not increase too much.
Abstract: Because current wireless communication requires high
reliability in a limited bandwidth environment, this paper proposes
the variable modulation scheme based on the codebook. The variable
modulation scheme adjusts transmission power using the codebook in
accordance with channel state. Also, if the codebook is composed of
many bits, the reliability is more improved by the proposed scheme.
The simulation results show that the performance of proposed scheme
has better reliability than the the performance of conventional scheme.