Search results for: inherent feature
1394 Black-Box-Base Generic Perturbation Generation Method under Salient Graphs
Authors: Dingyang Hu, Dan Liu
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DNN (Deep Neural Network) deep learning models are widely used in classification, prediction, and other task scenarios. To address the difficulties of generic adversarial perturbation generation for deep learning models under black-box conditions, a generic adversarial ingestion generation method based on a saliency map (CJsp) is proposed to obtain salient image regions by counting the factors that influence the input features of an image on the output results. This method can be understood as a saliency map attack algorithm to obtain false classification results by reducing the weights of salient feature points. Experiments also demonstrate that this method can obtain a high success rate of migration attacks and is a batch adversarial sample generation method.Keywords: adversarial sample, gradient, probability, black box
Procedia PDF Downloads 881393 Vibration-Based Monitoring of Tensioning Stay Cables of an Extradosed Bridge
Authors: Chun-Chung Chen, Bo-Han Lee, Yu-Chi Sung
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Monitoring the status of tensioning force of stay cables is a significant issue for the assessment of structural safety of extradosed bridges. Moreover, it is known that there is a high correlation between the existing tension force and the vibration frequencies of cables. This paper presents the characteristic of frequencies of stay cables of a field extradosed bridge by using vibration-based monitoring methods. The vibration frequencies of each stay cables were measured in stages from the beginning to the completion of bridge construction. The result shows that the vibration frequency variation trend of different lengths of cables at each measured stage is different. The observed feature can help the application of the bridge long-term monitoring system and contribute to the assessment of bridge safety.Keywords: vibration-based method, extradosed bridges, bridge health monitoring, bridge stay cables
Procedia PDF Downloads 1411392 Exploring the Success of Live Streaming Commerce in China: A Literature Analysis
Authors: Ming Gao, Matthew Tingchi Liu, Hoi Ngan Loi
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Live streaming refers to the video contents generated by broadcasters and shared with viewers in real-time by uploading them to short-video platforms. In recent years, individual KOL broadcasters have successfully made use of live streams to sell a large amount of goods to the consumers. For example, Wei Ya, the Number 1 broadcaster in Taobao Live, sold products worth RMB 2.7 billion (USD 0.38 billion) in 2018. Regarding the success of live streaming commerce (LSC) in China, this study explores the elements of the booming LSC industry and attempts to explain the reasons behind its prosperity. A systematic review of industry reports and academic papers was conducted to summarize the latest findings in this field. And the results of this investigation showed that a live streaming eco-system has been established by the LSC players, namely, the platform, the broadcaster, the product supplier, and the viewer. In this eco-system, all players have complementary advantages and needs, and their close cooperation leads to a win-win situation. For instance, platforms and broadcasters have abundant internet traffic, which needs to be monetized, while product suppliers have mature supply chains and the need of promoting the products. In addition, viewers are attached to the LSC platforms to get product information, bargains, and entertainment. This study highlights the importance of the mass-personal hybrid communication nature of live streaming because its interpersonal communication feature increases consumers’ positive experiences, while its mass media broadcasting feature facilitates product promotion. Another innovative point of this study lies in its inclusion of the special characteristic of Chinese Internet culture - entertainment. The entertaining genres of the live streams created by broadcasters serve as down-to-earth approaches to reach their audiences easily. Further, the nature of video, i.e., the dynamic and salient stimulus, is emphasized in this study. Since video is more engaging, it can attract viewers in a quick and easy way. Meanwhile, the abundant, interesting, high-quality, and free short videos have added “stickiness” to platforms by retaining users and prolonging their staying time on the platforms. In addition, broadcasters’ important characters, such as physical attractiveness, humor, sex appeal, kindness, communication skills, and interactivity, are also identified as important factors that influence consumers’ engagement and purchase intention. In conclusion, all players have their own proper places in this live streaming eco-system, in which they work seamlessly to give full play to their respective advantages, with each player taking what it needs and offering what it has. This has contributed to the success of live streaming commerce in China.Keywords: broadcasters, communication, entertainment, live streaming commerce, viewers
Procedia PDF Downloads 1141391 Diagnosis of Diabetes Using Computer Methods: Soft Computing Methods for Diabetes Detection Using Iris
Authors: Piyush Samant, Ravinder Agarwal
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Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction
Procedia PDF Downloads 3921390 Road Vehicle Recognition Using Magnetic Sensing Feature Extraction and Classification
Authors: Xiao Chen, Xiaoying Kong, Min Xu
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This paper presents a road vehicle detection approach for the intelligent transportation system. This approach mainly uses low-cost magnetic sensor and associated data collection system to collect magnetic signals. This system can measure the magnetic field changing, and it also can detect and count vehicles. We extend Mel Frequency Cepstral Coefficients to analyze vehicle magnetic signals. Vehicle type features are extracted using representation of cepstrum, frame energy, and gap cepstrum of magnetic signals. We design a 2-dimensional map algorithm using Vector Quantization to classify vehicle magnetic features to four typical types of vehicles in Australian suburbs: sedan, VAN, truck, and bus. Experiments results show that our approach achieves a high level of accuracy for vehicle detection and classification.Keywords: vehicle classification, signal processing, road traffic model, magnetic sensing
Procedia PDF Downloads 3091389 Effect of Dust on Performances of Single Crystal Photovoltaic Solar Module
Authors: A. Benatiallah, D. Benatiallah, A. Harrouz, F. Abaidi, S. Mansouri
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Photovoltaic system is established as a reliable and economical source of electricity in rural and Sahara areas, especially in developing countries where the population is dispersed, has low consumption of energy and the grid power is not extended to these areas due to viability and financial problems. The production of energy by the photovoltaic system fluctuates and depend on meteorological conditions. Wind is a very important and often neglected parameter in the behavior of the solar module. The electric performances of a solar module to the silicon are very appreciable to the blows; in the present work, we have studied the behavior of multi-crystal solar module according to the density of dust, and the principals electric feature of the solar module. An evaluation permits to affirm that a solar module under the effect of sand will collect a lower flux to the normal conditions.Keywords: solar modulen pv, dust effect, experimental, performances
Procedia PDF Downloads 4871388 Authentication Based on Hand Movement by Low Dimensional Space Representation
Authors: Reut Lanyado, David Mendlovic
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Most biological methods for authentication require special equipment and, some of them are easy to fake. We proposed a method for authentication based on hand movement while typing a sentence with a regular camera. This technique uses the full video of the hand, which is harder to fake. In the first phase, we tracked the hand joints in each frame. Next, we represented a single frame for each individual using our Pose Agnostic Rotation and Movement (PARM) dimensional space. Then, we indicated a full video of hand movement in a fixed low dimensional space using this method: Fixed Dimension Video by Interpolation Statistics (FDVIS). Finally, we identified each individual in the FDVIS representation using unsupervised clustering and supervised methods. Accuracy exceeds 96% for 80 individuals by using supervised KNN.Keywords: authentication, feature extraction, hand recognition, security, signal processing
Procedia PDF Downloads 1191387 Using Self Organizing Feature Maps for Automatic Prostate Segmentation in TRUS Images
Authors: Ahad Salimi, Hassan Masoumi
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Prostate cancer is one of the most common recognized cancers in men, and, is one of the most important mortality factors of cancer in this group. Determining of prostate’s boundary in TRUS (Transrectal Ultra Sound) images is very necessary for prostate cancer treatments. The weakness edges and speckle noise make the ultrasound images inherently to segment. In this paper a new automatic algorithm for prostate segmentation in TRUS images proposed that include three main stages. At first morphological smoothing and sticks filtering are used for noise removing. In second step, for finding a point in prostate region, SOFM algorithm is enlisted and in the last step, the boundary of prostate extracting accompanying active contour is employed. For validation of proposed method, a number of experiments are conducted. The results obtained by our algorithm show the promise of the proposed algorithm.Keywords: SOFM, preprocessing, GVF contour, segmentation
Procedia PDF Downloads 3181386 Mechanical-Reliability Coupling for a Bearing Capacity Assessment of Shallow Foundations
Authors: Amal Hentati, Mbarka Selmi, Tarek Kormi, Julien Baroth, Barthelemy Harthong
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The impact of uncertainties on the performance assessment of shallow foundations is often significant. The need of the geotechnical engineers to a more objective and rigorous description of soil variations permitting to quantify these uncertainties and to incorporate them into calculation methods led to the development of reliability approaches. In this context, a mechanical-reliability coupling was developed in this paper, using a program coded in Matlab and the finite element software Abaqus, for the bearing capacity assessment of shallow foundations. The reliability analysis, based on the finite element method, assumed both soil cohesion and friction angle as uncertain parameters characterized by normal or lognormal probability distributions. The inherent spatial variability of both soil properties was, then, taken into account using 1D stationary random fields. The application of the proposed methodology to a shallow foundation subjected to a centered vertical loading permitted to highlight the proposed process interest. Findings proved the insufficiency of the conventional approach to predict the foundation failure and a high sensitivity of the ultimate loads to the soil properties uncertainties, mainly those related to the friction angle, was noted. Moreover, an asymmetry of both displacement and velocity fields was obtained.Keywords: mechanical-reliability coupling, finite element method, shallow foundation, random fields, spatial variability
Procedia PDF Downloads 6531385 A Web-Based Real Property Updating System for Efficient and Sustainable Urban Development: A Case Study in Ethiopia
Authors: Eyosiyas Aga
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The development of information communication technology has transformed the paper-based mapping and land registration processes to a computerized and networked system. The computerization and networking of real property information system play a vital role in good governance and sustainable development of emerging countries through cost effective, easy and accessible service delivery for the customer. The efficient, transparent and sustainable real property system is becoming the basic infrastructure for the urban development thus improve the data management system and service delivery in the organizations. In Ethiopia, the real property administration is paper based as a result, it confronted problems of data management, illegal transactions, corruptions, and poor service delivery. In order to solve this problem and to facilitate real property market, the implementation of web-based real property updating system is crucial. A web-based real property updating is one of the automation (computerizations) methods to facilitate data sharing, reduce time and cost of the service delivery in real property administration system. In additions, it is useful for the integration of data onto different information systems and organizations. This system is designed by combining open source software which supported by open Geo-spatial consortium. The web-based system is mainly designed by using open source software with the help of open Geo-spatial Consortium. The Open Geo-spatial Consortium standards such as the Web Feature Service and Web Map Services are the most widely used standards to support and improves web-based real property updating. These features allow the integration of data from different sources, and it can be used to maintain consistency of data throughout transactions. The PostgreSQL and Geoserver are used to manage and connect a real property data to the flex viewer and user interface. The system is designed for both internal updating system (municipality); which is mainly updating of spatial and textual information, and the external system (customer) which focus on providing and interacting with the customer. This research assessed the potential of open source web applications and adopted this technology for real property updating system in Ethiopia through simple, cost effective and secured way. The system is designed by combining and customizing open source software to enhance the efficiency of the system in cost effective way. The existing workflow for real property updating is analyzed to identify the bottlenecks, and the new workflow is designed for the system. The requirement is identified through questionnaire and literature review, and the system is prototype for the study area. The research mainly aimed to integrate human resource with technology in designing of the system to reduce data inconsistency and security problems. In additions, the research reflects on the current situation of real property administration and contributions of effective data management system for efficient, transparent and sustainable urban development in Ethiopia.Keywords: cadaster, real property, sustainable, transparency, web feature service, web map service
Procedia PDF Downloads 2571384 Comparison of Machine Learning and Deep Learning Algorithms for Automatic Classification of 80 Different Pollen Species
Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie
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Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. That is why the need for automation of this task is urgent. A lot of studies have investigated the subject using different standard image processing descriptors and sometimes hand-crafted ones.In this work, we make a comparative study between classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN, Autoencoders, Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approachesKeywords: pollens identification, features extraction, pollens classification, automated palynology
Procedia PDF Downloads 1241383 Influence of Annealing on the Mechanical Properties of Polyester-Cotton Friction Spun Yarn
Authors: Sujit Kumar Sinha, R. Chattopadhyay
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In the course of processing phases and use, fibres, yarns, or fabrics are subjected to a variety of stresses and strains, which cause the development of internal stresses. Given an opportunity, these inherent stresses try to bring back the structure to the original state. As an example, a twisted yarn always shows a tendency to untwist whenever its one end is made free. If the yarn is not held under tension, it may form snarls due to the presence of excessive torque. The running performance of such yarn or thread may, therefore, get negatively affected by it, as a snarl may not pass through the knitting or sewing needle smoothly, leading to an end break. A fabric shows a tendency to form wrinkles whenever squeezed. It may also shrink when brought to a relaxed state. In order to improve performance (i.e., dimensional stability or appearance), stabilization of the structure is needed. The stabilization can be attained through the release of internal stresses, which can be brought about by the process of annealing and/or other finishing treatments. When a fabric is subjected to heat, a change in the properties of the fibers, yarns, and fabric is expected. The degree to which the properties are affected would depend upon the condition of heat treatment and on the properties & structure of fibres, yarns, and fabric. In the present study, an attempt has been made to investigate the effect of annealing treatment on the properties of polyester cotton yarns with varying sheath structures.Keywords: friction spun yarn, annealing, tenacity, structural integrity, decay
Procedia PDF Downloads 481382 Oxygen Absorption Enhancement during Sulfite Forced Oxidation in the Presence of Nano-Particles
Authors: Zhao Bo
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The TiO2-Na2SO3 and SiO2-Na2SO3 nano-fluids were prepared using ultrasonic dispertion method without any surfactant addition to study the influence of nano-fluids on the mass transfer during forced sulfite oxidation in a thermostatic stirred tank, and the kinetic viscosity of nano-fluids was measured. The influence of temperature (30 ℃ ~ 50 ℃), solid loading of fine particle (0 Kg/m³~1.0 Kg/m³), stirring speed (50 r/min ~ 400 r/min), and particle size (10 nm~100 nm) on the average oxygen absorption rate were investigated in detail. Both TiO2 nano-particles and SiO2 nano-particles could remarkably improve the gas-liquid mass transfer. Oxygen absorption enhancement factor increases with the increase of solid loading of nano-particles to a critical value and then decreases with further increase of solid loading under 30℃. Oxygen absorption rate together with absorption enhancement factor increases with stirring speed. However, oxygen absorption enhancement factor decreases with the increase of temperature due to aggregation of nano-particles. Further inherent relationship between particle size, loading, surface area, viscosity, stirring speed, temperature, adsorption, desorption, and mass transfer was discussed in depth by analyzing the interaction mechanism.Keywords: fine particles, nano-fluid, mass transfer enhancement, solid loading
Procedia PDF Downloads 2291381 Towards a Deeper Understanding of 21st Century Global Terrorism
Authors: Francis Jegede
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This paper examines essential issues relating to the rise and nature of violent extremism involving non-state actors and groups in the early 21st century. The global trends in terrorism and violent extremism are examined in relation to Western governments’ counter terror operations. The paper analyses the existing legal framework for fighting violent extremism and terrorism and highlights the inherent limitations of the current International Law of War in dealing with the growing challenges posed by terrorists and violent extremist groups. The paper discusses how terrorist groups use civilians, women and children as tools and weapon of war to fuel their campaign of terror and suggests ways in which the international community could deal with the challenge of fighting terrorist groups without putting civilians, women and children in harm way. The paper emphasises the need to uphold human rights values and respect for the law of war in our response to global terrorism. The paper poses the question as to whether the current legal framework for dealing with terrorist groups is sufficient without contravening the essential provisions and ethos of the International Law of War and Human Rights. While the paper explains how terrorist groups flagrantly disregard the rule of law and disrespect human rights in their campaign of terror, it also notes instances in which the current Western strategy in fighting terrorism may be viewed or considered as conflicting with human rights and international law.Keywords: terrorism, law of war, international law, violent extremism
Procedia PDF Downloads 3121380 Charting Sentiments with Naive Bayes and Logistic Regression
Authors: Jummalla Aashrith, N. L. Shiva Sai, K. Bhavya Sri
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The swift progress of web technology has not only amassed a vast reservoir of internet data but also triggered a substantial surge in data generation. The internet has metamorphosed into one of the dynamic hubs for online education, idea dissemination, as well as opinion-sharing. Notably, the widely utilized social networking platform Twitter is experiencing considerable expansion, providing users with the ability to share viewpoints, participate in discussions spanning diverse communities, and broadcast messages on a global scale. The upswing in online engagement has sparked a significant curiosity in subjective analysis, particularly when it comes to Twitter data. This research is committed to delving into sentiment analysis, focusing specifically on the realm of Twitter. It aims to offer valuable insights into deciphering information within tweets, where opinions manifest in a highly unstructured and diverse manner, spanning a spectrum from positivity to negativity, occasionally punctuated by neutrality expressions. Within this document, we offer a comprehensive exploration and comparative assessment of modern approaches to opinion mining. Employing a range of machine learning algorithms such as Naive Bayes and Logistic Regression, our investigation plunges into the domain of Twitter data streams. We delve into overarching challenges and applications inherent in the realm of subjectivity analysis over Twitter.Keywords: machine learning, sentiment analysis, visualisation, python
Procedia PDF Downloads 441379 Adaptive Threshold Adjustment of Clear Channel Assessment in LAA Down Link
Authors: Yu Li, Dongyao Wang, Xiaobao Sun, Wei Ni
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In long-term evolution (LTE), the carriers around 5GHz are planned to be utilized without licenses to further enlarge system capacity. This feature is termed licensed assisted access (LAA). The channel sensing (clean channel assessment, CCA) is required before any transmission on these unlicensed carriers, in order to make sure the harmonious co-existence of LAA with other radio access technology in the unlicensed band. Obviously, the CCA threshold is very critical, which decides whether the transmission right following CCA is delivered in time and without collisions. An improper CCA threshold may cause buffer overflow of some eNodeBs if the eNodeBs are heavily loaded with the traffic. Thus, to solve these problems, we propose an adaptive threshold adjustment method for CCA in the LAA downlink. Both the load and transmission opportunities are concerned. The trend of the LAA throughput as the threshold varies is obtained, which guides the threshold adjustment. The co-existing between LAA and Wi-Fi is particularly tested. The results from system-level simulation confirm the merits of our design, especially in heavy traffic cases.Keywords: LTE, LAA, CCA, threshold adjustment
Procedia PDF Downloads 1331378 A Review of In-Vehicle Network for Cloud Connected Vehicle
Authors: Hanbhin Ryu, Ilkwon Yun
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Automotive industry targets to provide an improvement in safety and convenience through realizing fully autonomous vehicle. For partially realizing fully automated driving, Current vehicles already feature varieties of advanced driver assistance system (ADAS) for safety and infotainment systems for the driver’s convenience. This paper presents Cloud Connected Vehicle (CCV) which connected vehicles with cloud data center via the access network to control the vehicle for achieving next autonomous driving form and describes its features. This paper also describes the shortcoming of the existing In-Vehicle Network (IVN) to be a next generation IVN of CCV and organize the 802.3 Ethernet, the next generation of IVN, related research issue to verify the feasibility of using Ethernet. At last, this paper refers to additional considerations to adopting Ethernet-based IVN for CCV.Keywords: autonomous vehicle, cloud connected vehicle, ethernet, in-vehicle network
Procedia PDF Downloads 4681377 Controlling Excitons Complexes in Two Dimensional MoS₂ Monolayers
Authors: Arslan Usman, Abdul Sattar, Hamid Latif, Afshan Ashfaq, Muhammad Rafique, Martin Koch
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Two-dimensional materials have promising applications in optoelectronic and photonics; MoS₂ is the pioneer 2D material in the family of transition metal dichalcogenides. Its optical, optoelectronic, and structural properties are of practical importance along with its exciton dynamics. Exciton, along with exciton complexes, plays a vital role in realizing quantum devices. MoS₂ monolayers were synthesized using chemical vapour deposition (CVD) technique on SiO₂ and hBN substrates. Photoluminescence spectroscopy (PL) was used to identify the monolayer, which also reflects the substrate based peak broadening due to screening effects. In-plane and out of plane characteristic vibrational modes E¹₂g and A₁g, respectively, were detected in a different configuration on the substrate. The B-excitons and trions showed a dominant feature at low temperatures due to electron-phonon coupling effects, whereas their energies are separated by 100 meV.Keywords: 2D materials, photoluminescence, AFM, excitons
Procedia PDF Downloads 1391376 Keyframe Extraction Using Face Quality Assessment and Convolution Neural Network
Authors: Rahma Abed, Sahbi Bahroun, Ezzeddine Zagrouba
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Due to the huge amount of data in videos, extracting the relevant frames became a necessity and an essential step prior to performing face recognition. In this context, we propose a method for extracting keyframes from videos based on face quality and deep learning for a face recognition task. This method has two steps. We start by generating face quality scores for each face image based on the use of three face feature extractors, including Gabor, LBP, and HOG. The second step consists in training a Deep Convolutional Neural Network in a supervised manner in order to select the frames that have the best face quality. The obtained results show the effectiveness of the proposed method compared to the methods of the state of the art.Keywords: keyframe extraction, face quality assessment, face in video recognition, convolution neural network
Procedia PDF Downloads 2191375 Me and My Selfie: Identity Building Through Self Representation in Social Media
Authors: Revytia Tanera
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This research is a pilot study to examine the rise of selfie trend in dealing with individual self representation and identity building in social media. The symbolic interactionism theory is used as the concept of the desired self image, and Cooley’s looking glass-self concept is used to analyze the mechanical reflection of ourselves; how do people perform their “digital self” in social media. In-depth interviews were conducted in the study with a non-random sample who owns a smartphone with a front camera feature and are active in social media. This research is trying to find out whether the selfie trend brings any influence on identity building on each individual. Through analysis of interview results, it can be concluded that people take selfie photos in order to express themselves and to boost their confidence. This study suggests a follow up and more in depth analysis on identity and self representation from various age groups.Keywords: self representation, selfie, social media, symbolic interaction, looking glass-self
Procedia PDF Downloads 2901374 The Examination of Prospective ICT Teachers’ Attitudes towards Application of Computer Assisted Instruction
Authors: Agâh Tuğrul Korucu, Ismail Fatih Yavuzaslan, Lale Toraman
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Nowadays, thanks to development of technology, integration of technology into teaching and learning activities is spreading. Increasing technological literacy which is one of the expected competencies for individuals of 21st century is associated with the effective use of technology in education. The most important factor in effective use of technology in education institutions is ICT teachers. The concept of computer assisted instruction (CAI) refers to the utilization of information and communication technology as a tool aided teachers in order to make education more efficient and improve its quality in the process of educational. Teachers can use computers in different places and times according to owned hardware and software facilities and characteristics of the subject and student in CAI. Analyzing teachers’ use of computers in education is significant because teachers are the ones who manage the course and they are the most important element in comprehending the topic by students. To accomplish computer-assisted instruction efficiently is possible through having positive attitude of teachers. Determination the level of knowledge, attitude and behavior of teachers who get the professional knowledge from educational faculties and elimination of deficiencies if any are crucial when teachers are at the faculty. Therefore, the aim of this paper is to identify ICT teachers' attitudes toward computer-assisted instruction in terms of different variables. Research group consists of 200 prospective ICT teachers studying at Necmettin Erbakan University Ahmet Keleşoğlu Faculty of Education CEIT department. As data collection tool of the study; “personal information form” developed by the researchers and used to collect demographic data and "the attitude scale related to computer-assisted instruction" are used. The scale consists of 20 items. 10 of these items show positive feature, while 10 of them show negative feature. The Kaiser-Meyer-Olkin (KMO) coefficient of the scale is found 0.88 and Barlett test significance value is found 0.000. The Cronbach’s alpha reliability coefficient of the scale is found 0.93. In order to analyze the data collected by data collection tools computer-based statistical software package used; statistical techniques such as descriptive statistics, t-test, and analysis of variance are utilized. It is determined that the attitudes of prospective instructors towards computers do not differ according to their educational branches. On the other hand, the attitudes of prospective instructors who own computers towards computer-supported education are determined higher than those of the prospective instructors who do not own computers. It is established that the departments of students who previously received computer lessons do not affect this situation so much. The result is that; the computer experience affects the attitude point regarding the computer-supported education positively.Keywords: computer based instruction, teacher candidate, attitude, technology based instruction, information and communication technologies
Procedia PDF Downloads 2871373 Estimating the Receiver Operating Characteristic Curve from Clustered Data and Case-Control Studies
Authors: Yalda Zarnegarnia, Shari Messinger
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Receiver operating characteristic (ROC) curves have been widely used in medical research to illustrate the performance of the biomarker in correctly distinguishing the diseased and non-diseased groups. Correlated biomarker data arises in study designs that include subjects that contain same genetic or environmental factors. The information about correlation might help to identify family members at increased risk of disease development, and may lead to initiating treatment to slow or stop the progression to disease. Approaches appropriate to a case-control design matched by family identification, must be able to accommodate both the correlation inherent in the design in correctly estimating the biomarker’s ability to differentiate between cases and controls, as well as to handle estimation from a matched case control design. This talk will review some developed methods for ROC curve estimation in settings with correlated data from case control design and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using Conditional ROC curves will be demonstrated, to provide appropriate ROC curves for correlated paired data. The proposed approach will use the information about the correlation among biomarker values, producing conditional ROC curves that evaluate the ability of a biomarker to discriminate between diseased and non-diseased subjects in a familial paired design.Keywords: biomarker, correlation, familial paired design, ROC curve
Procedia PDF Downloads 2311372 Entrepreneurship and Innovation: The Essence of Sustainable, Smart and Inclusive Economies
Authors: Isabel Martins, Orlando Pereira, Ana Martins
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This study aims to highlight that, in changing environments, organisations need to adapt their behaviours to the demands of the new economic reality. The main purpose of this study focuses on the relationship between entrepreneurship, innovation with learning as the mediating factor. It is within this entrepreneurial spirit that literature reveals a concern with the current economic perspective towards knowledge and considers it as both the production factor par excellence and a source of entrepreneurial capacity and innovation. Entrepreneurship is a mind-set focused on identifying opportunities of economic value and translates these into the pursuit of business opportunities through innovation. It connects art and science and is a way of life, as opposed to a simple mode of business creation and profiteering. This perspective underlines the need to develop the global individual for the globalised world, the strategic key to economic and social development. The objective of this study is to explore the notion that relational capital which is established between the entrepreneur and all the other economic role players both inside and outside the organization, is indeed determinant in developing the entrepreneurial capacity. However, this depends on the organizational culture of innovation. In this context, entrepreneurship is an ‘entrepreneurial capital’ inherent in the organization that is not limited to skills needed for work. This study is a critique of extant literature review which will be also be supported by primary data collection gathered to study graduates’ perceptions towards their entrepreneurial capital. Limitations are centered on both the design and of the sample of this study. This study is of added value for both scholars and organisations in the current innovation economy.Keywords: entrepreneurship, innovation, learning, relational capital
Procedia PDF Downloads 2161371 Empowerment Model: A Strategy for Supporting Creative Economy through Traditional Weaving in Anajiaka Village
Authors: Sita Yuliastuti Amijaya, Wiyatiningsih Wiyatiningsih, Paulus Bawole
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Weaving skills were not originally a way to earn money for the traditional people on Sumba Island. Weaving is a leisure activity carried out between farming and caring for families. It is quite understandable if the weavers are women. At this time, weaving crafts become a unique potential inherent in an area, so that the weaver women also have the potential to drive economic activity in regional tourism sector. This study aims to measure the sustainability of traditional weaving business activities in Anajiaka Village, Umbu Ratu Nggay Barat, Central Sumba Regency, which is able to support the creative economy. The analysis was performed using qualitative descriptive methods by comparing the criteria of smart living and smart economy in the study of smart city. This study found that business sustainability will be better maintained if it is bound in a joint commitment, for example by forming a group of craftsmen. Other challenges besides the commitment of the group members are aspects of local government support and related agencies, in the form of guidance, funding, and promotion. In addition, fabric order targets, maintaining family and community balance, are recognized as obstacles for craftsmen. The modern marketing model is not yet mastered by the craftsmen group, so it needs assistance for future development.Keywords: agriculture, craftsmen, creativepreneur, smart economy, smart living
Procedia PDF Downloads 1601370 A Study of Effective Stereo Matching Method for Long-Wave Infrared Camera Module
Authors: Hyun-Koo Kim, Yonghun Kim, Yong-Hoon Kim, Ju Hee Lee, Myungho Song
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In this paper, we have described an efficient stereo matching method and pedestrian detection method using stereo types LWIR camera. We compared with three types stereo camera algorithm as block matching, ELAS, and SGM. For pedestrian detection using stereo LWIR camera, we used that SGM stereo matching method, free space detection method using u/v-disparity, and HOG feature based pedestrian detection. According to testing result, SGM method has better performance than block matching and ELAS algorithm. Combination of SGM, free space detection, and pedestrian detection using HOG features and SVM classification can detect pedestrian of 30m distance and has a distance error about 30 cm.Keywords: advanced driver assistance system, pedestrian detection, stereo matching method, stereo long-wave IR camera
Procedia PDF Downloads 3961369 Online Authenticity Verification of a Biometric Signature Using Dynamic Time Warping Method and Neural Networks
Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof
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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature
Procedia PDF Downloads 1611368 A Study of Electrowetting-Assisted Mold Filling in Nanoimprint Lithography
Authors: Wei-Hsuan Hsu, Yi-Xuan Huang
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Nanoimprint lithography (NIL) possesses the advantages of sub-10-nm feature and low cost. NIL patterns the resist with physical deformation using a mold, which can easily reproduce the required nano-scale pattern. However, the variation of process parameters and environmental conditions seriously affect reproduction quality. How to ensure the quality of imprinted pattern is essential for industry. In this study, the authors used the electrowetting technology to assist mold filling in the NIL process. A special mold structure was designed to cause electrowetting. During the imprinting process, when a voltage was applied between the mold and substrate, the hydrophilicity/hydrophobicity of the surface of the mold can be converted. Both simulation and experiment confirmed that the electrowetting technology can assist mold filling and avoid incomplete filling rate. The proposed method can also reduce the crack formation during the de-molding process. Therefore, electrowetting technology can improve the process quality of NIL.Keywords: electrowetting, mold filling, nano-imprint, surface modification
Procedia PDF Downloads 1601367 Twitter's Impact on Print Media with Respect to Real World Events
Authors: Basit Shahzad, Abdullatif M. Abdullatif
Abstract:
Recent advancements in Information and Communication Technologies (ICT) and easy access to Internet have made social media the first choice for information sharing related to any important events or news. On Twitter, trend is a common feature that quantifies the level of popularity of a certain news or event. In this work, we examine the impact of Twitter trends on real world events by hypothesizing that Twitter trends have an influence on print media in Pakistan. For this, Twitter is used as a platform and Twitter trends as a base line. We first collect data from two sources (Twitter trends and print media) in the period May to August 2016. Obtained data from two sources is analyzed and it is observed that social media is significantly influencing the print media and majority of the news printed in newspaper are posted on Twitter earlier.Keywords: twitter trends, text mining, effectiveness of trends, print media
Procedia PDF Downloads 2531366 2.5D Face Recognition Using Gabor Discrete Cosine Transform
Authors: Ali Cheraghian, Farshid Hajati, Soheila Gheisari, Yongsheng Gao
Abstract:
In this paper, we present a novel 2.5D face recognition method based on Gabor Discrete Cosine Transform (GDCT). In the proposed method, the Gabor filter is applied to extract feature vectors from the texture and the depth information. Then, Discrete Cosine Transform (DCT) is used for dimensionality and redundancy reduction to improve computational efficiency. The system is combined texture and depth information in the decision level, which presents higher performance compared to methods, which use texture and depth information, separately. The proposed algorithm is examined on publically available Bosphorus database including models with pose variation. The experimental results show that the proposed method has a higher performance compared to the benchmark.Keywords: Gabor filter, discrete cosine transform, 2.5d face recognition, pose
Procedia PDF Downloads 3191365 Feature Extraction Technique for Prediction the Antigenic Variants of the Influenza Virus
Authors: Majid Forghani, Michael Khachay
Abstract:
In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.Keywords: antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition
Procedia PDF Downloads 143