Search results for: sequential patterns.

Authors: Lae-Jeong Park, Jung-Ho Moon

Abstract:

People detection from images has a variety of applications such as video surveillance and driver assistance system, but is still a challenging task and more difficult in crowded environments such as shopping malls in which occlusion of lower parts of human body often occurs. Lack of the full-body information requires more effective features than common features such as HOG. In this paper, new features are introduced that exploits global self-symmetry (GSS) characteristic in head-shoulder patterns. The features encode the similarity or difference of color histograms and oriented gradient histograms between two vertically symmetric blocks. The domain-specific features are rapid to compute from the integral images in Viola-Jones cascade-of-rejecters framework. The proposed features are evaluated with our own head-shoulder dataset that, in part, consists of a well-known INRIA pedestrian dataset. Experimental results show that the GSS features are effective in reduction of false alarmsmarginally and the gradient GSS features are preferred more often than the color GSS ones in the feature selection.

Keywords: Pedestrian detection, cascade of rejecters, feature extraction, self-symmetry, HOG.

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Authors: S. Qaedi, S. Seyedtabaii

Abstract:

Non-Destructive evaluation of in-service power transformer condition is necessary for avoiding catastrophic failures. Dissolved Gas Analysis (DGA) is one of the important methods. Traditional, statistical and intelligent DGA approaches have been adopted for accurate classification of incipient fault sources. Unfortunately, there are not often enough faulty patterns required for sufficient training of intelligent systems. By bootstrapping the shortcoming is expected to be alleviated and algorithms with better classification success rates to be obtained. In this paper the performance of an artificial neural network, K-Nearest Neighbour and support vector machine methods using bootstrapped data are detailed and shown that while the success rate of the ANN algorithms improves remarkably, the outcome of the others do not benefit so much from the provided enlarged data space. For assessment, two databases are employed: IEC TC10 and a dataset collected from reported data in papers. High average test success rate well exhibits the remarkable outcome.

Keywords: Dissolved gas analysis, Transformer incipient fault, Artificial Neural Network, Support Vector Machine (SVM), KNearest Neighbor (KNN)

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Authors: Chit Su Htwe, Win Htay

Abstract:

The iris recognition technology is the most accurate, fast and less invasive one compared to other biometric techniques using for example fingerprints, face, retina, hand geometry, voice or signature patterns. The system developed in this study has the potential to play a key role in areas of high-risk security and can enable organizations with means allowing only to the authorized personnel a fast and secure way to gain access to such areas. The paper aim is to perform the iris region detection and iris inner and outer boundaries localization. The system was implemented on windows platform using Visual C# programming language. It is easy and efficient tool for image processing to get great performance accuracy. In particular, the system includes two main parts. The first is to preprocess the iris images by using Canny edge detection methods, segments the iris region from the rest of the image and determine the location of the iris boundaries by applying Hough transform. The proposed system tested on 756 iris images from 60 eyes of CASIA iris database images.

Keywords: Canny, C#, hough transform, image preprocessing.

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Authors: Sattar Al-Jabair, Laith J. Habeeb

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In this work, the natural convection in a concentric annulus between a cold outer inclined square enclosure and heated inner circular cylinder is simulated for two-dimensional steady state. The Boussinesq approximation was applied to model the buoyancy-driven effect and the governing equations were solved using the time marching approach staggered by body fitted coordinates. The coordinate transformation from the physical domain to the computational domain is set up by an analytical expression. Numerical results for Rayleigh numbers 103 , 104 , 105 and 106, aspect ratios 1.5 , 3.0 and 4.5 for seven different inclination angles for the outer square enclosure 0o , -30o , -45o , -60o , -90o , -135o , -180o are presented as well. The computed flow and temperature fields were demonstrated in the form of streamlines, isotherms and Nusselt numbers variation. It is found that both the aspect ratio and the Rayleigh number are critical to the patterns of flow and thermal fields. At all Rayleigh numbers angle of inclination has nominal effect on heat transfer.

Keywords: natural convection, concentric annulus, square inclined enclosure

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Authors: Rolf Katzenbach, Frithjof Clauss, Jie Zheng

Abstract:

The final energy use can be divided mainly in four sectors: commercial, industrial, residential, and transportation. The trend in final energy consumption by sector plays as a most straightforward way to provide a wide indication of progress for reducing energy consumption and associated environmental impacts by different end use sectors. The average share of end use energy for residential sector in the world was nearly 20% until 2011, in Germany a higher proportion is between 25% and 30%. However, it remains less studied than energy use in other three sectors as well its impacts on climate and environment. The reason for this involves a wide range of fields, including the diversity of residential construction like different housing building design and materials, living or energy using behavioral patterns, climatic condition and variation as well other social obstacles, market trend potential and financial support from government.

This paper presents an extensive and in-depth analysis of the manner by which projects researched and operated by authors in the fields of energy efficiency primarily from the perspectives of both technical potential and initiative energy saving consciousness in the residential sectors especially in social housing buildings.

Keywords: Energy Efficiency, Renewable Energy, Retro-commissioning, Social Housing, Sustainability.

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Authors: Mária Stachová, Lukáš Sobíšek

Abstract:

Data mining incorporates a group of statistical methods used to analyze a set of information, or a data set. It operates with models and algorithms, which are powerful tools with the great potential. They can help people to understand the patterns in certain chunk of information so it is obvious that the data mining tools have a wide area of applications. For example in the theoretical chemistry data mining tools can be used to predict moleculeproperties or improve computer-assisted drug design. Classification analysis is one of the major data mining methodologies. The aim of thecontribution is to create a classification model, which would be able to deal with a huge data set with high accuracy. For this purpose logistic regression, Bayesian logistic regression and random forest models were built using R software. TheBayesian logistic regression in Latent GOLD software was created as well. These classification methods belong to supervised learning methods. It was necessary to reduce data matrix dimension before construct models and thus the factor analysis (FA) was used. Those models were applied to predict the biological activity of molecules, potential new drug candidates.

Keywords: data mining, classification, drug design, QSAR

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Authors: Ching M. Hsu, Rong F. Huang, Michael E. Loretero

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Shear-layer instabilities of a pulsed stack-issued transverse jet were studied experimentally in a wind tunnel. Jet pulsations were induced by means of acoustic excitation. Streak pictures of the smoke-flow patterns illuminated by the laser-light sheet in the median plane were recorded with a high-speed digital camera. Instantaneous velocities of the shear-layer instabilities in the flow were digitized by a hot-wire anemometer. By analyzing the streak pictures of the smoke-flow visualization, three characteristic flow modes, synchronized flapping jet, transition, and synchronized shear-layer vortices, are identified in the shear layer of the pulsed stack-issued transverse jet at various excitation Strouhal numbers. The shear-layer instabilities of the pulsed stack-issued transverse jet are synchronized by acoustic excitation except for transition mode. In transition flow mode, the shear-layer vortices would exhibit a frequency that would be twice as great as the acoustic excitation frequency.

Keywords: Acoustic excitation, jet in crossflow, shear-layer instability.

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Authors: Indah Kurniawaty, Yoki Yulizar, Haryo Satrya Oktaviano, Adam Kusuma Rianto

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Magnesium oxide nanoparticles (MgO NP) were successfully synthesized in this study using a one-pot green synthesis mediated by Calliandra calothyrsus leaf extract (CLE). CLE was prepared by maceration of the leaf using methanol with a ratio of 1:5 for 7 days. Secondary metabolites in CLE, such as alkaloids and flavonoids, served as a weak base provider and capping agent in the formation of MgO NP. CLE Fourier Transform Infra-Red (FTIR) spectra peak at 3255 cm-1, 1600 cm-1, 1384 cm-1, 1205 cm-1, 1041 cm-1, and 667 cm-1 showing the presence of vibrations O-H stretching, N-H bending, C-C stretching, C-N stretching and N-H wagging. During the experiment, different CLE volumes and calcined temperatures were used, resulting in a variety of structures. Energy Dispersive X-ray Spectrometer (EDS) and FTIR were used to characterize metal oxide particles. MgO diffraction patterns at 2θ of 36.9°; 42.9°; 62.2°; 74.6°; and 78.5° can be assigned to crystal planes (111), (200), (220), (311), and (222), respectively. Scanning Electron Microscopy (SEM) was used to characterize the surface morphology. The morphology ranged from sphere to flower-like resulting in crystallite sizes of 28 nm, 23 nm, 12 nm, and 9 nm.

Keywords: Calliandra calothyrsus, green-synthesis, magnesium oxide, nanoparticle.

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Authors: P. U. S. Peiris

Abstract:

The butterflies are ecologically very important insects. The adults generally feed on nectar and are important as pollinators of flowering plants. However, these pollinators are under threat with their habitat loss. One reason for habitat loss is spread of invasive plants. However, there are even beneficial exotic plants which can directly support for Butterfly Conservation Action Plan of Sri Lanka by attracting butterflies for nectar. Stachytarpheta jamaicensis (L.) is an important nectar plant which attracts a diverse set of butterflies in higher number. It comprises a violet color inflorescence which last for about 37 hours where it attracted a peak of butterflies around 9.00am having around average of 15 butterflies. There were no butterflies in early and late hours where the number goes to very low values as 2 at 1.00pm. it was found that a diverse group of butterflies were attracted from around 15 species including 01 endemic species, 02 endemic subspecies and 02 vulnerable species. Therefore, this is a beneficial exotic plant that could be used in butterfly attraction and conservation however with adequate monitoring of the plant population.

Keywords: Butterflies, exotic plants, pollinators, Stachytarpheta jamaicensis (L.), butterfly conservation

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Authors: Ilona Mewes, Helena Jenzer, Farshideh Einsele

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Objective: The objective of the study was to integrate two big databases from Swiss nutrition national survey (menuCH) and Swiss health national survey 2012 for data mining purposes. Each database has a demographic base data. An integrated Swiss database is built to later discover critical food consumption patterns linked with lifestyle diseases known to be strongly tied with food consumption. Design: Swiss nutrition national survey (menuCH) with approx. 2000 respondents from two different surveys, one by Phone and the other by questionnaire along with Swiss health national survey 2012 with 21500 respondents were pre-processed, cleaned and finally integrated to a unique relational database. Results: The result of this study is an integrated relational database from the Swiss nutritional and health databases.

Keywords: Health informatics, data mining, nutritional and health databases, nutritional and chronical databases.

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Authors: Mona Lisa M. Oliveira, Nara A. Policarpo, Ana Luiza B. P. Barros, Carla A. Silva

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Selective catalytic reduction systems for nitrogen oxides reduction by ammonia has been the chosen technology by most of diesel vehicle (i.e. bus and truck) manufacturers in Brazil, as also in Europe. Furthermore, at some conditions, over-stoichiometric ammonia availability is also needed that increases the NH₃ slips even more. Ammonia (NH₃) by this vehicle exhaust aftertreatment system provides a maximum efficiency of NOx removal if a significant amount of NH₃ is stored on its catalyst surface. In the other words, the practice shows that slightly less than 100% of the NOx conversion is usually targeted, so that the aqueous urea solution hydrolyzes to NH₃ via other species formation, under relatively low temperatures. This paper presents a model based on neural networks integrated with a road vehicle simulator that allows to estimate NH₃-slip emission factors for different driving conditions and patterns. The proposed model generates high NH₃slips which are not also limited in Brazil, but more efforts needed to be made to elucidate the contribution of vehicle-emitted NH₃ to the urban atmosphere.

Keywords: Ammonia slip, neural-network, vehicles emissions, SCR-NOx.

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Authors: Minsoo Lee, Yearn Jeong Kim, Yun-mi Kim, Sujeung Cheong, Sookyung Song

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Bio-chips are used for experiments on genes and contain various information such as genes, samples and so on. The two-dimensional bio-chips, in which one axis represent genes and the other represent samples, are widely being used these days. Instead of experimenting with real genes which cost lots of money and much time to get the results, bio-chips are being used for biological experiments. And extracting data from the bio-chips with high accuracy and finding out the patterns or useful information from such data is very important. Bio-chip analysis systems extract data from various kinds of bio-chips and mine the data in order to get useful information. One of the commonly used methods to mine the data is classification. The algorithm that is used to classify the data can be various depending on the data types or number characteristics and so on. Considering that bio-chip data is extremely large, an algorithm that imitates the ecosystem such as the ant algorithm is suitable to use as an algorithm for classification. This paper focuses on finding the classification rules from the bio-chip data using the Ant Colony algorithm which imitates the ecosystem. The developed system takes in consideration the accuracy of the discovered rules when it applies it to the bio-chip data in order to predict the classes.

Keywords: Ant Colony System, DNA chip data, Classification.

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Authors: C. Adam, G. Henri, T. Levent, J.-B. Mauro, A. -L. Mayet

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This paper is concerning the application of a deterministic decisional pattern to a multi-agent system which would provide intelligence to a distributed energy smart grid at local consumer level. Development of multi-agent application involves agent specifications, analysis, design and realization. It can be implemented by following several decisional patterns. The purpose of present article is to suggest a new approach to control the smart grid system in a decentralized competitive approach. The proposed algorithmic solution results from a deterministic dichotomous approach based on environment observation. It uses an iterative process to solve automatic learning problems. Through memory of collected past tries, the algorithm monotonically converges to very steep system operation point in attraction basin resulting from weak system nonlinearity. In this sense, system is given by (local) constitutive elementary rules the intelligence of its global existence so that it can self-organize toward optimal operating sequence.

Keywords: Decentralized Competitive System, Distributed Smart Grid, Multi-Agent System

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Authors: Divya Haridas, C. B. Sobhan

Abstract:

Laser interferometric methods have been utilized for the measurement of natural convection heat transfer from a heated vertical flat plate, in the investigation presented here. The study mainly aims at comparing two different fringe orientations in the wedge fringe setting of Mach-Zehnder interferometer (MZI), used for the measurements. The interference fringes are set in horizontal and vertical orientations with respect to the heated surface, and two different fringe analysis methods, namely the stepping method and the method proposed by Naylor and Duarte, are used to obtain the heat transfer coefficients. The experimental system is benchmarked with theoretical results, thus validating its reliability in heat transfer measurements. The interference fringe patterns are analyzed digitally using MATLAB 7 and MOTIC Plus softwares, which ensure improved efficiency in fringe analysis, hence reducing the errors associated with conventional fringe tracing. The work also discuss the relative merits and limitations of the two methods used.

Keywords: MZI, Natural Convection, Naylor Method, Vertical Flat Plate.

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Authors: G. Türkmen, Ö. Tekin, K. Kurtuluş, Y. Y. Yurtseven, M. Baran

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A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: Convolutional Neural Networks, deep learning, image classification, scanning electron microscope.

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Authors: D.Nuketaeva, A.Kanagatova, I.Khan, B.Kylyshbayeva, G.Bektenova

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This article describes the aspects of the formation of the national idea and national identity through the prism of gender control and its contradistinction to the obsolete, Soviet component. The role of females in ethnic and national projects is considered from the point of view of Dr. Nira Yuval-Davis: as biological reproducers of the ethnic communities- members; as reproducers of the boarders of ethnic/national groups; as central participants in the ideological reproduction of community and transducers of its culture; as symbols in ideology, reproduction and transformation of ethnic/national categories; and as participants of national, economical, political and military combats. The society of the transitional type uses the symbolic resources of the formation of gender component in the national project. The gender patterns act like cultural codes, executing the important ideological function in formation of the national female- image, i.e. the discussion on hijab - it-s not just the discussion on control over the female body, it-s the discussion on the metaphor of social order.

Keywords: nation, gender, hijab, Islam, ideology, politics, national idea, national identity, society of the transitional type

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Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

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Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: Die-Map Clustering, Feature Extraction, Pattern Recognition, Semiconductor Manufacturing Process.

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Authors: C. Ardil

Abstract:

Using the aid of Hausdorff distance function and Minkowski distance function, this study proposes a novel method for selecting combat aircraft for Air Force. In order to do this, the proximity measure method was developed with determinate fuzzy degrees based on the relationship between attributes and combat aircraft alternatives. The combat aircraft selection attributes were identified as payloadability, maneuverability, speedability, stealthability, and survivability. Determinate fuzzy data from the combat aircraft attributes was then aggregated using the determinate fuzzy weighted arithmetic average operator. For the selection of combat aircraft, correlation analysis of the ranking order patterns of options was also examined. A numerical example from military aviation is used to demonstrate the applicability and effectiveness of the proposed method.

Keywords: Combat aircraft selection, multiple criteria decision making, fuzzy sets, determinate fuzzy sets, intuitionistic fuzzy sets, proximity measure method, Hausdorff distance function, Minkowski distance function, PMM, MCDM

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Authors: Kamel Hashem, David Mioduser

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This paper describes part of a project about Learningby- Modeling (LbM). Studying complex systems is increasingly important in teaching and learning many science domains. Many features of complex systems make it difficult for students to develop deep understanding. Previous research indicates that involvement with modeling scientific phenomena and complex systems can play a powerful role in science learning. Some researchers argue with this view indicating that models and modeling do not contribute to understanding complexity concepts, since these increases the cognitive load on students. This study will investigate the effect of different modes of involvement in exploring scientific phenomena using computer simulation tools, on students- mental model from the perspective of structure, behavior and function. Quantitative and qualitative methods are used to report about 121 freshmen students that engaged in participatory simulations about complex phenomena, showing emergent, self-organized and decentralized patterns. Results show that LbM plays a major role in students' concept formation about complexity concepts.

Keywords: Complexity, Educational technology, Learning by modeling, Mental models

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Authors: Hong Pan, Yaping Zhu, Liang Zheng Xia

Abstract:

We propose a fast and robust hierarchical face detection system which finds and localizes face images with a cascade of classifiers. Three modules contribute to the efficiency of our detector. First, heterogeneous feature descriptors are exploited to enrich feature types and feature numbers for face representation. Second, a PSO-Adaboost algorithm is proposed to efficiently select discriminative features from a large pool of available features and reinforce them into the final ensemble classifier. Compared with the standard exhaustive Adaboost for feature selection, the new PSOAdaboost algorithm reduces the training time up to 20 times. Finally, a three-stage hierarchical classifier framework is developed for rapid background removal. In particular, candidate face regions are detected more quickly by using a large size window in the first stage. Nonlinear SVM classifiers are used instead of decision stump functions in the last stage to remove those remaining complex nonface patterns that can not be rejected in the previous two stages. Experimental results show our detector achieves superior performance on the CMU+MIT frontal face dataset.

Keywords: Adaboost, Face detection, Feature selection, PSO

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Authors: Riki H. Patel, Arpan Desai, Trushit Upadhyaya, Shobhit K. Patel

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The microstrip antennas area has seen some inventive work in recent years and is now one of the most dynamic fields of antenna theory. A novel and simple wideband monopole antenna is presented printed on a single dielectric substrate which is fed by a 50 ohm microstrip line having a low-profile antenna structure with two parallel s-shaped meandered line of same size. This antenna is fed by a coaxial feeding tube. In this research, S–form microstrip patch antenna is designed from measuring the prototypes of the proposed antenna one available bands with 10db return loss bandwidths of about GPS application (GPS L2 1490 MHz) and covering the 1400 to 1580 MHz frequency band at 1.5 GHz, the simulated results for main parameters such as return loss, impedance bandwidth, radiation patterns, and gains are also discussed herein. The modeling study shows that such antennas, in simplicity design and supply, can satisfy GPS application. Two parallel slots are incorporated to disturb the surface flow path, introducing local inductive effect. This antenna is fed by a coaxial feeding tube.

Keywords: Bandwidth, electrically small antenna, microstrip patch antenna, GPS.

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Authors: Mohammad Javad Shariatzadeh, Dana Grecov

Abstract:

The tribological tests were performed on a new tribometer, in order to measure the coefficient of friction of a gland seal packing material on stainless steel shafts in presence of Cellulose Nanocrystal (CNC) suspension as a sustainable, environmentally friendly, water-based lubricant. To simulate the real situation from the slurry pumps, silica sands were used as slurry particles. The surface profiles after tests were measured by interferometer microscope to characterize the surface wear. Moreover, the coefficient of friction and surface wear were measured between stainless steel shaft and chrome steel ball to investigate the tribological effects of CNC in boundary lubrication region. Alignment of nanoparticles in the CNC suspensions are the main reason for friction and wear reduction. The homogeneous concentrated suspensions showed fingerprint patterns of a chiral nematic liquid crystal. These properties made CNC a very good lubricant additive in water.

Keywords: Gland seal, lubricant additives, nanocrystalline cellulose, water-based lubricants.

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Authors: Yuyun, Fritz Akhmad Nuzir, Bart Julien Dewancker

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Check-in locations on social media provide information about an individual’s location. The millions of units of data generated from these sites provide knowledge for human activity. In this research, we used a geolocation service and users’ texts posted on Twitter social media to analyze human mobility. Our research will answer the questions; what are the movement patterns of a citizen? And, how far do people travel in the city? We explore the people trajectory of 201,118 check-ins and 22,318 users over a period of one month in Makassar city, Indonesia. To accommodate individual mobility, the authors only analyze the users with check-in activity greater than 30 times. We used sampling method with a systematic sampling approach to assign the research sample. The study found that the individual movement shows a high degree of regularity and intensity in certain places. The other finding found that the average distance an urban inhabitant can travel per day is as far as 9.6 km.

Keywords: Mobility, check-in, distance, Twitter.

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Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade

Abstract:

The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.

Keywords: Automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection.

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Authors: Ausra Turcinskaite-Balciuniene, Jonas Balciunas, Gediminas Merkys

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The problematic of gender and socioeconomic status biased differences in academic motivation patterns is discussed. Gender identity is understood according to symbolic interactionism perspective: as a result of reflected appraisals, social comparisons, self-attributions, and identifications, shaped by social environment and family context. The effects of socioeconomic status on academic motivation are conceptualized according to Bourdieu’s habitus concept, reflecting the role of unconscious and internalized cultural signals, proper to low and high socioeconomic status family contexts. Since families differ by various socioeconomic features, the hypothesis about possible impact of parents’ socioeconomic status on their children’s academic motivation interfering with gender socialization effects is held. The survey, aiming to seize gender differences in academic motivation and self-recorded improvementoriented efforts as a result of socialization processes operating in the families of low and high socioeconomic status, was designed. The results of Lithuanian higher education students’ survey are presented and discussed.

Keywords: Academic Motivation, Gender, Socialization, Socioeconomic Status.

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Authors: C. Adam, G. Henri, T. Levent, J-B Mauro, A-L Mayet

Abstract:

Energy Efficiency Management is the heart of a worldwide problem. The capability of a multi-agent system as a technology to manage the micro-grid operation has already been proved. This paper deals with the implementation of a decisional pattern applied to a multi-agent system which provides intelligence to a distributed local energy network considered at local consumer level. Development of multi-agent application involves agent specifications, analysis, design, and realization. Furthermore, it can be implemented by following several decisional patterns. The purpose of present article is to suggest a new approach for a decisional pattern involving a multi-agent system to control a distributed local energy network in a decentralized competitive system. The proposed solution is the result of a dichotomous approach based on environment observation. It uses an iterative process to solve automatic learning problems and converges monotonically very fast to system attracting operation point.

Keywords: Energy Efficiency Management, Distributed Smart- Grid, Multi-Agent System, Decisional Decentralized Competitive System.

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Authors: Galina Mihaleva, C. Koh

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Fashion, like many other design fields, undergoes numerous evolutions throughout the ages. This paper aims to recognize and evaluate the significance of advance technology in fashion design and examine how it changes the role of modern fashion designers by modifying the creation process. It also touches on how modern culture is involved in such developments and how it affects fashion design in terms of conceptualizing and fabrication. The methodology used is through surveying the various examples of technological applications to fashion design and drawing parallels between what was achievable then and what is achievable now. By comparing case studies, existing fashion design examples and crafting method experimentations; we then spot patterns in which to predict the direction of future developments in the field. A breakdown on the elements of technology in fashion design helps us understand the driving force behind such a trend. The results from explorations in the paper have shown that there is an observed pattern of a distinct increase in interest and progress in the field of fashion technology, which leads to the birth of hybrid crafting methods. In conclusion, it is shown that as fashion technology continues to evolve, their role in clothing crafting becomes more prominent and grows far beyond the humble sewing machine.

Keywords: Fashion design, functional aesthetics, smart textiles, 3D printing.

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Authors: A.M. Al-Fahed Nuseirat, R. Abu-Zitar

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In this paper the design of maximally flat linear phase finite impulse response (FIR) filters is considered. The problem is handled with totally two different approaches. The first one is completely deterministic numerical approach where the problem is formulated as a Linear Complementarity Problem (LCP). The other one is based on a combination of Markov Random Fields (MRF's) approach with messy genetic algorithm (MGA). Markov Random Fields (MRFs) are a class of probabilistic models that have been applied for many years to the analysis of visual patterns or textures. Our objective is to establish MRFs as an interesting approach to modeling messy genetic algorithms. We establish a theoretical result that every genetic algorithm problem can be characterized in terms of a MRF model. This allows us to construct an explicit probabilistic model of the MGA fitness function and introduce the Ising MGA. Experimentations done with Ising MGA are less costly than those done with standard MGA since much less computations are involved. The least computations of all is for the LCP. Results of the LCP, random search, random seeded search, MGA, and Ising MGA are discussed.

Keywords: Filter design, FIR digital filters, LCP, Ising model, MGA, Ising MGA.

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Authors: Elnaz Lashgari, Emel Demircan

Abstract:

Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.

Keywords: Electrocardiogram, manifold learning, Laplacian Eigenmaps, running pattern.

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Authors: Mohamed Haffar, Ramdane Djebarni, Russell Evans

Abstract:

Despite a growth in literature on distributed leadership, the majority of studies are centred on large public organisations particularly within the health and education sectors. The purpose of this study is to fill the gap in the literature by exploring employee experiences of distributed leadership within two commercial consultancy SME businesses in the UK and USA. The aim of the study informed an exploratory method of research to gather qualitative data drawn from semi-structured interviews involving a sample of employees in each organisation. A series of broad, open questions were used to explore the employees’ experiences; evidence of distributed leadership; and extant barriers and practices in each organisation. Whilst some of our findings aligned with patterns and practices in the existing literature, it importantly discovered some emergent themes that have not previously been recognised in the previous studies. Our investigation identified that whilst distributed leadership was in evidence in both organisations, the interviewees’ experience reported that it was sporadic and inconsistent. Moreover, non-client focused projects were reported to be less important and distributed leadership was found to be inconsistent or non-existent.

Keywords: Consultancy, distributed leadership, owner-manager, SME, entrepreneur.

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