Search results for: distinctive features
3842 Grammatical and Lexical Explorations on ‘Outer Circle’ Englishes and ‘Expanding Circle’ Englishes: A Corpus-Based Comparative Analysis
Authors: Orlyn Joyce D. Esquivel
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This study analyzed 50 selected research papers from professional language and linguistic academic journals to portray the differences between Kachru’s (1994) outer circle and expanding circle Englishes. The selected outer circle Englishes include those of Bangladesh, Malaysia, the Philippines, India, and Singapore; and the selected expanding circle Englishes are those of China, Indonesia, Japan, Korea, and Thailand. The researcher built ten corpora (five research papers for each corpus) to represent each variety of Englishes. The corpora were examined under grammatical and lexical features using Modified English TreeTagger in Sketch Engine. Results revealed the distinct grammatical and lexical features through the table and textual analyses, illustrated from the most to least dominant linguistic elements. In addition, comparative analyses were done to distinguish the features of each of the selected Englishes. The Language Change Theory was used as a basis in the discussion. Hence, the findings suggest that the ‘outer circle’ Englishes and ‘expanding circle’ Englishes will continue to drift from International English.Keywords: applied linguistics, English as a global language, expanding circle Englishes, global Englishes, outer circle Englishes
Procedia PDF Downloads 1473841 A Communication Signal Recognition Algorithm Based on Holder Coefficient Characteristics
Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo
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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model
Procedia PDF Downloads 1453840 Classifier for Liver Ultrasound Images
Authors: Soumya Sajjan
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Liver cancer is the most common cancer disease worldwide in men and women, and is one of the few cancers still on the rise. Liver disease is the 4th leading cause of death. According to new NHS (National Health Service) figures, deaths from liver diseases have reached record levels, rising by 25% in less than a decade; heavy drinking, obesity, and hepatitis are believed to be behind the rise. In this study, we focus on Development of Diagnostic Classifier for Ultrasound liver lesion. Ultrasound (US) Sonography is an easy-to-use and widely popular imaging modality because of its ability to visualize many human soft tissues/organs without any harmful effect. This paper will provide an overview of underlying concepts, along with algorithms for processing of liver ultrasound images Naturaly, Ultrasound liver lesion images are having more spackle noise. Developing classifier for ultrasound liver lesion image is a challenging task. We approach fully automatic machine learning system for developing this classifier. First, we segment the liver image by calculating the textural features from co-occurrence matrix and run length method. For classification, Support Vector Machine is used based on the risk bounds of statistical learning theory. The textural features for different features methods are given as input to the SVM individually. Performance analysis train and test datasets carried out separately using SVM Model. Whenever an ultrasonic liver lesion image is given to the SVM classifier system, the features are calculated, classified, as normal and diseased liver lesion. We hope the result will be helpful to the physician to identify the liver cancer in non-invasive method.Keywords: segmentation, Support Vector Machine, ultrasound liver lesion, co-occurance Matrix
Procedia PDF Downloads 4013839 Enhancing the Recruitment Process through Machine Learning: An Automated CV Screening System
Authors: Kaoutar Ben Azzou, Hanaa Talei
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Human resources is an important department in each organization as it manages the life cycle of employees from recruitment training to retirement or termination of contracts. The recruitment process starts with a job opening, followed by a selection of the best-fit candidates from all applicants. Matching the best profile for a job position requires a manual way of looking at many CVs, which requires hours of work that can sometimes lead to choosing not the best profile. The work presented in this paper aims at reducing the workload of HR personnel by automating the preliminary stages of the candidate screening process, thereby fostering a more streamlined recruitment workflow. This tool introduces an automated system designed to help with the recruitment process by scanning candidates' CVs, extracting pertinent features, and employing machine learning algorithms to decide the most fitting job profile for each candidate. Our work employs natural language processing (NLP) techniques to identify and extract key features from unstructured text extracted from a CV, such as education, work experience, and skills. Subsequently, the system utilizes these features to match candidates with job profiles, leveraging the power of classification algorithms.Keywords: automated recruitment, candidate screening, machine learning, human resources management
Procedia PDF Downloads 473838 Underwater Image Enhancement and Reconstruction Using CNN and the MultiUNet Model
Authors: Snehal G. Teli, R. J. Shelke
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CNN and MultiUNet models are the framework for the proposed method for enhancing and reconstructing underwater images. Multiscale merging of features and regeneration are both performed by the MultiUNet. CNN collects relevant features. Extensive tests on benchmark datasets show that the proposed strategy performs better than the latest methods. As a result of this work, underwater images can be represented and interpreted in a number of underwater applications with greater clarity. This strategy will advance underwater exploration and marine research by enhancing real-time underwater image processing systems, underwater robotic vision, and underwater surveillance.Keywords: convolutional neural network, image enhancement, machine learning, multiunet, underwater images
Procedia PDF Downloads 703837 Dentofacial-Targeted Bullying: A Review
Authors: Mai Ashraf Talaat
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Bullying is an aggressive behavior and a serious issue that should be addressed by everyone and should be avoided at all costs. It is very common among adolescents and schoolchildren and the effects can be devastating and long-lasting. Students are most commonly bullied about physical appearance, race, gender, disability, ethnicity, religion, and sexual orientation. Appearance-targeted bullying is a form of bullying that targets an aspect of a person's appearance, which includes facial and dental features. Deviation from accepted dentofacial aesthetics leads to elevated incidences of bullying in schoolchildren. The aim of this review article is to assess the prevalence of bullying due to dentofacial characteristics and evaluate the importance of dentofacial appearance on perceived social attractiveness based on multiple studies.Keywords: dentofacial features, orthodontics, malocclusion, adolescents, bullying
Procedia PDF Downloads 733836 Visualization of Flow Behaviour in Micro-Cavities during Micro Injection Moulding
Authors: Reza Gheisari, Paulo J. Bartolo, Nicholas Goddard
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Polymeric micro-cantilevers (Cs) are rapidly becoming popular for MEMS applications such as chemo- and bio-sensing as well as purely electromechanical applications such as microrelays. Polymer materials present suitable physical and chemical properties combined with low-cost mass production. Hence, micro-cantilevers made of polymers indicate much more biocompatibility and adaptability of rapid prototyping along with mechanical properties. This research studies the effects of three process and one size factors on the filling behaviour in micro cavity, and the role of each in the replication of micro parts using different polymer materials i.e. polypropylene (PP) SABIC 56M10 and acrylonitrile butadiene styrene (ABS) Magnum 8434. In particular, the following factors are considered: barrel temperature, mould temperature, injection speed and the thickness of micro features. The study revealed that the barrel temperature and the injection speed are the key factors affecting the flow length of micro features replicated in PP and ABS. For both materials, an increase of feature sizes improves the melt flow. However, the melt fill of micro features does not increase linearly with the increase of their thickness.Keywords: flow length, micro cantilevers, micro injection moulding, microfabrication
Procedia PDF Downloads 3873835 The Reflections of the K-12 English Language Teachers on the Implementation of the K-12 Basic Education Program in the Philippines
Authors: Dennis Infante
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This paper examined the reflections of teachers on curriculum reforms, the implementation of the K-12 Basic Education Program in the Philippines. The results revealed that problems and concerns raised by teachers could be classified into curriculum materials and design; competence, readiness and motivation of the teachers; the learning environment, and support systems; readiness, competence and motivation of students; and other relevant factors. The best features of the K-12 curriculum reforms included (1) the components, curriculum materials; (2) the design, structure and delivery of the lessons; (3) the framework and theoretical approach; (3) the qualities of the teaching-learning activities; (4) and other relevant features. With the demanding task of implementing the new curriculum, the teachers expressed their needs which included (1) making the curriculum materials available to achieve the goals of the curriculum reforms; (2) enrichment of the learning environments; (3) motivating and encouraging the teachers to embrace change; (4) providing appropriate support systems; (5) re-tooling, and empowering teachers to implement the curriculum reforms; and (6) other relevant factors. The research concluded with a synthesis that provided a paradigm for implementing curriculum reforms which recognizes the needs of the teachers and the features of the new curriculum.Keywords: curriculum reforms, K-12, teachers' reflections, implementing curriculum change
Procedia PDF Downloads 2723834 Praetical and Theoretical Study on Characteristic Landscape Construction of Tujia Village in Xiaguping, Shennongjia Forestry Distric
Authors: Tingting Chen, Shouliang Zhao
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Compared with other regions, the construction for villages and towns in regions inhabited by minority nationality shall be deeply rooted in natural and cultural endowment in locality, and more importance shall be attached to building of characteristics. In this kind of area, landscape design is very important for its character and tradition. By empirical study in Shennongjia Area, some findings could be summarized as below. There are unique natural and cultural resources in Shennongjia Forestry District; during transformation on style and features of Tujia Village, Xiaguping, special style and features have been successfully shaped through 4 strategies: (1) highlighting Tujia Culture and architectural style in west region of Hubei Province; (2) merging with local natural environment; (3) introducing system of rural coordination architect; and (4) making great efforts to design and construct environmental embellishments with village and town symbols.Keywords: rural coordination architect, special style and features, characteristic landscape, villages and towns in regions inhabited by minority nationality
Procedia PDF Downloads 2653833 The Analysis of Deceptive and Truthful Speech: A Computational Linguistic Based Method
Authors: Seham El Kareh, Miramar Etman
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Recently, detecting liars and extracting features which distinguish them from truth-tellers have been the focus of a wide range of disciplines. To the author’s best knowledge, most of the work has been done on facial expressions and body gestures but only few works have been done on the language used by both liars and truth-tellers. This paper sheds light on four axes. The first axis copes with building an audio corpus for deceptive and truthful speech for Egyptian Arabic speakers. The second axis focuses on examining the human perception of lies and proving our need for computational linguistic-based methods to extract features which characterize truthful and deceptive speech. The third axis is concerned with building a linguistic analysis program that could extract from the corpus the inter- and intra-linguistic cues for deceptive and truthful speech. The program built here is based on selected categories from the Linguistic Inquiry and Word Count program. Our results demonstrated that Egyptian Arabic speakers on one hand preferred to use first-person pronouns and present tense compared to the past tense when lying and their lies lacked of second-person pronouns, and on the other hand, when telling the truth, they preferred to use the verbs related to motion and the nouns related to time. The results also showed that there is a need for bigger data to prove the significance of words related to emotions and numbers.Keywords: Egyptian Arabic corpus, computational analysis, deceptive features, forensic linguistics, human perception, truthful features
Procedia PDF Downloads 2003832 Polycystic Ovary Syndrome - Clinical Profile of Women Attending NPFDB Subfertility Clinic
Authors: Komathy Thiagarajan, Mohd. Azizuddin Mohd. Yussof, Hasnoorina Husin, Noor Azreena Abd Aziz, Faezah Shekh Abdullah, Abdul Wahaf Abdul Wahid
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Polycystic Ovary Syndrome (PCOS) presents with a plethora of clinical features owing to the multifaceted underlying pathophysiology. This study was conducted to determine the clinical features unique to the sub fertile women attending the Sub fertility Clinic of the National Population and Family Development Board (NPFDB) so that a more holistic approach can be adopted to further enhance the pregnancy outcome in those women. This was a case-control study conducted over a span of three years (from January 2014 until December 2016), whereby women who fulfilled the Rotterdam Criteria 2004 were classified as PCOS (n=79) and women who did not fulfill the Rotterdam Criteria were classified as controls (n=88). The mean age of the women was 30.1 years and the mean duration of marriage was 3.93 years. The majority of women suffered from primary sub fertility (82.6%). The median age was lower among PCOS women (29.0 years) compared to the controls (30.0 years), p<0.05. The majority of PCOS women (43.0%) were obese (BMI > 30 kg/m2) compared to only 19.3% who were obese in the control group, p<0.05. Hypertension was present in 59.5% of PCOS women and only in 36.4% of the control group, p<0.05. There were significantly more women who presented with hirsutism in PCOS group (27.8%) as compared to the control group (5.7%), p<0.05. The findings of this study elucidate that the clinical features of significance among sub fertile women suffering from PCOS, if detected early, are amenable to lifestyle modifications and timely interventions can potentially improve the fertility outcomes in this group of women.Keywords: clinical features, fertility, lifestyle modification, PCOS
Procedia PDF Downloads 1393831 Unsupervised Reciter Recognition Using Gaussian Mixture Models
Authors: Ahmad Alwosheel, Ahmed Alqaraawi
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This work proposes an unsupervised text-independent probabilistic approach to recognize Quran reciter voice. It is an accurate approach that works on real time applications. This approach does not require a prior information about reciter models. It has two phases, where in the training phase the reciters' acoustical features are modeled using Gaussian Mixture Models, while in the testing phase, unlabeled reciter's acoustical features are examined among GMM models. Using this approach, a high accuracy results are achieved with efficient computation time process.Keywords: Quran, speaker recognition, reciter recognition, Gaussian Mixture Model
Procedia PDF Downloads 3763830 Human Action Retrieval System Using Features Weight Updating Based Relevance Feedback Approach
Authors: Munaf Rashid
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For content-based human action retrieval systems, search accuracy is often inferior because of the following two reasons 1) global information pertaining to videos is totally ignored, only low level motion descriptors are considered as a significant feature to match the similarity between query and database videos, and 2) the semantic gap between the high level user concept and low level visual features. Hence, in this paper, we propose a method that will address these two issues and in doing so, this paper contributes in two ways. Firstly, we introduce a method that uses both global and local information in one framework for an action retrieval task. Secondly, to minimize the semantic gap, a user concept is involved by incorporating features weight updating (FWU) Relevance Feedback (RF) approach. We use statistical characteristics to dynamically update weights of the feature descriptors so that after every RF iteration feature space is modified accordingly. For testing and validation purpose two human action recognition datasets have been utilized, namely Weizmann and UCF. Results show that even with a number of visual challenges the proposed approach performs well.Keywords: relevance feedback (RF), action retrieval, semantic gap, feature descriptor, codebook
Procedia PDF Downloads 4613829 Pilot-free Image Transmission System of Joint Source Channel Based on Multi-Level Semantic Information
Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu
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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness
Procedia PDF Downloads 1133828 Innovativeness of the Furniture Enterprises in Bulgaria
Authors: Radostina Popova
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The paper presents an analysis of the innovation performance of small and medium-sized furniture enterprises in Bulgaria, accounting for over 97% of the companies in the sector. It contains advanced features of innovation in enterprises, specific features of the furniture industry in Bulgaria and analysis of the results of studies on the topic. The results from studies of three successive periods - 2006-2008; 2008-2010; 2010-2012, during which were studied 594 small and medium-sized furniture enterprises. There are commonly used in the EU definitions and indicators (European Commission, OECD, Oslo Manual), which allows for the comparability of results.Keywords: innovation activity, competitiveness of innovation, furniture enterprises in Bulgaria
Procedia PDF Downloads 2653827 An Ensemble Deep Learning Architecture for Imbalanced Classification of Thoracic Surgery Patients
Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi
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Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection
Procedia PDF Downloads 1343826 Product Feature Modelling for Integrating Product Design and Assembly Process Planning
Authors: Baha Hasan, Jan Wikander
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This paper describes a part of the integrating work between assembly design and assembly process planning domains (APP). The work is based, in its first stage, on modelling assembly features to support APP. A multi-layer architecture, based on feature-based modelling, is proposed to establish a dynamic and adaptable link between product design using CAD tools and APP. The proposed approach is based on deriving “specific function” features from the “generic” assembly and form features extracted from the CAD tools. A hierarchal structure from “generic” to “specific” and from “high level geometrical entities” to “low level geometrical entities” is proposed in order to integrate geometrical and assembly data extracted from geometrical and assembly modelers to the required processes and resources in APP. The feature concept, feature-based modelling, and feature recognition techniques are reviewed.Keywords: assembly feature, assembly process planning, feature, feature-based modelling, form feature, ontology
Procedia PDF Downloads 3043825 Is Presence of Psychotic Features Themselves Carry a Risk for Metabolic Syndrome?
Authors: Rady A., Elsheshai A., Elsawy M., Nagui R.
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Background and Aim: Metabolic syndrome affect around 20% of general population , authors have incriminated antipsychotics as serious risk factor that may provoke such derangement. The aim of our study is to assess metabolic syndrome in patients presenting psychotic features (delusions and hallucinations) whether schizophrenia or mood disorder and compare results in terms of drug naïf, on medication and healthy control. Subjects and Methods: The study recruited 40 schizophrenic patients, half of them drug naïf and the other half on antipsychotics, 40 patients with mood disorder with psychotic features, half of them drug naïf and the other half on medication, 20 healthy control. Exclusion criteria were put in order to exclude patients having already endocrine or metabolic disorders that my interfere with results obtain to minimize confusion bias. Metabolic syndrome assessed by measuring parameters including weight, body mass index, waist circumference, triglyceride level, HDL, fasting glucose, fasting insulin and insulin resistance Results: No difference was found when comparing drug naïf to those on medication in both schizophrenic and psychotic mood disorder arms, schizophrenic patients whether on medication or drug naïf should difference with control group for fasting glucose, schizophrenic patients on medication also showed difference in insulin resistance compared to control group. On the other hand, patients with psychotic mood disorder whether drug naïf or on medication showed difference from control group for fasting insulin level. Those on medication also differed from control for insulin resistance Conclusion: Our study didn’t reveal difference in metabolic syndrome among patients with psychotic features whether on medication or drug naïf. Only patients with Psychotic features on medication showed insulin resistance. Schizophrenic patients drug naïf or on medication tend to show higher fasting glucose while psychotic mood disorder whether drug naïf or on medication tend to show higher fasting insulin. This study suggest that presence of psychotic features themselves regardless being on medication or not carries a risk for insulin resistance and metabolic syndrome. Limitation: This study is limited by number of participants and larger numbers in future studies should be included in order to extrapolate results. Cohort longitudinal studies are needed in order to evaluate such hypothesis.Keywords: schizophrenia, metabolic syndrome, psychosis, insulin, resistance
Procedia PDF Downloads 5293824 Features of Technological Innovation Management in Georgia
Authors: Ketevan Goletiani, Parmen Khvedelidze
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discusses the importance of the topic, which is reflected in the advanced and developed countries in the formation of a new innovative stage of the distinctive mark of the modern world development. This phase includes the construction of the economy, which generates stockpiling and use is based. Intensifying the production and use of the results of new scientific and technical innovation has led to a sharp reduction in the cycle and accelerate the pace of product and technology updates. The world's leading countries in the development of innovative management systems for the formation of long-term and stable development of the socio-economic order conditions. The last years of the 20th century, the social and economic relations, modification, accelerating economic reforms, and profound changes in the system of the time. At the same time, the country should own place in the world geopolitical and economic space. Accelerated economic development tasks, the World Trade Organization, the European Union deep and comprehensive trade agreement, the new system of economic management, technical and technological renewal of production potential, and scientific fields in the share of the total volume of GDP growth requires new approaches. XX - XXI centuries Georgia's socio-economic changes is one of the urgent tasks in the form of a rise to the need for change, involving the use of natural resource-based economy to the latest scientific and technical achievements of an innovative and dynamic economy based on an accelerated pace. But Georgia still remains unresolved in many methodological, theoretical, and practical nature of the problem relating to the management of the economy in various fields for the development of innovative systems for optimal implementation. Therefore, the development of an innovative system for the formation of a complex and multi-problem, which is reflected in the following: countries should have higher growth rates than the geopolitical space of the neighboring countries that its competitors are. Formation of such a system is possible only in a deep theoretical research and innovative processes in the multi-level (micro, meso- and macro-levels) management on the basis of creation.Keywords: georgia, innovative, socio-economic, innovative manage
Procedia PDF Downloads 1183823 Identification of Spam Keywords Using Hierarchical Category in C2C E-Commerce
Authors: Shao Bo Cheng, Yong-Jin Han, Se Young Park, Seong-Bae Park
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Consumer-to-Consumer (C2C) E-commerce has been growing at a very high speed in recent years. Since identical or nearly-same kinds of products compete one another by relying on keyword search in C2C E-commerce, some sellers describe their products with spam keywords that are popular but are not related to their products. Though such products get more chances to be retrieved and selected by consumers than those without spam keywords, the spam keywords mislead the consumers and waste their time. This problem has been reported in many commercial services like e-bay and taobao, but there have been little research to solve this problem. As a solution to this problem, this paper proposes a method to classify whether keywords of a product are spam or not. The proposed method assumes that a keyword for a given product is more reliable if the keyword is observed commonly in specifications of products which are the same or the same kind as the given product. This is because that a hierarchical category of a product in general determined precisely by a seller of the product and so is the specification of the product. Since higher layers of the hierarchical category represent more general kinds of products, a reliable degree is differently determined according to the layers. Hence, reliable degrees from different layers of a hierarchical category become features for keywords and they are used together with features only from specifications for classification of the keywords. Support Vector Machines are adopted as a basic classifier using the features, since it is powerful, and widely used in many classification tasks. In the experiments, the proposed method is evaluated with a golden standard dataset from Yi-han-wang, a Chinese C2C e-commerce, and is compared with a baseline method that does not consider the hierarchical category. The experimental results show that the proposed method outperforms the baseline in F1-measure, which proves that spam keywords are effectively identified by a hierarchical category in C2C e-commerce.Keywords: spam keyword, e-commerce, keyword features, spam filtering
Procedia PDF Downloads 2923822 Comparison of Presented Definitions to Authenticity and Integrity
Authors: Golnaz Salehi Mourkani
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Two conception of Integrity and authenticity, in texts have just applied respectively for adaptive reuse and conservation, which in comparison with word “Integrity” in texts related to adaptive reuse is much more seen than Authenticity, which is often applied with conservation. According to Stove, H., (2007) in some cases, this conception have used with this form “integrity/authenticity” in texts, that cause to infer one conception of both. In this article, with referring to definitions and comparison of aspects specialized to both concept of “Authenticity and Integrity” through literature review, it was attempted to examine common and distinctive aspects of each one, then with this method we can reach their differences in adaptive reuse.Keywords: adaptive reuse, integrity, authenticity, conservation
Procedia PDF Downloads 4203821 Aspects of Diglossia in Arabic Language Learning
Authors: Adil Ishag
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Diglossia emerges in a situation where two distinctive varieties of a language are used alongside within a certain community. In this case, one is considered as a high or standard variety and the second one as a low or colloquial variety. Arabic is an extreme example of a highly diglossic language. This diglossity is due to the fact that Arabic is one of the most spoken languages and spread over 22 Countries in two continents as a mother tongue, and it is also widely spoken in many other Islamic countries as a second language or simply the language of Quran. The geographical variation between the countries where the language is spoken and the duality of the classical Arabic and daily spoken dialects in the Arab world on the other hand; makes the Arabic language one of the most diglossic languages. This paper tries to investigate this phenomena and its relation to learning Arabic as a first and second language.Keywords: Arabic language, diglossia, first and second language, language learning
Procedia PDF Downloads 5573820 The Influence of Microscopic Features on the Self-Cleaning Ability of Developed 3D Printed Fabric-Like Structures Using Different Printing Parameters
Authors: Ayat Adnan Atwah, Muhammad A. Khan
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Self-cleaning surfaces are getting significant attention in industrial fields. Especially for textile fabrics, it is observed that self-cleaning textile fabric surfaces are created by manipulating the surface features with the help of coatings and nanoparticles, which are considered costly and far more complicated. However, controlling the fabrication parameters of textile fabrics at the microscopic level by exploring the potential for self-cleaning has not been addressed. This study aimed to establish the context of self-cleaning textile fabrics by controlling the fabrication parameters of the textile fabric at the microscopic level. Therefore, 3D-printed textile fabrics were fabricated using the low-cost fused filament fabrication (FFF) technique. The printing parameters, such as orientation angle (O), layer height (LH), and extruder width (EW), were used to control the microscopic features of the printed fabrics. The combination of three printing parameters was created to provide the best self-cleaning textile fabric surface: (LH) (0.15, 0.13, 0.10 mm) and (EW) (0.5, 0.4, 0.3 mm) along with two different (O) of (45º and 90º). Three different thermoplastic flexible filament materials were used: (TPU 98A), (TPE felaflex), and (TPC flex45). The printing parameters were optimised to get the optimum self-cleaning ability of the printed specimens. Furthermore, the impact of these characteristics on mechanical strength at the fabric-woven structure level was investigated. The study revealed that the printing parameters significantly affect the self-cleaning properties after adjusting the selected combination of layer height, extruder width, and printing orientation. A linear regression model was effectively developed to demonstrate the association between 3D printing parameters (layer height, extruder width, and orientation). According to the experimental results, (TPE felaflex) has a better self-cleaning ability than the other two materials.Keywords: 3D printing, self-cleaning fabric, microscopic features, printing parameters, fabrication
Procedia PDF Downloads 793819 A New Approach to Predicting Physical Biometrics from Behavioural Biometrics
Authors: Raid R. O. Al-Nima, S. S. Dlay, W. L. Woo
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A relationship between face and signature biometrics is established in this paper. A new approach is developed to predict faces from signatures by using artificial intelligence. A multilayer perceptron (MLP) neural network is used to generate face details from features extracted from signatures, here face is the physical biometric and signatures is the behavioural biometric. The new method establishes a relationship between the two biometrics and regenerates a visible face image from the signature features. Furthermore, the performance efficiencies of our new technique are demonstrated in terms of minimum error rates compared to published work.Keywords: behavioural biometric, face biometric, neural network, physical biometric, signature biometric
Procedia PDF Downloads 4693818 K-Means Based Matching Algorithm for Multi-Resolution Feature Descriptors
Authors: Shao-Tzu Huang, Chen-Chien Hsu, Wei-Yen Wang
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Matching high dimensional features between images is computationally expensive for exhaustive search approaches in computer vision. Although the dimension of the feature can be degraded by simplifying the prior knowledge of homography, matching accuracy may degrade as a tradeoff. In this paper, we present a feature matching method based on k-means algorithm that reduces the matching cost and matches the features between images instead of using a simplified geometric assumption. Experimental results show that the proposed method outperforms the previous linear exhaustive search approaches in terms of the inlier ratio of matched pairs.Keywords: feature matching, k-means clustering, SIFT, RANSAC
Procedia PDF Downloads 3483817 Hybrid Approach for Face Recognition Combining Gabor Wavelet and Linear Discriminant Analysis
Authors: A: Annis Fathima, V. Vaidehi, S. Ajitha
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Face recognition system finds many applications in surveillance and human computer interaction systems. As the applications using face recognition systems are of much importance and demand more accuracy, more robustness in the face recognition system is expected with less computation time. In this paper, a hybrid approach for face recognition combining Gabor Wavelet and Linear Discriminant Analysis (HGWLDA) is proposed. The normalized input grayscale image is approximated and reduced in dimension to lower the processing overhead for Gabor filters. This image is convolved with bank of Gabor filters with varying scales and orientations. LDA, a subspace analysis techniques are used to reduce the intra-class space and maximize the inter-class space. The techniques used are 2-dimensional Linear Discriminant Analysis (2D-LDA), 2-dimensional bidirectional LDA ((2D)2LDA), Weighted 2-dimensional bidirectional Linear Discriminant Analysis (Wt (2D)2 LDA). LDA reduces the feature dimension by extracting the features with greater variance. k-Nearest Neighbour (k-NN) classifier is used to classify and recognize the test image by comparing its feature with each of the training set features. The HGWLDA approach is robust against illumination conditions as the Gabor features are illumination invariant. This approach also aims at a better recognition rate using less number of features for varying expressions. The performance of the proposed HGWLDA approaches is evaluated using AT&T database, MIT-India face database and faces94 database. It is found that the proposed HGWLDA approach provides better results than the existing Gabor approach.Keywords: face recognition, Gabor wavelet, LDA, k-NN classifier
Procedia PDF Downloads 4643816 Malate Dehydrogenase Enabled ZnO Nanowires as an Optical Tool for Malic Acid Detection in Horticultural Products
Authors: Rana Tabassum, Ravi Kant, Banshi D. Gupta
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Malic acid is an extensively distributed organic acid in numerous horticultural products in minute amounts which significantly contributes towards taste determination by balancing sugar and acid fractions. An enhanced concentration of malic acid is utilized as an indicator of fruit maturity. In addition, malic acid is also a crucial constituent of several cosmetics and pharmaceutical products. An efficient detection and quantification protocol for malic acid is thus highly demanded. In this study, we report a novel detection scheme for malic acid by synergistically collaborating fiber optic surface plasmon resonance (FOSPR) and distinctive features of nanomaterials favorable for sensing applications. The design blueprint involves the deposition of an assembly of malate dehydrogenase enzyme entrapped in ZnO nanowires forming the sensing route over silver coated central unclad core region of an optical fiber. The formation and subsequent decomposition of the enzyme-analyte complex on exposure of the sensing layer to malic acid solutions of diverse concentration results in modification of the dielectric function of the sensing layer which is manifested in terms of shift in resonance wavelength. Optimization of experimental variables such as enzyme concentration entrapped in ZnO nanowires, dip time of probe for deposition of sensing layer and working pH range of the sensing probe have been accomplished through SPR measurements. The optimized sensing probe displays high sensitivity, broad working range and a minimum limit of detection value and has been successfully tested for malic acid determination in real samples of fruit juices. The current work presents a novel perspective towards malic acid determination as the unique and cooperative combination of FOSPR and nanomaterials provides myriad advantages such as enhanced sensitivity, specificity, compactness together with the possibility of online monitoring and remote sensing.Keywords: surface plasmon resonance, optical fiber, sensor, malic acid
Procedia PDF Downloads 3763815 Design and Implementation of an Image Based System to Enhance the Security of ATM
Authors: Seyed Nima Tayarani Bathaie
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In this paper, an image-receiving system was designed and implemented through optimization of object detection algorithms using Haar features. This optimized algorithm served as face and eye detection separately. Then, cascading them led to a clear image of the user. Utilization of this feature brought about higher security by preventing fraud. This attribute results from the fact that services will be given to the user on condition that a clear image of his face has already been captured which would exclude the inappropriate person. In order to expedite processing and eliminating unnecessary ones, the input image was compressed, a motion detection function was included in the program, and detection window size was confined.Keywords: face detection algorithm, Haar features, security of ATM
Procedia PDF Downloads 4103814 Using Bidirectional Encoder Representations from Transformers to Extract Topic-Independent Sentiment Features for Social Media Bot Detection
Authors: Maryam Heidari, James H. Jones Jr.
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Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event or product. However, this use raises an important question: what percentage of information available through these services is trustworthy? In particular, might some of this information be generated by a machine, i.e., a bot, instead of a human? Bots can be, and often are, purposely designed to generate enough volume to skew an apparent trend or position on a topic, yet the consumer of such content cannot easily distinguish a bot post from a human post. In this paper, we introduce a model for social media bot detection which uses Bidirectional Encoder Representations from Transformers (Google Bert) for sentiment classification of tweets to identify topic-independent features. Our use of a Natural Language Processing approach to derive topic-independent features for our new bot detection model distinguishes this work from previous bot detection models. We achieve 94\% accuracy classifying the contents of data as generated by a bot or a human, where the most accurate prior work achieved accuracy of 92\%.Keywords: bot detection, natural language processing, neural network, social media
Procedia PDF Downloads 1103813 Moving Object Detection Using Histogram of Uniformly Oriented Gradient
Authors: Wei-Jong Yang, Yu-Siang Su, Pau-Choo Chung, Jar-Ferr Yang
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Moving object detection (MOD) is an important issue in advanced driver assistance systems (ADAS). There are two important moving objects, pedestrians and scooters in ADAS. In real-world systems, there exist two important challenges for MOD, including the computational complexity and the detection accuracy. The histogram of oriented gradient (HOG) features can easily detect the edge of object without invariance to changes in illumination and shadowing. However, to reduce the execution time for real-time systems, the image size should be down sampled which would lead the outlier influence to increase. For this reason, we propose the histogram of uniformly-oriented gradient (HUG) features to get better accurate description of the contour of human body. In the testing phase, the support vector machine (SVM) with linear kernel function is involved. Experimental results show the correctness and effectiveness of the proposed method. With SVM classifiers, the real testing results show the proposed HUG features achieve better than classification performance than the HOG ones.Keywords: moving object detection, histogram of oriented gradient, histogram of uniformly-oriented gradient, linear support vector machine
Procedia PDF Downloads 587