Search results for: minimal potentially positive sign pattern.

Authors: J. P. Dubois, O. M. Abdul-Latif

Abstract:

Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of medical ultrasound images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to clinical ultrasound images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected ultrasound images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (detection hypotheses) in the original images.

Keywords: LS-SVM, medical ultrasound imaging, partially developed speckle, multi-look model.

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Authors: J. P. Dubois, O. M. Abdul-Latif

Abstract:

Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of SAR (synthetic aperture radar) images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to real SAR images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected SAR images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (the detection hypotheses) in the original images.

Keywords: Least Square-Support Vector Machine, SyntheticAperture Radar. Partially Developed Speckle, Multi-Look Model.

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Authors: Ihor Trots, Yuriy Tasinkevych, Andrzej Nowicki, Marcin Lewandowski

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In the paper the study of synthetic transmit aperture method applying the Golay coded transmission for medical ultrasound imaging is presented. Longer coded excitation allows to increase the total energy of the transmitted signal without increasing the peak pressure. Moreover signal-to-noise ratio and penetration depth are improved while maintaining high ultrasound image resolution. In the work the 128-element linear transducer array with 0.3 mm inter-element spacing excited by one cycle and the 8 and 16- bit Golay coded sequences at nominal frequency 4 MHz was used. To generate a spherical wave covering the full image region a single element transmission aperture was used and all the elements received the echo signals. The comparison of 2D ultrasound images of the tissue mimicking phantom and in vitro measurements of the beef liver is presented to illustrate the benefits of the coded transmission. The results were obtained using the synthetic aperture algorithm with transmit and receive signals correction based on a single element directivity function.

Keywords: Golay coded sequences, radiation pattern, signal processing, synthetic aperture, ultrasound imaging.

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Authors: Ming Ling Lai, Zalilawati Yaacob, Normah Omar, Norashikin Abdul Aziz, Bee Wah Yap

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This paper aims to (1) analyze the profiles of transgressors (detected evaders); (2) examine reason(s) that triggered a tax audit, causes of tax evasion, audit timeframe and tax penalty charged; and (3) to assess if tax auditors followed the guidelines as stated in the 'Tax Audit Framework' when conducting tax audits. In 2011, the Inland Revenue Board Malaysia (IRBM) had audited and finalized 557 company cases. With official permission, data of all the 557 cases were obtained from the IRBM. Of these, a total of 421 cases with complete information were analyzed. About 58.1% was small and medium corporations and from the construction industry (32.8%). The selection for tax audit was based on risk analysis (66.8%), information from third party (11.1%), and firm with low profitability or fluctuating profit pattern (7.8%). The three persistent causes of tax evasion by firms were over claimed expenses (46.8%), fraudulent reporting of income (38.5%) and overstating purchases (10.5%). These findings are consistent with past literature. Results showed that tax auditors took six to 18 months to close audit cases. More than half of tax evaders were fined 45% on additional tax raised during audit for the first offence. The study found tax auditors did follow the guidelines in the 'Tax Audit Framework' in audit selection, settlement and penalty imposition.

Keywords: Corporate tax fraud, tax non-compliance, tax evasion, tax audit, fraudulent reporting.

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Authors: Andy Tirta, Yus Prasetyo, Eung-Ryul. Baek, Chul-Jin. Choi , Hye-Moon. Lee

Abstract:

Recently, the advanced technologies that offer high precision product, relative easy, economical process and also rapid production are needed to realize the high demand of ultra precision micro part. In our research, micromanufacturing based on soft lithography and nanopowder injection molding was investigated. The silicone metal pattern with ultra thick and high aspect ratio succeeds to fabricate Polydimethylsiloxane (PDMS) micro mold. The process followed by nanopowder injection molding (PIM) by a simple vacuum hot press. The 17-4ph nanopowder with diameter of 100 nm, succeed to be injected and it forms green sample microbearing with thickness, microchannel and aspect ratio is 700μm, 60μm and 12, respectively. Sintering process was done in 1200 C for 2 hours and heating rate 0.83oC/min. Since low powder load (45% PL) was applied to achieve green sample fabrication, ~15% shrinkage happen in the 86% relative density. Several improvements should be done to produce high accuracy and full density sintered part.

Keywords: Micromanufacturing, Nano PIM, PDMS micro mould.

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Authors: Guyue Zhu, Liangping Hong

Abstract:

Chinese overall urban design faces a large number of problems such as the neglect of urban characteristics, generalization of content, and difficulty in implementation. Focusing on these issues, this paper proposes the main points of shaping urban characteristics in overall urban design: focuses on core problems in city function and scale, landscape pattern, historical culture, social resources and modern city style and digs the urban characteristic genes. Then, we put forward “core problem location and characteristic gene enhancement” as a kind of overall urban design technical method. Firstly, based on the main problems in urban space as a whole, for the operability goal, the method extracts the key genes and integrates into the multi-dimension system in a targeted manner. Secondly, hierarchical management and guidance system is established which may be in line with administrative management. Finally, by converting the results, action plan is drawn up that can be dynamically implemented. Based on the above idea and method, a practical exploration has been performed in the case of Xiangyang central city.

Keywords: City characteristics, overall urban design, planning implementation, Xiangyang central city.

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Authors: Chaiwat Waree, Kalanyoo Petcharaporn

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This research aims to develop and evaluate a training course to promote learning activities of 2nd year, Suan Sunandha Rajabhat University, faculty of education students using multiple intelligences theory. The process is divided into two phases: Phase 1 development of training course to promote learning activities consisting of principles, objectives of the course, structure, training duration, content, training materials, training activities, media training, monitoring, measurement and evaluation quality of the course. Phase 2 evaluation efficiency of training course was to use the improved curriculum with experimental group which is 2nd year, Suan Sunandha Rajabhat University, faculty of education students was drawn randomly 152 students. The experimental pattern was randomized Control Group Pre-Test Post-Test Design, Analysis Data by t-Test with the software SPFSS for Windows. Research has shown that: 1). the ability of teaching and learning according to the theory of multiple intelligences after training is higher than before training significantly in statistic at .01 level, 2). The satisfaction of students to the training courses was overall at the highest level.

Keywords: A training course, learning activities, multiple intelligences.

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Authors: Marcel Schneider, Nils Nießen

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Microscopic simulation tool kits allow for consideration of the two processes of railway operations and the previous timetable production. Block occupation conflicts on both process levels are often solved by using defined train priorities. These conflict resolutions (dispatching decisions) generate reactionary delays to the involved trains. The sum of reactionary delays is commonly used to evaluate the quality of railway operations, which describes the timetable robustness. It is either compared to an acceptable train performance or the delays are appraised economically by linear monetary functions. It is impossible to adequately evaluate dispatching decisions without a well-founded objective function. This paper presents a new approach for the evaluation of dispatching decisions. The approach uses mode choice models and considers the behaviour of the end-customers. These models evaluate the reactionary delays in more detail and consider other competing modes of transport. The new approach pursues the coupling of a microscopic model of railway operations with the macroscopic choice mode model. At first, it will be implemented for railway operations process but it can also be used for timetable production. The evaluation considers the possibility for the customer to interchange to other transport modes. The new approach starts to look at rail and road, but it can also be extended to air travel. The result of mode choice models is the modal split. The reactions by the end-customers have an impact on the revenue of the train operating companies. Different purposes of travel have different payment reserves and tolerances towards late running. Aside from changes to revenues, longer journey times can also generate additional costs. The costs are either time- or track-specific and arise from required changes to rolling stock or train crew cycles. Only the variable values are summarised in the contribution margin, which is the base for the monetary evaluation of delays. The contribution margin is calculated for different possible solutions to the same conflict. The conflict resolution is optimised until the monetary loss becomes minimal. The iterative process therefore determines an optimum conflict resolution by monitoring the change to the contribution margin. Furthermore, a monetary value of each dispatching decision can also be derived.

Keywords: Choice of mode, monetary evaluation, railway operations, reactionary delays.

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Authors: A. Kablan

Abstract:

The prediction of financial time series is a very complicated process. If the efficient market hypothesis holds, then the predictability of most financial time series would be a rather controversial issue, due to the fact that the current price contains already all available information in the market. This paper extends the Adaptive Neuro Fuzzy Inference System for High Frequency Trading which is an expert system that is capable of using fuzzy reasoning combined with the pattern recognition capability of neural networks to be used in financial forecasting and trading in high frequency. However, in order to eliminate unnecessary input in the training phase a new event based volatility model was proposed. Taking volatility and the scaling laws of financial time series into consideration has brought about the development of the Intraday Seasonality Observation Model. This new model allows the observation of specific events and seasonalities in data and subsequently removes any unnecessary data. This new event based volatility model provides the ANFIS system with more accurate input and has increased the overall performance of the system.

Keywords: Adaptive Neuro-fuzzy Inference system, High Frequency Trading, Intraday Seasonality Observation Model.

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Authors: Vinicius Binotte, Guilherme Baldo, Christiane Goulart, Carlos Valadão, Eliete Caldeira, Teodiano Bastos

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Socially assistive robotic has become increasingly active and it is present in therapies of people affected for several neurobehavioral conditions, such as Autism Spectrum Disorder (ASD). In fact, robots have played a significant role for positive interaction with children with ASD, by stimulating their social and cognitive skills. This work introduces a mobile socially-assistive robot, which was built for interaction with children with ASD, using non-linear control techniques for this interaction.

Keywords: Socially assistive robotics, mobile robot, autonomous control, autism.

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Authors: Somnath Dey, Debasis Samanta

Abstract:

Iris-based biometric authentication is gaining importance in recent times. Iris biometric processing however, is a complex process and computationally very expensive. In the overall processing of iris biometric in an iris-based biometric authentication system, feature processing is an important task. In feature processing, we extract iris features, which are ultimately used in matching. Since there is a large number of iris features and computational time increases as the number of features increases, it is therefore a challenge to develop an iris processing system with as few as possible number of features and at the same time without compromising the correctness. In this paper, we address this issue and present an approach to feature extraction and feature matching process. We apply Daubechies D4 wavelet with 4 levels to extract features from iris images. These features are encoded with 2 bits by quantizing into 4 quantization levels. With our proposed approach it is possible to represent an iris template with only 304 bits, whereas existing approaches require as many as 1024 bits. In addition, we assign different weights to different iris region to compare two iris templates which significantly increases the accuracy. Further, we match the iris template based on a weighted similarity measure. Experimental results on several iris databases substantiate the efficacy of our approach.

Keywords: Iris recognition, biometric, feature processing, patternrecognition, pattern matching.

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Authors: Meghal Desai, Jigisha Parikh

Abstract:

Aggregation behavior of sodium salicylate and sodium cumene sulfonate was studied in aqueous solution at different temperature. Specific conductivity and relative viscosity were measured at different temperature to find minimum hydrotropic concentration. The thermodynamic parameters (free energy, enthalpy and entropy) were evaluated in the temperature range of 30°C-70°C. The free energy decreased with increase in temperature. The aggregation was found to be exothermic in nature and favored by positive value of entropy.

Keywords: Hydrotropes, Enthalpy, Entropy, Free Energy, Minimum Hydrotropic Concentration.

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Authors: Arijit Ghosh, Tony Givargis

Abstract:

Video sensor networks operate on stringent requirements of latency. Packets have a deadline within which they have to be delivered. Violation of the deadline causes a packet to be treated as lost and the loss of packets ultimately affects the quality of the application. Network latency is typically a function of many interacting components. In this paper, we propose ways of reducing the forwarding latency of a packet at intermediate nodes. The forwarding latency is caused by a combination of processing delay and queueing delay. The former is incurred in order to determine the next hop in dynamic routing. We show that unless link failures in a very specific and unlikely pattern, a vast majority of these lookups are redundant. To counter this we propose source routing as the routing strategy. However, source routing suffers from issues related to scalability and being impervious to network dynamics. We propose solutions to counter these and show that source routing is definitely a viable option in practical sized video networks. We also propose a fast and fair packet scheduling algorithm that reduces queueing delay at the nodes. We support our claims through extensive simulation on realistic topologies with practical traffic loads and failure patterns.

Keywords: Sensor networks, Packet latency, Network design, Networkperformance.

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Authors: Li Xiguang

Abstract:

In this paper, by constructing a special operator and using fixed point index theorem of cone, we get the sufficient conditions for symmetric positive solution of a class of nonlinear singular boundary value problems with p-Laplace operator, which improved and generalized the result of related paper.

Keywords: Banach space, cone, fixed point index, singular differential equation, p-Laplace operator, symmetric solutions.

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Authors: Ryuya Uda

Abstract:

Nowadays, computer worms, viruses and Trojan horse become popular, and they are collectively called malware. Those malware just spoiled computers by deleting or rewriting important files a decade ago. However, recent malware seems to be born to earn money. Some of malware work for collecting personal information so that malicious people can find secret information such as password for online banking, evidence for a scandal or contact address which relates with the target. Moreover, relation between money and malware becomes more complex. Many kinds of malware bear bots to get springboards. Meanwhile, for ordinary internet users, countermeasures against malware come up against a blank wall. Pattern matching becomes too much waste of computer resources, since matching tools have to deal with a lot of patterns derived from subspecies. Virus making tools can automatically bear subspecies of malware. Moreover, metamorphic and polymorphic malware are no longer special. Recently there appears malware checking sites that check contents in place of users' PC. However, there appears a new type of malicious sites that avoids check by malware checking sites. In this paper, existing protocols and methods related with the web are reconsidered in terms of protection from current attacks, and new protocol and method are indicated for the purpose of security of the web.

Keywords: Information Security, Malware, Network Security, World Wide Web

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Authors: L. R. Ferreira, R. C. G. Bianchi, L. C.R. Ferreira, C. M. Galhardi, E. P. Baciuk, L. H. Oliveira

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Inhalation hazards are associated with potentially injurious exposure and increased risk for lung diseases, within the bauxite mining industry, especially for the smelter workers. Smoking is related to decreased lung function and leads to chronic lung diseases. This study had the objective to evaluate whether smoking is related to functional and radiographic respiratory changes in retired bauxite mining workers. Methods: This was a retrospective and cross-sectional study involving the analysis of database information of 140 retired bauxite mining workers from Poços de Caldas-MG evaluated at Worker’s Health Reference Center and at the Social Security Brazilian National Institute, from July 1^st, 2015 until June 30^th, 2016. The workers were divided into three groups: non-smokers (n = 47), ex-smokers (n = 46), and smokers (n = 47). The data included: age, gender, spirometry results, and the presence or not of pulmonary pleural and/or parenchymal changes in chest radiographs. Chi-Squared test was used (p < 0,05). Results: In the smokers’ group, 83% of spirometry tests and 64% of chest x-rays were altered. In the non-smokers’ group, 19% of spirometry tests and 13% of chest x-rays were altered. In the ex-smokers’ group, 35% of spirometry tests and 30% of chest x-rays were altered. Most of the results were statistically significant. Results demonstrated a significant difference between smokers’ and non-smokers’ groups in regard to spirometric and radiographic pulmonary alterations. Ex-smokers’ and non-smokers’ group demonstrated better results when compared to the smokers’ group in relation to altered spirometry and radiograph findings. These data may contribute to planning strategies to enhance smoking cessation programs within the bauxite mining industry.

Keywords: Bauxite mining, spirometry, chest radiography, smoking.

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Authors: Fahad Alsharari, Mohd Salmi Md Noorani

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A Motzkin shift is a mathematical model for constraints on genetic sequences. In terms of the theory of symbolic dynamics, the Motzkin shift is nonsofic, and therefore, we cannot use the Perron- Frobenius theory to calculate its topological entropy. The Motzkin shift M(M,N) which comes from language theory, is defined to be the shift system over an alphabet A that consists of N negative symbols, N positive symbols and M neutral symbols. For an x in the full shift, x will be in the Motzkin subshift M(M,N) if and only if every finite block appearing in x has a non-zero reduced form. Therefore, the constraint for x cannot be bounded in length. K. Inoue has shown that the entropy of the Motzkin shift M(M,N) is log(M + N + 1). In this paper, a new direct method of calculating the topological entropy of the Motzkin shift is given without any measure theoretical discussion.

Keywords: Motzkin shift, topological entropy.

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Authors: Hadi Veisi, Mansour Jamzad

Abstract:

In this paper we present an adaptive method for image compression that is based on complexity level of the image. The basic compressor/de-compressor structure of this method is a multilayer perceptron artificial neural network. In adaptive approach different Back-Propagation artificial neural networks are used as compressor and de-compressor and this is done by dividing the image into blocks, computing the complexity of each block and then selecting one network for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability in complexity estimation are evaluated and compared. In training and evaluation, each image block is assigned to a network based on its complexity value. Best-SNR is another alternative in selecting compressor network for image blocks in evolution phase which chooses one of the trained networks such that results best SNR in compressing the input image block. In our evaluations, best results are obtained when overlapping the blocks is allowed and choosing the networks in compressor is based on the Best-SNR. In this case, the results demonstrate superiority of this method comparing with previous similar works and JPEG standard coding.

Keywords: Adaptive image compression, Image complexity, Multi-layer perceptron neural network, JPEG Standard, PSNR.

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Authors: Ramesh K. Sunkaria, Puneeta Marwaha

Abstract:

Non linear methods of heart rate variability (HRV) analysis are becoming more popular. It has been observed that complexity measures quantify the regularity and uncertainty of cardiovascular RR-interval time series. In the present work, SampEn has been evaluated in healthy normal sinus rhythm (NSR) male and female subjects for different data lengths and tolerance level r. It is demonstrated that SampEn is small for higher values of tolerance r. Also SampEn value of healthy female group is higher than that of healthy male group for short data length and with increase in data length both groups overlap each other and it is difficult to distinguish them. The SampEn gives inaccurate results by assigning higher value to female group, because male subject have more complex HRV pattern than that of female subjects. Therefore, this traditional algorithm exhibits higher complexity for healthy female subjects than for healthy male subjects, which is misleading observation. This may be due to the fact that SampEn do not account for multiple time scales inherent in the physiologic time series and the hidden spatial and temporal fluctuations remains unexplored.

Keywords: Heart rate variability, normal sinus rhythm group, RR interval time series, sample entropy.

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Authors: Marios Poulos, George Bokos

Abstract:

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.

Keywords: Computational Geometry, MRI photos, Image processing, pattern Recognition.

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Authors: Deniz T. Sodiri, Venkat V S S Sastry

Abstract:

The paper presents an on-line recognition machine (RM) for continuous/isolated, dynamic and static gestures that arise in Flight Deck Officer (FDO) training. RM is based on generic pattern recognition framework. Gestures are represented as templates using summary statistics. The proposed recognition algorithm exploits temporal and spatial characteristics of gestures via dynamic programming and Markovian process. The algorithm predicts corresponding index of incremental input data in the templates in an on-line mode. Accumulated consistency in the sequence of prediction provides a similarity measurement (Score) between input data and the templates. The algorithm provides an intuitive mechanism for automatic detection of start/end frames of continuous gestures. In the present paper, we consider isolated gestures. The performance of RM is evaluated using four datasets - artificial (W TTest), hand motion (Yang) and FDO (tracker, vision-based ). RM achieves comparable results which are in agreement with other on-line and off-line algorithms such as hidden Markov model (HMM) and dynamic time warping (DTW). The proposed algorithm has the additional advantage of providing timely feedback for training purposes.

Keywords: On-line Recognition Algorithm, IsolatedDynamic/Static Gesture Recognition, On-line Markovian/DynamicProgramming, Training in Virtual Environments.

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Authors: S. U. Khan, T. Ayub, N. Shafiq

Abstract:

The properties of locally produced metakaolin (MK) as cement replacing material and the comparison of reactivity with commercially available micro-silica have been investigated. Compressive strength, splitting tensile strength, and load-deflection behaviour under bending are the properties that have been studied. The amorphous phase of MK with micro-silica was compared through X-ray diffraction (XRD) pattern. Further, interfacial transition zone of concrete with micro-silica and MK was observed through Field Emission Scanning Electron Microscopy (FESEM). Three mixes of concrete were prepared. One of the mix is without cement replacement as control mix, and the remaining two mixes are 10% cement replacement with micro-silica and MK. It has been found that MK, due to its irregular structure and amorphous phase, has high reactivity with portlandite in concrete. The compressive strength at early age is higher with MK as compared to micro-silica. MK concrete showed higher splitting tensile strength and higher load carrying capacity as compared to control and micro-silica concrete at all ages respectively.

Keywords: Metakaolin, compressive strength, splitting tensile strength, load deflection, interfacial transition zone.

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Authors: Lei Shi, Zhibin Yu, Artur J. Jaworski, Abdulrahman S. Abduljalil

Abstract:

This paper investigates vortex shedding processes occurring at the end of a stack of parallel plates, due to an oscillating flow induced by an acoustic standing wave within an acoustic resonator. Here, Particle Image Velocimetry (PIV) is used to quantify the vortex shedding processes within an acoustic cycle phase-by-phase, in particular during the “ejection" of the fluid out of the stack. Standard hot-wire anemometry measurement is also applied to detect the velocity fluctuations near the end of the stack. Combination of these two measurement techniques allowed a detailed analysis of the vortex shedding phenomena. The results obtained show that, as the Reynolds number varies (by varying the plate thickness and drive ratio), different flow patterns of vortex shedding are observed by the PIV measurement. On the other hand, the time-dependent hot-wire measurements allow obtaining detailed frequency spectra of the velocity signal, used for calculating characteristic Strouhal numbers. The impact of the plate thickness and the Reynolds number on the vortex shedding pattern has been discussed. Furthermore, a detailed map of the relationship between the Strouhal number and Reynolds number has been obtained and discussed.

Keywords: Oscillatory flow, Parallel-plate thermoacoustic stack, Strouhal numbers, Vortex shedding.

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Authors: Yi-Chun Kuo, Jo-Chieh Lin

Abstract:

The objective of a supply chain strategy is to reduce waste and increase efficiency to attain cost benefits, and to guarantee supply chain flexibility when facing the ever-changing market environment in order to meet customer requirements. Strategy implementation aims to fulfill common goals and attain benefits by integrating upstream and downstream enterprises, sharing information, conducting common planning, and taking part in decision making, so as to enhance the overall performance of the supply chain. With the rise of outsourcing and globalization, the increasing dependence on suppliers and customers and the rapid development of information technology, the complexity and uncertainty of the supply chain have intensified, and supply chain vulnerability has surged, resulting in adverse effects on supply chain performance. Thus, this study aims to use supply chain vulnerability as a moderating variable and apply structural equation modeling (SEM) to determine the relationships among supply chain strategy, supply chain integration, and supply chain performance, as well as the moderating effect of supply chain vulnerability on supply chain performance. The data investigation of this study was questionnaires which were collected from the management level of enterprises in Taiwan and China, 149 questionnaires were received. The result of confirmatory factor analysis shows that the path coefficients of supply chain strategy on supply chain integration and supply chain performance are positive (0.497, t= 4.914; 0.748, t= 5.919), having a significantly positive effect. Supply chain integration is also significantly positively correlated to supply chain performance (0.192, t = 2.273). The moderating effects of supply chain vulnerability on supply chain strategy and supply chain integration to supply chain performance are significant (7.407; 4.687). In Taiwan, 97.73% of enterprises are small- and medium-sized enterprises (SMEs) focusing on receiving original equipment manufacturer (OEM) and original design manufacturer (ODM) orders. In order to meet the needs of customers and to respond to market changes, these enterprises especially focus on supply chain flexibility and their integration with the upstream and downstream enterprises. According to the observation of this research, the effect of supply chain vulnerability on supply chain performance is significant, and so enterprises need to attach great importance to the management of supply chain risk and conduct risk analysis on their suppliers in order to formulate response strategies when facing emergency situations. At the same time, risk management is incorporated into the supply chain so as to reduce the effect of supply chain vulnerability on the overall supply chain performance.

Keywords: Supply chain integration, supply chain performance, supply chain vulnerability, structural equation modeling.

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Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

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All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: Currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features.

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Authors: Kevin Moustapha

Abstract:

Psychopathic disorders are taking an important part in judge sentencing, especially in Canada. First, we will see how this phenomenon can be illustrated by the high proportion of psychopath offenders incarcerated in North American prisons. Many decisions in Canadians courtrooms seem to point out that psychopathy is often used as a strong argument by the judges to preserve public safety. The fact that psychopathy is often associated with violence, recklessness and recidivism, could explain why many judges consider psychopathic disorders as an aggravating factor. Generally, the judge reasoning is based on Article 753 of Canadian Criminal Code related to dangerous offenders, which is used for individuals who show a pattern of repetitive and persistent aggressive behaviour. Then we will show how, with cognitive neurosciences, the psychopath’s situation in courtrooms would probably change. Cerebral imaging and news data provided by the neurosciences show that emotional and volitional functions in psychopath’s brains are impaired. Understanding these new issues could enable some judges to recognize psychopathic disorders as a mitigating factor. Finally, two important questions ought to be raised in this article: can exploring psychopaths ‘brains really change the judge sentencing in Canadian courtrooms? If yes, can judges consider psychopathy more as a mitigating factor than an aggravating factor?

Keywords: Criminal law, judges sentencing, neurosciences, psychopathy.

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Authors: Yang Song, Yifan Guo, Edward F. Gehringer

Abstract:

Fifty years of research has found great potential for peer assessment as a pedagogical approach. With peer assessment, not only do students receive more copious assessments; they also learn to become assessors. In recent decades, more educational peer assessments have been facilitated by online systems. Those online systems are designed differently to suit different class settings and student groups, but they basically fall into two categories: rating-based and ranking-based. The rating-based systems ask assessors to rate the artifacts one by one following some review rubrics. The ranking-based systems allow assessors to review a set of artifacts and give a rank for each of them. Though there are different systems and a large number of users of each category, there is no comprehensive comparison on which design leads to higher reliability. In this paper, we designed algorithms to evaluate assessors' reliabilities based on their rating/ranking against the global ranks of the artifacts they have reviewed. These algorithms are suitable for data from both rating-based and ranking-based peer assessment systems. The experiments were done based on more than 15,000 peer assessments from multiple peer assessment systems. We found that the assessors in ranking-based peer assessments are at least 10% more reliable than the assessors in rating-based peer assessments. Further analysis also demonstrated that the assessors in ranking-based assessments tend to assess the more differentiable artifacts correctly, but there is no such pattern for rating-based assessors.

Keywords: Peer assessment, peer rating, peer ranking, reliability.

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Authors: M. Antonelli, G. Frosini, B. Lazzerini, F. Marcelloni

Abstract:

In this paper we describe a computer-aided diagnosis (CAD) system for automated detection of pulmonary nodules in computed-tomography (CT) images. After extracting the pulmonary parenchyma using a combination of image processing techniques, a region growing method is applied to detect nodules based on 3D geometric features. We applied the CAD system to CT scans collected in a screening program for lung cancer detection. Each scan consists of a sequence of about 300 slices stored in DICOM (Digital Imaging and Communications in Medicine) format. All malignant nodules were detected and a low false-positive detection rate was achieved.

Keywords: computer assisted diagnosis, medical imagesegmentation, shape recognition.

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Authors: Sanjay Kumar Srivastava, Anu Rani Sharma, Kamna Sachdeva

Abstract:

Every year, fog formation over the Indo-Gangetic Plains (IGPs) of Indian region during the winter months of December and January is believed to create numerous hazards, inconvenience, and economic loss to the inhabitants of this densely populated region of Indian subcontinent. The aim of the paper is to analyze the spatial and temporal variability of winter fog over IGPs. Long term ground observations of visibility and other meteorological parameters (1971-2010) have been analyzed to understand the formation of fog phenomena and its relevance during the peak winter months of January and December over IGP of India. In order to examine the temporal variability, time series and trend analysis were carried out by using the Mann-Kendall Statistical test. Trend analysis performed by using the Mann-Kendall test, accepts the alternate hypothesis with 95% confidence level indicating that there exists a trend. Kendall tau’s statistics showed that there exists a positive correlation between time series and fog frequency. Further, the Theil and Sen’s median slope estimate showed that the magnitude of trend is positive. Magnitude is higher during January compared to December for the entire IGP except in December when it is high over the western IGP. Decade wise time series analysis revealed that there has been continuous increase in fog days. The net overall increase of 99 % was observed over IGP in last four decades. Diurnal variability and average daily persistence were computed by using descriptive statistical techniques. Geo-statistical analysis of fog was carried out to understand the spatial variability of fog. Geo-statistical analysis of fog revealed that IGP is a high fog prone zone with fog occurrence frequency of more than 66% days during the study period. Diurnal variability indicates the peak occurrence of fog is between 06:00 and 10:00 local time and average daily fog persistence extends to 5 to 7 hours during the peak winter season. The results would offer a new perspective to take proactive measures in reducing the irreparable damage that could be caused due to changing trends of fog.

Keywords: Fog, climatology, Mann-Kendall test, trend analysis, spatial variability, temporal variability, visibility.

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Authors: Mohd Hazwan bin Yusof, Hiroshi Katanoda

Abstract:

In order to clarify the structure of the cold flow discharged from the vortex tube (VT), the pressure of the cold flow was measured, and a simple flow visualization technique using a 0.75mm-diameter needle and an oily paint is made to study the reverse flow at the cold exit. It is clear that a negative pressure and positive pressure region exist at a certain pressure and cold fraction area, and that a reverse flow is observed in the negative pressure region.

Keywords: Flow visualization, Pressure measurement, Reverse flow, Vortex tube.

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