The Role of Driving Experience in Hazard Perception and Categorization: A Traffic-Scene Paradigm

This study examined the role of driving experience in hazard perception and categorization using traffic scene pictures. Specifically, young-inexperienced, moderately experienced and very experienced (taxi) drivers observed traffic scene pictures while connected to an eye tracking system and were asked to rate the level of hazardousness of each picture and to mention the three most prominent hazards in it. Target pictures included nine, nearly identical, pairs of pictures where one picture in each pair included an actual hazard as an additional element. Altogether, 22 areas of interest (AOIs) were predefined and included 13 potential hazards and 9 actual hazards. Data analysis included both verbal reports and eye scanning patterns of these AOIs. Generally, both experienced and taxi drivers noted a relatively larger number of potential hazards than young inexperienced drivers Thus, by relating to less salient potential hazards, experienced drivers have demonstrated a better situation model of the traffic environment.

Improved Artificial Immune System Algorithm with Local Search

The Artificial immune systems algorithms are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Artificial Immune System Algorithm is introduced for the first time to overcome its problems of artificial immune system. That use of the small size of a local search around the memory antibodies is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the standard artificial immune system algorithms

Sustainability Strategy and Firm Performance in Residential Trade and Industry: A Conceptual Analysis

The request for a sustainable development challenges both managers and consumers to rethink habitual practices and activities. While consumers are challenged to develop sustainable consumption patterns, companies are asked to establish managerial systems and structures considering economical, ecological, and social issues. As this is in particular true for housing associations, this paper aims first, at providing an understanding of sustainability strategy in residential trade and industry (RTI) by identifying relevant facets of this construct and second, at conceptually analyzing the impact of sustainability strategy in RTI on operational efficiency and performance of municipal housing companies. The author develops a model of sustainability strategy in RTI and its effects and further, sheds light in priorities for future research.

Effect of Heat Treatment on the Phase Formation of La0.6Sr0.4CoO3-α

Powder of La0.6Sr0.4CoO3-α (LSCO) was synthesized by a combined citrate-EDTA method. The as-synthesized LSCO powder was calcined, respectively at temperatures of 800, 900 and 1000 °C with different heating/cooling rates which are 2, 5, 10 and 15 °C min-1. The effects of heat treatments on the phase formation of perovskite phase of LSCO were investigated by powder X-ray diffraction (XRD). The XRD patterns revealed that the rate of 5 °C min-1 is the optimum heating/cooling rate to obtain a single perovskite phase of LSCO with calcination temperature of 800 °C. This result was confirmed by a thermogravimetric analysis (TGA) as it showed a complete decomposition of intermediate compounds to form oxide material was also observed at 800 °C.

Investigation of Increasing the Heat Transfer from Flat Surfaces Using Boundary Layer Excitation

The present study is concerned with effect of exciting boundary layer on increase in heat transfer from flat surfaces. As any increase in heat transfer between a fluid inside a face and another one outside of it can cause an increase in some equipment's efficiency, so at this present we have tried to increase the wall's heat transfer coefficient by exciting the fluid boundary layer. By a collision between flow and the placed block at the fluid way, the flow pattern and the boundary layer stability will change. The flow way inside the channel is simulated as a 2&3-dimensional channel by Gambit TM software. With studying the achieved results by this simulation for the flow way inside the channel with a block coordinating with Fluent TM software, it's determined that the figure and dimensions of the exciter are too important for exciting the boundary layer so that any increase in block dimensions in vertical side against the flow and any reduction in its dimensions at the flow side can increase the average heat transfer coefficient from flat surface and increase the flow pressure loss. Using 2&3-dimensional analysis on exciting the flow at the flow way inside a channel by cylindrical block at the same time with the external flow, we came to this conclusion that the heat flux transferred from the surface, is increased considerably in terms of the condition without excitation. Also, the k-e turbulence model is used.

Comparing Hilditch, Rosenfeld, Zhang-Suen,and Nagendraprasad -Wang-Gupta Thinning

This paper compares Hilditch, Rosenfeld, Zhang- Suen, dan Nagendraprasad Wang Gupta (NWG) thinning algorithms for Javanese character image recognition. Thinning is an effective process when the focus in not on the size of the pattern, but rather on the relative position of the strokes in the pattern. The research analyzes the thinning of 60 Javanese characters. Time-wise, Zhang-Suen algorithm gives the best results with the average process time being 0.00455188 seconds. But if we look at the percentage of pixels that meet one-pixel thickness, Rosenfelt algorithm gives the best results, with a 99.98% success rate. From the number of pixels that are erased, NWG algorithm gives the best results with the average number of pixels erased being 84.12%. It can be concluded that the Hilditch algorithm performs least successfully compared to the other three algorithms.

A New Heuristic Statistical Methodology for Optimizing Queuing Networks Using Discreet Event Simulation

Most of the real queuing systems include special properties and constraints, which can not be analyzed directly by using the results of solved classical queuing models. Lack of Markov chains features, unexponential patterns and service constraints, are the mentioned conditions. This paper represents an applied general algorithm for analysis and optimizing the queuing systems. The algorithm stages are described through a real case study. It is consisted of an almost completed non-Markov system with limited number of customers and capacities as well as lots of common exception of real queuing networks. Simulation is used for optimizing this system. So introduced stages over the following article include primary modeling, determining queuing system kinds, index defining, statistical analysis and goodness of fit test, validation of model and optimizing methods of system with simulation.

2-Dimensional Finger Gesture Based Mobile Robot Control Using Touch Screen

The purpose of this study was to present a reliable mean for human-computer interfacing based on finger gestures made in two dimensions, which could be interpreted and adequately used in controlling a remote robot's movement. The gestures were captured and interpreted using an algorithm based on trigonometric functions, in calculating the angular displacement from one point of touch to another as the user-s finger moved within a time interval; thereby allowing for pattern spotting of the captured gesture. In this paper the design and implementation of such a gesture based user interface was presented, utilizing the aforementioned algorithm. These techniques were then used to control a remote mobile robot's movement. A resistive touch screen was selected as the gesture sensor, then utilizing a programmed microcontroller to interpret them respectively.

Analysis of Plasmids and Restriction Fragment Length Polymorphisms of Acinetobacter baumannii Isolated from Hospitals- AL Jouf Region- KSA

Abstract–The objectives of the current study are to determine the prevalence, etiological agents, drug susceptibility pattern and plasmid profile of Acinetobacter baumannii isolates from Hospital-Acquired Infections (HAI) at Community Hospital, Al Jouf Province, Saudi Arabia. A total of 1890 patients had developed infection during hospital admission and were included in the study. Among those who developed nosocomial infections, 15(9.4), 10(2.7) and 118 (12.7) had respiratory tract infection (RTI), blood stream infections (BSI) and urinary tract (UTI) respectively. A total of 268 bacterial isolates were isolated from nosocomial infection. S. aureus was reported in 23.5% for of the total isolates followed by Klebsiella pneumoniae (17.5%), E. coli (17.2%), P. aeruginosa (11.9%), coagulase negative staphylococcus (9%), A. baumannii (7.1%), Enterobacter spp. (3.4%), Citrobacter freundii (3%), Proteus mirabilis (2.6%), and Proteus vulgaris and Enterococcous faecalis (0.7%). Isolated organisms are multi-drug resistant, predominantly Gram-positive pathogens with a high incidence of methicillin-resistant S. aureus, extended spectrum beta lactamase and vancomycin resistant enterococci organisms. The RFLP (Fragment Length Polymorphisms) patterns of plasmid preparations from isolated A. baumannii isolates had altered RFLP patterns, possibly due to the presence of plasmid(s). Five A. baumannii isolates harbored plasmids all of which were not less than 2.71kbp in molecular weight. Hence, it showed that the gene coding for the isolates were located on the plasmid DNA while the remaining isolates which have no plasmid might showed gene coding for antibiotic resistance being located on chromosomal DNA. Nosocomial infections represent a current problem in Community Hospital, Al Jouf Province, Saudi Arabia. Problems associated with SSI include infection with multidrug resistant pathogens which are difficult to treat and are associated with increased mortality.

Feature Reduction of Nearest Neighbor Classifiers using Genetic Algorithm

The design of a pattern classifier includes an attempt to select, among a set of possible features, a minimum subset of weakly correlated features that better discriminate the pattern classes. This is usually a difficult task in practice, normally requiring the application of heuristic knowledge about the specific problem domain. The selection and quality of the features representing each pattern have a considerable bearing on the success of subsequent pattern classification. Feature extraction is the process of deriving new features from the original features in order to reduce the cost of feature measurement, increase classifier efficiency, and allow higher classification accuracy. Many current feature extraction techniques involve linear transformations of the original pattern vectors to new vectors of lower dimensionality. While this is useful for data visualization and increasing classification efficiency, it does not necessarily reduce the number of features that must be measured since each new feature may be a linear combination of all of the features in the original pattern vector. In this paper a new approach is presented to feature extraction in which feature selection, feature extraction, and classifier training are performed simultaneously using a genetic algorithm. In this approach each feature value is first normalized by a linear equation, then scaled by the associated weight prior to training, testing, and classification. A knn classifier is used to evaluate each set of feature weights. The genetic algorithm optimizes a vector of feature weights, which are used to scale the individual features in the original pattern vectors in either a linear or a nonlinear fashion. By this approach, the number of features used in classifying can be finely reduced.

Statistics over Lyapunov Exponents for Feature Extraction: Electroencephalographic Changes Detection Case

A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.

Extraction of Semantic Digital Signatures from MRI Photos for Image-Identification Purposes

This paper makes an attempt to solve the problem of searching and retrieving of similar MRI photos via Internet services using morphological features which are sourced via the original image. This study is aiming to be considered as an additional tool of searching and retrieve methods. Until now the main way of the searching mechanism is based on the syntactic way using keywords. The technique it proposes aims to serve the new requirements of libraries. One of these is the development of computational tools for the control and preservation of the intellectual property of digital objects, and especially of digital images. For this purpose, this paper proposes the use of a serial number extracted by using a previously tested semantic properties method. This method, with its center being the multi-layers of a set of arithmetic points, assures the following two properties: the uniqueness of the final extracted number and the semantic dependence of this number on the image used as the method-s input. The major advantage of this method is that it can control the authentication of a published image or its partial modification to a reliable degree. Also, it acquires the better of the known Hash functions that the digital signature schemes use and produces alphanumeric strings for cases of authentication checking, and the degree of similarity between an unknown image and an original image.

Study on Mixed Convection Heat Transfer in Vertical Ducts with Radiation Effects

Experiments have been performed to investigate the radiation effects on mixed convection heat transfer for thermally developing airflow in vertical ducts with two differentially heated isothermal walls and two adiabatic walls. The investigation covers the Reynolds number Re = 800 to Re = 2900, heat flux varied from 256 W/m2 to 863 W/m2, hot wall temperature ranges from 27°C to 100 °C, aspect ratios 1 & 0.5 and the emissivity of internal walls are 0.05 and 0.85. In the present study, combined flow visualization was conducted to observe the flow patterns. The effect of surface temperature along the walls was studied to investigate the local Nusselt number variation within the duct. The result shows that flow condition and radiation significantly affect the total Nusselt number and tends to reduce the buoyancy condition.

Titania and Cu-Titania Composite Layer on Graphite Substrate as Negative Electrode for Li-Ion Battery

This research study the application of the immobilized TiO2 layer and Cu-TiO2 layer on graphite substrate as a negative electrode or anode for Li-ion battery. The titania layer was produced through chemical bath deposition method, meanwhile Cu particles were deposited electrochemically. A material can be used as an electrode as it has capability to intercalates Li ions into its crystal structure. The Li intercalation into TiO2/Graphite and Cu- TiO2/Graphite were analyzed from the changes of its XRD pattern after it was used as electrode during discharging process. The XRD patterns were refined by Le Bail method in order to determine the crystal structure of the prepared materials. A specific capacity and the cycle ability measurement were carried out to study the performance of the prepared materials as negative electrode of the Li-ion battery. The specific capacity was measured during discharging process from fully charged until the cut off voltage. A 300 was used as a load. The result shows that the specific capacity of Li-ion battery with TiO2/Graphite as negative electrode is 230.87 ± 1.70mAh.g-1 which is higher than the specific capacity of Li-ion battery with pure graphite as negative electrode, i.e 140.75 ±0.46mAh.g-1. Meanwhile deposition of Cu onto TiO2 layer does not increase the specific capacity, and the value even lower than the battery with TiO2/Graphite as electrode. The cycle ability of the prepared battery is only two cycles, due to the Li ribbon which was used as cathode became fragile and easily broken.

Hierarchies Based On the Number of Cooperating Systems of Finite Automata on Four-Dimensional Input Tapes

In theoretical computer science, the Turing machine has played a number of important roles in understanding and exploiting basic concepts and mechanisms in computing and information processing [20]. It is a simple mathematical model of computers [9]. After that, M.Blum and C.Hewitt first proposed two-dimensional automata as a computational model of two-dimensional pattern processing, and investigated their pattern recognition abilities in 1967 [7]. Since then, a lot of researchers in this field have been investigating many properties about automata on a two- or three-dimensional tape. On the other hand, the question of whether processing fourdimensional digital patterns is much more difficult than two- or threedimensional ones is of great interest from the theoretical and practical standpoints. Thus, the study of four-dimensional automata as a computasional model of four-dimensional pattern processing has been meaningful [8]-[19],[21]. This paper introduces a cooperating system of four-dimensional finite automata as one model of four-dimensional automata. A cooperating system of four-dimensional finite automata consists of a finite number of four-dimensional finite automata and a four-dimensional input tape where these finite automata work independently (in parallel). Those finite automata whose input heads scan the same cell of the input tape can communicate with each other, that is, every finite automaton is allowed to know the internal states of other finite automata on the same cell it is scanning at the moment. In this paper, we mainly investigate some accepting powers of a cooperating system of eight- or seven-way four-dimensional finite automata. The seven-way four-dimensional finite automaton is an eight-way four-dimensional finite automaton whose input head can move east, west, south, north, up, down, or in the fu-ture, but not in the past on a four-dimensional input tape.

Mining Frequent Patterns with Functional Programming

Frequent patterns are patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a dataset. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages such as C, Cµ, Java. The imperative paradigm is significantly inefficient when itemset is large and the frequent pattern is long. We suggest a high-level declarative style of programming using a functional language. Our supposition is that the problem of frequent pattern discovery can be efficiently and concisely implemented via a functional paradigm since pattern matching is a fundamental feature supported by most functional languages. Our frequent pattern mining implementation using the Haskell language confirms our hypothesis about conciseness of the program. The performance studies on speed and memory usage support our intuition on efficiency of functional language.

The Effects of RCA Clean Variables on Particle Removal Efficiency

Shrunken patterning for integrated device manufacturing requires surface cleanliness and surface smoothness in wet chemical processing [1]. It is necessary to control all process parameters perfectly especially for the common cleaning technique RCA clean (SC-1 and SC-2) [2]. In this paper the characteristic and effect of surface preparation parameters are discussed. The properties of RCA wet chemical processing in silicon technology is based on processing time, temperature, concentration and megasonic power of SC-1 and QDR. An improvement of wafer surface preparation by the enhanced variables of the wet cleaning chemical process is proposed.

Photograph Based Pair-matching Recognition of Human Faces

In this paper, a novel system recognition of human faces without using face different color photographs is proposed. It mainly in face detection, normalization and recognition. Foot method of combination of Haar-like face determined segmentation and region-based histogram stretchi (RHST) is proposed to achieve more accurate perf using Haar. Apart from an effective angle norm side-face (pose) normalization, which is almost a might be important and beneficial for the prepr introduced. Then histogram-based and photom normalization methods are investigated and ada retinex (ASR) is selected for its satisfactory illumin Finally, weighted multi-block local binary pattern with 3 distance measures is applied for pair-mat Experimental results show its advantageous perfo with PCA and multi-block LBP, based on a principle.

Synthesis of Silver Nanoparticles by Chemical Reduction Method and Their Antibacterial Activity

Silver nanoparticles were prepared by chemical reduction method. Silver nitrate was taken as the metal precursor and hydrazine hydrate as a reducing agent. The formation of the silver nanoparticles was monitored using UV-Vis absorption spectroscopy. The UV-Vis spectroscopy revealed the formation of silver nanopart├¡cles by exhibing the typical surface plasmon absorption maxima at 418-420 nm from the UV–Vis spectrum. Comparison of theoretical (Mie light scattering theory) and experimental results showed that diameter of silver nanoparticles in colloidal solution is about 60 nm. We have used energy-dispersive spectroscopy (EDX), X-ray diffraction (XRD), transmission electron microscopy (TEM) and, UV–Vis spectroscopy to characterize the nanoparticles obtained. The energy-dispersive spectroscopy (EDX) of the nanoparticles dispersion confirmed the presence of elemental silver signal no peaks of other impurity were detected. The average size and morphology of silver nanoparticles were determined by transmission electron microscopy (TEM). TEM photographs indicate that the nanopowders consist of well dispersed agglomerates of grains with a narrow size distribution (40 and 60 nm), whereas the radius of the individual particles are between 10 and 20 nm. The synthesized nanoparticles have been structurally characterized by X-ray diffraction and transmission high-energy electron diffraction (HEED). The peaks in the XRD pattern are in good agreement with the standard values of the face-centered-cubic form of metallic silver (ICCD-JCPDS card no. 4-0787) and no peaks of other impurity crystalline phases were detected. Additionally, the antibacterial activity of the nanopart├¡culas dispersion was measured by Kirby-Bauer method. The nanoparticles of silver showed high antimicrobial and bactericidal activity against gram positive bacteria such as Escherichia Coli, Pseudimonas aureginosa and staphylococcus aureus which is a highly methicillin resistant strain.

Impact of a Proposed Pier on Tidal Currents:Koa Kood Island, Thailand

The impact of a proposed pier on tidal current alteration was evaluated. The proposed pier location was in Salad Bay on Koa Kood Island, Trat province, Thailand, and was designed to accommodate passenger ships with a draft of less than 2 m. The study began with collecting necessary data, including bathymetric, water elevation and tidal current characteristics. The impact was assessed using a software package (MIKE21). Although the results showed that the pier would affect the existing current pattern, the change was determined to be insignificant, as the design of the piles for the pier provided sufficient spacing to let the current flow as freely as possible. Consequences of the altered current, such as seabed erosion, water stagnation, sediment deposition and navigational risk were assessed. Environmental mitigation measures might be necessary if the impacts were considered unacceptable.