Search results for: features comparison

Authors: Siti Rafeah Md Rafei, Karen Wang Yanping, Park Mi Kyoung

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Tissue samples are precious supply for molecular studies or disease identification diagnosed using molecular assays, namely real-time PCR (qPCR). It is critical to establish the most favorable nucleic acid extraction that gives the PCR-amplifiable genomic DNA. Furthermore, automated nucleic acid extraction is an appealing alternative to labor-intensive manual methods. Operational complexity, defined as the number of steps required to obtain an extracted sample, is one of the criteria in the comparison. Here we are comparing the One BioMed’s automated X8 platform with the commercially available manual-operated kits from QIAGEN Mini Kit and Roche. We extracted DNA from rat fresh-frozen tissue (from different type of organs) in the matrices. After tissue pre-treatment, it is added to the One BioMed’s X8 pre-filled cartridge, and the QIAGEN QIAmp column respectively. We found that the results after subjecting the eluates to the Real Time PCR using BIORAD CFX are comparable.

Keywords: DNA extraction, frozen tissue, PCR, qPCR, rat

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Authors: Rana Daneshvar Salehi

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In many Iranian cities including ‎‎Mashhad‎, the capital of ‎‎‎‎Razavi Khorasan Province‏‎, ‎ordinary samples of domestic architecture ‎on a ‎‏small scale is not ‎‎‎considered as ‎heritage. ‎While the ‎principals of house formation are ‎‎respected in all ‎‎traditional Iranian ‎‎‎‎houses‎; ‎from moderate to great ones. During the past decade, Mashhad has lost its identity, and has become a modern city. Identifying it as the capital of the Islamic Culture in 2017 by ISESCO and consequently looking for new developments and transfiguration caused to demolish a large ‎number ‎of ‎traditional modest habitation. ‎For this ‎reason, the present paper aims to introduce ‎the three ‎undiscovered houses with the ‎historical and monumental values located in the ‎oldest ‎neighborhoods of Mashhad which have been neglected in the cultural ‎heritage field. The preliminary phase of this approach will be a measured survey to identify the significant characteristics ‎of ‎selected dwellings and understand the challenges through focusing on building ‎form, orientation, ‎‎room function, space proportion and ornamental elements’ details. A comparison between the ‎‎case studies and the wealthy domestically buildings ‎presents that a house belongs to inhabitants ‎with an average income could introduce the same accurate, regular, harmonic and proportionate ‎design which can be found in the great mansions. It reveals that an ordinary traditional house can ‎be regarded as valuable construction not only for its historical characteristics but also ‎for its ‎aesthetical and architectural features that could avoid further destructions in the future.

Keywords: traditional ordinary house, architectural characteristic, proportion, heritage

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Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe

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Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.

Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects

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Authors: Kazuko Sakamoto

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It is difficult to explain the factor of design preference only in culture or a geographical environment. It is necessary to turn one's eyes also to the factor in an individual. The purpose of this research is to clarify design potential which is inherent in consumers. Design potential is the consciousness and interpretation to an individual design. That is, it catches quantitatively the preparatory state which faces design. For example, a mobile phone differs in designs, such as a color and a form, by the country or the area. It is considered because a regional consumer taste exists. The root is design potential. This consists of design participation, design knowledge, and design sensitivity. Having focused this time is by design sensitivity, and international comparison of the Netherlands, Bangladesh, China, and Japan was performed. As a result, very interesting finding has been derived. For example, although Bangladesh caught the similarity of goods by the color, other three nations were caught in the form. Moreover, although the Netherlands, Bangladesh, and China liked symmetry, only Japan liked asymmetry. This shows that history and a cultural background have had big influence to the design.

Keywords: design-potential, cultural difference, form characteristic, product development

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Authors: Rezvan Hosseinian

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Aim: Systemic sclerosis (SSc) is a chronic connective tissue disease with the clinical hallmark of skin thickening and tethering. The correlation of musculoskeletal features with other parameters should be considered in SSc patients. Methods: We reviewed the records of all patients who had more than one visit and standard anteroposterior radiography of hand. We used univariate analysis, and factors with p<0.05 were included in logistic regression to find out dependent factors. Results: Overall, 180 SSc patients were enrolled in our study, 161 (89.4%) of whom were women. The median age (IQR) was 47.0 years (16), and 52% had a diffuse subtype of the disease. In multivariate analysis, tendon friction rubs (TFRs) were associated with the presence of calcinosis, muscle tenderness, and flexion contracture (FC) on physical examination (p<0.05). Arthritis showed no differences in the two subtypes of the disease (p=0.98), and in multivariate analysis, there were no correlations between radiographic arthritis and serological and clinical features. The radiographic results indicated that disease duration correlated with joint erosion, acro-osteolysis, resorption of the distal ulna, calcinosis and radiologic FC (p< 0.05). Acro-osteolysis was more frequent in the dcSSc subtype, TFRs, and anti-TOPO I antibody. Radiologic FC showed an association with skin score, calcinosis and haematocrit <30% (p<0.05). Joint flexion on radiography was associated with disease duration, modified Rodnan skin score, calcinosis, and low hematocrit (P<0.01). Conclusion: Disease duration was a main dependent factor for developing joint erosion, acro-osteolysis, bone resorption, calcinosis, and flexion contracture on hand radiography. Acro-osteolysis presented in the severe form of the disease. Acro-osteolysis was the only dependent variable associated with bone demineralization.

Keywords: disease subsets, hand radiography, joint erosion, sclerosis

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Authors: Nasrin Azarbani

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Aim: Systemic sclerosis (SSc) is a chronic connective tissue disease with the clinical hallmark of skin thickening and tethering. Correlation of musculoskeletal features with other parameters should be considered in SSc patients. Methods: We reviewed the records of all patients who had more than one visit and standard anteroposterior radiography of hand. We used univariate analysis, and factors with p<0.05 were included in logistic regression to find out dependent factors. Results: Overall, 180 SSc patients were enrolled in our study, 161 (89.4%) of whom were women. Median age (IQR) was 47.0 years (16), and 52% had diffuse subtype of the disease. In multivariate analysis, tendon friction rubs (TFRs) was associated with the presence of calcinosis, muscle tenderness, and flexion contracture (FC) on physical examination (p<0.05). Arthritis showed no differences in the two subtypes of the disease (p=0.98), and in multivariate analysis, there were no correlations between radiographic arthritis and serological and clinical features. The radiographic results indicated that disease duration correlated with joint erosion, acro-osteolysis, resorption of distal ulna, calcinosis and radiologic FC (p< 0.05). Acro-osteolysis was more frequent in the dcSSc subtype, TFRs, and anti-TOPO I antibody. Radiologic FC showed an association with skin score, calcinosis and haematocrit <30% (p<0.05). Joint flexion on radiography was associated with disease duration, modified Rodnan skin score, calcinosis, and low haematocrit (P<0.01). Conclusion: Disease duration was a main dependent factor for developing joint erosion, acro-osteolysis, bone resorption, calcinosis, and flexion contracture on hand radiography. Acro-osteolysis presented in the severe form of the disease. Acro-osteolysis was the only dependent variable associated with bone demineralization.

Keywords: sclerosis, disease subsets, joint erosion, musculoskeletal

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Authors: Shu-Min Tsao, Chung-Ming Lo, Shao-Chun Chen

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Most diabetes patients tend to suffer from its complication of retina diseases. Therefore, early detection and early treatment are important. In clinical examinations, using color fundus image was the most convenient and available examination method. According to the exudates appeared in the retinal image, the status of retina can be confirmed. However, the routine screening of diabetic retinopathy by color fundus images would bring time-consuming tasks to physicians. This study thus proposed a computer-aided exudate diagnosis for the screening of diabetic retinopathy. After removing vessels and optic disc in the retinal image, six quantitative features including region number, region area, and gray-scale values etc… were extracted from the remaining regions for classification. As results, all six features were evaluated to be statistically significant (p-value < 0.001). The accuracy of classifying the retinal images into normal and diabetic retinopathy achieved 82%. Based on this system, the clinical workload could be reduced. The examination procedure may also be improved to be more efficient.

Keywords: computer-aided diagnosis, diabetic retinopathy, exudate, image processing

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Authors: Giulia Leoni, Cristina Florio

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The paper aims to investigate the factors driving the increasing alignment of Italian earnings management (EM) research to US research on the same field. After characterizing the progressive similarity of Italian EM research with respect to US one by means of an historical comparison, the paper relies on a subsequent secondary source analysis to detect the possible causes of said alignment. Once identified that the alignment increased along three subsequent periods, the paper analyses and discusses this incremental similarity according to new institutional sociology (NIS) and highlights the presence of different combination of isomorphic pressures that help explaining this incremental similarity. The paper contributes to the institutional literature by providing evidence of isomorphism in academic research; it also contributes to accounting research by indicating the forces that are able to drive change and development in accounting research at national and international level. The paper also enlarges the explanatory value of NIS in alternative contexts, like academic accounting research.

Keywords: accounting research, earnings management, international comparison, Italy, new institutional sociology, US

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Authors: Javier A. Dominguez Caballero, Graeme A. Manson, Matthew B. Marshall

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Cutting tools with ceramic inserts are often used in the process of machining many types of superalloy, mainly due to their high strength and thermal resistance. Nevertheless, during the cutting process, the plastic flow wear generated in these inserts enhances and propagates cracks due to high temperature and high mechanical stress. This leads to a very variable failure of the cutting tool. This article explores the relationship between the continuous wear that ceramic SiAlON (solid solutions based on the Si3N4 structure) inserts experience during a high-speed machining process and the evolution of sparks created during the same process. These sparks were analysed through pictures of the cutting process recorded using an SLR camera. Features relating to the intensity and area of the cutting sparks were extracted from the individual pictures using image processing techniques. These features were then related to the ceramic insert’s crater wear area.

Keywords: ceramic cutting tools, high speed machining, image processing, tool condition monitoring, tool wear

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Authors: Rebecca J. Hafner, Daniel Read, David Elmes

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The current research applies decision making theory in order to address the problem of increasing uptake of energy-efficient technologies in the market place, where uptake is currently slower than one might predict following rational choice models. Specifically, in two studies we apply the alignable/non-alignable features effect and explore the impact of varying information structure on the consumers’ preference for standard versus energy efficient technologies. As researchers in the Interdisciplinary centre for Storage, Transformation and Upgrading of Thermal Energy (i-STUTE) are currently developing energy efficient heating systems for homes and businesses, we focus on the context of home heating choice, and compare preference for a standard condensing boiler versus an energy efficient heat pump, according to experimental manipulations in the structure of prior information. In Study 1, we find that people prefer stronger alignable features when options are similar; an effect which is mediated by an increased tendency to infer missing information is the same. Yet, in contrast to previous research, we find no effects of alignability on option preference when options differ. The advanced methodological approach used here, which is the first study of its kind to randomly allocate features as either alignable or non-alignable, highlights potential design effects in previous work. Study 2 is designed to explore the interaction between alignability and construal level as an explanation for the shift in attentional focus when options differ. Theoretical and applied implications for promoting energy efficient technologies are discussed.

Keywords: energy-efficient technologies, decision-making, alignability effects, construal level theory, CO2 reduction

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Authors: Yagya Raj Pandeya, Joonwhoan Lee

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The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.

Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean

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Authors: Wang Yanping Karen, Mohd Rafeah Siti, Park MI Kyoung

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Formalin-fixed paraffin embedded (FFPE) tissue is important in the area of oncological diagnostics. This method of preserving tissues enabling them to be stored easily at ambient temperature for a long time. This decreases the risk of losing the DNA quantity and quality after extraction, reducing sample wastage, and making FFPE more cost effective. However, extracting DNA from FFPE tissue is a challenge as DNA purified is often highly cross-linked, fragmented, and degraded. In addition, this causes problems for many downstream processes. In this study, there will be a comparison of DNA extraction efficiency between One BioMed’s Xceler8 automated platform with commercial available extraction kits (Qiagen and Roche). The FFPE tissue slices were subjected to deparaffinization process, pretreatment and then DNA extraction using the three mentioned platforms. The DNA quantity were determined with real-time PCR (BioRad CFX ) and gel electrophoresis. The amount of DNA extracted with the One BioMed’s X8 platform was found to be comparable with the other two manual extraction kits.

Keywords: DNA extraction, FFPE tissue, qiagen, roche, one biomed X8

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Authors: T. Bensana, S. Mekhilef

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The methodology of vibration based condition monitoring technology has been developing at a rapid stage in the recent years suiting to the maintenance of sophisticated and complicated machines. The ability of wavelet analysis to efficiently detect non-stationary, non-periodic, transient features of the vibration signal makes it a demanding tool for condition monitoring. This paper presents a methodology for fault diagnosis of rolling element bearings based on wavelet envelope power spectrum technique is analysed in both the time and frequency domains. In the time domain the auto-correlation of the wavelet de-noised signal is applied to evaluate the period of the fault pulses. However, in the frequency domain the wavelet envelope power spectrum has been used to identify the fault frequencies with the single sided complex Laplace wavelet as the mother wavelet function. Results show the superiority of the proposed method and its effectiveness in extracting fault features from the raw vibration signal.

Keywords: preventive maintenance, fault diagnostics, rolling element bearings, wavelet de-noising

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Authors: Umair Rashid

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Normally softmax loss is used as the supervision signal in face recognition (FR) system, and it boosts the separability of features. In the last two years, a number of techniques have been proposed by reformulating the original softmax loss to enhance the discriminating power of Deep Convolutional Neural Networks (DCNNs) for FR system. To learn angularly discriminative features Cosine-Margin based softmax has been adjusted as monotonically decreasing angular function, that is the main challenge for angular based softmax. On that issue, we propose monotonically decreasing element for Cosine-Margin based softmax and also, we discussed the effect of different monotonically decreasing parameters on angular Margin softmax for FR system. We train the model on publicly available dataset CASIA- WebFace via our proposed monotonically decreasing parameters for cosine function and the tests on YouTube Faces (YTF, Labeled Face in the Wild (LFW), VGGFace1 and VGGFace2 attain the state-of-the-art performance.

Keywords: deep convolutional neural networks, cosine margin face recognition, softmax loss, monotonically decreasing parameter

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Authors: Yang Yu, Jian Wang, Jiqiang Liu, Lei Han, Xudong He, Shaohua Lv

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As the increasing network attacks become more and more complex, network situation assessment based on log analysis cannot meet the requirements to ensure network security because of the low quality of logs and alerts. This paper addresses the lack of consideration of security attributes of hosts and attacks in the network. Identity and effectiveness of Distributed Denial of Service (DDoS) are hard to be proved in risk assessment based on alerts and flow matching. This paper proposes a multi-dimension threat situation assessment method based on network security attributes. First, the paper offers an improved Common Vulnerability Scoring System (CVSS) calculation, which includes confident risk, integrity risk, availability risk and a weighted risk. Second, the paper introduces deterioration rate of properties collected by sensors in hosts and network, which aimed at assessing the time and level of DDoS attacks. Third, the paper introduces distribution of asset value in security attributes considering features of attacks and network, which aimed at assessing and show the whole situation. Experiments demonstrate that the approach reflects effectiveness and level of DDoS attacks, and the result can show the primary threat in network and security requirement of network. Through comparison and analysis, the method reflects more in security requirement and security risk situation than traditional methods based on alert and flow analyzing.

Keywords: DDoS evaluation, improved CVSS, network security attribute, threat situation assessment

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

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Authors: Eda Jazexhiu-Postoli, Gladiola Hoxha, Ada Simeoni, Sonila Biba

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Background Neonatal hypotonia represents a commonly encountered issue in the Neonatal Intensive Care Unit and newborn nursery. The differential diagnosis is broad, encompassing chromosome abnormalities, primary muscular dystrophies, neuropathies and inborn errors of metabolism. Aim of study Our study describes some of the main clinical features of hypotonia in newborns and presents clinical cases of neonatal hypotonia we treated in our Neonatal unit in the last 3 years. Case reports Four neonates born in our hospital presented with hypotonia after birth, one preterm newborn 35-36 weeks of gestational age and three other term newborns (38-39 weeks of gestational age). Prenatal data revealed a decrease in fetal movements in both cases. Intrapartum meconium-stained amniotic fluid was found in 75% of our hypotonic newborns. Clinical features included inability to establish effective respiratory movements and need for resuscitation in the delivery room, respiratory distress syndrome, feeding difficulties and need for oro-gastric tube feeding, dysmorphic features, hoarse voice and moderate to severe muscular hypotonia. The genetic workup revealed the diagnosis of Autosomal Recessive Congenital Myasthenic Syndrome 1-B, Sotos Syndrome, Spinal Muscular Atrophy Type 1 and Transient Hypotonia of the Newborn. Two out of four hypotonic neonates were transferred to the Pediatric Intensive Care Unit and died at the age of three to five months old. Conclusion Hypotonia is a concerning finding in neonatal care and it is suggested by decreased intrauterine fetal movements, failure to establish first breaths, respiratory distress and feeding difficulties in the neonate. Prognosis is determined by its etiology and time of diagnosis and intervention.

Keywords: hypotonic neonate, respiratory distress, feeding difficulties, fetal movements

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Authors: Drissi Mokhtaria, Chouaih Abdelkader, Fodil Hamzaoui

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Our work is about a comparison of experimental and theoretical results of the electron charge density distribution and the electrostatic potential around the M-Nitrophenol Molecule (m-NPH) kwon for its interesting physical characteristics. The molecular experimental results have been obtained from a high-resolution X-ray diffraction study. Theoretical investigations were performed under the Gaussian program using the Density Functional Theory at B3LYP level of theory at 6-31G*. The multipolar model of Hansen and Coppens was used for the experimental electron charge density distribution around the molecule, while we used the DFT methods for the theoretical calculations. The electron charge density obtained in both methods allowed us to find out the different molecular properties such us the electrostatic potential and the dipole moment which were finally subject to a comparison leading to an outcome of a good matching results obtained in both methods.

Keywords: electron charge density, m-nitrophenol, nonlinear optical compound, electrostatic potential, optimized geometric

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Authors: Trude Tørset, María Díez Gutiérrez

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The west coast of Norway features numerous islands and fjords. Ferry services connect the roads when these features make the construction challenging. Currently, scientific effort is designated to assess potential ferry replacement projects along the European road E-39. The inconvenience of ferry dependency is imprecisely represented in the transport models, thus transport analyses of ferry replacement projects appear as guesstimates rather than reliable input to decision-making processes of such costly projects. Trips including ferry connections imply more inconvenient elements than just travel time and cost. The goal of this paper is to understand and explain the extra inconveniences associated to the dependency of the ferry. The first scientific approach is to identify the characteristics of the ferry travelers and their trips’ features, as well as whether the ferry represents an obstacle for some specific trip types. In doing so, a survey was conducted in 2011 in eight E-39 ferries and in 2013 in 18 ferries connecting different road categories. More than 20,000 passengers answered with their trip and socioeconomic characteristics. The travel patterns in the different ferry connections were compared. The analysis showed that the trip features differed based on the location of the ferry connections, yet independently of the road category. Additionally, the patterns were compared to the national travel survey to detect differences in the travel patterns due to the use of the ferry connections. The results showed that the share of commuting trips within the same travel time was lower if the ferry was part of the trip. The second scientific approach is to know how the different travelers perceive potential benefits for a ferry replacement project. In the 2011 survey, some of the questions were about the relevance of nine different benefits this project might bring. Travelers identified the better access to public services and job market as the most valuable benefits, followed by the reduced planning of the trip. In 2016, a follow-up survey in some of the ferry connections was carried out in order to investigate variations in travelers’ perceptions. The growing interest in ferry replacement projects might make travelers more aware of the potential benefits these would bring to their daily lives. This paper describes the travel behaviour of travelers using a ferry connection as part of their trips, as well as the potential inconveniences associated to these trips. The findings might provide valuable input to further development of transport models, concept evaluations and cost benefit analysis methods.

Keywords: ferry connections, ferry trip, inconvenience costs, travel behaviour

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Authors: Pradeepa Teegala, Ramreddy Chetteti

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This work emphasizes the effects of heat generation/absorption and Joule heating on chemically reacting micropolar fluid flow over a truncated cone with convective boundary condition. For this complex fluid flow problem, the similarity solution does not exist and hence using non-similarity transformations, the governing fluid flow equations along with related boundary conditions are transformed into a set of non-dimensional partial differential equations. Several authors have applied the spectral quasi-linearization method to solve the ordinary differential equations, but here the resulting nonlinear partial differential equations are solved for non-similarity solution by using a recently developed method called the spectral quasi-linearization method (SQLM). Comparison with previously published work on special cases of the problem is performed and found to be in excellent agreement. The influence of pertinent parameters namely Biot number, Joule heating, heat generation/absorption, chemical reaction, micropolar and magnetic field on physical quantities of the flow are displayed through graphs and the salient features are explored in detail. Further, the results are analyzed by comparing with two special cases, namely, vertical plate and full cone wherever possible.

Keywords: chemical reaction, convective boundary condition, joule heating, micropolar fluid, spectral quasilinearization method

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Authors: Mohammed Sherzad

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The Sahara desert covers third of the total surface of Africa with a quarter of this area within the national boundaries of Algeria. Sand drift and deposition is considered one of the major factors of the desertification process in the area. It is estimated that a third of the world's hot arid lands are covered by aeolian sand deposits, forming extensive sand bedforms. The Gourrara region in the Grand Erg Occidental (west of Algerian Sahara) and the region of Souf in the Grand Erg Oriental (east of Algerian Sahara) have been chosen as case studies. These were significant cultural and trading centers for many centuries despite their remote location and their harsh desert environment particularly solar radiation and sand drift and deposition. The architecture of the sustained vernacular settlements in each of the two regions has unique design features for this environment. So do the irrigation systems used - palm groves and the foggara system for capturing and distributing groundwater. However, the ecological balance which enabled the Saharans to live with the desert has been upset. New buildings often use technology based on models imported or imposed from areas that climatically have little in common. These make the inhabitants live ‘in the desert’ rather than ‘with the desert’. This paper will describe the qualities of the vernacular architecture and demonstrate its effectiveness and adaptability to the region’s harsh desert environment in comparison with contemporary buildings. Developing design guides and approaches based on lessons from the traditional architecture is important to ensure sustained livelihoods of the inhabitants in these areas.

Keywords: vernacular architecture, desert architecture, hot climate, aeolian sand deposition

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Authors: Anna Perrone, Federico Martinelli

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Olive fruit is well-known for the high content in secondary metabolites with high interest at nutritional, nutraceutical, antioxidant, and healthy levels. The content of secondary metabolites in olive at harvest may be affected by different water regimes, with significant effects on olive oil composition and quality and, consequently, on its healthy and nutritional features. In this work, a summary of several research studies dealing with the biosynthesis of healthy and nutraceutical metabolites of the secondary metabolism in olive fruit will be reported. The phytochemical findings have been correlated with the expression of key genes involved in polyphenol, terpenoid, and carotenoid biosynthesis and metabolism in response to different development stages and water regimes. Flavonoids were highest in immature fruits, while anthocyanins increased at ripening. In epicarp tissue, this was clearly associated with an up-regulation of the UFGT gene. Olive fruits cultivated under different water regimes were analyzed by metabolomics. This method identified several hundred metabolites in the ripe mesocarp. Among them, 46 were differentially accumulated in the comparison between rain-fed and irrigated conditions. Well-known healthy metabolites were more abundant at a higher level of water regimes. Increased content of polyphenols was observed in the rain-fed fruit; particularly, anthocyanin concentration was higher at ripening. Several secondary metabolites were differentially accumulated between different irrigation conditions. These results showed that these metabolic approaches could be efficiently used to determine the effects of agronomic treatments on olive fruit physiology and, consequently, on nutritional and healthy properties of the obtained extra-virgin olive oil.

Keywords: olea europea, anthocyanins, polyphenols, water regimes

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Authors: Saed Khawaldeh, Mohamed Elsharnouby, Alaa Eddin Alchalabi, Usama Pervaiz, Tajwar Aleef, Vu Hoang Minh

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Taxonomic classification has a wide-range of applications such as finding out more about the evolutionary history of organisms that can be done by making a comparison between species living now and species that lived in the past. This comparison can be made using different kinds of extracted species’ data which include DNA sequences. Compared to the estimated number of the organisms that nature harbours, humanity does not have a thorough comprehension of which specific species they all belong to, in spite of the significant development of science and scientific knowledge over many years. One of the methods that can be applied to extract information out of the study of organisms in this regard is to use the DNA sequence of a living organism as a marker, thus making it available to classify it into a taxonomy. The classification of living organisms can be done in many machine learning techniques including Neural Networks (NNs). In this study, DNA sequences classification is performed using Convolutional Neural Networks (CNNs) which is a special type of NNs.

Keywords: deep networks, convolutional neural networks, taxonomic classification, DNA sequences classification

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Authors: Saumya Srivastava, Rina Maiti

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In order to achieve a better performance of vehicle detection in a complex environment, we present an efficient approach for a multi-vehicle detection system using an adaptive sliding window technique. For a given frame, image segmentation is carried out to establish the region of interest. Gradient computation followed by thresholding, denoising, and morphological operations is performed to extract the binary search image. Near-region field and far-region field are defined to generate hypotheses using the adaptive sliding window technique on the resultant binary search image. For each vehicle candidate, features are extracted using a histogram of oriented gradients, and a pre-trained support vector machine is applied for hypothesis verification. Later, the Kalman filter is used for tracking the vanishing point. The experimental results show that the method is robust and effective on various roads and driving scenarios. The algorithm was tested on highways and urban roads in India.

Keywords: gradient, vehicle detection, histograms of oriented gradients, support vector machine

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Authors: Elnaz Lashgari, Emel Demircan

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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: electromyography, manifold learning, ISOMAP, Laplacian Eigenmaps, locally linear embedding

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Authors: Tsz Ching Jasmine Lam

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Linguistic landscape (LL) can serve as both top-down and bottom-up approaches to understanding language planning policy in various dimensions. It can reflect the language identities, motives and contestations perceived by stakeholders of different decision-making levels. Prior studies adopted the bottom-up approach to investigate the language practice and ideologies reflected by the design and linguistic features observed in the linguistic landscapes in ethnically and linguistically diverse areas, like Medan in Russia and Seoul in Korea. As Hong Kong is also a trilingual city with an inclusive combination of nationalities, this paper is intended to take it as a case study to explore the de facto language ideologies reflected by LL at the micro-level. We would look into the catering industry from a holistic perspective by reviewing the food menus of 66 restaurants located in diversified districts and serving different types of cuisines. This bottom-up LL research reveals that business owners and the public share the language ideologies of perceiving English as a prestigious language, multilingualism and traditional Chinese as a standard character.

Keywords: bottom-up, language ideologies, language planning policy, language policy, language identities, linguistic landscape

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Authors: Musaab Salman Sultan

Abstract:

The surface and bulk magnetization behavior of template released isolated ferromagnetic Ni₆₀Fe₄₀ nanowires of relatively thick diameters (~200 nm), deposited from a dilute suspension onto pre-patterned insulating chips have been investigated experimentally, using a highly sensitive Magneto-Optical Ker Effect (MOKE) magnetometry and Magneto-Resistance (MR) measurements, respectively. The MR data were consistent with the theoretical predictions of the anisotropic magneto-resistance (AMR) effect. The MR measurements, in all the angles of investigations, showed large features and a series of nonmonotonic "continuous small features" in the resistance profiles. The extracted switching fields from these features and from MOKE loops were compared with each other and with the switching fields reported in the literature that adopted the same analytical techniques on the similar compositions and dimensions of nanowires. A large difference between MOKE and MR measurments was noticed. The disparate between MOKE and MR results is attributed to the variance in the micro-magnetic structure of the surface and the bulk of such ferromagnetic nanowires. This result was ascertained using micro-magnetic simulations on an individual: cylindrical and rectangular cross sections NiFe nanowires, with the same diameter/thickness of the experimental wires, using the Object Oriented Micro-magnetic Framework (OOMMF) package where the simulated loops showed different switching events, indicating that such wires have different magnetic states in the reversal process and the micro-magnetic spin structures during switching behavior was complicated. These results further supported the difference between surface and bulk magnetization behavior in these nanowires. This work suggests that a combination of MOKE and MR measurements is required to fully understand the magnetization behavior of such relatively thick isolated cylindrical ferromagnetic nanowires.

Keywords: MOKE magnetometry, MR measurements, OOMMF package, micromagnetic simulations, ferromagnetic nanowires, surface magnetic properties

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Authors: Artur Daniel Ramos Modolo

Abstract:

Popular science magazines are an important way to communicate scientific information to lay audience in science. Since the popularization of social networking sites (SNSs) such as Facebook and Twitter, these magazines are trying to adapt their content to these new media. In this study, one hundred posts of popular science magazines on Facebook are analyzed regarding the use of genres of communication and readers’ reactions. The quantitative analysis of these features considers the variety of genres and how the users of Facebook answer to them (liking, sharing and commenting). The first hypothesis was that these magazines used the genres of communication posted on Facebook both to marketing and informational purposes and that these mixed intentions have an impact in the number of readers’ reactions. In order to analyze these features, twenty timeline posts published by five magazines: Cosmos, Galileu, New Scientist, Scientific American and Superinteressante were gathered during the period of three days (6th November 2015–8th November 2015). This research shows that the hyperlinks posted by these magazines created ways to diversify the communication genres used on their pages and, at the same time, revealed that, overall, readers react quantitatively different to these genres.

Keywords: Facebook, genres of communication, likes, popular science magazines, social networking sites

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Authors: Ryotaro Ishikawa

Abstract:

Obsessive-Compulsive Disorder (OCD) is a common, chronic and long-lasting disorder in which a person has uncontrollable, reoccurring thoughts (obsessions) and behaviors (compulsions) that he or she feels the urge to repeat over and over. Inflated responsibility attitude and interpretation are central beliefs in a cognitive model of OCD. This study aimed to develop a Japanese version of the Responsibility Attitude Scale (RAS-J) and Responsibility Interpretation Questionnaire (RIQ-J). 98 participants (OCD group = 37; anxiety control group = 24; healthy control group = 37) completed the RAS-J, RIQ-J and other measures to assess the validity of the RAS-J and RIQ-J. As a result of analysis, both scales had adequate concurrent validity, demonstrated by significant correlations with other measures of OCD, anxiety, and depression. Group comparison data using ANOVA with Bonferroni method indicated that RAS-J and RIQ-J scores for the OCD group not only differed from the nonclinical group, but also from the clinically anxious comparison group. In conclusion, this study indicated that the developed RAS-J and RIQ-J effectively measure responsibility attitude and responsibility interpretation in the Japanese population.

Keywords: obsessive-compulsive disorder, responsibility, cognitive theory, anxiety disorder

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Authors: Zakaria Aketouane, Mustapha Malha, Abdellah Bah, Omar Ansari, Mohamed Asbik

Abstract:

The present paper deals with the thermal performance of a hollow-brick filled with Phase Change Material (PCM). The main objective is to study the effect of percentage and melting temperature of the PCM on the thermal inertia and internal surface temperature of the hollow-brick. A numerical model based on the heat transfer equation and the apparent heat capacity method has been validated using experimental study from the literature. The results show that increasing the percentage of the PCM has a significant effect on time lag and decrement factor that define the thermal inertia; the internal temperature is reduced by 1.36°C to 5.39°C for a percentage from 11% to 71% in comparison to a brick without PCM. In addition, an appropriate melting temperature of 37°C has been deduced for the horizontal wall orientation in Rabat in comparison to 27°C and 47°C.

Keywords: appropriate melting temperature, decrement factor, phase change material, thermal inertia, time lag

Procedia PDF Downloads 217