Investigation of New Gait Representations for Improving Gait Recognition

This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.

Benchmarking Role in Internal Supply Chain Management of Indian Manufacturing Industries

Due to day by day competition in the market, the implementation of benchmarking practice is necessary for improving existing internal supply chain management performance of manufacturing industries. The continuous benchmarking practice might be helpful to increase the productivity of middle scale medium enterprises (MSMEs) by reducing the idle time during the flow of raw material/products, funds and information. The objective of this research paper is to provide an overview of benchmarking, benchmarking wheel, benchmarking tool and techniques and its importance through literature review of reputed journals. This concept of benchmarking may be fruitful in the process of gap identification and for improving the performance of internal supply chain management of Indian manufacturing industries.

Rear Seat Belt Use in Developing Countries: A Case Study from the United Arab Emirates

The seat belt is a vital tool in improving traffic safety conditions and minimising injuries due to traffic accidents. Most developing countries are facing a big problems associated with the human and financial losses due to traffic accidents. One way to minimise these losses is the use of seat belts by passengers both in the front and rear seats of a vehicle; however, at the same time, close to nothing is known about the rates of seat belt utilisation among rear seat passengers in many developing countries. Therefore, there is a need to estimate these rates in order to know the extent of this problem and how people interact with traffic safety measures like seat belts and find demographic characteristics that contribute to wearing or non-wearing of seat belts with the aim of finding solutions to improve wearing rates. In this paper, an observational study was done to gather data on restraints use in motor vehicle rear seats in eight observational stations in a rapidly developing country, the United Arab Emirates (UAE), and estimate a use rate for the whole country. Also, a questionnaire was used in order to study demographic characteristics affecting the wearing of seatbelts in rear seats. Results of the observational study showed that the overall wearing/usage rate was 12.3%, which is considered very low when compared to other countries. Survey results show that single, male, less educated passengers from Arab and South Asian backgrounds use seat belts reportedly less than others. Finally, solutions are put forward to improve this wearing rate based on the results of this study.

Social Capital in Housing Reconstruction Post Disaster Case of Yogyakarta Post Earthquake

This paper will focus on the concept of social capital for especially housing reconstruction Post Disaster. The context of the study is Indonesia and Yogyakarta Post Earthquake 2006 as a case, but it is expected that the concept can be adopted in general post disaster reconstruction. The discussion will begin by addressing issues on House Reconstruction Post Disaster in Indonesia and Yogyakarta; defining Social Capital as a concept for effective management capacity based on community; Social Capital Post Java Earthquake utilizing Gotong Royong—community mutual self-help, and Approach and Strategy towards Community-based Reconstruction.

Enabling the Physical Elements of a Pedestrian Friendly District around a Rail Station for Supporting Transit Oriented Development

Rail-station area development that is based on the concept of TOD (Transit Oriented Development) is principally oriented to pedestrian accessibility for daily mobility. The aim of this research is elaborating how far the existing physical elements of a rail-station district could facilitate pedestrian mobility and establish a pedestrian friendly district toward implementation of a TOD concept. This research was conducted through some steps: (i) mapping the rail-station area pedestrian sidewalk and pedestrian network as well as activity nodes and transit nodes, (ii) assessing the level of pedestrian sidewalk connectivity joining trip origin and destination. The research area coverage in this case is limited to walking distance of the rail station (around 500 meters or 10-15 minutes walking). The findings of this research on the current condition of the street and pedestrian sidewalk network and connectivity, show good preference for the foot modal share (more than 50%) is achieved. Nevertheless, it depends on the distance from the trip origin to destination.

Automated Video Surveillance System for Detection of Suspicious Activities during Academic Offline Examination

This research work aims to develop a system that will analyze and identify students who indulge in malpractices/suspicious activities during the course of an academic offline examination. Automated Video Surveillance provides an optimal solution which helps in monitoring the students and identifying the malpractice event immediately. This work is organized into three modules. The first module deals with performing an impersonation check using a PCA-based face recognition method which is done by cross checking his profile with the database. The presence or absence of the student is even determined in this module by implementing an image registration technique wherein a grid is formed by considering all the images registered using the frontal camera at the determined positions. Second, detecting such facial malpractices in which a student gets involved in conversation with another, trying to obtain unauthorized information etc., based on the threshold range evaluated by considering his/her mouth state whether open or closed. The third module deals with identification of unauthorized material or gadgets used in the examination hall by training the positive samples of the object through various stages. Here, a top view camera feed is analyzed to detect the suspicious activities. The system automatically alerts the administration when any suspicious activities are identified, thereby reducing the error rate caused due to manual monitoring. This work is an improvement over our previous work published in identifying suspicious activities done by examinees in an offline examination.

Comparisons of Surveying with Terrestrial Laser Scanner and Total Station for Volume Determination of Overburden and Coal Excavations in Large Open-Pit Mine

The volume of overburden and coal excavations in open-pit mine is generally determined by conventional survey such as total station. This study aimed to evaluate the accuracy of terrestrial laser scanner (TLS) used to measure overburden and coal excavations, and to compare TLS survey data sets with the data of the total station. Results revealed that, the reference points measured with the total station showed 0.2 mm precision for both horizontal and vertical coordinates. When using TLS on the same points, the standard deviations of 4.93 cm and 0.53 cm for horizontal and vertical coordinates, respectively, were achieved. For volume measurements covering the mining areas of 79,844 m2, TLS yielded the mean difference of about 1% and the surface error margin of 6 cm at the 95% confidence level when compared to the volume obtained by total station.

Numerical Analysis of Effect of Crack Location on the Crack Breathing Behavior

In this work, a three-dimensional finite element model was developed to investigate the crack breathing behavior at different crack locations considering the effect of unbalance force. A two-disk rotor with a crack is simulated using ABAQUS. The duration of each crack status (open, closed and partially open/closed) during a full shaft rotation was examined to analyse the crack breathing behavior. Unbalanced shaft crack breathing behavior was found to be different at different crack locations. The breathing behavior of crack along the shaft length is divided into different regions depending on the unbalance force and crack location. The simulated results in this work can be further utilised to obtain the time-varying stiffness matrix of the cracked shaft element under the influence of unbalance force.

An Efficient Stud Krill Herd Framework for Solving Non-Convex Economic Dispatch Problem

The problem of economic dispatch (ED) is the basic problem of power framework, its main goal is to find the most favorable generation dispatch to generate each unit, reduce the whole power generation cost, and meet all system limitations. A heuristic algorithm, recently developed called Stud Krill Herd (SKH), has been employed in this paper to treat non-convex ED problems. The proposed KH has been modified using Stud selection and crossover (SSC) operator, to enhance the solution quality and avoid local optima. We are demonstrated SKH effects in two case study systems composed of 13-unit and 40-unit test systems to verify its performance and applicability in solving the ED problems. In the above systems, SKH can successfully obtain the best fuel generator and distribute the load requirements for the online generators. The results showed that the use of the proposed SKH method could reduce the total cost of generation and optimize the fulfillment of the load requirements.

An Improved Limited Tolerance Rough Set Model

Some extended rough set models in incomplete information system cannot distinguish the two objects that have few known attributes and more unknown attributes; some cannot make a flexible and accurate discrimination. In order to solve this problem, this paper suggests an improved limited tolerance rough set model using two thresholds to control what two objects have a relationship between them in limited tolerance relation and to classify objects. Our practical study case shows the model can get fine and reasonable decision results.

The Inhibition of Relapse of Orthodontic Tooth Movement by NaF Administration in Expressions of TGF-β1, Runx2, Alkaline Phosphatase and Microscopic Appearance of Woven Bone

The prevalence of post-treatment relapse in orthodontics in the community is high enough; therefore, relapses in orthodontic treatment must be prevented well. The aim of this study is to experimentally test the inhibition of relapse of orthodontics tooth movement in NaF of expression TGF-β1, Runx2, alkaline phosphatase (ALP) and microscopic of woven bone. The research method used was experimental laboratory research involving 30 rats, which were divided into three groups. Group A: rats were not given orthodontic tooth movement and without NaF. Group B: rats were given orthodontic tooth movement and without 11.5 ppm by topical application. Group C: rats were given orthodontic tooth movement and 11.75 ppm by topical application. Orthodontic tooth movement was conducted by applying ligature wires of 0.02 mm in diameter on the molar-1 (M-1) of left permanent maxilla and left insisivus of maxilla. Immunohistochemical examination was conducted to calculate the number of osteoblast to determine TGF β1, Runx2, ALP and haematoxylin to determine woven bone on day 7 and day 14. Results: It was shown that administrations of Natrium Fluoride topical application proved effective to increase the expression of TGF-β1, Runx2, ALP and to increase woven bone in the tension area greater than administration without natrium fluoride topical application (p < 0.05), except the expression of ALP on day 7 and day 14 which was significant. The results of the study show that NaF significantly increases the expressions of TGF-β1, Runx2, ALP and woven bone. The expression of the variables enhanced on day 7 compared on that on day 14, except ALP. Thus, it can be said that the acceleration of woven bone occurs on day 7.

Research and Application of Consultative Committee for Space Data Systems Wireless Communications Standards for Spacecraft

According to the new requirements of the future spacecraft, such as networking, modularization and non-cable, this paper studies the CCSDS wireless communications standards, and focuses on the low data-rate wireless communications for spacecraft monitoring and control. The application fields and advantages of wireless communications are analyzed. Wireless communications technology has significant advantages in reducing the weight of the spacecraft, saving time in spacecraft integration, etc. Based on this technology, a scheme for spacecraft data system is put forward. The corresponding block diagram and key wireless interface design of the spacecraft data system are given. The design proposal of the wireless node and information flow of the spacecraft are also analyzed. The results show that the wireless communications scheme is reasonable and feasible. The wireless communications technology can meet the future spacecraft demands in networking, modularization and non-cable.

Evaluation of Classification Algorithms for Road Environment Detection

The road environment information is needed accurately for applications such as road maintenance and virtual 3D city modeling. Mobile laser scanning (MLS) produces dense point clouds from huge areas efficiently from which the road and its environment can be modeled in detail. Objects such as buildings, cars and trees are an important part of road environments. Different methods have been developed for detection of above such objects, but still there is a lack of accuracy due to the problems of illumination, environmental changes, and multiple objects with same features. In this work the comparison between different classifiers such as Multiclass SVM, kNN and Multiclass LDA for the road environment detection is analyzed. Finally the classification accuracy for kNN with LBP feature improved the classification accuracy as 93.3% than the other classifiers.

An Optimization Modelling to Evaluate Flights Scheduling at Tourist Airports

Airport’s serving a tourist destination are an essential counterpart of the tourist demand supply chain, and their productivity is related to the region’s attractiveness and is enhanced by the air transport business. In this paper, the evaluation framework of the scheduled flights between two tourist airports is taken into consideration. By adopting a systemic approach, the arrivals from an airport that its connectivity heavily depended on the departures of another major airport are reviewed. The methodology framework, based on inventory control theory and the numerical example, promotes the use of the modelling formulation. The results would be essential for comparison and exercising to other similar cases.

The DAQ Debugger for iFDAQ of the COMPASS Experiment

In general, state-of-the-art Data Acquisition Systems (DAQ) in high energy physics experiments must satisfy high requirements in terms of reliability, efficiency and data rate capability. This paper presents the development and deployment of a debugging tool named DAQ Debugger for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. Utilizing a hardware event builder, the iFDAQ is designed to be able to readout data at the average maximum rate of 1.5 GB/s of the experiment. In complex softwares, such as the iFDAQ, having thousands of lines of code, the debugging process is absolutely essential to reveal all software issues. Unfortunately, conventional debugging of the iFDAQ is not possible during the real data taking. The DAQ Debugger is a tool for identifying a problem, isolating the source of the problem, and then either correcting the problem or determining a way to work around it. It provides the layer for an easy integration to any process and has no impact on the process performance. Based on handling of system signals, the DAQ Debugger represents an alternative to conventional debuggers provided by most integrated development environments. Whenever problem occurs, it generates reports containing all necessary information important for a deeper investigation and analysis. The DAQ Debugger was fully incorporated to all processes in the iFDAQ during the run 2016. It helped to reveal remaining software issues and improved significantly the stability of the system in comparison with the previous run. In the paper, we present the DAQ Debugger from several insights and discuss it in a detailed way.

A Study of General Attacks on Elliptic Curve Discrete Logarithm Problem over Prime Field and Binary Field

This paper begins by describing basic properties of finite field and elliptic curve cryptography over prime field and binary field. Then we discuss the discrete logarithm problem for elliptic curves and its properties. We study the general common attacks on elliptic curve discrete logarithm problem such as the Baby Step, Giant Step method, Pollard’s rho method and Pohlig-Hellman method, and describe in detail experiments of these attacks over prime field and binary field. The paper finishes by describing expected running time of the attacks and suggesting strong elliptic curves that are not susceptible to these attacks.c

An Improved C-Means Model for MRI Segmentation

Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Speech Enhancement Using Wavelet Coefficients Masking with Local Binary Patterns

In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhancement in each high-frequency subband is performed by binary labels through the local binary pattern masking that encodes the ratio between the original value of each coefficient and the values of the neighbour coefficients. This approach enhances the high-frequency spectra of the wavelet transform instead of eliminating them through a threshold. A comparative analysis is carried out with conventional speech enhancement algorithms, demonstrating that the proposed technique achieves significant improvements in terms of PESQ, an international recommendation of objective measure for estimating subjective speech quality. Informal listening tests also show that the proposed method in an acoustic context improves the quality of speech, avoiding the annoying musical noise present in other speech enhancement techniques. Experimental results obtained with a DNN based speech recognizer in noisy environments corroborate the superiority of the proposed scheme in the robust speech recognition scenario.

Animation of Objects on the Website by Application of CSS3 Language

Scientific work analytically explores and demonstrates techniques that can animate objects and geometric characters using CSS3 language by applying proper formatting and positioning of elements. This paper presents examples of optimum application of the CSS3 descriptive language when generating general web animations (e.g., billiards and movement of geometric characters, etc.). The paper presents analytically, the optimal development and animation design with the frames within which the animated objects are. The originally developed content is based on the upgrading of existing CSS3 descriptive language animations with more complex syntax and project-oriented work. The purpose of the developed animations is to provide an overview of the interactive features of CSS3 descriptive language design for computer games and the animation of important analytical data based on the web view. It has been analytically demonstrated that CSS3 as a descriptive language allows inserting of various multimedia elements into websites for public and internal sites.

Effect of Three Drying Methods on Antioxidant Efficiency and Vitamin C Content of Moringa oleifera Leaf Extract

Moringa oleifera is a plant containing many nutrients that are mostly concentrated within the leaves. Commonly, the separation process of these nutrients involves solid-liquid extraction followed by evaporation and drying to obtain a concentrated extract, which is rich in proteins, vitamins, carbohydrates, and other essential nutrients that can be used in the food industry. In this work, three drying methods were used, which involved very different temperature and pressure conditions, to evaluate the effect of each method on the vitamin C content and the antioxidant efficiency of the extracts. Solid-liquid extractions of Moringa leaf (LE) were carried out by employing an ethanol solution (35% v/v) at 50 °C for 2 hours. The resulting extracts were then dried i) in a convective oven (CO) at 100 °C and at an atmospheric pressure of 750 mbar for 8 hours, ii) in a vacuum evaporator (VE) at 50 °C and at 300 mbar for 2 hours, and iii) in a freeze-drier (FD) at -40 °C and at 0.050 mbar for 36 hours. The antioxidant capacity (EC50, mg solids/g DPPH) of the dry solids was calculated by the free radical inhibition method employing DPPH˙ at 517 nm, resulting in a value of 2902.5 ± 14.8 for LE, 3433.1 ± 85.2 for FD, 3980.1 ± 37.2 for VE, and 8123.5 ± 263.3 for CO. The calculated antioxidant efficiency (AE, g DPPH/(mg solids·min)) was 2.920 × 10-5 for LE, 2.884 × 10-5 for FD, 2.512 × 10-5 for VE, and 1.009 × 10-5 for CO. Further, the content of vitamin C (mg/L) determined by HPLC was 59.0 ± 0.3 for LE, 49.7 ± 0.6 for FD, 45.0 ± 0.4 for VE, and 23.6 ± 0.7 for CO. The results indicate that the convective drying preserves vitamin C and antioxidant efficiency to 40% and 34% of the initial value, respectively, while vacuum drying to 76% and 86%, and freeze-drying to 84% and 98%, respectively.