Search results for: valuable components.

Authors: Anshu Manik, William G. Buttlar, Kasthurirangan Gopalakrishnan

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Over the years, there is a growing trend towards quality-based specifications in highway construction. In many Quality Control/Quality Assurance (QC/QA) specifications, the contractor is primarily responsible for quality control of the process, whereas the highway agency is responsible for testing the acceptance of the product. A cooperative investigation was conducted in Illinois over several years to develop a prototype End-Result Specification (ERS) for asphalt pavement construction. The final characteristics of the product are stipulated in the ERS and the contractor is given considerable freedom in achieving those characteristics. The risk for the contractor or agency depends on how the acceptance limits and processes are specified. Stochastic simulation models are very useful in estimating and analyzing payment risk in ERS systems and these form an integral part of the Illinois-s prototype ERS system. This paper describes the development of an innovative methodology to estimate the variability components in in-situ density, air voids and asphalt content data from ERS projects. The information gained from this would be crucial in simulating these ERS projects for estimation and analysis of payment risks associated with asphalt pavement construction. However, these methods require at least two parties to conduct tests on all the split samples obtained according to the sampling scheme prescribed in present ERS implemented in Illinois.

Keywords: Asphalt Pavement, Risk Analysis, StochasticSimulation, QC/QA.

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Authors: Walaa Khalaf, Calogero Pace, Manlio Gaudioso

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We present an Electronic Nose (ENose), which is aimed at identifying the presence of one out of two gases, possibly detecting the presence of a mixture of the two. Estimation of the concentrations of the components is also performed for a volatile organic compound (VOC) constituted by methanol and acetone, for the ranges 40-400 and 22-220 ppm (parts-per-million), respectively. Our system contains 8 sensors, 5 of them being gas sensors (of the class TGS from FIGARO USA, INC., whose sensing element is a tin dioxide (SnO2) semiconductor), the remaining being a temperature sensor (LM35 from National Semiconductor Corporation), a humidity sensor (HIH–3610 from Honeywell), and a pressure sensor (XFAM from Fujikura Ltd.). Our integrated hardware–software system uses some machine learning principles and least square regression principle to identify at first a new gas sample, or a mixture, and then to estimate the concentrations. In particular we adopt a training model using the Support Vector Machine (SVM) approach with linear kernel to teach the system how discriminate among different gases. Then we apply another training model using the least square regression, to predict the concentrations. The experimental results demonstrate that the proposed multiclassification and regression scheme is effective in the identification of the tested VOCs of methanol and acetone with 96.61% correctness. The concentration prediction is obtained with 0.979 and 0.964 correlation coefficient for the predicted versus real concentrations of methanol and acetone, respectively.

Keywords: Electronic nose, Least square regression, Mixture ofgases, Support Vector Machine.

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Authors: M.S. Mazăre, A. M. Pană, L. M. Ştefan, M. Silion, M. Bălan, G. Bandur, L. M. Rusnac

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In the last decade, carbohydrates have attracted great attention as renewable resources for the chemical industry. Carbohydrates are abundantly found in nature in the form of monomers, oligomers and polymers, or as components of biopolymers and other naturally occurring substances. As natural products, they play important roles in conferring certain physical, chemical, and biological properties to their carrier molecules.The synthesis of this particular carbohydrate glycomonomer is part of our work to obtain biodegradable polymers. Our current paper describes the synthesis and characterization of a novel carbohydrate glycomonomer starting from D-glucose, in several synthesis steps, that involve the protection/deprotection of the D-glucose ring via acetylation, tritylation, then selective deprotection of the aromaticaliphatic protective group, in order to obtain 1,2,3,4-tetra-O-acetyl- 6-O-allyl-β-D-glucopyranose. The glycomonomer was then obtained by the allylation in drastic conditions of 1,2,3,4-tetra-O-acetyl-6-Oallyl- β-D-glucopyranose with allylic alcohol in the presence of stannic chloride, in methylene chloride, at room temperature. The proposed structure of the glycomonomer, 2,3,4-tri-O-acetyl-1,6-di- O-allyl-β-D-glucopyranose, was confirmed by FTIR, NMR and HPLC-MS spectrometry. This glycomonomer will be further submitted to copolymerization with certain acrylic or methacrylic monomers in order to obtain competitive plastic materials for applications in the biomedical field.

Keywords: allylation, D-glucose, glycomonomer, trityl chloride

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Authors: Sofien Chtourou, Mohamed Chtourou, Omar Hammami

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Embedded systems need to respect stringent real time constraints. Various hardware components included in such systems such as cache memories exhibit variability and therefore affect execution time. Indeed, a cache memory access from an embedded microprocessor might result in a cache hit where the data is available or a cache miss and the data need to be fetched with an additional delay from an external memory. It is therefore highly desirable to predict future memory accesses during execution in order to appropriately prefetch data without incurring delays. In this paper, we evaluate the potential of several artificial neural networks for the prediction of instruction memory addresses. Neural network have the potential to tackle the nonlinear behavior observed in memory accesses during program execution and their demonstrated numerous hardware implementation emphasize this choice over traditional forecasting techniques for their inclusion in embedded systems. However, embedded applications execute millions of instructions and therefore millions of addresses to be predicted. This very challenging problem of neural network based prediction of large time series is approached in this paper by evaluating various neural network architectures based on the recurrent neural network paradigm with pre-processing based on the Self Organizing Map (SOM) classification technique.

Keywords: Address, data set, memory, prediction, recurrentneural network.

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Authors: Mahmud Gungor, Ali Aydin, Erdal Akyol, Suat Tasdelen

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The understanding of geotechnical characteristics of near-surface material and the effects of the groundwater is very important problem in such as site studies. For showing the relations between seismic data and groundwater, we selected about 25 km2 as the study area. It has been presented which is a detailed work of seismic data and groundwater depths of Gokpinar Damp area. Seismic waves velocity (Vp and Vs) are very important parameters showing the soil properties. The seismic records were used the method of the multichannel analysis of surface waves near area of Gokpinar Damp area. Sixty sites in this area have been investigated with survey lines about 60 m in length. MASW (Multichannel analysis of surface wave) method has been used to generate onedimensional shear wave velocity profile at locations. These shear wave velocities are used to estimate equivalent shear wave velocity in the study area at every 2 and 5 m intervals up to a depth of 45 m. Levels of equivalent shear wave velocity of soil are used the classified of the study area. After the results of the study, it must be considered as components of urban planning and building design of Gokpinar Damp area, Denizli and the application and use of these results should be required and enforced by municipal authorities.

Keywords: Seismic data, Gokpinar Damp, urban planning, Denizli.

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Authors: O. Matarazzo, L. Abbamonte, G. Nigro

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This study aimed at assessing whether and to what extent moral judgment and behaviour were: 1. situation-dependent; 2. selectively dependent on cognitive and affective components; 3. influenced by gender and age; 4. reciprocally congruent. In order to achieve these aims, four different types of moral dilemmas were construed and five types of thinking were presented for each of them – representing five possible ways to evaluate the situation. The judgment criteria included selfishness, altruism, sense of justice, and the conflict between selfishness and the two moral issues. The participants were 250 unpaid volunteers (50% male; 50% female) belonging to two age-groups: young people and adults. The study entailed a 2 (gender) x 2 (age-group) x 5 (type of thinking) x 4 (situation) mixed design: the first two variables were betweensubjects, the others were within-subjects. Results have shown that: 1. moral judgment and behaviour are at least partially affected by the type of situations and by interpersonal variables such as gender and age; 2. moral reasoning depends in a similar manner on cognitive and affective factors; 3. there is not a gender polarity between the ethic of justice and the ethic of cure/ altruism; 4. moral reasoning and behavior are perceived as reciprocally congruent even though their congruence decreases with a more objective assessment. Such results were discussed in the light of contrasting theories on morality.

Keywords: Contextual-pragmatic approach to morality, ethic ofcare, ethic of justice, Kohlbergian approach, moral behaviour, moralreasoning.

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Authors: H. L. Ku, K. C. Yang, S. Y. Jhou, S. C. Lee, C. S. Lin

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Characterized as rich mineral substances, low temperature, few bacteria, and stability with numerous implementation aspects on aquaculture, food, drinking, and leisure, the deep sea water (DSW) development has become a new industry in the world. It has been report that marine algae contain various biologically active compounds. This research focued on the affections in cultivating Sagrassum cristaefolium with different concentration of deep sea water(DSW) and surface sea water(SSW). After two and four weeks, the total phenolic contents were compared in Sagrassum cristaefolium culturing with different ways, and the reductive activity of them was also be tried with potassium ferricyanide. Those fresh seaweeds were dried with oven and were ground to powder. Progressively, the marine algae we cultured was extracted by water under the condition with heating them at 90Ôäâ for 1hr.The total phenolic contents were be executed using Folin–Ciocalteu method. The results were explaining as follows: the highest total phenolic contents and the best reductive ability of all could be observed on the 1/4 proportion of DSW to SSW culturing in two weeks. Furthermore, the 1/2 proportion of DSW to SSW also showed good reductive ability and plentiful phenolic compositions. Finally, we confirmed that difference proportion of DSW and SSW is the major point relating to ether the total phenolic components or the reductive ability in the Sagrassum cristaefolium. In the future, we will use this way to mass production the marine algae or other micro algae on industry applications.

Keywords: deep sea water(DSW), surface sea water(SSW), phenolic contents, reductive ability.

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Authors: Celso A. G. Santos, Paula K. M. M. Freire

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The urban centers within northeastern Brazil are mainly influenced by the intense rainfalls, which can occur after long periods of drought, when flood events can be observed during such events. Thus, this paper aims to study the rainfall frequencies in such region through the wavelet transform. An application of wavelet analysis is done with long time series of the total monthly rainfall amount at the capital cities of northeastern Brazil. The main frequency components in the time series are studied by the global wavelet spectrum and the modulation in separated periodicity bands were done in order to extract additional information, e.g., the 8 and 16 months band was examined by an average of all scales, giving a measure of the average annual variance versus time, where the periods with low or high variance could be identified. The important increases were identified in the average variance for some periods, e.g. 1947 to 1952 at Teresina city, which can be considered as high wet periods. Although, the precipitation in those sites showed similar global wavelet spectra, the wavelet spectra revealed particular features. This study can be considered an important tool for time series analysis, which can help the studies concerning flood control, mainly when they are applied together with rainfall-runoff simulations.

Keywords: rainfall data, urban center, wavelet transform.

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Authors: R. Rafiemanzelat

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One of the most recent fields of investigation in urban issues focuses on the walkability in urban spaces. Considering the importance of walkability apart from pedestrian transportation, increasing walkability will help to reduce the congestion and environmental impact. This subject also matters as it has a social life, experiential quality and economical sustainability value. This study focused on the effects of walkability and place identity on each other in urban public spaces, streets in particular, as a major indicator of their success. The theoretical aspects which examine for this purpose consist of two parts: The first will evaluate the essential components of place identity in the streets and the second one will discuss the concept of walkability and its development theories which have been derived from walkable spaces. Finally, research investigates place identity and walkability and their determinants in two major streets in different cities. The streets are Chaharbagh Street in Isfahan/Iran and Dereboyu Street in Lefkosa/North Cyprus. This study has a qualitative approach with the research method of walkability studies. The qualitative method is combined with the collection of data relating to walking behavior and place identity through an observational field study. The result will show a relationship between pedestrian-friendly spaces and identity by related variables which has obtained.

Keywords: Place identity, walkability, urban public space, streets, pedestrian-friendly.

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Authors: Handan Ertaş

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The aim of the study is to determine the relationship between organizational trust level and organizational justice of Municipality officials. Correlational method has been used via descriptive survey model and Organizational Justice Perception Scale, Organizational Trust Inventory and Interpersonal Trust Scale have been applied to 353 participants who work in Konya Metropolitan Municipality and central district municipalities in the study. Frequency as statistical method, Independent Samples t test for binary groups, One Way-ANOVA analyses for multi-groups and Pearson Correlation analysis have been used to determine the relation in the data analysis process.It has been determined in the outcomes of the study that participants have high level of organizational trust, “Interpersonal Trust” is in the first place and there is a significant difference in the favor of male officials in terms of Trust on the Organization Itself and Interpersonal Trust. It has also been understood that officials in district municipalities have higher perception level in all dimensions, there is a significant difference in Trust on the Organization sub-dimension and work status is an important factor on organizational trust perception. Moreover, the study has shown that organizational justice implementations are important in raising trust of official on the organization, administrator and colleagues, and there is a parallel relation between Organizational Trust components and Organizational Trust dimensions.

Keywords: Konya, Organizational Justice, Organizational.

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Authors: J.V.R.Ravindra, M.B.Srinivas,

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Accurate modeling of high speed RLC interconnects has become a necessity to address signal integrity issues in current VLSI design. To accurately model a dispersive system of interconnects at higher frequencies; a full-wave analysis is required. However, conventional circuit simulation of interconnects with full wave models is extremely CPU expensive. We present an algorithm for reducing large VLSI circuits to much smaller ones with similar input-output behavior. A key feature of our method, called Frequency Shift Technique, is that it is capable of reducing linear time-varying systems. This enables it to capture frequency-translation and sampling behavior, important in communication subsystems such as mixers, RF components and switched-capacitor filters. Reduction is obtained by projecting the original system described by linear differential equations into a lower dimension. Experiments have been carried out using Cadence Design Simulator cwhich indicates that the proposed technique achieves more % reduction with less CPU time than the other model order reduction techniques existing in literature. We also present applications to RF circuit subsystems, obtaining size reductions and evaluation speedups of orders of magnitude with insignificant loss of accuracy.

Keywords: Model order Reduction, RLC, crosstalk

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Authors: J.-C. Cexus, A.O. Boudraa

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In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.

Keywords: Target recognition, Empirical mode decomposition, Teager-Kaiser energy operator, Features extraction.

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Authors: Hariton N. Costin, Iulian Ciocoiu, Tudor Barbu, Cristian Rotariu

Abstract:

In this paper three different approaches for person verification and identification, i.e. by means of fingerprints, face and voice recognition, are studied. Face recognition uses parts-based representation methods and a manifold learning approach. The assessment criterion is recognition accuracy. The techniques under investigation are: a) Local Non-negative Matrix Factorization (LNMF); b) Independent Components Analysis (ICA); c) NMF with sparse constraints (NMFsc); d) Locality Preserving Projections (Laplacianfaces). Fingerprint detection was approached by classical minutiae (small graphical patterns) matching through image segmentation by using a structural approach and a neural network as decision block. As to voice / speaker recognition, melodic cepstral and delta delta mel cepstral analysis were used as main methods, in order to construct a supervised speaker-dependent voice recognition system. The final decision (e.g. “accept-reject" for a verification task) is taken by using a majority voting technique applied to the three biometrics. The preliminary results, obtained for medium databases of fingerprints, faces and voice recordings, indicate the feasibility of our study and an overall recognition precision (about 92%) permitting the utilization of our system for a future complex biometric card.

Keywords: Biometry, image processing, pattern recognition, speech analysis.

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Authors: P. Vaattovaara, H. B. Swan, G. B. Jones, E. Deschaseaux, B. Miljevic, A. Laaksonen, Z. D. Ristovski

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In order to investigate the properties of coral reef origin secondary aerosol and especially the contribution of secondary organic aerosol, ethanol affinity to atmospheric nucleation mode particles (diameter<15nm) was measured at the Heron reef marine environment in the South Pacific Ocean during the first coral reef aerosol characterization experiment in May-June 2011 using an ultrafine organic tandem differential mobility analyzer.

Our campaign study at Heron reef showed that the nucleation mode size particles (diameter =10nm) composition contain internally mixed sulfate and oxidized organic components in approximately equal proportion in sunny and still conditions around low tide time, indicating local biogenic sources. The produced secondary compounds and aerosols have potential to contribute to cloud condensation nuclei formation and properties that may affect local low-level cloud formation over the GBR. Additionally, primary marine sea-salt and organic material during windy conditions and anthropogenic/biogenic sources during continental air masses can affect the properties of these particles.

Keywords: Coral reef, DMS, particle composition, secondary organics.

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Authors: José M. Cantera, Miguel Jiménez, Genoveva López, Javier Soriano

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With the advent of emerging personal computing paradigms such as ubiquitous and mobile computing, Web contents are becoming accessible from a wide range of mobile devices. Since these devices do not have the same rendering capabilities, Web contents need to be adapted for transparent access from a variety of client agents. Such content adaptation is exploited for either an individual element or a set of consecutive elements in a Web document and results in better rendering and faster delivery to the client device. Nevertheless, Web content adaptation sets new challenges for semantic markup. This paper presents an advanced components platform, called SMC, enabling the development of mobility applications and services according to a channel model based on the principles of Services Oriented Architecture (SOA). It then goes on to describe the potential for integration with the Semantic Web through a novel framework of external semantic annotation that prescribes a scheme for representing semantic markup files and a way of associating Web documents with these external annotations. The role of semantic annotation in this framework is to describe the contents of individual documents themselves, assuring the preservation of the semantics during the process of adapting content rendering. Semantic Web content adaptation is a way of adding value to Web contents and facilitates repurposing of Web contents (enhanced browsing, Web Services location and access, etc).

Keywords: Semantic web, ubiquitous and mobile computing, web content transcoding. semantic mark-up, mobile computing, middleware and services.

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Authors: Mehdi Modabberifar, Sanaz Jabary, Mojtaba Ghodsi

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Stiffness sensing is an important issue in medical diagnostic, robotics surgery, safe handling, and safe grasping of objects in production lines. Detecting and obtaining the characteristics in dwelling lumps embedded in a soft tissue and safe removing and handling of detected lumps is needed in surgery. Also in industry, grasping and handling an object without damaging in a place where it is not possible to access a human operator is very important. In this paper, a method for object handling is presented. It is based on the use of an intelligent gripper to detect the object stiffness and then setting a programmable force for grasping the object to move it. The main components of this system includes sensors (sensors for measuring force and displacement), electrical (electrical and electronic circuits, tactile data processing and force control system), mechanical (gripper mechanism and driving system for the gripper) and the display unit. The system uses a rotary potentiometer for measuring gripper displacement. A microcontroller using the feedback received by the load cell, mounted on the finger of the gripper, calculates the amount of stiffness, and then commands the gripper motor to apply a certain force on the object. Results of Experiments on some samples with different stiffness show that the gripper works successfully. The gripper can be used in haptic interfaces or robotic systems used for object handling.

Keywords: Gripper, haptic, stiffness, robotic.

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Authors: Fatma El-zahraa El-taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions is critical to decisions such as crossing roads or selecting safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition  problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset are examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of detection of intersections in satellite images is evaluated.

Keywords: Satellite images, remote sensing images, data acquisition, autonomous vehicles, robot navigation, route planning, road intersections.

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Authors: Yi Jianjun, Sun Yingce, Hu Diqing, Li Chenggang

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Modularized design approach can facilitate the modeling of complex systems and support behavior analysis and simulation in an iterative and thus complex engineering process, by using encapsulated submodels of components and of their interfaces. Therefore it can improve the design efficiency and simplify the solving complicated problem. Multi-drivers off-road vehicle is comparatively complicated. Driving-line is an important core part to a vehicle; it has a significant contribution to the performance of a vehicle. Multi-driver off-road vehicles have complex driving-line, so its performance is heavily dependent on the driving-line. A typical off-road vehicle-s driving-line system consists of torque converter, transmission, transfer case and driving-axles, which transfer the power, generated by the engine and distribute it effectively to the driving wheels according to the road condition. According to its main function, this paper puts forward a modularized approach for designing and evaluation of vehicle-s driving-line. It can be used to effectively estimate the performance of driving-line during concept design stage. Through appropriate analysis and assessment method, an optimal design can be reached. This method has been applied to the practical vehicle design, it can improve the design efficiency and is convenient to assess and validate the performance of a vehicle, especially of multi-drivers off-road vehicle.

Keywords: Heavy-loaded Off-road Vehicle, Power Driving-line, Modularized Design, Performance Assessment.

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Authors: R.S.Sabeenian, V.Palanisamy

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Texture classification is a trendy and a catchy technology in the field of texture analysis. Textures, the repeated patterns, have different frequency components along different orientations. Our work is based on Texture Classification and its applications. It finds its applications in various fields like Medical Image Classification, Computer Vision, Remote Sensing, Agricultural Field, and Textile Industry. Weed control has a major effect on agriculture. A large amount of herbicide has been used for controlling weeds in agriculture fields, lawns, golf courses, sport fields, etc. Random spraying of herbicides does not meet the exact requirement of the field. Certain areas in field have more weed patches than estimated. So, we need a visual system that can discriminate weeds from the field image which will reduce or even eliminate the amount of herbicide used. This would allow farmers to not use any herbicides or only apply them where they are needed. A machine vision precision automated weed control system could reduce the usage of chemicals in crop fields. In this paper, an intelligent system for automatic weeding strategy Multi Resolution Combined Statistical & spatial Frequency is used to discriminate the weeds from the crops and to classify them as narrow, little and broad weeds.

Keywords: crop weed discrimination, MRCSF, MRFM, Weeddetection, Spatial Frequency.

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Authors: Saeedeh Shafiee Nahrkhalaji

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Metacognitive knowledge increases EFL students’ ability to be successful learners. Although this relationship has been investigated by a number of scholars, EFL teachers’ explicit awareness of their cognitive knowledge has not been sufficiently explored. The aim of this study was to examine the role of EFL teachers’ metacognitive knowledge in their pedagogical performance. Furthermore, the role played by years of their academic education and teaching experience was also studied. Fifty female EFL teachers were selected. They completed Metacognitive Awareness Inventory (MAI) that assessed six components of metacognition including procedural knowledge, declarative knowledge, conditional knowledge, planning, evaluating, and management strategies. Near the end of the academic semester, the students of each class filled in ‘the Language Teacher Characteristics Questionnaire’ to evaluate their teachers’ pedagogical performance. Four elements of MAI, declarative knowledge, planning, evaluating, and management strategies were found to be significantly correlated with EFL teachers’ pedagogical success. Significant correlation was also established between metacognitive knowledge and EFL teachers’ years of academic education and teaching experience. The findings obtained from this research have contributing implication for EFL teacher educators. The discussion concludes by setting out directions for future research.

Keywords: Metacognotive Knowledge, Pedagogical Performance, Language Teacher Characteristics Questionnaire, Metacognitive Awareness Inventory.

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Authors: Ferhat Kadioglu, Ahmet Reha Gunay

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Correct measurement of a structural damping value is an important issue for the reliable design of the components exposed to vibratory and noise conditions. As far as a vibrating beam technique is concerned, the specimens under the test somehow are interacted with measuring and exciting devices and also with boundary conditions of the test set-up. The aim of this study is to propose a vibrating beam method that offers a non-contact dynamic measurement of solid beam specimens. To evaluate possible effects of the clamped portion of the specimens with clamped-free ends on the dynamic values (damping and the elastic modulus), the same measuring devices were used, and the results were compared to those with the free-free ends. To get clear idea about the sensitivity of the boundary conditions to the damping values at low, medium and high levels, representative materials were subjected to the tests. The results show that the specimens with low damping values are especially sensitive to the boundary conditions and the most reliable structural damping values are obtained for the specimens with free-free ends. For the damping values at the low levels, a deviation of about 368% was obtained between the specimens with free-free and clamped-free ends, yet, for those having high inherent damping values, comparable results were obtained.

Keywords: Vibrating beam technique, dynamic values, damping, boundary conditions, non-contact measuring systems.

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Authors: Chen-Fu Wang, Lin-Ya Kung

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For traditional painting materials, the artisan used to combine the pigments with different binders to create colors. As time goes by, the materials used for painting evolved from natural to chemical materials. The vast variety of ingredients used in chemical materials has complicated restoration work; it makes conservation work more difficult. Conservation work also becomes harder when the materials cannot be easily identified; therefore, it is essential that we take a more scientific approach to assist in conservation work. Paintings materials are high molecular weight polymer, and their analysis is very complicated as well other contamination such as smoke and dirt can also interfere with the analysis of the material. The current methods of composition analysis of painting materials include Fourier transform infrared spectroscopy (FT-IR), mass spectrometer, Raman spectroscopy, X-ray diffraction spectroscopy (XRD), each of which has its own limitation. In this study, FT-IR was used to analyze the components of the paint coating. We have taken the most commonly seen materials as samples and deteriorated it. The aged information was then used for the database to exam the temple painting materials. By observing the FT-IR changes over time, we can tell all of the painting materials will be deteriorated by the UV light, but only the speed of its degradation had some difference. From the deterioration experiment, the acrylic resin resists better than the others. After collecting the painting materials aging information on FT-IR, we performed some test on the paintings on the temples. It was found that most of the artisan used tune-oil for painting materials, and some other paintings used chemical materials. This method is now working successfully on identifying the painting materials. However, the method is destructive and high cost. In the future, we will work on the how to know the painting materials more efficiently.

Keywords: Temple painting, painting material, conservation, FT-IR.

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Authors: Dehong Li, Yuchen Chen, Alireza Kaboorani, Denis Rodrigue, Xiaodong (Alice) Wang

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Utilizing solar energy for thermal energy storage has emerged as an appealing option for lowering the amount of energy that is consumed by buildings. Due to their high heat storage density, non-corrosive and non-polluting properties, alcohols can be a good alternative to petroleum-derived paraffin phase change materials (PCMs). In this paper, ternary eutectic PCMs with suitable phase change temperatures were designed and prepared using lauryl alcohol (LA), cetyl alcohol (CA), stearyl alcohol (SA) and xylitol (X). The Differential Scanning Calorimetry (DSC) results revealed that the phase change temperatures of LA-CA-SA, LA-CA-X, and LA-SA-X were 20.52 °C, 20.37 °C, and 22.18 °C, respectively. The latent heat of phase change of the ternary eutectic PCMs were all stronger than that of the paraffinic PCMs at roughly the same temperature. The highest latent heat was 195 J/g. It had good thermal energy storage capacity. The preparation mechanism was investigated using Fourier-transform Infrared Spectroscopy (FTIR), and it was found that the ternary eutectic PCMs were only physically mixed among the components. Ternary eutectic PCMs had a simple preparation process, suitable phase change temperature, and high energy storage density. They are suitable for low-temperature architectural packaging applications.

Keywords: Thermal energy storage, buildings, phase change materials, alcohols.

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Authors: M. Ezkurra, J. A. Esnaola, M. Martinez-Agirre, U. Etxeberria, U. Lertxundi, L. Colomo, M. Begiristain, I. Zurutuza

Abstract:

Butterfly valves are widely used industrial piping components as on-off and flow controlling devices. The main challenge in the design process of this type of valves is the correct dimensioning to ensure proper mechanical performance as well as to minimise flow losses that affect the efficiency of the system. Butterfly valves are typically dimensioned in a closed position based on mechanical approaches considering uniform hydrostatic pressure, whereas the flow losses are analysed by means of CFD simulations. The main limitation of these approaches is that they do not consider either the influence of the dynamics of the manoeuvring stage or coupled phenomena. Recent works have included the influence of the flow on the mechanical behaviour for different opening angles by means of one-way FSI approach. However, these works consider steady-state flow for the selected angles, not capturing the effect of the transient flow evolution during the manoeuvring stage. Two-way FSI modelling approach could allow overcoming such limitations providing more accurate results. Nevertheless, the use of this technique is limited due to the increase in the computational cost. In the present work, the applicability of FSI one-way and two-way approaches is evaluated for the analysis of butterfly valves, showing that not considering fluid-structure coupling involves not capturing the most critical situation for the valve disc.

Keywords: Butterfly valves, fluid-structure interaction, one-way approach, two-way approach.

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Authors: Angie M. Wolf, Angie Del Prado Lippman, DeVone Boggan, Caroline Glesmann, Estivaliz Castro

Abstract:

This paper highlights an innovative and nontraditional violence prevention program that is making a noticeable impact in what was once one of the country’s most violent communities. With unique and tailored strategies, the Operation Peacemaker Fellowship, established in Richmond, California, combines components of evidence-based practices with a community-oriented focus on relationships and mentoring to fill a gap in services and increase community safety. In an effort to highlight these unique strategies and provide a blueprint for other communities with violent crime problems, the authors of this paper hope to clearly delineate how one community is moving forward with vanguard approaches to invest in the lives of young men who once were labeled their community’s most violent, even most deadly, youth. The impact of this program is evidenced through the fellows’ own voices as they illuminate the experience of being in the Fellowship. In interviews, fellows describe how participating in this program has transformed their lives and the lives of those they love. The authors of this article spent more than two years researching this Fellowship program in order to conduct an evaluation of it and, ultimately, to demonstrate how this program is a testament to the power of relationships and love combined with evidence-based practices, consequently enriching the lives of youth and the community that embraces them.

Keywords: Community violence, firearm violence, interventions for violent crime, violence prevention.

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Authors: Nuzlinda Abdul Rahman, Syerrina Zakaria

Abstract:

Deprivation indices are widely used in public health study. These indices are also referred as the index of inequalities or disadvantage. Even though, there are many indices that have been built before, it is believed to be less appropriate to use the existing indices to be applied in other countries or areas which had different socio-economic conditions and different geographical characteristics. The objective of this study is to construct the index based on the geographical and socio-economic factors in Peninsular Malaysia which is defined as the weighted household-based deprivation index. This study has employed the variables based on household items, household facilities, school attendance and education level obtained from Malaysia 2000 census report. The factor analysis is used to extract the latent variables from indicators, or reducing the observable variable into smaller amount of components or factor. Based on the factor analysis, two extracted factors were selected, known as Basic Household Amenities and Middle-Class Household Item factor. It is observed that the district with a lower index values are located in the less developed states like Kelantan, Terengganu and Kedah. Meanwhile, the areas with high index values are located in developed states such as Pulau Pinang, W.P. Kuala Lumpur and Selangor.

Keywords: Factor Analysis, Basic Household Amenities, Middle-Class Household Item, Socio-economic Index

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Authors: Heba Mohammed Nagy, Walid Mohamed Aly, Osama Fathy Hegazy

Abstract:

Educational  data mining  is  a  specific  data   mining field applied to data originating from educational environments, it relies on different  approaches to discover hidden knowledge  from  the  available   data. Among these approaches are   machine   learning techniques which are used to build a system that acquires learning from previous data. Machine learning can be applied to solve different regression, classification, clustering and optimization problems.

In  our  research, we propose  a “Student  Advisory  Framework” that  utilizes  classification  and  clustering  to  build  an  intelligent system. This system can be used to provide pieces of consultations to a first year  university  student to  pursue a  certain   education   track   where  he/she  will  likely  succeed  in, aiming  to  decrease   the  high  rate   of  academic  failure   among these  students.  A real case study  in Cairo  Higher  Institute  for Engineering, Computer  Science  and  Management  is  presented using  real  dataset   collected  from  2000−2012.The dataset has two main components: pre-higher education dataset and first year courses results dataset. Results have proved the efficiency of the suggested framework.

Keywords: Classification, Clustering, Educational Data Mining (EDM), Machine Learning.

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Authors: Wen-Hsiang Lai

Abstract:

Except for the internal aspects of entrepreneurship (i.e.motivation, opportunity perspective and alertness), there are external aspects that affecting entrepreneurship (i.e. the industrial cluster). By comparing the machinery companies located inside and outside the industrial district, this study aims to explore the cluster effects on the entrepreneurship of companies in Taiwan machinery clusters (TMC). In this study, three factors affecting the entrepreneurship in TMC are conducted as “competition”, “embedded-ness” and “specialized knowledge”. The “competition” in the industrial cluster is defined as the competitive advantages that companies gain in form of demand effects and diversified strategies; the “embedded-ness” refers to the quality of company relations (relational embedded-ness) and ranges (structural embedded-ness) with the industry components (universities, customers and complementary) that affecting knowledge transfer and knowledge generations; the “specialized knowledge” shares theinternal knowledge within industrial clusters. This study finds that when comparing to the companieswhich are outside the cluster, the industrial cluster has positive influence on the entrepreneurship. Additionally, the factor of “relational embedded-ness” has significant impact on the entrepreneurship and affects the adaptation ability of companies in TMC. Finally, the factor of “competition” reveals partial influence on the entrepreneurship.

Keywords: Entrepreneurship, Industrial Cluster, Industrial District, Economies of Agglomerations, Taiwan Machinery Cluster (TMC).

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Authors: M. Zellagui, A. Chaghi

Abstract:

This paper presents the impact study of GTO Controlled Series Capacitor (GCSC) parameters on measured impedance (Zseen) by MHO distance relays for single transmission line high voltage 220 kV in the presence of single phase to earth fault with fault resistance (RF). The study deals with a 220 kV single electrical transmission line of Eastern Algerian transmission networks at Group Sonelgaz (Algerian Company of Electrical and Gas) compensated by series Flexible AC Transmission System (FACTS) i.e. GCSC connected at midpoint of the transmission line. The transmitted active and reactive powers are controlled by three GCSC-s. The effects of maximum reactive power injected as well as injected maximum voltage by GCSC on distance relays measured impedance is treated. The simulations results investigate the effects of GCSC injected parameters: variable reactance (XGCSC), variable voltage (VGCSC) and reactive power injected (QGCSC) on measured resistance and reactance in the presence of earth fault with resistance fault varied between 5 to 50 Ω for three cases study.

Keywords: GCSC Parameters, Transmission line, Earth fault, Symmetrical components, Distance protection, Measured impedance.

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Authors: Khalid Ali, Manar Jammal

Abstract:

In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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