Person Identification using Gait by Combined Features of Width and Shape of the Binary Silhouette

Current image-based individual human recognition methods, such as fingerprints, face, or iris biometric modalities generally require a cooperative subject, views from certain aspects, and physical contact or close proximity. These methods cannot reliably recognize non-cooperating individuals at a distance in the real world under changing environmental conditions. Gait, which concerns recognizing individuals by the way they walk, is a relatively new biometric without these disadvantages. The inherent gait characteristic of an individual makes it irreplaceable and useful in visual surveillance. In this paper, an efficient gait recognition system for human identification by extracting two features namely width vector of the binary silhouette and the MPEG-7-based region-based shape descriptors is proposed. In the proposed method, foreground objects i.e., human and other moving objects are extracted by estimating background information by a Gaussian Mixture Model (GMM) and subsequently, median filtering operation is performed for removing noises in the background subtracted image. A moving target classification algorithm is used to separate human being (i.e., pedestrian) from other foreground objects (viz., vehicles). Shape and boundary information is used in the moving target classification algorithm. Subsequently, width vector of the outer contour of binary silhouette and the MPEG-7 Angular Radial Transform coefficients are taken as the feature vector. Next, the Principal Component Analysis (PCA) is applied to the selected feature vector to reduce its dimensionality. These extracted feature vectors are used to train an Hidden Markov Model (HMM) for identification of some individuals. The proposed system is evaluated using some gait sequences and the experimental results show the efficacy of the proposed algorithm.

Tobephobia: Teachers- Ineptitude to Manage Curriculum Change

In this paper, Tobephobia (TBP) alludes to the fear of failure experienced by teachers to manage curriculum change. TBP is an emerging concept and it extends the boundaries of research in terms of how we view achievement and failure in education. Outcomes-based education (OBE) was introduced fifteen years ago in South African schools without simultaneously upgrading teachers- professional competencies. This exploratory research, therefore examines a simple question: What is the impact of TBP and OBE on teachers? Teacher ineptitude to cope with the OBE curriculum in the classroom is a serious problem affecting large numbers of South African teachers. This exploratory study sought to determine the perceived negative impact of OBE and TBP on teachers. A survey was conducted amongst 311 teachers in Port Elizabeth and Durban, South Africa. The results confirm the very negative impact of TBP and OBE on teachers. This exploratory study authenticates the existence of TBP.

Beneficial Use of Coal Combustion By-products in the Rehabilitation of Failed Asphalt Pavements

This study demonstrates the use of Class F fly ash in combination with lime or lime kiln dust in the full depth reclamation (FDR) of asphalt pavements. FDR, in the context of this paper, is a process of pulverizing a predetermined amount of flexible pavement that is structurally deficient, blending it with chemical additives and water, and compacting it in place to construct a new stabilized base course. Test sections of two structurally deficient asphalt pavements were reclaimed using Class F fly ash in combination with lime and lime kiln dust. In addition, control sections were constructed using cement, cement and emulsion, lime kiln dust and emulsion, and mill and fill. The service performance and structural behavior of the FDR pavement test sections were monitored to determine how the fly ash sections compared to other more traditional pavement rehabilitation techniques. Service performance and structural behavior were determined with the use of sensors embedded in the road and Falling Weight Deflectometer (FWD) tests. Monitoring results of the FWD tests conducted up to 2 years after reclamation show that the cement, fly ash+LKD, and fly ash+lime sections exhibited two year resilient modulus values comparable to open graded cement stabilized aggregates (more than 750 ksi). The cement treatment resulted in a significant increase in resilient modulus within 3 weeks of construction and beyond this curing time, the stiffness increase was slow. On the other hand, the fly ash+LKD and fly ash+lime test sections indicated slower shorter-term increase in stiffness. The fly ash+LKD and fly ash+lime section average resilient modulus values at two years after construction were in excess of 800 ksi. Additional longer-term testing data will be available from ongoing pavement performance and environmental condition data collection at the two pavement sites.

Intelligent Video-Based Monitoring of Freeway Traffic

Freeways are originally designed to provide high mobility to road users. However, the increase in population and vehicle numbers has led to increasing congestions around the world. Daily recurrent congestion substantially reduces the freeway capacity when it is most needed. Building new highways and expanding the existing ones is an expensive solution and impractical in many situations. Intelligent and vision-based techniques can, however, be efficient tools in monitoring highways and increasing the capacity of the existing infrastructures. The crucial step for highway monitoring is vehicle detection. In this paper, we propose one of such techniques. The approach is based on artificial neural networks (ANN) for vehicles detection and counting. The detection process uses the freeway video images and starts by automatically extracting the image background from the successive video frames. Once the background is identified, subsequent frames are used to detect moving objects through image subtraction. The result is segmented using Sobel operator for edge detection. The ANN is, then, used in the detection and counting phase. Applying this technique to the busiest freeway in Riyadh (King Fahd Road) achieved higher than 98% detection accuracy despite the light intensity changes, the occlusion situations, and shadows.

Reducing Cognitive Load in Learning Computer Programming

Many difficulties are faced in the process of learning computer programming. This paper will propose a system framework intended to reduce cognitive load in learning programming. In first section focus is given on the process of learning and the shortcomings of the current approaches to learning programming. Finally the proposed prototype is suggested along with the justification of the prototype. In the proposed prototype the concept map is used as visualization metaphor. Concept maps are similar to the mental schema in long term memory and hence it can reduce cognitive load well. In addition other method such as part code method is also proposed in this framework to can reduce cognitive load.

Comparative Study on Production of Fructooligosaccharides by p. Simplicissimum Using Immobilized Cells and Conventional Reactor System

Fructooligosaccharides derived from microbial enzyme especially from fungal sources has been received particular attention due to its beneficial effects as prebiotics and mass production. However, fungal fermentation is always cumbersome due to its broth rheology problem that will eventually affect the production of FOS. This study investigated the efficiency of immobilized cell system using rotating fibrous bed bioreactor (RFBB) in producing fructooligosaccharides (FOS). A comparative picture with respect to conventional stirred tank bioreactor (CSTB) and RFBB has been presented. To demonstrate the effect of agitation intensity and aeration rate, a laboratory-scale bioreactor 2.5 L was operated in three phases (high, medium, low) for 48 hours. Agitation speed has a great influence on P. simplicissimum fermentation for FOS production, where the volumetric FOS productivity using RFBB is increased with almost 4 fold compared to the FOS productivity in CSTB that only 0.319 g/L/h. Rate of FOS production increased up to 1.2 fold when immobilized cells system was employed at aeration rate similar to the freely suspended cells at 2.0 vvm.

Evaluating the Effect of Domestic Price on Rice Production in an African Setting: A Typical Evidence of the Sierra Leone Case

Rice, which is the staple food in Sierra Leone, is consumed on a daily basis. It is the most imperative food crop extensively grown by farmers across all ecologies in the country. Though much attention is now given to rice grain production through the small holder commercialization programme (SHCP), however, no attention has been given in investigating the limitations faced by rice producers. This paper will contribute to attempts to overcome the development challenges caused by food insecurity. The objective of this paper is thus, to analysis the relationship between rice production and the domestic retail price of rice. The study employed a log linear model in which, the quantity of rice produced is the dependent variable, quantity of rice imported, price of imported rice and price of domestic rice as explanatory variables. Findings showed that, locally produced rice is even more expensive than the imported rice per ton, and almost all the inhabitants in the capital city which hosts about 65% of the entire population of the country favor imported rice, as it is free from stones with other impurities. On the other hand, to control price and simultaneously increase rice production, the government should purchase the rice from the farmers and then sell to private retailers.

Gene Selection Guided by Feature Interdependence

Cancers could normally be marked by a number of differentially expressed genes which show enormous potential as biomarkers for a certain disease. Recent years, cancer classification based on the investigation of gene expression profiles derived by high-throughput microarrays has widely been used. The selection of discriminative genes is, therefore, an essential preprocess step in carcinogenesis studies. In this paper, we have proposed a novel gene selector using information-theoretic measures for biological discovery. This multivariate filter is a four-stage framework through the analyses of feature relevance, feature interdependence, feature redundancy-dependence and subset rankings, and having been examined on the colon cancer data set. Our experimental result show that the proposed method outperformed other information theorem based filters in all aspect of classification errors and classification performance.

TiO2-Zeolite Y Catalyst Prepared Using Impregnation and Ion-Exchange Method for Sonocatalytic Degradation of Amaranth Dye in Aqueous Solution

Characteristics and sonocatalytic activity of zeolite Y catalysts loaded with TiO2 using impregnation and ion exchange methods for the degradation of amaranth dye were investigated. The Ion-exchange method was used to encapsulate the TiO2 into the internal pores of the zeolite while the incorporation of TiO2 mostly on the external surface of zeolite was carried out using the impregnation method. Different characterization techniques were used to elucidate the physicochemical properties of the produced catalysts. The framework of zeolite Y remained virtually unchanged after the encapsulation of TiO2 while the crystallinity of zeolite decreased significantly after the incorporation of 15 wt% of TiO2. The sonocatalytic activity was enhanced by TiO2 incorporation with maximum degradation efficiencies of 50% and 68% for the encapsulated titanium and titanium loaded onto the zeolite, respectively after 120min of reaction. Catalysts characteristics and sonocatalytic behaviors were significantly affected by the preparation method and the location of TiO2 introduced with zeolite structure. Behaviors in the sonocatalytic process were successfully correlated with the characteristics of the catalysts used.

Active Tendons for Seismic Control of Buildings

In this study, active tendons with Proportional Integral Derivation type controllers were applied to a SDOF and a MDOF building model. Physical models of buildings were constituted with virtual springs, dampers and rigid masses. After that, equations of motion of all degrees of freedoms were obtained. Matlab Simulink was utilized to obtain the block diagrams for these equations of motion. Parameters for controller actions were found by using a trial method. After earthquake acceleration data were applied to the systems, building characteristics such as displacements, velocities, accelerations and transfer functions were analyzed for all degrees of freedoms. Comparisons on displacement vs. time, velocity vs. time, acceleration vs. time and transfer function (Db) vs. frequency (Hz) were made for uncontrolled and controlled buildings. The results show that the method seems feasible.

The Effects of the Impact of Instructional Immediacy on Cognition and Learning in Online Classes

Current research has explored the impact of instructional immediacy, defined as those behaviors that help build close relationships or feelings of closeness, both on cognition and motivation in the traditional classroom and online classroom; however, online courses continue to suffer from higher dropout rates. Based on Albert Bandura-s Social Cognitive Theory, four primary relationships or interactions in an online course will be explored in light of how they can provide immediacy thereby reducing student attrition and improving cognitive learning. The four relationships are teacher-student, student-student, and student-content, and studentcomputer. Results of a study conducted with inservice teachers completing a 14-week online professional development technology course will be examined to demonstrate immediacy strategies that improve cognitive learning and reduce student attrition. Results of the study reveal that students can be motivated through various interactions and instructional immediacy behaviors which lead to higher completion rates, improved self-efficacy, and cognitive learning.

An Experimental Study of Tip Vortex Cavitation Inception in an Axial Flow Pump

The interaction of the blade tip with the casing boundary layer and the leakage flow may lead to a kind of cavitation namely tip vortex cavitation. In this study, the onset of tip vortex cavitation was experimentally investigated in an axial flow pump. For a constant speed and a fixed angle of attack and by changing the flow rate, the pump head, input power, output power and efficiency were calculated and the pump characteristic curves were obtained. The cavitation phenomenon was observed with a camera and a stroboscope. Finally, the critical flow region, which tip vortex cavitation might have occurred, was identified. The results show that just by adjusting the flow rate, out of the specified region, the possibility of occurring tip vortex cavitation, decreases to a great extent.

Biplot Analysis for Evaluation of Tolerance in Some Bean (Phaseolus vulgaris L.) Genotypes to Bean Common Mosaic Virus (BCMV)

The common bean is the most important grain legume for direct human consumption in the world and BCMV is one of the world's most serious bean diseases that can reduce yield and quality of harvested product. To determine the best tolerance index to BCMV and recognize tolerant genotypes, 2 experiments were conducted in field conditions. Twenty five common bean genotypes were sown in 2 separate RCB design with 3 replications under contamination and non-contamination conditions. On the basis of the results of indices correlations GMP, MP and HARM were determined as the most suitable tolerance indices. The results of principle components analysis indicated 2 first components totally explained 98.52% of variations among data. The first and second components were named potential yield and stress susceptible respectively. Based on the results of BCMV tolerance indices assessment and biplot analysis WA8563-4, WA8563-2 and Cardinal were the genotypes that exhibited potential seed yield under contamination and noncontamination conditions.

Transmit Sub-aperture Optimization in MSTA Ultrasound Imaging Method

The paper presents the optimization problem for the multi-element synthetic transmit aperture method (MSTA) in ultrasound imaging applications. The optimal choice of the transmit aperture size is performed as a trade-off between the lateral resolution, penetration depth and the frame rate. Results of the analysis obtained by a developed optimization algorithm are presented. Maximum penetration depth and the best lateral resolution at given depths are chosen as the optimization criteria. The optimization algorithm was tested using synthetic aperture data of point reflectors simulated by Filed II program for Matlab® for the case of 5MHz 128-element linear transducer array with 0.48 mm pitch are presented. The visualization of experimentally obtained synthetic aperture data of a tissue mimicking phantom and in vitro measurements of the beef liver are also shown. The data were obtained using the SonixTOUCH Research systemequipped with a linear 4MHz 128 element transducerwith 0.3 mm element pitch, 0.28 mm element width and 70% fractional bandwidth was excited by one sine cycle pulse burst of transducer's center frequency.

A Dynamic Composition of an Adaptive Course

The number of framework conceived for e-learning constantly increase, unfortunately the creators of learning materials and educational institutions engaged in e-formation adopt a “proprietor" approach, where the developed products (courses, activities, exercises, etc.) can be exploited only in the framework where they were conceived, their uses in the other learning environments requires a greedy adaptation in terms of time and effort. Each one proposes courses whose organization, contents, modes of interaction and presentations are unique for all learners, unfortunately the latter are heterogeneous and are not interested by the same information, but only by services or documents adapted to their needs. Currently the new tendency for the framework conceived for e-learning, is the interoperability of learning materials, several standards exist (DCMI (Dublin Core Metadata Initiative)[2], LOM (Learning Objects Meta data)[1], SCORM (Shareable Content Object Reference Model)[6][7][8], ARIADNE (Alliance of Remote Instructional Authoring and Distribution Networks for Europe)[9], CANCORE (Canadian Core Learning Resource Metadata Application Profiles)[3]), they converge all to the idea of learning objects. They are also interested in the adaptation of the learning materials according to the learners- profile. This article proposes an approach for the composition of courses adapted to the various profiles (knowledge, preferences, objectives) of learners, based on two ontologies (domain to teach and educational) and the learning objects.

Brain Drain of Doctors; Causes and Consequences in Pakistan

Pakistani doctors (MBBS) are emigrating towards developed countries for professional adjustments. This study aims to highlight causes and consequences of doctors- brain drain from Pakistan. Primary data was collected from Mayo Hospital, Lahore by interviewing doctors (n=100) through systematic random sampling technique. It found that various socio-economic and political conditions are working as push and pull factors for brain drain of doctors in Pakistan. Majority of doctors (83%) declared poor remunerations and professional infrastructure of health department as push factor of doctors- brain drain. 81% claimed that continuous instability in political situation and threats of terrorism are responsible for emigration of doctors. 84% respondents considered fewer opportunities of further studies responsible for their emigration. Brain drain of doctors is affecting health sector-s policies / programs, standard doctor-patient ratios and quality of health services badly.

Surface Flattening Assisted with 3D Mannequin Based On Minimum Energy

The topic of surface flattening plays a vital role in the field of computer aided design and manufacture. Surface flattening enables the production of 2D patterns and it can be used in design and manufacturing for developing a 3D surface to a 2D platform, especially in fashion design. This study describes surface flattening based on minimum energy methods according to the property of different fabrics. Firstly, through the geometric feature of a 3D surface, the less transformed area can be flattened on a 2D platform by geodesic. Then, strain energy that has accumulated in mesh can be stably released by an approximate implicit method and revised error function. In some cases, cutting mesh to further release the energy is a common way to fix the situation and enhance the accuracy of the surface flattening, and this makes the obtained 2D pattern naturally generate significant cracks. When this methodology is applied to a 3D mannequin constructed with feature lines, it enhances the level of computer-aided fashion design. Besides, when different fabrics are applied to fashion design, it is necessary to revise the shape of a 2D pattern according to the properties of the fabric. With this model, the outline of 2D patterns can be revised by distributing the strain energy with different results according to different fabric properties. Finally, this research uses some common design cases to illustrate and verify the feasibility of this methodology.

Motivated Support Vector Regression using Structural Prior Knowledge

It-s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in the form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prior Knowledge, SPK). This paper explores the incorporation of SPK in SVR by constructing appropriate admissible support vector kernel (SV kernel) based on the properties of reproducing kernel (R.K). Three-levels specifications of SPK are studied with the corresponding sub-levels of prior knowledge that can be considered for the method. These include Hierarchical SPK (HSPK), Interactional SPK (ISPK) consisting of independence, global and local interaction, Functional SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A convenient tool for describing the SPK, namely Description Matrix of SPK is introduced. Subsequently, a new SVR, namely Motivated Support Vector Regression (MSVR) whose structure is motivated in part by SPK, is proposed. Synthetic examples show that it is possible to incorporate a wide variety of SPK and helpful to improve the approximation performance in complex cases. The benefits of MSVR are finally shown on a real-life military application, Air-toground battle simulation, which shows great potential for MSVR to the complex military applications.

The Effect of Soil Surface Slope on Splash Distribution under Water Drop Impact

The effects of down slope steepness on soil splash distribution under a water drop impact have been investigated in this study. The equipment used are the burette to simulate a water drop, a splash cup filled with sandy soil which forms the source area and a splash board to collect the ejected particles. The results found in this study have shown that the apparent mass increased with increasing downslope angle following a linear regression equation with high coefficient of determination. In the same way, the radial soil splash distribution over the distance has been analyzed statistically, and an exponential function was the best fit of the relationship for the different slope angles. The curves and the regressions equations validate the well known FSDF and extend the theory of Van Dijk.

Preparation of Nanosized Iron Oxide and their Photocatalytic Properties for Congo Red

Nanostructured Iron Oxide with different morphologies of rod-like and granular have been suc-cessfully prepared via a solid-state reaction in the presence of NaCl, NaBr, NaI and NaN3, respectively. The added salts not only prevent a drastic increase in the size of the products but also provide suitable conditions for the oriented growth of primary nanoparticles. The formation mechanisms of these materials by solid-state reaction at ambient temperature are proposed. The photocatalytic experiments for congo red (CR) have demonstrated that the mixture of α-Fe2O3 and Fe3O4 nanostructures were more efficient than α-Fe2O3 nanostructures.