Search results for: Fraudulent pattern recognition
3765 Drug Sensitivity Pattern of Organisms Causing Chronic Suppurative Otitis Media
Authors: Fatma M. Benrabha
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The aim of the study was to determine the type and pattern of antibiotic susceptibility of the pathogenic microorganisms causing chronic suppurative otitis media (CSOM), which could lead to better therapeutic decisions and consequently avoidance of appearance of resistance to specific antibiotics. Most frequently isolated agents were Pseudomonas aeruginosa 28.5%; followed by Staphylococcus aureus 18.2%; proteus mirabilis 13.9%; Providencia stuartti 6.7%; Bacteroides melaninogenicus, Aspergillus sp., candida sp., 4.2% each; and other microorganisms were represented in 3-0.2%. Drug sensitivities pattern of Pseudomonas aeruginosa showed that ciprofloxacin was active against the majority of isolates (93.9%) followed by ceftazidime 86.2%, amikacin 76.2% and gentamicin 40.8%. However, Staphylococcus aureus isolates were resistant to penicillin 72.7%, erythromycin 28.6%, cephalothin 18.2%, cloxacillin 8.3% and ciprofloxacin was active against 96.2% of isolates. The resistance pattern of proteus mirabilis were 55.6% to ampicillin, 47.1% to carbencillin, 29.4% to cephalothin, 14.3% to gentamicin and 4.8% to amikacin while 100% were sensitive to ciprofloxacin. We conclude that ciprofloxacin is the best drug of choice in treatment of CSOM caused by the common microorganisms.Keywords: otitis media, chronic suppurative otitis media (CSOM), microorganism, drug sensitivity
Procedia PDF Downloads 4043764 The Influence of Job Recognition and Job Motivation on Organizational Commitment in Public Sector: The Mediation Role of Employee Engagement
Authors: Muhammad Tayyab, Saba Saira
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It is an established fact that organizations across the globe consider employees as their assets and try to advance their well-being. However, the local firms of developing countries are mostly profit oriented and do not have much concern about their employees’ engagement or commitment. Like other developing countries, the local organizations of Pakistan are also less concerned about the well-being of their employees. Especially public sector organizations lack concern regarding engagement, satisfaction or commitment of the employees. Therefore, this study aimed at investigating the impact of job recognition and job motivation on organizational commitment in the mediation role of employee engagement. The data were collected from land record officers of board of revenue, Punjab, Pakistan. Structured questionnaire was used to collect data through physically visiting land record officers and also through the internet. A total of 318 land record officers’ responses were finalized to perform data analysis. The data were analyzed through confirmatory factor analysis and structural equation modeling technique. The findings revealed that job recognition and job motivation have direct as well as indirect positive and significant impact on organizational commitment. The limitations, practical implications and future research indications are also explained.Keywords: job motivation, job recognition, employee engagement, employee commitment, public sector, land record officers
Procedia PDF Downloads 1363763 Applying Sequential Pattern Mining to Generate Block for Scheduling Problems
Authors: Meng-Hui Chen, Chen-Yu Kao, Chia-Yu Hsu, Pei-Chann Chang
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The main idea in this paper is using sequential pattern mining to find the information which is helpful for finding high performance solutions. By combining this information, it is defined as blocks. Using the blocks to generate artificial chromosomes (ACs) could improve the structure of solutions. Estimation of Distribution Algorithms (EDAs) is adapted to solve the combinatorial problems. Nevertheless many of these approaches are advantageous for this application, but only some of them are used to enhance the efficiency of application. Generating ACs uses patterns and EDAs could increase the diversity. According to the experimental result, the algorithm which we proposed has a better performance to solve the permutation flow-shop problems.Keywords: combinatorial problems, sequential pattern mining, estimationof distribution algorithms, artificial chromosomes
Procedia PDF Downloads 6123762 An Automatic Speech Recognition of Conversational Telephone Speech in Malay Language
Authors: M. Draman, S. Z. Muhamad Yassin, M. S. Alias, Z. Lambak, M. I. Zulkifli, S. N. Padhi, K. N. Baharim, F. Maskuriy, A. I. A. Rahim
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The performance of Malay automatic speech recognition (ASR) system for the call centre environment is presented. The system utilizes Kaldi toolkit as the platform to the entire library and algorithm used in performing the ASR task. The acoustic model implemented in this system uses a deep neural network (DNN) method to model the acoustic signal and the standard (n-gram) model for language modelling. With 80 hours of training data from the call centre recordings, the ASR system can achieve 72% of accuracy that corresponds to 28% of word error rate (WER). The testing was done using 20 hours of audio data. Despite the implementation of DNN, the system shows a low accuracy owing to the varieties of noises, accent and dialect that typically occurs in Malaysian call centre environment. This significant variation of speakers is reflected by the large standard deviation of the average word error rate (WERav) (i.e., ~ 10%). It is observed that the lowest WER (13.8%) was obtained from recording sample with a standard Malay dialect (central Malaysia) of native speaker as compared to 49% of the sample with the highest WER that contains conversation of the speaker that uses non-standard Malay dialect.Keywords: conversational speech recognition, deep neural network, Malay language, speech recognition
Procedia PDF Downloads 3233761 Local Image Features Emerging from Brain Inspired Multi-Layer Neural Network
Authors: Hui Wei, Zheng Dong
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Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.Keywords: biological model, feature extraction, multi-layer neural network, object recognition
Procedia PDF Downloads 5443760 A New Lateral Load Pattern for Pushover Analysis of RC Frame Structures
Authors: Mohammad Reza Ameri, Ali Massumi, Mohammad Haghbin
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Non-linear static analysis, commonly referred to as pushover analysis, is a powerful tool for assessing the seismic response of structures. A suitable lateral load pattern for pushover analysis can bring the results of this simple, quick and low-cost analysis close to the realistic results of nonlinear dynamic analyses. In this research, four samples of 10- and 15 story (two- and four-bay) reinforced concrete frames were studied. The lateral load distribution patterns recommended in FEMA 273/356 guidelines were applied to the sample models in order to perform pushover analyses. The results were then compared to the results obtained from several nonlinear incremental dynamic analyses for a range of earthquakes. Finally, a lateral load distribution pattern was proposed for pushover analysis of medium-rise reinforced concrete buildings based on the results of nonlinear static and dynamic analyses.Keywords: lateral load pattern, nonlinear static analysis, incremental dynamic analysis, medium-rise reinforced concrete frames, performance based design
Procedia PDF Downloads 4783759 The Combination of the Mel Frequency Cepstral Coefficients (MFCC), Perceptual Linear Prediction (PLP), JITTER and SHIMMER Coefficients for the Improvement of Automatic Recognition System for Dysarthric Speech
Authors: Brahim-Fares Zaidi, Malika Boudraa, Sid-Ahmed Selouani
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Our work aims to improve our Automatic Recognition System for Dysarthria Speech (ARSDS) based on the Hidden Models of Markov (HMM) and the Hidden Markov Model Toolkit (HTK) to help people who are sick. With pronunciation problems, we applied two techniques of speech parameterization based on Mel Frequency Cepstral Coefficients (MFCC's) and Perceptual Linear Prediction (PLP's) and concatenated them with JITTER and SHIMMER coefficients in order to increase the recognition rate of a dysarthria speech. For our tests, we used the NEMOURS database that represents speakers with dysarthria and normal speakers.Keywords: hidden Markov model toolkit (HTK), hidden models of Markov (HMM), Mel-frequency cepstral coefficients (MFCC), perceptual linear prediction (PLP’s)
Procedia PDF Downloads 1643758 A Two-Stage Adaptation towards Automatic Speech Recognition System for Malay-Speaking Children
Authors: Mumtaz Begum Mustafa, Siti Salwah Salim, Feizal Dani Rahman
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Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.Keywords: Automatic Speech Recognition System, children speech, adaptation, Malay
Procedia PDF Downloads 3983757 Facial Expression Phoenix (FePh): An Annotated Sequenced Dataset for Facial and Emotion-Specified Expressions in Sign Language
Authors: Marie Alaghband, Niloofar Yousefi, Ivan Garibay
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Facial expressions are important parts of both gesture and sign language recognition systems. Despite the recent advances in both fields, annotated facial expression datasets in the context of sign language are still scarce resources. In this manuscript, we introduce an annotated sequenced facial expression dataset in the context of sign language, comprising over 3000 facial images extracted from the daily news and weather forecast of the public tv-station PHOENIX. Unlike the majority of currently existing facial expression datasets, FePh provides sequenced semi-blurry facial images with different head poses, orientations, and movements. In addition, in the majority of images, identities are mouthing the words, which makes the data more challenging. To annotate this dataset we consider primary, secondary, and tertiary dyads of seven basic emotions of "sad", "surprise", "fear", "angry", "neutral", "disgust", and "happy". We also considered the "None" class if the image’s facial expression could not be described by any of the aforementioned emotions. Although we provide FePh as a facial expression dataset of signers in sign language, it has a wider application in gesture recognition and Human Computer Interaction (HCI) systems.Keywords: annotated facial expression dataset, gesture recognition, sequenced facial expression dataset, sign language recognition
Procedia PDF Downloads 1603756 Multi-Agent Railway Control System: Requirements Definitions of Multi-Agent System Using the Behavioral Patterns Analysis (BPA) Approach
Authors: Assem I. El-Ansary
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This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Multi-Agent Railway Control System (MARCS). The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are the Behavioral Pattern Analysis (BPA) modeling methodology, and the development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.Keywords: analysis, multi-agent, railway control, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases
Procedia PDF Downloads 5473755 Lip Localization Technique for Myanmar Consonants Recognition Based on Lip Movements
Authors: Thein Thein, Kalyar Myo San
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Lip reading system is one of the different supportive technologies for hearing impaired, or elderly people or non-native speakers. For normal hearing persons in noisy environments or in conditions where the audio signal is not available, lip reading techniques can be used to increase their understanding of spoken language. Hearing impaired persons have used lip reading techniques as important tools to find out what was said by other people without hearing voice. Thus, visual speech information is important and become active research area. Using visual information from lip movements can improve the accuracy and robustness of a speech recognition system and the need for lip reading system is ever increasing for every language. However, the recognition of lip movement is a difficult task because of the region of interest (ROI) is nonlinear and noisy. Therefore, this paper proposes method to detect the accurate lips shape and to localize lip movement towards automatic lip tracking by using the combination of Otsu global thresholding technique and Moore Neighborhood Tracing Algorithm. Proposed method shows how accurate lip localization and tracking which is useful for speech recognition. In this work of study and experiments will be carried out the automatic lip localizing the lip shape for Myanmar consonants using the only visual information from lip movements which is useful for visual speech of Myanmar languages.Keywords: lip reading, lip localization, lip tracking, Moore neighborhood tracing algorithm
Procedia PDF Downloads 3533754 A Discovery on the Symmetrical Pattern of Mirror Primes in P²: Applications in the Formal Proof of the Goldbach Conjecture
Authors: Yingxu Wang
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The base 6 structure and properties of mirror primes are discovered in this work towards the proof of Goldbach Conjecture. This paper reveals a fundamental pattern on pairs of mirror primes adjacent to any even number nₑ > 2 with symmetrical distances on both sides determined by a methodology of Mirror Prime Decomposition (MPD). MPD leads to a formal proof of the Goldbach conjecture, which states that the conjecture holds because any pivot even number, nₑ > 2, is a sum of at least an adjacent pair of primes divided by 2. This work has not only revealed the analytic pattern of base 6 primes but also proven the infinitive validation of the Goldbach conjecture.Keywords: number theory, primes, mirror primes, double recursive patterns, Goldbach conjecture, formal proof, mirror-prime decomposition, applications
Procedia PDF Downloads 523753 Drug Sensitivity Pattern of Organisms Causing Suppurative Otitis Media
Authors: Nagat M. Saeed, Mabruka S. Elashheb, Fatma M. Ben Rabaha, Aisha M Edrah
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The aim of the study was to determine the type and pattern of antibiotic susceptibility of the pathogenic microorganisms causing chronic suppurative otitis media (CSOM), which could lead to better therapeutic decisions and consequently avoidance of appearance of resistance to specific antibiotics. Most frequently isolated agents were Pseudomonas aeruginosa 28.5%; followed by Staphylococcus aureus 18.2%; proteus mirabilis 13.9%; Providencia stuartti 6.7%; Bacteroides melaninogenicus, Aspergillus sp., candida sp., 4.2% each; and other microorganisms were represented in 3-0.2%. Drug sensitivities pattern of Pseudomonas aeruginosa showed that ciprofloxacin was active against the majority of isolates (93.9%) followed by ceftazidime 86.2%, amikacin 76.2% and gentamicin 40.8%. However, Staphylococcus aureus isolates were resistant to penicillin 72.7%, erythromycin 28.6%, cephalothin 18.2%, cloxacillin 8.3% and ciprofloxacin was active against 96.2% of isolates. The resistance pattern of proteus mirabilis was 55.6% to ampicillin, 47.1% to carbencillin, 29.4% to cephalothin, 14.3% to gentamicin and 4.8% to amikacin while 100% were sensitive to ciprofloxacin. We conclude that ciprofloxacin is the best drug of choice in the treatment of CSOM caused by the common microorganisms.Keywords: otitis media, chronic suppurative otitis media (CSOM), microorganisms, drug sensitivity
Procedia PDF Downloads 3473752 Humanitarian Emergency of the Refugee Condition for Central American Immigrants in Irregular Situation
Authors: María de los Ángeles Cerda González, Itzel Arriaga Hurtado, Pascacio José Martínez Pichardo
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In México, the recognition of refugee condition is a fundamental right which, as host State, has the obligation of respect, protect, and fulfill to the foreigners – where we can find the figure of immigrants in irregular situation-, that cannot return to their country of origin for humanitarian reasons. The recognition of the refugee condition as a fundamental right in the Mexican law system proceeds under these situations: 1. The immigrant applies for the refugee condition, even without the necessary proving elements to accredit the humanitarian character of his departure from his country of origin. 2. The immigrant does not apply for the recognition of refugee because he does not know he has the right to, even if he has the profile to apply for. 3. The immigrant who applies fulfills the requirements of the administrative procedure and has access to the refugee recognition. Of the three situations above, only the last one is contemplated for the national indexes of the status refugee; and the first two prove the inefficiency of the governmental system viewed from its lack of sensibility consequence of the no education in human rights matter and which results in the legal vulnerability of the immigrants in irregular situation because they do not have access to the procuration and administration of justice. In the aim of determining the causes and consequences of the no recognition of the refugee status, this investigation was structured from a systemic analysis which objective is to show the advances in Central American humanitarian emergency investigation, the Mexican States actions to protect, respect and fulfil the fundamental right of refugee of immigrants in irregular situation and the social and legal vulnerabilities suffered by Central Americans in Mexico. Therefore, to achieve the deduction of the legal nature of the humanitarian emergency from the Human Rights as a branch of the International Public Law, a conceptual framework is structured using the inductive deductive method. The problem statement is made from a legal framework to approach a theoretical scheme under the theory of social systems, from the analysis of the lack of communication of the governmental and normative subsystems of the Mexican legal system relative to the process undertaken by the Central American immigrants to achieve the recognition of the refugee status as a human right. Accordingly, is determined that fulfilling the obligations of the State referent to grant the right of the recognition of the refugee condition, would mean a guideline for a new stage in Mexican Law, because it would enlarge the constitutional benefits to everyone whose right to the recognition of refugee has been denied an as consequence, a great advance in human rights matter would be achieved.Keywords: central American immigrants in irregular situation, humanitarian emergency, human rights, refugee
Procedia PDF Downloads 2913751 Hand Symbol Recognition Using Canny Edge Algorithm and Convolutional Neural Network
Authors: Harshit Mittal, Neeraj Garg
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Hand symbol recognition is a pivotal component in the domain of computer vision, with far-reaching applications spanning sign language interpretation, human-computer interaction, and accessibility. This research paper discusses the approach with the integration of the Canny Edge algorithm and convolutional neural network. The significance of this study lies in its potential to enhance communication and accessibility for individuals with hearing impairments or those engaged in gesture-based interactions with technology. In the experiment mentioned, the data is manually collected by the authors from the webcam using Python codes, to increase the dataset augmentation, is applied to original images, which makes the model more compatible and advanced. Further, the dataset of about 6000 coloured images distributed equally in 5 classes (i.e., 1, 2, 3, 4, 5) are pre-processed first to gray images and then by the Canny Edge algorithm with threshold 1 and 2 as 150 each. After successful data building, this data is trained on the Convolutional Neural Network model, giving accuracy: 0.97834, precision: 0.97841, recall: 0.9783, and F1 score: 0.97832. For user purposes, a block of codes is built in Python to enable a window for hand symbol recognition. This research, at its core, seeks to advance the field of computer vision by providing an advanced perspective on hand sign recognition. By leveraging the capabilities of the Canny Edge algorithm and convolutional neural network, this study contributes to the ongoing efforts to create more accurate, efficient, and accessible solutions for individuals with diverse communication needs.Keywords: hand symbol recognition, computer vision, Canny edge algorithm, convolutional neural network
Procedia PDF Downloads 663750 Input Data Balancing in a Neural Network PM-10 Forecasting System
Authors: Suk-Hyun Yu, Heeyong Kwon
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Recently PM-10 has become a social and global issue. It is one of major air pollutants which affect human health. Therefore, it needs to be forecasted rapidly and precisely. However, PM-10 comes from various emission sources, and its level of concentration is largely dependent on meteorological and geographical factors of local and global region, so the forecasting of PM-10 concentration is very difficult. Neural network model can be used in the case. But, there are few cases of high concentration PM-10. It makes the learning of the neural network model difficult. In this paper, we suggest a simple input balancing method when the data distribution is uneven. It is based on the probability of appearance of the data. Experimental results show that the input balancing makes the neural networks’ learning easy and improves the forecasting rates.Keywords: artificial intelligence, air quality prediction, neural networks, pattern recognition, PM-10
Procedia PDF Downloads 2333749 Shiite and Secular Approaches to Gender Minorities: A Comparative Study of Iran, Turkey, and Germany
Authors: Morteza Azimi
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The demand for recognition among LGBTQIA+ groups has grown significantly in modern times, particularly since the second half of the twentieth century, when human rights discourse became increasingly prominent, especially in the West. In contrast, the classic readings of the Quran and Hadith, whose roots lie in pre-modern times, and the Shiite Figh (Islamic jurisprudence) seem not to be updated and responsive to the need for recognition by gender minority identities. Moreover, the recognition of such minority identities within Shiite Islam and its intersection with secular frameworks remains an underexplored topic. This paper explores what Islamic texts, such as the Quran, Hadith, and Shiite Fiqh, address regarding the recognition and rights of gender minorities. It further examines the Islamic Republic of Iran as an example of a dominant Shiite political system, comparing it with Turkey and Germany as secular models. While Turkey, a secular state, is deeply influenced by its predominantly Muslim population and culture, Germany represents a Western model characterized by the widespread recognition of LGBTQIA+ rights. The rationale for this comparative approach lies in understanding how different political systems influence the recognition of gender minorities. Moreover, the study investigates whether Shiite Islamic frameworks can provide solutions to these demands or whether secular systems, as exemplified by Turkey and Germany, are more effective in addressing issues of gender minorities. Hence, this study offers a novel perspective by juxtaposing Shiite Islamic textual interpretations with secular legal frameworks to explore the evolving recognition of gender minorities, demonstrating how varying political and cultural contexts shape the lived experiences of LGBTQIA+ individuals in Iran, Turkey, and Germany. This research relies on secondary literature as the primary data source, especially regarding the issue of gender in Shiite Islamic texts. The author employs a comparative textual analysis of Shiite Islamic texts (e.g., Quran, Hadith, and Fiqh) and secular legal frameworks in Turkey and Germany to explore how different systems address the recognition of gender minorities. Findings reveal that classical interpretations of Islamic texts and Shiite Fiqh employed by the Islamic Republic of Iran fail to provide laws and frameworks that recognize LGBTQIA+ identities. This gap contributes to the marginalization of gender minority identities, fostering environments of suppression, violence, and exclusion. The findings of this study could inform policymaking and advocacy efforts by shedding light on the necessity of a change toward inclusive legal and cultural frameworks for gender minorities in Muslim countries like Iran.Keywords: gender minorities, LGBTQIA+ recognition, shiite islam, comparative analysis
Procedia PDF Downloads 73748 Multimodal Database of Emotional Speech, Video and Gestures
Authors: Tomasz Sapiński, Dorota Kamińska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari
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People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.Keywords: body movement, emotion recognition, emotional corpus, facial expressions, gestures, multimodal database, speech
Procedia PDF Downloads 3493747 An Approach for Vocal Register Recognition Based on Spectral Analysis of Singing
Authors: Aleksandra Zysk, Pawel Badura
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Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.Keywords: classification, singing, spectral analysis, vocal emission, vocal register
Procedia PDF Downloads 3053746 An Introduction to Giulia Annalinda Neglia Viewpoint on Morphology of the Islamic City Using Written Content Analysis Approach
Authors: Mohammad Saber Eslamlou
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Morphology of Islamic cities has been extensively studied by researchers of Islamic cities and different theories could be found about it. In this regard, there exist much difference in method of analysis, classification, recognition, confrontation and comparative method of urban morphology. The present paper aims to examine the previous methods, approaches and insights and that how Dr. Giulia Annalinda Neglia dealt with the analysis of morphology of Islamic cities. Neglia is assistant professor in University of Bari, Italy (UNIBA) who has published numerous papers and books on Islamic cities. I introduce her works in the field of morphology of Islamic cities. And then, her thoughts, insights and research methodologies are presented and analyzed in critical perspective. This is a qualitative research on her written works, which have been classified in three major categories. The first category consists mainly of her works on morphology and physical shape of Islamic cities. The results of her works’ review suggest that she has used Moratoria typology in investigating morphology of Islamic cities. Moreover, overall structure of the cities under investigation is often described linear; however, she’s against to define a single framework for the recognition of morphology in Islamic cities. She states that ‘to understand the physical complexity and irregularities in Islamic cities, it is necessary to study the urban fabric by typology method, focusing on transformation processes of the buildings’ form and their surrounding open spaces’ and she believes that fabric of each region in the city follows from the principles of an specific period or urban pattern, in particular, Hellenistic and Roman structures. Furthermore, she believes that it is impossible to understand the morphology of a city without taking into account the obvious and hidden developments associated with it, because form of building and their surrounding open spaces are written history of the city.Keywords: city, Islamic city, Giulia Annalinda Neglia, morphology
Procedia PDF Downloads 983745 ViraPart: A Text Refinement Framework for Automatic Speech Recognition and Natural Language Processing Tasks in Persian
Authors: Narges Farokhshad, Milad Molazadeh, Saman Jamalabbasi, Hamed Babaei Giglou, Saeed Bibak
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The Persian language is an inflectional subject-object-verb language. This fact makes Persian a more uncertain language. However, using techniques such as Zero-Width Non-Joiner (ZWNJ) recognition, punctuation restoration, and Persian Ezafe construction will lead us to a more understandable and precise language. In most of the works in Persian, these techniques are addressed individually. Despite that, we believe that for text refinement in Persian, all of these tasks are necessary. In this work, we proposed a ViraPart framework that uses embedded ParsBERT in its core for text clarifications. First, used the BERT variant for Persian followed by a classifier layer for classification procedures. Next, we combined models outputs to output cleartext. In the end, the proposed model for ZWNJ recognition, punctuation restoration, and Persian Ezafe construction performs the averaged F1 macro scores of 96.90%, 92.13%, and 98.50%, respectively. Experimental results show that our proposed approach is very effective in text refinement for the Persian language.Keywords: Persian Ezafe, punctuation, ZWNJ, NLP, ParsBERT, transformers
Procedia PDF Downloads 2183744 Enhancing Traditional Saudi Designs Pattern Cutting to Integrate Them Into Current Clothing Offers
Authors: Faizah Almalki, Simeon Gill, Steve G. Hayes, Lisa Taylor
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A core element of cultural identity is the traditional costumes that provide insight into the heritage that has been acquired over time. This heritage is apparent in the use of colour, the styles and the functions of the clothing and it also reflects the skills of those who created the items and the time taken to produce them. Modern flat pattern drafting methods for making garment patterns are simple in comparison to the relatively laborious traditional approaches that would require personal interaction with the wearer throughout the production process. The current study reflects on the main elements of the pattern cutting system and how this has evolved in Saudi Arabia to affect the design of the Sawan garment. Analysis of the traditional methods for constructing Sawan garments was undertaken through observation of the practice and the garments and consulting documented guidance. This provided a foundation through which to explore how modern technology can be applied to improve the process. In this research, modern methods are proposed for producing traditional Saudi garments more efficiently while retaining elements of the conventional style and design. The current study has documented the vital aspects of Sawan garment style. The result showed that the method had been used to take the body measurements and pattern making was elementary and offered simple geometric shape and the Sawan garment is composed of four pieces. Consequently, this research allows for classical pattern shapes to be embedded in garments now worn in Saudi Arabia and for the continuation of cultural heritage.Keywords: traditional Sawan garment technique, modern pattern cutting technique, the shape of the garment and software, Lectra Modaris
Procedia PDF Downloads 1333743 Cross Attention Fusion for Dual-Stream Speech Emotion Recognition
Authors: Shaode Yu, Jiajian Meng, Bing Zhu, Hang Yu, Qiurui Sun
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Speech emotion recognition (SER) is for recognizing human subjective emotions through audio data in-depth analysis. From speech audios, how to comprehensively extract emotional information and how to effectively fuse extracted features remain challenging. This paper presents a dual-stream SER framework that embraces both full training and transfer learning of different networks for thorough feature encoding. Besides, a plug-and-play cross-attention fusion (CAF) module is implemented for the valid integration of the dual-stream encoder output. The effectiveness of the proposed CAF module is compared to the other three fusion modules (feature summation, feature concatenation, and feature-wise linear modulation) on two databases (RAVDESS and IEMO-CAP) using different dual-stream encoders (full training network, DPCNN or TextRCNN; transfer learning network, HuBERT or Wav2Vec2). Experimental results suggest that the CAF module can effectively reconcile conflicts between features from different encoders and outperform the other three feature fusion modules on the SER task. In the future, the plug-and-play CAF module can be extended for multi-branch feature fusion, and the dual-stream SER framework can be widened for multi-stream data representation to improve the recognition performance and generalization capacity.Keywords: speech emotion recognition, cross-attention fusion, dual-stream, pre-trained
Procedia PDF Downloads 793742 Predicting Medical Check-Up Patient Re-Coming Using Sequential Pattern Mining and Association Rules
Authors: Rizka Aisha Rahmi Hariadi, Chao Ou-Yang, Han-Cheng Wang, Rajesri Govindaraju
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As the increasing of medical check-up popularity, there are a huge number of medical check-up data stored in database and have not been useful. These data actually can be very useful for future strategic planning if we mine it correctly. In other side, a lot of patients come with unpredictable coming and also limited available facilities make medical check-up service offered by hospital not maximal. To solve that problem, this study used those medical check-up data to predict patient re-coming. Sequential pattern mining (SPM) and association rules method were chosen because these methods are suitable for predicting patient re-coming using sequential data. First, based on patient personal information the data was grouped into … groups then discriminant analysis was done to check significant of the grouping. Second, for each group some frequent patterns were generated using SPM method. Third, based on frequent patterns of each group, pairs of variable can be extracted using association rules to get general pattern of re-coming patient. Last, discussion and conclusion was done to give some implications of the results.Keywords: patient re-coming, medical check-up, health examination, data mining, sequential pattern mining, association rules, discriminant analysis
Procedia PDF Downloads 6423741 Algorithm for Path Recognition in-between Tree Rows for Agricultural Wheeled-Mobile Robots
Authors: Anderson Rocha, Pedro Miguel de Figueiredo Dinis Oliveira Gaspar
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Machine vision has been widely used in recent years in agriculture, as a tool to promote the automation of processes and increase the levels of productivity. The aim of this work is the development of a path recognition algorithm based on image processing to guide a terrestrial robot in-between tree rows. The proposed algorithm was developed using the software MATLAB, and it uses several image processing operations, such as threshold detection, morphological erosion, histogram equalization and the Hough transform, to find edge lines along tree rows on an image and to create a path to be followed by a mobile robot. To develop the algorithm, a set of images of different types of orchards was used, which made possible the construction of a method capable of identifying paths between trees of different heights and aspects. The algorithm was evaluated using several images with different characteristics of quality and the results showed that the proposed method can successfully detect a path in different types of environments.Keywords: agricultural mobile robot, image processing, path recognition, hough transform
Procedia PDF Downloads 1473740 Multi-Agent TeleRobotic Security Control System: Requirements Definitions of Multi-Agent System Using The Behavioral Patterns Analysis (BPA) Approach
Authors: Assem El-Ansary
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This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Multi-Agent TeleRobotic Security Control System (MTSCS). The event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are the Behavioral Pattern Analysis (BPA) modeling methodology, and the development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.Keywords: analysis, multi-agent, TeleRobotics control, security, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases
Procedia PDF Downloads 4393739 Deep Learning Application for Object Image Recognition and Robot Automatic Grasping
Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting
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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator
Procedia PDF Downloads 2503738 Shrinkage Evaluation in a Stepped Wax Pattern – a Simulation Approach
Authors: Alok S Chauhan, Sridhar S., Pradyumna R.
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In the process of precision investment casting of turbine hollow blade/vane components, a part of the dimensional deviations observed in the castings can be attributed to the wax pattern. In the process of injection moulding of wax to produce patterns, heated wax shrinks in size during cooling in the die, leading to a reduction in the dimensions of the pattern. Also, flow and thermal induced residual stresses result in shrinkage & warpage of the component after removal from the die, further adding to the deviations. Injection moulding parameters such as wax temperature, flow rate, packing pressure, etc. affect the flow and thermal behavior of the component and hence are directly responsible for the dimensional deviations. There is a need to precisely determine and control these deviations in order to achieve stringent dimensional accuracies imposed on these castings by aerospace standards. Simulation based approaches provide a platform to predict these dimensional deviations without resorting to elaborate experimentation. In the present paper, Moldex3D simulation package has been utilized to analyze the effect of variations in injection temperature, packing pressure and cooling time on the shrinkage behavior of a stepped pattern. Two types of waxes with different rheological properties have been included in the study to gauge the effect of change in wax on the dimensional deviations. A full factorial design of experiments has been configured with these parameters and results of analysis of variance have been presented.Keywords: wax patterns, investment casting, pattern die/mould, wax injection, Moldex3D simulation
Procedia PDF Downloads 3743737 A Computational Cost-Effective Clustering Algorithm in Multidimensional Space Using the Manhattan Metric: Application to the Global Terrorism Database
Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami
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The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.Keywords: pattern recognition, global terrorism database, Manhattan distance, k-means clustering, terrorism data analysis
Procedia PDF Downloads 3863736 'Value-Based Re-Framing' in Identity-Based Conflicts: A Skill for Mediators in Multi-Cultural Societies
Authors: Hami-Ziniman Revital, Ashwall Rachelly
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The conflict resolution realm has developed tremendously during the last half-decade. Three main approaches should be mentioned: an Alternative Dispute Resolution (ADR) suggesting processes such as Arbitration or Interests-based Negotiation was developed as an answer to obligations and rights-based conflicts. The Pragmatic mediation approach focuses on the gap between interests and needs of disputants. The Transformative mediation approach focusses on relations and suits identity-based conflicts. In the current study, we examine the conflictual relations between religious and non-religious Jews in Israel and the impact of three transformative mechanisms: Inter-group recognition, In-group empowerment and Value-based reframing on the relations between the participants. The research was conducted during four facilitated joint mediation classes. A unique finding was found. Using both transformative mechanisms and the Contact Hypothesis criteria, we identify transformation in participants’ relations and a considerable change from anger, alienation, and suspiciousness to an increased understanding, affection and interpersonal concern towards the out-group members. Intergroup Recognition, In-group empowerment, and Values-based reframing were the skills discovered as the main enablers of the change in the relations and the research participants’ fostered mutual recognition of the out-group values and identity-based issues. We conclude this transformation was possible due to a constant intergroup contact, based on the Contact Hypothesis criteria. In addition, as Interests-based mediation uses “Reframing” as a skill to acknowledge both mutual and opposite needs of the disputants, we suggest the use of “Value-based Reframing” in intergroup identity-based conflicts, as a skill contributes to the empowerment and the recognition of both mutual and different out-group values. We offer to implement those insights and skills to assist conflict resolution facilitators in various intergroup identity-based conflicts resolution efforts and to establish further research and knowledge.Keywords: empowerment, identity-based conflict, intergroup recognition, intergroup relations, mediation skills, multi-cultural society, reframing, value-based recognition
Procedia PDF Downloads 343