Evaluating per-user Fairness of Goal-Oriented Parallel Computer Job Scheduling Policies
Fair share objective has been included into the goaloriented
parallel computer job scheduling policy recently. However,
the previous work only presented the overall scheduling performance.
Thus, the per-user performance of the policy is still lacking. In this
work, the details of per-user fair share performance under the
Tradeoff-fs(Tx:avgX) policy will be further evaluated. A basic fair
share priority backfill policy namely RelShare(1d) is also studied.
The performance of all policies is collected using an event-driven
simulator with three real job traces as input. The experimental results
show that the high demand users are usually benefited under most
policies because their jobs are large or they have a lot of jobs. In the
large job case, one job executed may result in over-share during that
period. In the other case, the jobs may be backfilled for
performances. However, the users with a mixture of jobs may suffer
because if the smaller jobs are executing the priority of the remaining
jobs from the same user will be lower. Further analysis does not show
any significant impact of users with a lot of jobs or users with a large
runtime approximation error.
An Improved Integer Frequency Offset Estimator using the P1 Symbol for OFDM System
This paper suggests an improved integer frequency
offset (IFO) estimation scheme using P1 symbol for orthogonal
frequency division multiplexing (OFDM) based the second generation
terrestrial digital video broadcasting (DVB-T2) system. Proposed
IFO estimator is designed by a low-complexity blind IFO estimation
scheme, which is implemented with complex additions. Also, we
propose active carriers (ACs) selection scheme in order to prevent
performance degradation in blind IFO estimation. The simulation
results show that under the AWGN and TU6 channels, the proposed
method has low complexity than conventional method and almost
similar performance in comparison with the conventional method.
The Balanced Hamiltonian Cycle on the Toroidal Mesh Graphs
The balanced Hamiltonian cycle problemis a quiet new topic of graph theorem. Given a graph G = (V, E), whose edge set can be partitioned into k dimensions, for positive integer k and a Hamiltonian cycle C on G. The set of all i-dimensional edge of C, which is a subset by E(C), is denoted as Ei(C).
Efficient Hardware Implementation of an Elliptic Curve Cryptographic Processor Over GF (2 163)
A new and highly efficient architecture for elliptic curve scalar point multiplication which is optimized for a binary field recommended by NIST and is well-suited for elliptic curve cryptographic (ECC) applications is presented. To achieve the maximum architectural and timing improvements we have reorganized and reordered the critical path of the Lopez-Dahab scalar point multiplication architecture such that logic structures are implemented in parallel and operations in the critical path are diverted to noncritical paths. With G=41, the proposed design is capable of performing a field multiplication over the extension field with degree 163 in 11.92 s with the maximum achievable frequency of 251 MHz on Xilinx Virtex-4 (XC4VLX200) while 22% of the chip area is occupied, where G is the digit size of the underlying digit-serial finite field multiplier.
A Short Reflection on the Strengths and Weaknesses of Simulation Optimization
The paper provides the basic overview of simulation optimization. The procedure of its practical using is demonstrated on the real example in simulator Witness. The simulation optimization is presented as a good tool for solving many problems in real praxis especially in production systems. The authors also characterize their own experiences and they mention the strengths and weakness of simulation optimization.
Enabling Automated Deployment for Cluster Computing in Distributed PC Classrooms
The rapid improvement of the microprocessor and network has made it possible for the PC cluster to compete with conventional supercomputers. Lots of high throughput type of applications can be satisfied by using the current desktop PCs, especially for those in PC classrooms, and leave the supercomputers for the demands from large scale high performance parallel computations. This paper presents our development on enabling an automated deployment mechanism for cluster computing to utilize the computing power of PCs such as reside in PC classroom. After well deployment, these PCs can be transformed into a pre-configured cluster computing resource immediately without touching the existing education/training environment installed on these PCs. Thus, the training activities will not be affected by this additional activity to harvest idle computing cycles. The time and manpower required to build and manage a computing platform in geographically distributed PC classrooms also can be reduced by this development.
Simulation of Activity Stream inside Energy Social Business Environment using Assemblage Theory and Simplicial Complex Tool
Social, mobility and information aggregation inside
business environment need to converge to reach the next step of
collaboration to enhance interaction and innovation. The following
article is based on the “Assemblage" concept seen as a framework to
formalize new user interfaces and applications. The area of research
is the Energy Social Business Environment, especially the Energy
Smart Grids, which are considered as functional and technical
foundations of the revolution of the Energy Sector of tomorrow. The
assemblages are modelized by means of mereology and simplicial
complexes. Its objective is to offer new central attention and
decision-making tools to end-users.
The Research of Fuzzy Classification Rules Applied to CRM
In the era of great competition, understanding and satisfying
customers- requirements are the critical tasks for a company
to make a profits. Customer relationship management (CRM) thus
becomes an important business issue at present. With the help of
the data mining techniques, the manager can explore and analyze
from a large quantity of data to discover meaningful patterns and
rules. Among all methods, well-known association rule is most
commonly seen. This paper is based on Apriori algorithm and uses
genetic algorithms combining a data mining method to discover fuzzy
classification rules. The mined results can be applied in CRM to
help decision marker make correct business decisions for marketing
Applying Fuzzy Analytic Hierarchy Process for Evaluating Service Quality of Online Auction
This paper applies fuzzy AHP to evaluate the service
quality of online auction. Service quality is a composition of various
criteria. Among them many intangible attributes are difficult to
measure. This characteristic introduces the obstacles for respondents
on reply in the survey. So as to overcome this problem, we invite
fuzzy set theory into the measurement of performance and use AHP in
obtaining criteria. We found the most concerned dimension of service
quality is Transaction Safety Mechanism and the least is Charge Item.
Other criteria such as information security, accuracy and information
are too vital.
High Capacity Data Hiding based on Predictor and Histogram Modification
In this paper, we propose a high capacity image hiding
technology based on pixel prediction and the difference of modified histogram. This approach is used the pixel prediction and the
difference of modified histogram to calculate the best embedding point.
This approach can improve the predictive accuracy and increase the pixel difference to advance the hiding capacity. We also use the
histogram modification to prevent the overflow and underflow. Experimental results demonstrate that our proposed method within the
same average hiding capacity can still keep high quality of image and low distortion
A Methodology for Data Migration between Different Database Management Systems
In present days the area of data migration is very topical. Current tools for data migration in the area of relational database have several disadvantages that are presented in this paper. We propose a methodology for data migration of the database tables and their data between various types of relational database systems (RDBMS). The proposed methodology contains an expert system. The expert system contains a knowledge base that is composed of IFTHEN rules and based on the input data suggests appropriate data types of columns of database tables. The proposed tool, which contains an expert system, also includes the possibility of optimizing the data types in the target RDBMS database tables based on processed data of the source RDBMS database tables. The proposed expert system is shown on data migration of selected database of the source RDBMS to the target RDBMS.
Building a Trend Based Segmentation Method with SVR Model for Stock Turning Detection
This research focus on developing a new segmentation method for improving forecasting model which is call trend based segmentation method (TBSM). Generally, the piece-wise linear representation (PLR) can finds some of pair of trading points is well for time series data, but in the complicated stock environment it is not well for stock forecasting because of the stock has more trends of trading. If we consider the trends of trading in stock price for the trading signal which it will improve the precision of forecasting model. Therefore, a TBSM with SVR model used to detect the trading points for various stocks of Taiwanese and America under different trend tendencies. The experimental results show our trading system is more profitable and can be implemented in real time of stock market
A Robust Frequency Offset Estimation Scheme for OFDM System with Cyclic Delay Diversity
Cyclic delay diversity (CDD) is a simple technique to
intentionally increase frequency selectivity of channels for orthogonal
frequency division multiplexing (OFDM).This paper proposes a residual
carrier frequency offset (RFO) estimation scheme for OFDMbased
broadcasting system using CDD. In order to improve the RFO
estimation, this paper addresses a decision scheme of the amount of
cyclic delay and pilot pattern used to estimate the RFO. By computer
simulation, the proposed estimator is shown to benefit form propoerly
chosen delay parameter and perform robustly.
An LMI Approach of Robust H∞ Fuzzy State-Feedback Controller Design for HIV/AIDS Infection System with Dual Drug Dosages
This paper examines the problem of designing robust H controllers for for HIV/AIDS infection system with dual drug dosages described by a Takagi-Sugeno (S) fuzzy model. Based on a linear matrix inequality (LMI) approach, we develop an H controller which guarantees the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value for the system. A sufficient condition of the controller for this system is given in term of Linear Matrix Inequalities (LMIs). The effectiveness of the proposed controller design methodology is finally demonstrated through simulation results. It has been shown that the anti-HIV vaccines are critically important in reducing the infected cells.
Face Localization and Recognition in Varied Expressions and Illumination
In this paper, we propose a robust scheme to work face alignment and recognition under various influences. For face representation, illumination influence and variable expressions are the important factors, especially the accuracy of facial localization and face recognition. In order to solve those of factors, we propose a robust approach to overcome these problems. This approach consists of two phases. One phase is preprocessed for face images by means of the proposed illumination normalization method. The location of facial features can fit more efficient and fast based on the proposed image blending. On the other hand, based on template matching, we further improve the active shape models (called as IASM) to locate the face shape more precise which can gain the recognized rate in the next phase. The other phase is to process feature extraction by using principal component analysis and face recognition by using support vector machine classifiers. The results show that this proposed method can obtain good facial localization and face recognition with varied illumination and local distortion.
Evaluation of Evolution Strategy, Genetic Algorithm and their Hybrid on Evolving Simulated Car Racing Controllers
Researchers have been applying tional intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI
methods with respect to each game application. In th
our experimental result on the comparison of three evolutionary algorithms – evolution strategy, genetic algorithm, and their hybrid
applied to evolving controller agents for the CIG 2007 Simulated Car Racing competition. Our experimental result shows that, premature
convergence of solutions was observed in the case of ES, and GA outperformed ES in the last half of generations. Besides, a hybrid
which uses GA first and ES next evolved the best solution among the whole solutions being generated. This result shows the ability of GA in
globally searching promising areas in the early stage and the ability of ES in locally searching the focused area (fine-tuning solutions).
Development of Non-functional Requirements for Decision Support Systems
Decision Support System (DSS) are interactive
software systems that are built to assist the management of an
organization in the decision making process when faced with nonroutine
problems in a specific application domain. Non-functional
requirements (NFRs) for a DSS deal with the desirable qualities and
restrictions that the DSS functionalities must satisfy. Unlike the
functional requirements, which are tangible functionalities provided
by the DSS, NFRs are often hidden and transparent to DSS users but
affect the quality of the provided functionalities. NFRs are often
overlooked or added later to the system in an ad hoc manner, leading
to a poor overall quality of the system. In this paper, we discuss the
development of NFRs as part of the requirements engineering phase
of the system development life cycle of DSSs. To help eliciting
NFRs, we provide a comprehensive taxonomy of NFRs for DSSs.
Detecting and Tracking Vehicles in Airborne Videos
In this work, we present an automatic vehicle detection
system for airborne videos using combined features. We propose a
pixel-wise classification method for vehicle detection using Dynamic
Bayesian Networks. In spite of performing pixel-wise classification,
relations among neighboring pixels in a region are preserved in the
feature extraction process. The main novelty of the detection scheme is
that the extracted combined features comprise not only pixel-level
information but also region-level information. Afterwards, tracking is
performed on the detected vehicles. Tracking is performed using
efficient Kalman filter with dynamic particle sampling. Experiments
were conducted on a wide variety of airborne videos. We do not
assume prior information of camera heights, orientation, and target
object sizes in the proposed framework. The results demonstrate
flexibility and good generalization abilities of the proposed method on
a challenging dataset.
Combine a Population-based Incremental Learning with Artificial Immune System for Intrusion Detection System
This research focus on the intrusion detection system (IDS) development which using artificial immune system (AIS) with population based incremental learning (PBIL). AIS have powerful distinguished capability to extirpate antigen when the antigen intrude into human body. The PBIL is based on past learning experience to adjust new learning. Therefore we propose an intrusion detection system call PBIL-AIS which combine two approaches of PBIL and AIS to evolution computing. In AIS part we design three mechanisms such as clonal selection, negative selection and antibody level to intensify AIS performance. In experimental result, our PBIL-AIS IDS can capture high accuracy when an intrusion connection attacks.
Information Quality Evaluation Framework: Extending ISO 25012 Data Quality Model
The world wide web coupled with the ever-increasing
sophistication of online technologies and software applications puts
greater emphasis on the need of even more sophisticated and
consistent quality requirements modeling than traditional software
applications. Web sites and Web applications (WebApps) are
becoming more information driven and content-oriented raising the
concern about their information quality (InQ). The consistent and
consolidated modeling of InQ requirements for WebApps at different
stages of the life cycle still poses a challenge. This paper proposes an
approach to specify InQ requirements for WebApps by reusing and
extending the ISO 25012:2008(E) data quality model. We also
discuss learnability aspect of information quality for the WebApps.
The proposed ISO 25012 based InQ framework is a step towards a
standardized approach to evaluate WebApps InQ.
Concurrent Access to Complex Entities
In this paper we present a way of controlling the
concurrent access to data in a distributed application using the
Pessimistic Offline Lock design pattern. In our case, the application
processes a complex entity, which contains in a hierarchical structure
different other entities (objects). It will be shown how the complex
entity and the contained entities must be locked in order to control
the concurrent access to data.
Research on Strategy for Automated Scaleless-Map Compilation
As a tool for human spatial cognition and thinking, the map has been playing an important role. Maps are perhaps as fundamental to society as language and the written word. Economic and social development requires extensive and in-depth understanding of their own living environment, from the scope of the overall global to urban housing. This has brought unprecedented opportunities and challenges for traditional cartography . This paper first proposed the concept of scaleless-map and its basic characteristics, through the analysis of the existing multi-scale representation techniques. Then some strategies are presented for automated mapping compilation. Taking into account the demand of automated map compilation, detailed proposed the software - WJ workstation must have four technical features, which are generalization operators, symbol primitives, dynamically annotation and mapping process template. This paper provides a more systematic new idea and solution to improve the intelligence and automation of the scaleless cartography.
A Fast Replica Placement Methodology for Large-scale Distributed Computing Systems
Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.
A Methodology for Creating a Conceptual Model Under Uncertainty
This article deals with the conceptual modeling under uncertainty. First, the division of information systems with their definition will be described, focusing on those where the construction of a conceptual model is suitable for the design of future information system database. Furthermore, the disadvantages of the traditional approach in creating a conceptual model and database design will be analyzed. A comprehensive methodology for the creation of a conceptual model based on analysis of client requirements and the selection of a suitable domain model is proposed here. This article presents the expert system used for the construction of a conceptual model and is a suitable tool for database designers to create a conceptual model.
, conceptual modeling
, information system
, conceptual domain model
Audio User Interface for Visually Impaired Computer Users: in a Two Dimensional Audio Environment
In this paper we discuss a set of guidelines which
could be adapted when designing an audio user interface for the
visually impaired. It is based on an audio environment that is
focused on audio positioning. Unlike current applications which only
interpret Graphical User Interface (GUI) for the visually impaired,
this particular audio environment bypasses GUI to provide a direct
auditory output. It presents the capability of two dimensional (2D)
navigation on audio interfaces. This paper highlights the significance
of a 2D audio environment with spatial information in the context
of the visually impaired. A thorough usability study has been conducted
to prove the applicability of proposed design guidelines for
these auditory interfaces. While proving these guidelines, previously
unearthed design aspects have been revealed in this study.
Adopting Procedural Animation Technology to Generate Locomotion of Quadruped Characters in Dynamic Environments
A procedural-animation-based approach which rapidly
synthesize the adaptive locomotion for quadruped characters that they
can walk or run in any directions on an uneven terrain within a
dynamic environment was proposed. We devise practical motion
models of the quadruped animals for adapting to a varied terrain in a
real-time manner. While synthesizing locomotion, we choose the
corresponding motion models by means of the footstep prediction of
the current state in the dynamic environment, adjust the key-frames of
the motion models relying on the terrain-s attributes, calculate the
collision-free legs- trajectories, and interpolate the key-frames
according to the legs- trajectories. Finally, we apply dynamic time
warping to each part of motion for seamlessly concatenating all desired
transition motions to complete the whole locomotion. We reduce the
time cost of producing the locomotion and takes virtual characters to
fit in with dynamic environments no matter when the environments are
changed by users.
Development of Decision Support System for House Evaluation and Purchasing
Home is important for Chinese people. Because the
information regarding the house attributes and surrounding
environments is incomplete in most real estate agency, most house
buyers are difficult to consider the overall factors effectively and only
can search candidates by sorting-based approach. This study aims to
develop a decision support system for housing purchasing, in which
surrounding facilities of each house are quantified. Then, all
considered house factors and customer preferences are incorporated
into Simple Multi-Attribute Ranking Technique (SMART) to support
the housing evaluation. To evaluate the validity of proposed approach,
an empirical study was conducted from a real estate agency. Based on
the customer requirement and preferences, the proposed approach can
identify better candidate house with consider the overall house
attributes and surrounding facilities.
Towards Cloud Computing Anatomy
Cloud Computing has recently emerged as a
compelling paradigm for managing and delivering services over the
internet. The rise of Cloud Computing is rapidly changing the
landscape of information technology, and ultimately turning the longheld
promise of utility computing into a reality. As the development
of Cloud Computing paradigm is speedily progressing, concepts, and
terminologies are becoming imprecise and ambiguous, as well as
different technologies are interfering. Thus, it becomes crucial to
clarify the key concepts and definitions. In this paper, we present the
anatomy of Cloud Computing, covering its essential concepts,
prominent characteristics, its affects, architectural design and key
technologies. We differentiate various service and deployment
models. Also, significant challenges and risks need are tackled in
order to guarantee the long-term success of Cloud Computing. The
aim of this paper is to provide a better understanding of the anatomy
of Cloud Computing and pave the way for further research in this
Comparison of Evolutionary Algorithms and their Hybrids Applied to MarioAI
Researchers have been applying artificial/ computational intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI methods with respect to each game application. In thispaper, we report our experimental result on the comparison of evolution strategy, genetic algorithm and their hybrids, applied to evolving controller agents for MarioAI. GA revealed its advantage in our experiment, whereas the expected ability of ES in exploiting (fine-tuning) solutions was not clearly observed. The blend crossover operator and the mutation operator of GA might contribute well to explore the vast search space.
Auto-Parking System via Intelligent Computation Intelligence
In this paper, an intelligent automatic parking control method is proposed. First, the dynamical equation of the rear parking control is derived. Then a fuzzy logic control is proposed to perform the parking planning process. Further, a rear neural network is proposed for the steering control. Through the simulations and experiments, the intelligent auto-parking mode controllers have been shown to achieve the demanded goals with satisfactory control performance and to guarantee the system robustness under parametric variations and external disturbances. To improve some shortcomings and limitations in conventional parking mode control and further to reduce consumption time and prime cost.
Implementation of Security Algorithms for u-Health Monitoring System
Data security in u-Health system can be an important
issue because wireless network is vulnerable to hacking. However, it is
not easy to implement a proper security algorithm in an embedded
u-health monitoring because of hardware constraints such as low
performance, power consumption and limited memory size and etc. To
secure data that contain personal and biosignal information, we
implemented several security algorithms such as Blowfish, data
encryption standard (DES), advanced encryption standard (AES) and
Rivest Cipher 4 (RC4) for our u-Health monitoring system and the
results were successful. Under the same experimental conditions, we
compared these algorithms. RC4 had the fastest execution time.
Memory usage was the most efficient for DES. However, considering
performance and safety capability, however, we concluded that AES
was the most appropriate algorithm for a personal u-Health monitoring
Analysis of Aiming Performance for Games Using Mapping Method of Corneal Reflections Based on Two Different Light Sources
Fundamental motivation of this paper is how gaze estimation can be utilized effectively regarding an application to games. In games, precise estimation is not always important in aiming targets but an ability to move a cursor to an aiming target accurately is also significant. Incidentally, from a game producing point of view, a separate expression of a head movement and gaze movement sometimes becomes advantageous to expressing sense of presence. A case that panning a background image associated with a head movement and moving a cursor according to gaze movement can be a representative example. On the other hand, widely used technique of POG estimation is based on a relative position between a center of corneal reflection of infrared light sources and a center of pupil. However, a calculation of a center of pupil requires relatively complicated image processing, and therefore, a calculation delay is a concern, since to minimize a delay of inputting data is one of the most significant requirements in games. In this paper, a method to estimate a head movement by only using corneal reflections of two infrared light sources in different locations is proposed. Furthermore, a method to control a cursor using gaze movement as well as a head movement is proposed. By using game-like-applications, proposed methods are evaluated and, as a result, a similar performance to conventional methods is confirmed and an aiming control with lower computation power and stressless intuitive operation is obtained.
Active Intra-ONU Scheduling with Cooperative Prediction Mechanism in EPONs
Dynamic bandwidth allocation in EPONs can be
generally separated into inter-ONU scheduling and intra-ONU scheduling. In our previous work, the active intra-ONU scheduling
(AS) utilizes multiple queue reports (QRs) in each report message to cooperate with the inter-ONU scheduling and makes the granted
bandwidth fully utilized without leaving unused slot remainder (USR).
This scheme successfully solves the USR problem originating from the
inseparability of Ethernet frame. However, without proper setting of
threshold value in AS, the number of QRs constrained by the IEEE
802.3ah standard is not enough, especially in the unbalanced traffic
environment. This limitation may be solved by enlarging the threshold
value. The large threshold implies the large gap between the adjacent QRs, thus resulting in the large difference between the best granted bandwidth and the real granted bandwidth. In this paper, we integrate
AS with a cooperative prediction mechanism and distribute multiple
QRs to reduce the penalty brought by the prediction error.
Furthermore, to improve the QoS and save the usage of queue reports,
the highest priority (EF) traffic which comes during the waiting time is
granted automatically by OLT and is not considered in the requested
bandwidth of ONU. The simulation results show that the proposed
scheme has better performance metrics in terms of bandwidth
utilization and average delay for different classes of packets.
Video Quality Assessment using Visual Attention Approach for Sign Language
Visual information is very important in human perception
of surrounding world. Video is one of the most common ways to
capture visual information. The video capability has many benefits
and can be used in various applications. For the most part, the
video information is used to bring entertainment and help to relax,
moreover, it can improve the quality of life of deaf people. Visual
information is crucial for hearing impaired people, it allows them to
communicate personally, using the sign language; some parts of the
person being spoken to, are more important than others (e.g. hands,
face). Therefore, the information about visually relevant parts of the
image, allows us to design objective metric for this specific case. In
this paper, we present an example of an objective metric based on
human visual attention and detection of salient object in the observed
Research Trend Analysis – A Sample in the Field of Information Systems
As research performance in academia is treated as one of indices for national competency, many countries devote much attention and resources to increasing their research performance. Understand the research trend is the basic step to improve the research performance. The goal of this research is to design an analysis system to evaluate research trends from analyzing data from different countries. In this paper, information system researches in Taiwan and other countries, including Asian countries and prominent countries represented by the Group of Eight (G8) is used as example. Our research found the trends are varied in different countries. Our research suggested that Taiwan-s scholars can pay more attention to interdisciplinary applications and try to increase their collaboration with other countries, in order to increase Taiwan's competency in the area of information science.
File System-Based Data Protection Approach
As data to be stored in storage subsystems
tremendously increases, data protection techniques have become more
important than ever, to provide data availability and reliability. In this
paper, we present the file system-based data protection (WOWSnap)
that has been implemented using WORM (Write-Once-Read-Many)
scheme. In the WOWSnap, once WORM files have been created, only
the privileged read requests to them are allowed to protect data against
any intentional/accidental intrusions. Furthermore, all WORM files
are related to their protection cycle that is a time period during which
WORM files should securely be protected. Once their protection cycle
is expired, the WORM files are automatically moved to the
general-purpose data section without any user interference. This
prevents the WORM data section from being consumed by
unnecessary files. We evaluated the performance of WOWSnap on
Behavioral Signature Generation using Shadow Honeypot
A novel behavioral detection framework is proposed
to detect zero day buffer overflow vulnerabilities (based on network
behavioral signatures) using zero-day exploits, instead of the
signature-based or anomaly-based detection solutions currently
available for IDPS techniques. At first we present the detection
model that uses shadow honeypot. Our system is used for the online
processing of network attacks and generating a behavior detection
profile. The detection profile represents the dataset of 112 types of
metrics describing the exact behavior of malware in the network. In
this paper we present the examples of generating behavioral
signatures for two attacks – a buffer overflow exploit on FTP server
and well known Conficker worm. We demonstrated the visualization
of important aspects by showing the differences between valid
behavior and the attacks. Based on these metrics we can detect
attacks with a very high probability of success, the process of
detection is however very expensive.
Human Interactive E-learning Systems using Head Posture Images
This paper explains a novel approach to human interactive e-learning systems using head posture images. Students- face and hair information are used to identify a human presence and estimate the gaze direction. We then define the human-computer interaction level and test the definition using ten students and seventy different posture images. The experimental results show that head posture images provide adequate information for increasing human-computer interaction in e-learning systems.
Clustering Approach to Unveiling Relationships between Gene Regulatory Networks
Reverse engineering of genetic regulatory network involves the modeling of the given gene expression data into a form of the network. Computationally it is possible to have the relationships between genes, so called gene regulatory networks (GRNs), that can help to find the genomics and proteomics based diagnostic approach for any disease. In this paper, clustering based method has been used to reconstruct genetic regulatory network from time series gene expression data. Supercoiled data set from Escherichia coli has been taken to demonstrate the proposed method.