Search results for: Images in Performances

Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

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Authors: Kapila Warnakulasuriya, Walimuni Janaka Mendis

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In this study, an artificial intelligence-based approach is developed to diagnose abnormal tissues in human or animal bodies by analyzing magnetic resonance signals. As opposed to the conventional method of generating an image from the magnetic resonance signals, which are then evaluated by a radiologist for the diagnosis of abnormalities, in the discussed approach, the magnetic resonance signals are analyzed by an artificial intelligence algorithm without having to generate or analyze an image. The AI-based program compares magnetic resonance signals with millions of possible magnetic resonance waveforms which can be generated from various types of normal tissues. Waveforms generated by abnormal tissues are then identified, and images of the abnormal tissues are generated with the possible location of them in the body for further diagnostic tests.

Keywords: magnetic resonance, artificial intelligence, magnetic waveform analysis, abnormal tissues

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Authors: Dinku Seyoum Zeleke, Rong Fung Huang, Ching Min Hsu

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Comparison of flow and mixing characteristics between non-oscillating jet and transversely oscillating jet was investigated experimentally. Flow evolution process was detected by using high-speed digital camera, and jet spread width was calculated using binary edge detection techniques by using the long-exposure images. The velocity characteristics of transversely oscillating jet induced by a V-shaped fluidic oscillator were measured using single component hot-wire anemometer. The jet spread width of non-oscillating jet was much smaller than the jet exit gap because of behaving natural jet behaviors. However, the transversely oscillating jet has a larger jet spread width, which was associated with the excitation of the flow by self-induced oscillation. As a result, the flow mixing characteristics desperately improved both near-field and far-field. Therefore, this transversely oscillating jet has a better turbulence intensity, entrainment, and spreading width so that it augments flow-mixing characteristics desperately.

Keywords: flow mixing, transversely oscillating, spreading width, velocity characteristics

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Authors: Rita A. Sunday-Kanu

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This article reports on an evaluation of lunch hour concert and its effectiveness in improving undergraduate performance ability. In particular, it examines the aptitude of students in classroom applied music and their reaction/responses to true life concert situations. It further investigated factors affecting students’ confidence during performances, the relationship between stage fright and confidence building in regular concert participation. The Department of Music, University of Port Harcourt runs monthly lunch our concerts which are coordinated by undergraduates for the university community. Forty music students who have participated in or coordinated lunch hour concerts were chosen for this survey. Eight music lecturers who have supervised the monthly lunch hour concert were also chosen for this study. The attitude and view on the effectiveness of lunch hour concert in enhancing students’ performance skills were gotten through questionnaires survey, in-depth interview and participant observation to determine if classroom based applied music alone is as successful in grooming performance genius as the lunch hour concert. Result indicated that students’ participation in lunch hour concert did indeed broaden and strengthened their performance experiences. This observation led to a recommendation that regular community based concerts be considered as a standard for performance practices in the university curriculum since it serves as a preparatory platform for acquiring professional performance skills before graduation.

Keywords: lunch hour concert, performance, performing skill, community concert

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Authors: Menouar Hanafi

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The original function of the process of platforming is to develop heavy naphtha (HSRN), coming from the atmospheric unit of distillation with a weak octane number (NO=44), to obtain a mixture of fuels â number octane raised by catalytically supporting specific groups of chemical reactions. The installation is divided into two sections: Section hydrobon. Section platforming. The rafinat coming from the bottom of column 12C2 to feed the section platforming, is divided into two parts whose flows are controlled and mixed with gas rich in hydrogen. Bottom of the column, we obtain stabilized reformat which is aspired by there pump to ensure the heating of the column whereas a part is sent towards storage after being cooled by the air cooler and the condenser. In catalytic catalyst of reforming, there is voluntarily associated a hydrogenating function-dehydrogenating, brought by platinum deposited, with an acid function brought by the alumina support (Al 2 0 3). The mechanism of action of this bifunctional catalyst depends on the severity of the operation, of the quality of the load and the type of catalyst. The catalyst used in the catalytic process of reforming is a very elaborate bifunctional catalyst whose performances are constantly improved thanks to the experimental research supported on an increasingly large comprehension of the phenomena. The American company Universel 0i1 petroleum (UOP) marketed several series of bimetallic catalysts such as R16, R20, R30, and R62 consisted Platinum/Rhenium on an acid support consisted the alumina added with a halogenous compound (chlorine).

Keywords: platforming, amelioration, octane number, catalyst

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Authors: Mahyar Maali, Merve Sagiroglu

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Steel, which is one of the base materials we prefer in the building construction, is the material with the highest ratio to weight of carrying capacity. Due to the carrying capacity, lighter and better quality steel in smaller sections and sizes has recently been used as a frame system in cold-formed steel structures. While light steel elements used as secondary frame elements during the past, they have nowadays started to be preferred as the main frame in low/middle story buildings and detached houses with advantages such as quick and easy installation, time-saving, and small amount of scrap. It is also economically ideal because the weight of structure is lighter than other steel profiles. Structural performances and failure modes of cold-formed structures are different from conventional ones due to their thin-walled structures. One of the most important elements of light steel structures to ensure stability is the connection. The screwed connections, which have self-drilling properties with special drilling tools, are widely used in the installation of cold-formed profiles. The length of the screw is selected according to the total thickness of the elements after the screw thickness is determined according to the elements of connections. The thickness of the material depends on the length of the drilling portion at the end of the screw. The shear tests of plates connected with self-drilling screws are carried out depending on the screw length, and their failure modes were evaluated in this study.

Keywords: cold-formed steel, screwed connection, connection, screw length

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Authors: Andrea Bellucci, Martina Tofi

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The aim of paper is to analyze business models of bancassurance in Italy for life business. The life insurance business is very developed in the Italian market and banks branches have 80% of the market share. Given its maturity, the life insurance market needs to consolidate its organizational form to allow for the development of non-life business, which nowadays collects few premiums but represents a great opportunity to enlarge the market share of bancassurance using its strength in the distribution channel while the market share of independent agents is decreasing. Starting with the main business model of bancassurance for life business, this paper will analyze the performances of life companies in the Italian market by balance sheet indicators and by main discriminant variables of business models. The study will observe trends from 2013 to 2015 for the Italian market by exploiting a database managed by Associazione Nazionale delle Imprese di Assicurazione (ANIA). The applied approach is based on a bottom-up analysis starting with variables and indicators to define business models’ classification. The statistical classification algorithm proposed by Ward is employed to design business models’ profiles. Results from the analysis will be a representation of the main business models built by their profile related to indicators. In that way, an unsupervised analysis is developed that has the limit of its judgmental dimension based on research opinion, but it is possible to obtain a design of effective business models.

Keywords: bancassurance, business model, non life bancassurance, insurance business value drivers

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Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

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Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

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Authors: Elmira Fotoohi

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Representation of women in commercials and the place of sex in advertising is a part of communication studies and all of them are subset of advertising sociology. In this context, a lot of national and international studies have been done from different aspects. But in the meantime, and in connection with women issues, researchers in Communication Science and Sociology are interested in two topics “use of pornographic images of women” and “repeated representations of women in traditional roles and gender stereotypes by emphasizing the differences between men and women”, more than any other topics. Considering a number of changes that have occurred in social institutions and at different levels, the main research question currently are, what is the role of women in our TV ads and how are they represented in them? Do the local television ads represent women in the same issues as the researchers on this topic has proposed or new changes have occurred? Many scholars and thinkers in the field of media outlet that, today, media not just focus on women as gender issues or sex objects, but also seeks to strengthen the gender division of labor in the family and emphasize on the traditional muliebrity and masculinity stereotype.

Keywords: women, representation, tv commercials, advertising sociology, gender stereotypes

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Authors: Craig Mertens

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Teaching art history or any other academic subject to EFL students can be done successfully. A course called Western Images was created to teach Japanese students art history while only using English in the classroom. An approach known as Content and Language Integrated Learning (CLIL) was used as a basis for this course. This paper’s purpose is to state the reasons why learning about art history is important, go through the process of creating content for the course, and suggest multiple tasks to help students practice the critical thinking skills used in analyzing and drawing conclusions of works of art from western culture. As a guide for this paper, Brown’s (1995) six elements of a language curriculum will be used. These stages include needs analysis, goals and objectives, assessment, materials, teaching method and tasks, and evaluation of the course. The goal here is to inspire debate and discussion regarding CLIL and its pros and cons, and to question current curriculum in university language courses.

Keywords: art history, EFL, content and language integration learning, critical thinking

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Authors: J. T. Pitale, S. Ghassab, H. Ay, N. Berme

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Biomechanics researchers commonly use marker-based optical motion capture (MoCap) systems to extract human body kinematic data. These systems use cameras to detect passive or active markers placed on the subject. The cameras use triangulation methods to form images of the markers, which typically require each marker to be visible by at least two cameras simultaneously. Cameras in a conventional optical MoCap system are mounted at a distance from the subject, typically on walls, ceiling as well as fixed or adjustable frame structures. To accommodate for space constraints and as portable force measurement systems are getting popular, there is a need for smaller and smaller capture volumes. When the efficacy of a MoCap system is investigated, it is important to consider the tradeoff amongst the camera distance from subject, pixel density, and the field of view (FOV). If cameras are mounted relatively close to a subject, the area corresponding to each pixel reduces, thus increasing the image resolution. However, the cross section of the capture volume also decreases, causing reduction of the visible area. Due to this reduction, additional cameras may be required in such applications. On the other hand, mounting cameras relatively far from the subject increases the visible area but reduces the image quality. The goal of this study was to develop a quantitative methodology to investigate marker occlusions and optimize camera placement for a given capture volume and subject postures using three-dimension computer-aided design (CAD) tools. We modeled a 4.9m x 3.7m x 2.4m (LxWxH) MoCap volume and designed a mounting structure for cameras using SOLIDWORKS (Dassault Systems, MA, USA). The FOV was used to generate the capture volume for each camera placed on the structure. A human body model with configurable posture was placed at the center of the capture volume on CAD environment. We studied three postures; initial contact, mid-stance, and early swing. The human body CAD model was adjusted for each posture based on the range of joint angles. Markers were attached to the model to enable a full body capture. The cameras were placed around the capture volume at a maximum distance of 2.7m from the subject. We used the Camera View feature in SOLIDWORKS to generate images of the subject as seen by each camera and the number of markers visible to each camera was tabulated. The approach presented in this study provides a quantitative method to investigate the efficacy and efficiency of a MoCap camera setup. This approach enables optimization of a camera setup through adjusting the position and orientation of cameras on the CAD environment and quantifying marker visibility. It is also possible to compare different camera setup options on the same quantitative basis. The flexibility of the CAD environment enables accurate representation of the capture volume, including any objects that may cause obstructions between the subject and the cameras. With this approach, it is possible to compare different camera placement options to each other, as well as optimize a given camera setup based on quantitative results.

Keywords: motion capture, cameras, biomechanics, gait analysis

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Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other. As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO

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Authors: Jiahe Liu, Hongyang Yu, Miao Luo, Feng Qian

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The widespread application of 3D human body reconstruction spans various fields. Smplify-X, an algorithm reliant on single-image input, employs three distinct body parameter templates, necessitating gender classification of individuals within the input image. Researchers employed a ResNet18 network to train a gender classifier within the Smplify-X framework, setting the threshold at 0.9, designating images falling below this threshold as having neutral gender. This model achieved 62.38% accurate predictions and 7.54% incorrect predictions. Our improvement involved refining the MobileNet network, resulting in a raised threshold of 0.97. Consequently, we attained 78.89% accurate predictions and a mere 0.2% incorrect predictions, markedly enhancing prediction precision and enabling more precise 3D human body reconstruction.

Keywords: SMPLX, mobileNet, gender classification, 3D human reconstruction

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Authors: Yessi Rahmawati, Andiga Kusuma Nur Ichsan, Fitria Nur Anggraeni

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Climate change is one of the focus studies that many researchers focus on in the present world, either in the emerging countries or developed countries which is one of the main pillars on Sustainable Development Goals (SDGs). There is on-going discussion that climate change can affect natural disaster, namely drought, storm, flood, and many others; and also the impact on human life. East Java is the best performances and has economic potential that should be utilized. Despite the economic performance and high agriculture productivity, East Java has the highest number of people under the poverty line. The present study is to measuring the contribution of drought and productivity of agriculture to the poverty in East Java, Indonesia, using spatial econometrics analysis. The authors collect data from 2008 – 2015 from Indonesia’s Ministry of Agriculture, Natural Disaster Management Agency (BNPB), and Official Statistic (BPS). First, the result shows the existence of spatial autocorrelation between drought and poverty. Second, the present research confirms that there is strong relationship between drought and poverty. the majority of farmer in East Java are still relies on the rainfall and traditional irrigation system. When the drought strikes, mostly the farmer will lose their income; make them become more vulnerable household, and trap them into poverty line. The present research will give empirical studies regarding drought and poverty in the academics world.

Keywords: SDGs, drought, poverty, Indonesia, spatial econometrics, spatial autocorrelation

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Authors: André Smith, Amr Abdel-Dayem

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The stereo matching problem, while having been present for several decades, continues to be an active area of research. The goal of this research is to find correspondences between elements found in a set of stereoscopic images. With these pairings, it is possible to infer the distance of objects within a scene, relative to the observer. Advancements in this field have led to experimentations with various techniques, from graph-cut energy minimization to artificial neural networks. At the basis of these techniques is a cost function, which is used to evaluate the likelihood of a particular match between points in each image. While at its core, the cost is based on comparing the image pixel data; there is a general lack of consistency as to what image data representation to use. This paper presents an experimental analysis to compare the effectiveness of more common image data representations. The goal is to determine the effectiveness of these data representations to reduce the cost for the correct correspondence relative to other possible matches.

Keywords: colour data, local stereo matching, stereo correspondence, disparity map

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Authors: Walid Abdallah, Noureddine Boudriga

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Wireless sensor networks have shown their effectiveness in the deployment of many critical applications especially in the military domain. Border surveillance is one of these applications where a set of wireless sensors are deployed along a country border line to detect illegal intrusion attempts to the national territory and report this to a control center to undergo the necessary measures. Regarding its nature, this wireless sensor network can be the target of many security attacks trying to compromise its normal operation. Particularly, in this application the deployment and location of sensor nodes are of great importance for detecting and tracking intruders. This paper proposes a location-based authentication and key distribution mechanism to secure wireless sensor networks intended for border surveillance where the key establishment is performed using elliptic curve cryptography and identity-based public key scheme. In this scheme, the public key of each sensor node will be authenticated by keys that depend on its position in the monitored area. Before establishing a pairwise key between two nodes, each one of them must verify the neighborhood location of the other node using a message authentication code (MAC) calculated on the corresponding public key and keys derived from encrypted beacon messages broadcast by anchor nodes. We show that our proposed public key authentication and key distribution scheme is more resilient to node capture and node replication attacks than currently available schemes. Also, the achievement of the key distribution between nodes in our scheme generates less communication overhead and hence increases network performances.

Keywords: wireless sensor networks, border surveillance, security, key distribution, location-based

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Authors: Ayyaz Hussain, Tariq Sadad

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Breast cancer (BC) is one of the widespread ailments among females globally. The early prognosis of BC can decrease the mortality rate. Exact findings of benign tumors can avoid unnecessary biopsies and further treatments of patients under investigation. However, due to variations in images, it is a tough job to isolate cancerous cases from normal and benign ones. The machine learning technique is widely employed in the classification of BC pattern and prognosis. In this research, a deep convolution neural network (DCNN) called AlexNet architecture is employed to get more discriminative features from breast tissues. To achieve higher accuracy, K-nearest neighbor (KNN) classifiers are employed as a substitute for the softmax layer in deep learning. The proposed model is tested on a widely used breast image database called MIAS dataset for experimental purposes and achieved 99% accuracy.

Keywords: breast cancer, DCNN, KNN, mammography

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Authors: Seyedeh Azadeh Johari

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For thousand years, the literature of the world has been mostly composed of men, and in all different forms of it, men have tried to propose their masculine desires, ideologies, and beliefs. What has been less written about or studied, however, was the role that female desire plays in the predominantly masculine society, and mostly the role of male desires was the key point in literature. Male writers have mostly shown their female characters either as stereotypes and void of dynamic characters, images of a meek person who bent to the will of her male superiors or as wicked or villains. The only exception was the kind of strong and courageous women who have mostly been masculinized by their authors, mostly male authors, as showing the valuable or important features of men, instead of women’s. These characters are transgendered by the author and have a gender identity or expression that differs from the sex to which they were assigned. This is the issue that is discussed in this project. We will refer to some examples of female characters who show masculine traits and characteristics.

Keywords: comparative literature, female, masculinized, transgendered

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Authors: Omer Faruk Sarioglu, Asli Celebioglu, Turgay Tekinay, Tamer Uyar

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Fibrous biocomposites were developed by immobilization of a Cr(VI) reducing bacterial strain, morganella morganii STB5, on electrospun polystyrene (PS) and polysulfone (PSU) webs. Cr(VI) removal characteristics of STB5/PS and STB5/PSU fibrous biocomposites were determined at 25 mg L-1 of initial Cr(VI) and 70.41% and 68.27% of removal were observed within 72 h, respectively. Reusability test results indicate that both biocomposites are potentially reusable and can be used for at least 5 cycles. After storage test results suggest that the biocomposites can be stored awhile without losing their Cr(VI) bioremoval capabilities. SEM images of STB5 immobilized PS and PSU webs after the reusability test exhibit strong attachment of bacterial biofilms onto fibrous surfaces. Our results are quite promising and suggesting that reusable bacteria immobilized electrospun fibrous biocomposites might be applicable for Cr(VI) remediation in water systems.

Keywords: electrospinning, polystyrene, polysulfone, Cr(VI) bioremoval, environmental sustainability

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Authors: I. Slim, H. Akkari, A. Ben Abdallah, I. Bhouri, M. Hedi Bedoui

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Osteoporosis is a common disease characterized by low bone mass and deterioration of micro-architectural bone tissue, which provokes an increased risk of fracture. This work treats the texture characterization of trabecular bone radiographs. The aim was to analyze according to clinical research a group of 174 subjects: 87 osteoporotic patients (OP) with various bone fracture types and 87 control cases (CC). To characterize osteoporosis, Fractal and MultiFractal (MF) methods were applied to images for features (attributes) extraction. In order to improve the results, a new method of MF spectrum based on the q-stucture function calculation was proposed and a combination of Fractal and MF attributes was used. The Support Vector Machines (SVM) was applied as a classifier to distinguish between OP patients and CC subjects. The features fusion (fractal and MF) allowed a good discrimination between the two groups with an accuracy rate of 96.22%.

Keywords: fractal, micro-architecture analysis, multifractal, osteoporosis, SVM

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Authors: Areerut Jaipadub

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The purpose of this research is to analyze the pattern of television commercials and how they encourage non-governmental organizations to build their image in Thailand. It realizes how public relations can impact an organization's image. It is a truth that bad public relations management can cause hurt a reputation. On the other hand, a very small amount of work in public relations helps your organization to be recognized broadly and eventually accepted even wider. The main idea in this paper is to study and analyze patterns of television commercials that could impact non-governmental organization's images in a greater way. This research uses questionnaires and content analysis to summarize results. The findings show the aspects of how patterns of television commercials that are suited to non-governmental organization work in Thailand. It will be useful for any non-governmental organization that wishes to build their image through television commercials and also for further work based on this research.

Keywords: television commercial (TVC), organization image, non-governmental organization (NGO), public relation

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Authors: Husham Mahmood Ahmed

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For so many reasons, fresh water scarcity is one of major problems facing the world and in particularly in the third world in the Northern Africa, the Middle East, the Southwest of Asia, and many other desert areas. Solar distillation offers one of the most promising solutions of renewable energy to this aggravated situation. The main obstacle hindering the spread of the use of solar technology for fresh water production is its low efficiency. Therefore, enhancing the solar stills performances by studying the parameters affecting their productivity and implementing new ideas and a different design are the main goals of the investigators in recent years. The present research is experimental work that tests a new design of solar still with a hemispherical top cover for water desalination with and without external reflectors under the climate of the Kingdom of Bahrain during the autumn season. The hemispherical cover has a base diameter of 1m and a depth of 0.4m, die cast from a 6 mm thick Lexan plastic sheet. The net effective area was 0.785 m2. It has been found that the average daily production rate obtained from the hemispherical top cover solar still is 3.610 liter/day. This yield is 11.1% higher than the yield of a conventional simple type single slope solar still having 20ᴼ slope glass cover and a larger effective area of 1 m2 obtained in previous research under similar climatic conditions. It has also been found that adding 1.2m long by 0.15 curved reflectors increased the yield of the hemispherical solar still by 5.5 %, while the 1.2 long by 0.3m curved reflector increased the yield by about 8%.

Keywords: hemispherical solar still, solar desalination, solar energy, the Northern Africa

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Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

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In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets

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Authors: Masoud Rabbani, Majede Smizadeh, Hamed Farrokhi-Asl

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We study jointly determining prices and production in a multiple period horizon under a general non-stationary stochastic demand with continuous prices. In some periods we need to increase capacity of production to satisfy demand. This paper presents a model to aid multi-period production capacity planning by quantifying the trade-off between product quality and production cost. The product quality is estimated as the statistical variation from the target performances obtained from the output tolerances of the production machines that manufacture the components. We consider different tolerance for different machines that use to increase capacity. The production cost is estimated as the total cost of owning and operating a production facility during the planning horizon.so capacity planning has cost that impact on price. Pricing products often turns out to be difficult to measure them because customers have a reservation price to pay that impact on price and demand. We decide to determine prices and production for periods after enhance capacity and consider reservation price to determine price. First we use an algorithm base on fuzzy set of the optimal objective function values to determine capacity planning by determine maximize interval from upper bound in minimum objectives and define weight for objectives. Then we try to determine inventory and pricing policies. We can use a lemma to solve a problem in MATLAB and find exact answer.

Keywords: price policy, inventory policy, capacity planning, product quality, epsilon -constraint

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Authors: Mauricio George Miguel Jardini, Jose Antonio Jardini

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Transmission power utilities participate with kilometers of circuits, many with particularities in terms of vegetation growth. To control these rights-of-way, maintenance teams perform ground, and air inspections, and the identification method is subjective (indirect). On a ground inspection, when identifying an irregularity, for example, high vegetation threatening contact with the conductor cable, pruning or suppression is performed immediately. In an aerial inspection, the suppression team is mobilized to the identified point. This work investigates the use of 3D modeling of a transmission line segment using RGB (red, blue, and green) images and LiDAR (Light Detection and Ranging) sensor data. Both sensors are coupled to unmanned aerial vehicle. The goal is the accurate and timely detection of vegetation along the right-of-way that can cause shutdowns.

Keywords: 3D modeling, LiDAR, right-of-way, transmission lines, vegetation

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Authors: Sujith Rajashekar Swamy, Meghana Rajashekara Swamy

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Although T1-weighted gadolinium-enhanced imaging (T1-Gd) has its established clinical role in diagnosing brain lesions of infectious and metastatic origins, the use of post-contrast susceptibility-weighted imaging (SWI) has been understudied. This observational study aims to explore and compare the prominence of brain parenchymal lesions between T1-Gd and SWI-Gd images. A cross-sectional study design was utilized to analyze 58 patients with brain parenchymal lesions using T1-Gd and SWI-Gd scanning techniques. Our results indicated that SWI-Gd enhanced the conspicuity of metastatic as well as infectious brain lesions when compared to T1-Gd. Consequently, it can be used as an adjunct to T1-Gd for post-contrast imaging, thereby avoiding additional contrast administration. Improved conspicuity of brain lesions translates directly to enhanced patient outcomes, and hence SWI-Gd imaging proves useful to meet that endpoint.

Keywords: susceptibility weighted, T1 weighted, brain lesions, gadolinium contrast

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Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

Abstract:

Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

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Authors: Iyabo Aremu

Abstract:

The role of the teacher in stirring a qualitative and distinctive knowledge-driven and value-laden environment with modern teaching practices cannot be over accentuated. In spite of the myriad advantages the use of Information and Communication Technology (ICT) promises, many teachers are still at the rear of this archetypical transition. These teachers; notable forces needed to elicit positive academic performances of students of higher learning are ill-equipped for the task. In view of this, the research work sought to assess how teachers have been able to effectively apply ICT tools to improve students’ academic performance in the higher institution and to evaluate the challenges faced by teachers in using these tools. Thus, the research adopted descriptive survey research design and involved a sample of 25 lecturers from five schools in the study area: Adeniran Ogunsanya College of Education (AOCOED). The barrier to Teachers’ Use of ICT Questionnaire (BTUICTQ) was used to gather data from these respondents. The data gathered was tested with chi-square at 0.05 level of significance. The results revealed that the perception and attitude of teachers towards the use of ICT is not favourable. It was also discovered that teachers suffer from gaps in ICT knowledge and skills. Finally, the research showed that lack of training and inadequate support is a major challenge teacher contend with. The study recommended that teachers should be given adequate training and support and that teachers’ unrestricted access to ICT gadgets should be ensured by schools.

Keywords: ICT, teachers, AOCOED, academic performance

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Authors: Ujjal Chattaraj, P. C. Dasbebartta, S. Bhuyan

Abstract:

This paper aims to propose a method to detect the action of the driver’s eyes, using the concept of face detection. There are three major key contributing methods which can rapidly process the framework of the facial image and hence produce results which further can program the reactions of the vehicles as pre-programmed for the traffic safety. This paper compares and analyses the methods on the basis of their reaction time and their ability to deal with fluctuating images of the driver. The program used in this study is simple and efficient, built using the AdaBoost learning algorithm. Through this program, the system would be able to discard background regions and focus on the face-like regions. The results are analyzed on a common computer which makes it feasible for the end users. The application domain of this experiment is quite wide, such as detection of drowsiness or influence of alcohols in drivers or detection for the case of identification.

Keywords: AdaBoost learning algorithm, face detection, framework, traffic safety

Procedia PDF Downloads 157

Authors: Kuay Hue San, Muaz Haqim Shaharum, Nasir Yusoff

Abstract:

Gender plays a big role in psychosocial development. This study aimed to investigate whether gender moderates the relationship between moral identity (internalization and symbolization) and risk-smoking behavior. An online cross-sectional study was carried out on 388 (61% female) youths who fulfilled the study’s inclusion and exclusion criteria. While viewing images of smoking behavior, participants rated their emotional state, which ranged from unpleasant to pleasant. Participants were also asked to fill out the eight-item Moral Identity Scale and provide their socio-demographic information. Gender significantly moderated the relationship between symbolization and smoking behavior. However, the moderation effect was not shown by internalization Finding highlights the implication of gender on moral identity and smoking behavior and the importance of considering this in the public health intervention and program.

Keywords: smoking behaviour, gender, emotion, moral identity

Procedia PDF Downloads 107