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IJACSA Vol. 5 Issue 11 (2014)

Open Access | | 26 papers

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

1

Handwritten Pattern Recognition Using Kohonen Neural Network Based on Pixel Character

Author 1: Lulu C. Munggaran Author 2: Suryarini Widodo Author 3: Cipta A.M Author 4: Nuryuliani

Handwriting is the human way in communicating each other using written media. By the advancement in technology and development of science, there are a lot of changes of technology in terms of communication with computer through handwriting. Therefore, it is needed computer able to receive input in the form of handwriting data and able to recognize the handwriting input. Therefore, this research focuses on handwritten character recognition using Kohonen neural network. The purpose of this research is to find handwriting recognition algorithm which can receive handwriting input and recognize handwritten character directly inputted in computer using Kohonen neural network. This method studies the distribution of a set of patterns without any class information. The basic idea of this technique is understood from how human brain stores images/patterns that have been recognized through eyes, and then able to reveal the images/patterns back. This research has been successful in developing an application to recognize handwritten characters using Kohonen neural network method, and it has been tested. The application is personal computer based and using a canvas as input media. The recognition process consist of 3 stages layer: Input layer, Training Layer and Hidden Layer. The Kohonen neural network method on handwritten character recognition application has good similarity level of character patterns in character mapping process.

handwriting recognition Kohonen neural network similarity character
2

Basic Study for New Assistive Technology Based on Brain Activity during Car Driving

Author 1: Hiroaki Inoue Author 2: Fumikazu Miwakeichi Author 3: Shunji Shimizu Author 4: Noboru Takahashi Author 5: Yasuhito Yoshizawa Author 6: Nobuhide Hirai Author 7: Hiroyuki Nara Author 8: Senichiro Kikuchi Author 9: Satoshi Kato Author 10: Eiju Watanabe

Recently, it is necessary to develop a new system which assists driving car and wheelchair as aged society. The final our purpose in this research is to contribute to developing of assistive robot and related-apparatus. In terms of developing a new system, we thought that it is important to examine behaviors as well as spatial recognition. Therefore, experiments have been performed for an examination of human spatial perceptions, especially right and left recognition, during car driving by using NIRS. In previous research, it has been documented that there were significant differences at dorsolateral prefrontal cortex at left hemisphere during virtual driving task and actual driving. In this paper, we performed measuring the brain activity during car driving by using NIRS. And we performed statistical analysis of the brain activity. The purpose of this paper is discovering the brain region which was involved in decision making when human drive a car and considering between human movement and brain activity during car driving.

brain information processing during driving task spatial cognitive task determining direction NIRS
3

A Smartphone Intervention for Cycle Commuting

Author 1: Yun-Maw Cheng Author 2: Chao-Lung Lee

For those who new to cycling to and from work, how do you inspire yourself to keep up with it? Previous research has identified that having a partner is crucial to create and maintain a new habit. However, the rapidly changing work dynamics pose a challenge on this basis. Frequently failing to show up at the appointed or expected time can cause the motivation breakdown. In this paper, we introduce BikeTogether, a smartphone app that encourages and supports its users to cycle home with each other over the Internet. The app employs the metaphor of a bicycle flashlight to represent closeness, leading, and following between two sides. The cycling performance is also recorded so the users can track how they are doing over time. 10 participants were instructed and randomly paired to take a two-phases test ride on different routes. Results indicated that the app can help create the sense of being with each other while cycling and promote not only accompanied but competing ride. In addition, the outcome of the desirability towards the app implies a higher chance it will lead to a behavior change. This provides a new way that we can commit to remain encouraged.

copresence behavioral nudge persuasive computing smartphone app
4

Broadband Access for All: Strategies and Tactis of Wireless Traffic Sharing

Author 1: Jinadu Olayinka T. Author 2: Owa Victor K..

Network engineers have designed an array of protocols that enabled shared access in various wired and wireless contexts at different layers of the protocol stack [1]. One approach to managing unlicensed spectrum is to rely on a technical protocol to allocate and manage shared access Lehr [2]. This paper addressed the benefits of unlicensed wireless traffic within licensed traffic (anticipated as cognitive router-based networking). A focus on shared access to non-exclusive use of the spectrum with an holistic view of technical and institutional features is suggested for effective management of ‘spectrum commons’. Using the adapted cognitive radio architectural model and its associated multi-hop ad-hoc networking strategies to implement the ‘spectrum-common’, mobility is enhanced with each node acting as a router and packet forwarder. We formulate management frameworks that can integrate well with liquid protocols for mobile nodes. Also, these frameworks incorporate new strategies of intelligently adapting the nodes to dynamically participate in setting bandwidth capacity stochastically. The projected use of dynamic bandwidth shaping algorithm for the cognitive radio-based network (CRN) when implemented will make broadband access more economical to users and the spectrum used effectively.

ad-hoc spectrum commons etiquettes software defined radio (SDR) MIMO
5

Feedback Optimal Control for Inverted Pendulum Problem by Using the Generating Function Technique

Author 1: Hany R. Dwidar

In this paper, a model is described for a system consisting of an inverted pendulum attached to a cart. We design for this model a feedback optimal control based on Linear Quadratic regulator, LQR by using the generating Function technique. This design with hard and soft constraints will help the pendulum to stabilize in the upright position. A solution of the continuous low-thrust optimal control problem based on LQR method is implemented. An example applied to this control design for a hard constraint boundary condition.

Inverted pendulum Feedback control Stability analysis
6

Efficient Identification of Common Subsequences from Big Data Streams Using Sliding Window Technique

Author 1: Adi Alhudhaif

We propose an efficient Frequent Sequence Stream algorithm for identifying the top k most frequent subsequences over big data streams. Our Sequence Stream algorithm gains its efficiency by its time complexity of linear time and very limited space complexity. With a pre-specified subsequence window size S and the k value, in very high probabilities, the Sequence Stream algorithm retrieve the top k most frequent subsequences of size S. The Stream Sequence algorithm also provides a high accuracy of the estimation of the number of occurrences of each promoted subsequence. Our experiments indicate several factors that influence the result accuracy of the Sequence Stream algorithm: stream size, subsequence size S and frequency of the subsequence.

Frequent subsequence Stream processing Periodic pattern Pattern recognition Big data processing
7

A Study of Privatized Synthetic Data Generation Using Discrete Cosine Transforms

Author 1: Kato Mivule

In order to comply with data confidentiality requirements, while meeting usability needs for researchers, entities are faced with the challenge of how to publish privatized data sets that preserve the statistical traits of the original data. One solution to this problem, is the generation of privatized synthetic data sets. However, during data privatization process, the usefulness of data, have a propensity to diminish even as privacy might be guaranteed. Furthermore, researchers have documented that finding an equilibrium between privacy and utility is intractable, often requiring trade-offs. Therefore, as a contribution, the Filtered Classification Error Gauge heuristic, is presented. The suggested heuristic is a data privacy and usability model that employs data privacy, signal processing, and machine learning techniques to generate privatized synthetic data sets with acceptable levels of usability. Preliminary results from this study show that it might be possible to generate privacy compliant synthetic data sets using a combination of data privacy, signal processing, and machine learning techniques, while preserving acceptable levels of data usability.

Privatized synthetic data Signal processing Data privacy Discrete cosine transforms Moving average filtering
8

Vector Autoregression (Var) Model for Rainfall Forecast and Isohyet Mapping in Semarang – Central Java – Indonesia

Author 1: Adi Nugroho Author 2: Subanar Author 3: Sri Hartati Author 4: Khabib Mustofa

Agricultural and plantation activities in Indonesia, especially in Semarang, Central Java, Indonesia rely on water supply from the rainfall. The rainfall in the future is basically influenced by rainfall patterns, humidity and temperature in the past. In this case, Vector Autoregression (VAR) multivariate model is applied to forecast the rainfall in the future, in which all along Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG) generally uses ARIMA model (Autoregressive Integrated Moving Average) to carry out the same thing. The study applied the data, comprising the data of rainfall, humidity and temperature taken on a monthly basis during 2001-2013 periods from 5 measurement stations. Plotting of rainfall forecast result with VAR method is portrayed in the form of isohyet contour map to see the correlation between rainfall and coordinates of the area of the rainfall. The forecast result shows that VAR method is quite accurate to use for rainfall forecast in the study area as well as better than ARIMA method to forecast the same thing as having smaller Mean Absolute Error (MAE) and Mean Absolute Percentage Error(MAPE).

Rainfall Forecast VAR Multivariate Time Series Isohyet
9

A Three-Dimensional Motion Anlaysis of Horse Rider in Wireless Sensor Network Environments

Author 1: Jae-Neung Lee Author 2: Keun-Chang Kwak

This paper constructed a database of the national representative level of a professional horse-rider by wearing a motion-capture suit attached with 16 inertial sensors under an inertial sensor-based wireless network environment, then made a visual comparative analysis through a few methods (graphical and statistical) on the values of all motion features (elbow angle, knee angle, knee-elbow distance, backbone angle and hip position) classified depending on horse types (using two horses named Warm-blood and Thoroughbred) and footpace types (at a trot and a canter) and obtained by various methods of calculating Euclidean distance, the second cosine, maximum and minimum values, and made a comparative analysis depending on motion features of a horse-rider by using MVN studio software. In the study, the experimental results confirmed the validity of the proposed method of obtaining the motion feature database of a horse-rider in the wireless sensor network environment and making an analytical system.

3D motion capture and analysis inertial sensor wireless network
10

Data and Knowledge Extraction Based on Structure Analysis of Homogeneous Websites

Author 1: Mohammed Abdullah Hassan Al-Hagery

The World Wide Web includes several types of website applications. Mainly these applications are related to business, organizations, companies, and others. There is a lack to get raw data sets to study the behavior of the internal structure of each type of these websites. Where websites structures include treasure of links, and sub-links, in addition to some embedded features associated with the internal structure of each website. The objective of this paper is to analysis a set of homogeneous websites to establish raw data sets. These data sets can be employed for several research purposes. It also can be used to extract some invisible aspects/features within the structure. Several steps are required to accomplish this objective; first, to propose an algorithm for structure analysis, second, to implement the proposed algorithm as a software tool for the purpose of extraction and establishment of raw data sets (real data set), third, to extrapolate a set of rules or relations from these data sets. This data set can be employed for researches purposes in the field of web structure mining, to estimate important factors related to websites development processes, and websites ranking. The results comprise creation of Oriented Data Sets (ODS) for research purposes and also for deducing a set of features represents a type of new discovered knowledge in this ODS.

Hyperlinks Analysis Tools Features Extraction Oriented Data Sets generation Knowledge Discovery in Oriented Data Sets
11

The Experience-Based Safety Training System Using Vr Technology for Chemical Plant

Author 1: Atsuko Nakai Author 2: Yuta Kaihata Author 3: Kazuhiko Suzuki

In chemical plants, safety measures are needed in order to minimize the impact of severe accidents and natural disasters. At the same time, carrying out the education and training to workers the corresponding operation in non-stationary situation is essential. However, reproducing the non-stationary conditions to actual equipment or mock-up cannot be performed because it is dangerous. By using the virtual reality (VR) technology, we can build up a virtual chemical plant with lower cost compared to real plant. The operator can experience the fire and explosion accidents in the virtual space. Therefore, in this paper, we propose an experienced-based safety training system for implementing the education and training by using the non-stationary situation in the computer. This proposed system is linked with the dynamic plant simulator. A trainee can learn the correct operation through the simulated experience to prevent an accident. The safety awareness of workers will improve by experiential learning. The proposed system is useful for safety education in chemical plant.

safety education training system virtual reality
12

Evaluating Arabic to English Machine Translation

Author 1: Laith S. Hadla Author 2: Taghreed M. Hailat Author 3: Mohammed N. Al-Kabi

Online text machine translation systems are widely used throughout the world freely. Most of these systems use statistical machine translation (SMT) that is based on a corpus full with translation examples to learn from them how to translate correctly. Online text machine translation systems differ widely in their effectiveness, and therefore we have to fairly evaluate their effectiveness. Generally the manual (human) evaluation of machine translation (MT) systems is better than the automatic evaluation, but it is not feasible to be used. The distance or similarity of MT candidate output to a set of reference translations are used by many MT evaluation approaches. This study presents a comparison of effectiveness of two free online machine translation systems (Google Translate and Babylon machine translation system) to translate Arabic to English. There are many automatic methods used to evaluate different machine translators, one of these methods; Bilingual Evaluation Understudy (BLEU) method. BLEU is used to evaluate translation quality of two free online machine translation systems under consideration. A corpus consists of more than 1000 Arabic sentences with two reference English translations for each Arabic sentence is used in this study. This corpus of Arabic sentences and their English translations consists of 4169 Arabic words, where the number of unique Arabic words is 2539. This corpus is released online to be used by researchers. These Arabic sentences are distributed among four basic sentence functions (declarative, interrogative, exclamatory, and imperative). The experimental results show that Google machine translation system is better than Babylon machine translation system in terms of precision of translation from Arabic to English.

component Machine Translation Arabic-English Corpus Google Translator Babylon Translator BLEU
13

Routing in Wireless Sensor Networks based on Generalized Data Stack Programming Model

Author 1: Hala Elhadidy Author 2: Rawya Rizk Author 3: Hassan T. Dorrah

Generalized Data Stack Programming (GDSP) model describes that any affected activity or varying environment is intelligently self-recorded inside the system in form of stack-based layering types where stack is re-defined to be one of six classes. The multi-stacking network is presented thinking of that any system connects to other system to work properly. This addresses a novel way to investigate and analyze any system. Wireless Sensor Networks (WSNs) monitor the environment and take action accordingly. However, WSN suffers from some weakness due to nodes failure or interference which affects the network topology and the routing table at each node. In this paper, the GDSP model is applied on the routing problems in WSNs. A history matrix at the user side is proposed to retrieve and backward the events affected the network.

GDSP history matrix multi-stacking network network topology routing table WSN
14

RETRACTED: Towards a Transformation Model of a Pedagogy Collaborative Project (PCP) Scenario

Author 1: Maroua AULAD BEN TAHAR Author 2: Az-eddine NASSEH Author 3: Mohamed KHALDI

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IJACSA`s Publication Principles. We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper. Retraction DOI: 10.14569/IJACSA.2014.051114.retraction

Pedagogy Collaborative Project (PCP) MDA Transformation rules Atlas Transformation Language (ATL) Moodle
15

Data Protection Control and Learning Conducted Via Electronic Media I.E. Internet

Author 1: Mohamed F. AlAjmi Author 2: Shakir Khan Author 3: Abdulkadir Alaydarous

numerous e-taking in establishments are hurrying into receiving ICT without precisely arranging and seeing any related security concerns. E-learning is another technique for taking in which eventually relies on upon the Internet in its execution. The Internet has turned into the venue for another set of unlawful exercises, and the e-taking in environment is notwithstanding laid open to such dangers. In this paper, e-learning setting, definition, aspects, improvement, development, profits and tests are all explained upon. This paper examines the security components needed to be executed inside e-learning situations. Moreover, the paper clarifies the circumstances and existing examination relating to security in e-taking in. Besides, data security administration is inferred to help setting up a secured e-taking nature's turf.

e-Learning e-taking ICT data security component
16

A Code Level Based Programmer Assessment and Selection Criterion Using Metric Tools

Author 1: Ezekiel U. Okike

this study presents a code level measurement of computer programs developed by computer programmers using a Chidamber and Kemerer Java metric (CKJM) tool and the Myers Briggs Type Indicator (MBTI) tool. The identification of potential computer programmers using personality trait factors does not seem to be the best approach without a code level measurement of the quality of programs. Hence the need to evolve a metric tool which measures both personality traits of programmers and code level quality of programs developed by programmers. This is the focus of this study. In this experiment, a set of Java based programming tasks were given to 33 student programmers who could confidently use the Java programming language. The codes developed by these students were analyzed for quality using a CKJM tool. Cohesion, coupling and number of public methods (NPM) metrics were used in the study. The choice of these three metrics from the CKJM suite was because they are useful in measuring well designed codes. By examining the cohesion values of classes, high cohesion ranges [0,1] and low coupling imply well designed code. Also number of methods (NPM) in a well-designed class is always less than 5 when cohesion range is [0,1]. Results from this study show that 19 of the 33 programmers developed good and cohesive programs while 14 did not. Further analysis revealed the personality traits of programmers and the number of good programs written by them. Programmers with Introverted Sensing Thinking Judging (ISTJ) traits produced the highest number of good programs, followed by Introverted iNtuitive Thinking Perceiving (INTP), Introverted iNtuitive Feelingng Perceiving (INTP), and Extroverted Sensing Thinking Judging (ESTJ)

computer programs program quality class cohesion programmers personality traits
17

Segmentation of Acute Lymphoblastic Leukemia Using C-Y Color Space

Author 1: Reham Mohammed Author 2: Omima Nomir Author 3: Iraky Khalifa

Medical image analysis process usually starts with segmentation step, which aims to separate different objects in the image scene. This is achieved by mainly dividing the image into two parts, the region of interest (ROI) and the background. Segmentation of acute lymphoblastic leukemia blood cell (ALL) based on microscope color image is one of the important step in the recognition process. This paper proposed a technique which aims to segment the color image of acute leukemia by transforming the RGB color space to C-Y color space .in the C-Y color space, the luminance component is used to segment (ALL) .The proposed algorithm runs on 100 microscopic ALL images and the experimental result shows that the proposed system can provide a good segmentation of ALL from its complicated background and shows that the segmentation accuracy of the proposed technique is 98.38% compared to the result of the manual segmentation method by expert.

Image Segmentation acute lymphoblastic leukemia RGB C-Y color space
18

Clustering of Slow Learners Behavior for Discovery of Optimal Patterns of Learning

Author 1: Thakaa Z. Mohammad Author 2: Abeer M.Mahmoud

with the increased rates of the slow learners (SL) enrolled in schools nowadays; the schools realized that the traditional academic curriculum is inadequate. Some schools have developed a special curricula that are particularly suited a slow learner while others are focusing their efforts on the devising of better and more effective methods and techniques in teaching. In the other hand, knowledge discovery and data mining techniques certainly can help to understand more about these students and their educational behaviors. This paper discusses the clustering of elementary school slow learner students behavior for the discovery of optimal learning patterns that enhance their learning capabilities. The development stages of an integrated E-Learning and mining system are briefed. The results show that after applying the clustering algorithms Expectation maximization and K-Mean on the slow learner’s data, a reduced set of five optimal patterns list (RSWG, RWSG, RWGS, GRSW, and SGWR) is reached. Actually, the students followed these five patterns reached grads higher than 75%. Therefore, the proposed system is significant for slow learners, teachers and schools.

Data mining E-learning Slow Learners
19

Fundamental Study to New Evaluation Method Based on Physical and Psychological Load in Care

Author 1: Hiroaki Inoue Author 2: Shunji Shimizu Author 3: Hirotaka Ishihara Author 4: Yuuki Nakata Author 5: Takeshi Tsuruga Author 6: Fumikazu Miwakeichi Author 7: Nobuhide Hirai Author 8: Senichiro Kikuchi Author 9: Satoshi Kato Author 10: Eiju Watanabe

In Japan and developed countries, it has become aged society, and wide variety welfare device or system have been developed. But these evaluation methods of welfare device or system are limited only stability, intensity and partial operability. Because of, it is not clear to determine the standard to evaluation for welfare device or system of usefulness. Therefore, we will attempt to establish the standard for evaluation about usefulness for objectively and quantitatively for including non-verbal cognition. We examine the relationship between human movements and brain activity, and consider the evaluation method of welfare devices and systems to measure the load and fatigue which were felt by human. In this paper, we measure the load for sitting and standing movement using NISR. We tried to make sure for the possibility of the quantitatively estimation for physical or psychological load or fatigue by measuring of brain activity using NIRS(Near Infra Red Spectroscopy). As results, when subjects perform the movement task, the statistical significant difference was shown in the specific part of the brain region.

component Evaluation Movement Exercise NIRS Care Welfare Technology Useful welfare device evaluation Evaluation method
20

Improved Security of Audit Trail Logs in Multi-Tenant Cloud Using ABE Schemes

Author 1: Bhanu Prakash Gopularam Author 2: Nalini N

Cloud computing is delivery of services rather than a product and among different cloud deployment models, the public cloud provides improved scalability and cost reduction when compared to others. Security and privacy of data is one of the key factors in transitioning to cloud. Typically the cloud providers have a demilitarized zone protecting the data center along with a reverse proxy setup. The reverse proxy gateway acts as initial access point and provides additional capabilities like load balancing, caching, security monitoring capturing events, syslogs related to hosts residing in the cloud. The audit-trail logs captured by reverse proxy server comprise important information related to all the tenants. While the PKI infrastructure works in cloud scenario it becomes cumbersome from manageability point of view and they lack flexibility in providing controlled access to data. In this paper we evaluate risks associated with security and privacy of audit logs produced by reverse proxy server. We provide a two-phase approach for sharing the audit-logs with users allowing fine-grained access. In this paper we evaluate certain Identity-Based and Attribute-Based Encryption schemes and provide detailed analysis on performance.

multi-tenancy audit-trail log attribute-based encryption reverse proxy security
21

A System Supporting Qualitative Research

Author 1: Emilia Todorova Author 2: Dimo Milev Author 3: Ivaylo Donchev

this paper presents a system aimed to be entirely located in the Internet. The database, server side, logic and user interface are accessible regardless the location and equipment of the working team members. The system supports qualitative analysis of large datasets, and the work can be distributed among several team members or teams. A modified mixed method for developing software projects is used, according to the peculiarities of our case, splitting the phase of code writing into two sub-phases each with different number of iterations.

Information systems (IS) Qualitative data analysis (QDA) NoSQL Database Software Design Computer Assisted Qualitative Data Analysis Software (CAQDAS)
22

Robust Increased Capacity Image Steganographic Scheme

Author 1: M. Khurrum Rahim Rashid Author 2: Nadeem Salamat Author 3: Saad Missen Author 4: Aqsa Rashid

with the rising tempo of unconventional right to use and hit protection of secret information is of extreme value. With the rising tempo of unconventional right to use and hit, protection of secret information is of extreme value. Steganography is the vital matter in information hiding. Steganography refers to the technology of hiding data into digital media without depiction of any misgiving. Lot of techniques has been projected during past years. In this paper, a new steganography approach for hiding data in digital images is presented with a special feature that it increases the capacity of hiding data in digital images with the least change in images perceptual appearance and statistical properties at too much less level which will be very difficult to detect.

Image steganography LSB Security Analysis Robustness Analysis
23

A Hybrid Multi-Tenant Database Schema for Multi-Level Quality of Service

Author 1: Ahmed I. Saleh Author 2: Mohammed A. Fouad Author 3: Mervat Abu-Elkheir

Software as a Service (SaaS) providers can serve hundreds of thousands of customers using sharable resources to reduce costs. Multi-tenancy architecture allows SaaS providers to run a single application and a database instance, which support multiple tenants with various business needs and priorities. Until now, the database management systems (DBMSs) have not had the notion of multi-tenancy, and they have not been equipped to handle customization or scalability requirements, that are typical in multi-tenant applications. The multi-tenant database performance should adapt to tenants workloads and fit their special requirements. In this paper, we propose a new multi-tenant database schema design approach, that adapts to multi-tenant application requirements, in addition to tenants needs of data security, isolation, queries performance and response time speed. Our proposed methodology provides a trade-off between the performance and the storage space. This proposal caters for the diversity in tenants via defining multi-level quality of service for the different types of tenants, depending on tenant rate and system rate. The proposal presents a new technique to distribute data in a multi-tenant database horizontally to a set of allotment tables using an isolation point, and vertically to a set of extension tables using a merger point. Finally, we present a prototype implementation of our method using a real-world case study, showing that the proposed solution can achieve high scalability and increase performance for tenants who need speedy performance and economize storage space for tenants who do not have demanding quality of service.

Multi-Tenancy Flexible Database Schema Design Data Customization
24

A Novel Approach for Bioinformatics Workflow Discovery

Author 1: Walaa Nagy Author 2: Hoda M. O. Mokhtar

Workflow systems are typical fit for in the explorative research of bioinformaticians. These systems can help bioinformaticians to design and run their experiments and to automatically capture and store the data generated at runtime. On the other hand, Web services are increasingly used as the preferred method for accessing and processing the information coming from the diverse life science sources. In this work we provide an efficient approach for creating bioinformatic workflow for all-service architecture systems (i.e., all system components are services ). This architecture style simplifies the user interaction with workflow systems and facilitates both the change of individual components, and the addition of new components to adopt to other workflow tasks if required. We finally present a case study for the bioinformatics domain to elaborate the applicability of our proposed approach.

Web services In-silico Workflows Quality of Services (QoS) Web services for bioinformatics Bioinformatics services
25

Timed-Release Hierarchical Identity-Based Encryption

Author 1: Toru Oshikiri Author 2: Taiichi Saito

We propose a notion of hierarchical identity-based encryption (HIBE) scheme with timed-release encryption (TRE) mechanism, timed-release hierarchical identity-based encryption (TRHIBE), and define its security models. We also show a generic construction of TRHIBE from HIBE and one-time signature, and discuss the security of the constructed scheme.

timed-release encryption hierarchical identity-based encryption one-time signature
26

A Comparison of the Effects of K-Anonymity on Machine Learning Algorithms

Author 1: Hayden Wimmer Author 2: Loreen Powell

While research has been conducted in machine learning algorithms and in privacy preserving in data mining (PPDM), a gap in the literature exists which combines the aforementioned areas to determine how PPDM affects common machine learning algorithms. The aim of this research is to narrow this literature gap by investigating how a common PPDM algorithm, K-Anonymity, affects common machine learning and data mining algorithms, namely neural networks, logistic regression, decision trees, and Bayesian classifiers. This applied research reveals practical implications for applying PPDM to data mining and machine learning and serves as a critical first step learning how to apply PPDM to machine learning algorithms and the effects of PPDM on machine learning. Results indicate that certain machine learning algorithms are more suited for use with PPDM techniques.

Privacy Preserving Data Mining Machine Learning Decision Tree Neural Network Logistic Regression Bayesian Classifier