Fuzzy Approach for Ranking of Motor Vehicles Involved in Road Accidents

Increasing number of vehicles and lack of awareness among road users may lead to road accidents. However no specific literature was found to rank vehicles involved in accidents based on fuzzy variables of road users. This paper proposes a ranking of four selected motor vehicles involved in road accidents. Human and non-human factors that normally linked with road accidents are considered for ranking. The imprecision or vagueness inherent in the subjective assessment of the experts has led the application of fuzzy sets theory to deal with ranking problems. Data in form of linguistic variables were collected from three authorised personnel of three Malaysian Government agencies. The Multi Criteria Decision Making, fuzzy TOPSIS was applied in computational procedures. From the analysis, it shows that motorcycles vehicles yielded the highest closeness coefficient at 0.6225. A ranking can be drawn using the magnitude of closeness coefficient. It was indicated that the motorcycles recorded the first rank.

A Parametric Study: Frame Analysis Method for Masonry Arch Bridges

The predictability of masonry arch bridges and their behaviour is widely considered doubtful due to the lack of knowledge about the conditions of a given masonry arch bridge. The assessment methods for masonry arch bridges are MEXE, ARCHIE, RING and Frame Analysis Method. The material properties of the masonry and fill material are extremely difficult to determine accurately. Consequently, it is necessary to examine the effect of load dispersal angle through the fill material, the effect of variations in the stiffness of the masonry, the tensile strength of the masonry mortar continuum and the compressive strength of the masonry mortar continuum. It is also important to understand the effect of fill material on load dispersal angle to determine their influence on ratings. In this paper a series of parametric studies, to examine the sensitivity of assessment ratings to the various sets of input data required by the frame analysis method, are carried out.

Growth and Stomatal Responses of Bread Wheat Genotypes in Tolerance to Salt Stress

Plant growth is affected by the osmotic stress as well as toxicity of salt in leaves. In order to study of salt stress effects on stomatal conductance and growth rate and relationship between them as wells osmotic and Na+-specific effects on these traits, four bread wheat genotypes differing in salt tolerance were selected. Salinity was applied when the leaf 4 was fully expanded. Sodium (Na+) concentrations in flag leaf blade at 3 salinity levels (0, 100 and 200 mM NaCl) were measured. Salt-tolerant genotypes showed higher stomatal conductance and growth rate compared to salt-sensitive ones. After 10 and 20 days exposure to salt, stomatal conductance and relative growth rate were reduced, but the reduction was greater in sensitive genotypes. Growth rate was reduced severely in the first period (1-10 days) of salt commencements and it was due to osmotic effect of salt not Na+ toxicity. In the second period (11-20 days) after salt treatment growth reduced only when salt accumulated to toxic concentrations in the leaves. A positive relationship between stomatal conductance and relative growth rate showed that stomatal conductance can be a reliable indicator of growth rate, and finally can be considered as a sensitive indicator of the osmotic stress. It seems 20 days after salinity, the major effect of salt, especially at low to moderate salinity levels on growth properties was due to the osmotic effect of salt, not to Na+-specific effects within the plant.

Radiological Risk Assessment in Soil Samples of Western Haryana, India

The measurements of 226Ra, 232Th and 40K using gamma spectrometry and radon concentration and exhalation rates measurements using solid state nuclear track (LR-115, Type-II plastic) detectors are used to asses a first order exposure risk for the persons residing in Fatehbad and Hissar districts of Western Haryana, India. The concentration of Radium, Thorium and Potassium in the soil samples varies from 13.37 Bq m-3 to 24.67 Bq m-3, 34.67 Bq m-3 to 67.34 Bq m-3 and 298.78 Bq m-3 to 405.67 Bq m-3 respectively with average values of 18.78, 47.35 and 361.57 Bq m-3 respectively. The radium equivalent activity (Raeq) calculated for the same soil samples varies from 92.72 Bq m-3 to 140.6 Bq m-3 with an average value of 111.80 Bq m-3. The values of absorbed dose and annual effective dose (indoors and outdoors) are found to vary from 44.18 nGy h-1 to 65.23 nGy h-1, 0.22 mSv y-1 to 0.32 mSv y-1 and 0.05 mSv y-1 to 0.08 mSv y-1 respectively. The radon concentration and exhalation rates have also been reported. The radium equivalent activities in all the soil samples were found to be lower than the limit (370 Bq kg-1) set in the Organization for Economic Cooperation and Development (OECD) report and the value of Hex in all the samples is less than unity.

A Data Hiding Model with High Security Features Combining Finite State Machines and PMM method

Recent years have witnessed the rapid development of the Internet and telecommunication techniques. Information security is becoming more and more important. Applications such as covert communication, copyright protection, etc, stimulate the research of information hiding techniques. Traditionally, encryption is used to realize the communication security. However, important information is not protected once decoded. Steganography is the art and science of communicating in a way which hides the existence of the communication. Important information is firstly hidden in a host data, such as digital image, video or audio, etc, and then transmitted secretly to the receiver.In this paper a data hiding model with high security features combining both cryptography using finite state sequential machine and image based steganography technique for communicating information more securely between two locations is proposed. The authors incorporated the idea of secret key for authentication at both ends in order to achieve high level of security. Before the embedding operation the secret information has been encrypted with the help of finite-state sequential machine and segmented in different parts. The cover image is also segmented in different objects through normalized cut.Each part of the encoded secret information has been embedded with the help of a novel image steganographic method (PMM) on different cuts of the cover image to form different stego objects. Finally stego image is formed by combining different stego objects and transmit to the receiver side. At the receiving end different opposite processes should run to get the back the original secret message.

Evaluation of Fuzzy ARTMAP with DBSCAN in VLSI Application

The various applications of VLSI circuits in highperformance computing, telecommunications, and consumer electronics has been expanding progressively, and at a very hasty pace. This paper describes a new model for partitioning a circuit using DBSCAN and fuzzy ARTMAP neural network. The first step is concerned with feature extraction, where we had make use DBSCAN algorithm. The second step is the classification and is composed of a fuzzy ARTMAP neural network. The performance of both approaches is compared using benchmark data provided by MCNC standard cell placement benchmark netlists. Analysis of the investigational results proved that the fuzzy ARTMAP with DBSCAN model achieves greater performance then only fuzzy ARTMAP in recognizing sub-circuits with lowest amount of interconnections between them The recognition rate using fuzzy ARTMAP with DBSCAN is 97.7% compared to only fuzzy ARTMAP.

GSM-Based Approach for Indoor Localization

Ability of accurate and reliable location estimation in indoor environment is the key issue in developing great number of context aware applications and Location Based Services (LBS). Today, the most viable solution for localization is the Received Signal Strength (RSS) fingerprinting based approach using wireless local area network (WLAN). This paper presents two RSS fingerprinting based approaches – first we employ widely used WLAN based positioning as a reference system and then investigate the possibility of using GSM signals for positioning. To compare them, we developed a positioning system in real world environment, where realistic RSS measurements were collected. Multi-Layer Perceptron (MLP) neural network was used as the approximation function that maps RSS fingerprints and locations. Experimental results indicate advantage of WLAN based approach in the sense of lower localization error compared to GSM based approach, but GSM signal coverage by far outreaches WLAN coverage and for some LBS services requiring less precise accuracy our results indicate that GSM positioning can also be a viable solution.

Modeling of Bio Scaffolds: Structural and Fluid Transport Characterization

Scaffolds play a key role in tissue engineering and can be produced in many different ways depending on the applications and the materials used. Most researchers used an experimental trialand- error approach into new biomaterials but computer simulation applied to tissue engineering can offer a more exhaustive approach to test and screen out biomaterials. This paper develops the model of scaffolds and Computational Fluid Dynamics that show the value of computer simulations in determining the influence of the geometrical scaffold parameter porosity, pore size and shape on the permeability of scaffolds, magnitude of velocity, drop pressure, shear stress distribution and level and the proper design of the geometry of the scaffold. This creates a need for more advanced studies that include aspects of dynamic conditions of a micro fluid passing through the scaffold were characterized for tissue engineering applications and differentiation of tissues within scaffolds.

Technological Deep Assessment of Automotive Parts Manufacturers Case of Iranian Manufacturers

In order to develop any strategy, it is essential to first identify opportunities, threats, weak and strong points. Assessment of technology level provides the possibility of concentrating on weak and strong points. The results of technology assessment have a direct effect on decision making process in the field of technology transfer or expansion of internal research capabilities so it has a critical role in technology management. This paper presents a conceptual model to analyze the technology capability of a company as a whole and in four main aspects of technology. This model was tested on 10 automotive parts manufacturers in IRAN. Using this model, capability level of manufacturers was investigated in four fields of managing aspects, hard aspects, human aspects, and information and knowledge aspects. Results show that these firms concentrate on hard aspect of technology while others aspects are poor and need to be supported more. So this industry should develop other aspects of technology as well as hard aspect to have effective and efficient use of its technology. These paper findings are useful for the technology planning and management in automotive part manufactures in IRAN and other Industries which are technology followers and transport their needed technologies.

Analysis of Normal Penetration of Ogive -Nose Projectiles into Thin Metallic Plates

In this note, a theoretical model for analyzing of normal penetration of the ogive – nose projectile into metallic targets is presented .The failure is assumed to be asymmetry petalling and the analysis is performed by using the energy balance and work done .The work done consist of the work required for plastic deformation Wp, the work for transferring the matter to new position Wd and the work for bending of the petals Wb. In several studies, it has been shown that we can neglect the loss of energy by temperature. In this present study, in first, by assuming the crater formation after perforation, the value of work done is calculated during the normal penetration of conical projectiles into thin metallic targets. Then the value of residual velocity and ballistic limit of the projectile is predicated by using the energy balance. In final, theoretical and experimental results is compared.

Improving the Quality of e-learning Courses in Higher Education through Student Satisfaction

Thepurpose of the research is to characterize the levels of satisfaction of the students in e-learning post-graduate courses, taking into account specific dimensions of the course which were considered as benchmarks for the quality of this type of online learning initiative, as well as the levels of satisfaction towards each specific indicator identified in each dimension. It was also an aim of this study to understand how thesedimensions relate to one another. Using a quantitative research approach in the collection and analysis of the data, the study involves the participation of the students who attended on e-learning course in 2010/2011. The conclusions of this study suggest that online students present relatively high levels of satisfaction, which points towards a positive experience during the course. It is possible to note that there is a correlation between the different dimensions studied, consequently leading to different improvement strategies. Ultimately, this investigation aims to contribute to the promotion of quality and the success of e-learning initiatives in Higher Education.

WiPoD Wireless Positioning System based on 802.11 WLAN Infrastructure

This paper describes WiPoD (Wireless Position Detector) which is a pure software based location determination and tracking (positioning) system. It uses empirical signal strength measurements from different wireless access points for mobile user positioning. It is designed to determine the location of users having 802.11 enabled mobile devices in an 802.11 WLAN infrastructure and track them in real time. WiPoD is the first main module in our LBS (Location Based Services) framework. We tested K-Nearest Neighbor and Triangulation algorithms to estimate the position of a mobile user. We also give the analysis results of these algorithms for real time operations. In this paper, we propose a supportable, i.e. understandable, maintainable, scalable and portable wireless positioning system architecture for an LBS framework. The WiPoD software has a multithreaded structure and was designed and implemented with paying attention to supportability features and real-time constraints and using object oriented design principles. We also describe the real-time software design issues of a wireless positioning system which will be part of an LBS framework.

Multi Task Scheme to Monitor Multivariate Environments Using Artificial Neural Network

When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.

Knowledge Discovery Techniques for Talent Forecasting in Human Resource Application

Human Resource (HR) applications can be used to provide fair and consistent decisions, and to improve the effectiveness of decision making processes. Besides that, among the challenge for HR professionals is to manage organization talents, especially to ensure the right person for the right job at the right time. For that reason, in this article, we attempt to describe the potential to implement one of the talent management tasks i.e. identifying existing talent by predicting their performance as one of HR application for talent management. This study suggests the potential HR system architecture for talent forecasting by using past experience knowledge known as Knowledge Discovery in Database (KDD) or Data Mining. This article consists of three main parts; the first part deals with the overview of HR applications, the prediction techniques and application, the general view of Data mining and the basic concept of talent management in HRM. The second part is to understand the use of Data Mining technique in order to solve one of the talent management tasks, and the third part is to propose the potential HR system architecture for talent forecasting.

Simulation of Propagation of Cos-Gaussian Beam in Strongly Nonlocal Nonlinear Media Using Paraxial Group Transformation

In this paper, propagation of cos-Gaussian beam in strongly nonlocal nonlinear media has been stimulated by using paraxial group transformation. At first, cos-Gaussian beam, nonlocal nonlinear media, critical power, transfer matrix, and paraxial group transformation are introduced. Then, the propagation of the cos-Gaussian beam in strongly nonlocal nonlinear media is simulated. Results show that beam propagation has periodic structure during self-focusing effect in this case. However, this simple method can be used for investigation of propagation of kinds of beams in ABCD optical media.

e-Service Innovation within Open Innovation Networks

Service innovations are central concerns in fast changing environment. Due to the fitness in customer demands and advances in information technologies (IT) in service management, an expanded conceptualization of e-service innovation is required. Specially, innovation practices have become increasingly more challenging, driving managers to employ a different open innovation model to maintain competitive advantages. At the same time, firms need to interact with external and internal customers in innovative environments, like the open innovation networks, to co-create values. Based on these issues, an important conceptual framework of e-service innovation is developed. This paper aims to examine the contributing factors on e-service innovation and firm performance, including financial and non-financial aspects. The study concludes by showing how e-service innovation will play a significant role in growing the overall values of the firm. The discussion and conclusion will lead to a stronger understanding of e-service innovation and co-creating values with customers within open innovation networks.

Use of Semantic Networks as Learning Material and Evaluation of the Approach by Students

This article first summarizes reasons why current approaches supporting Open Learning and Distance Education need to be complemented by tools permitting lecturers, researchers and students to cooperatively organize the semantic content of Learning related materials (courses, discussions, etc.) into a fine-grained shared semantic network. This first part of the article also quickly describes the approach adopted to permit such a collaborative work. Then, examples of such semantic networks are presented. Finally, an evaluation of the approach by students is provided and analyzed.

A Normalization-based Robust Image Watermarking Scheme Using SVD and DCT

Digital watermarking is one of the techniques for copyright protection. In this paper, a normalization-based robust image watermarking scheme which encompasses singular value decomposition (SVD) and discrete cosine transform (DCT) techniques is proposed. For the proposed scheme, the host image is first normalized to a standard form and divided into non-overlapping image blocks. SVD is applied to each block. By concatenating the first singular values (SV) of adjacent blocks of the normalized image, a SV block is obtained. DCT is then carried out on the SV blocks to produce SVD-DCT blocks. A watermark bit is embedded in the highfrequency band of a SVD-DCT block by imposing a particular relationship between two pseudo-randomly selected DCT coefficients. An adaptive frequency mask is used to adjust local watermark embedding strength. Watermark extraction involves mainly the inverse process. The watermark extracting method is blind and efficient. Experimental results show that the quality degradation of watermarked image caused by the embedded watermark is visually transparent. Results also show that the proposed scheme is robust against various image processing operations and geometric attacks.

Simulating Pathogen Transport with in a Naturally Ventilated Hospital Ward

Understanding how airborne pathogens are transported through hospital wards is essential for determining the infection risk to patients and healthcare workers. This study utilizes Computational Fluid Dynamics (CFD) simulations to explore possible pathogen transport within a six-bed partitioned Nightingalestyle hospital ward. Grid independence of a ward model was addressed using the Grid Convergence Index (GCI) from solutions obtained using three fullystructured grids. Pathogens were simulated using source terms in conjunction with a scalar transport equation and a RANS turbulence model. Errors were found to be less than 4% in the calculation of air velocities but an average of 13% was seen in the scalar field. A parametric study of variations in the pathogen release point illustrated that its distribution is strongly influenced by the local velocity field and the degree of air mixing present.

Generating Qualitative Causal Graph using Modeling Constructs of Qualitative Process Theory for Explaining Organic Chemistry Reactions

This paper discusses the causal explanation capability of QRIOM, a tool aimed at supporting learning of organic chemistry reactions. The development of the tool is based on the hybrid use of Qualitative Reasoning (QR) technique and Qualitative Process Theory (QPT) ontology. Our simulation combines symbolic, qualitative description of relations with quantity analysis to generate causal graphs. The pedagogy embedded in the simulator is to both simulate and explain organic reactions. Qualitative reasoning through a causal chain will be presented to explain the overall changes made on the substrate; from initial substrate until the production of final outputs. Several uses of the QPT modeling constructs in supporting behavioral and causal explanation during run-time will also be demonstrated. Explaining organic reactions through causal graph trace can help improve the reasoning ability of learners in that their conceptual understanding of the subject is nurtured.