Search results for: product recognition

Authors: Cholpassorn Sitthiwarongchai

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The purposes of this paper were to search for the uniqueness of community products from Bang Khonthi District, Samut Songkram Province, Thailand and to create a proper brand for the community products. Four important questions were asked to identify the uniqueness of the community products. The first question: What is the brand of coconut sugar that community wants to imply? The answer was 100 percent authentic coconut sugar. The second question: What is the nature of this product? The answer was that it is a natural product without any harmful chemical. The third question is: Who are the target customers? The answer was that homemakers and tourists are target customers. The fourth question: What is the brand guarantee to customers? The answer was that the brand guarantees that the product is 100 percent natural process with a high quality and it is a community production. The findings revealed that in terms of product, customers rated quality and package as the two most important factors. In terms of price, customers rated lower price and a visible label as the two most important factors. In terms of place, customer rated layout and the cleanliness of the place as the two most important factors. In terms of promotion, customer rated public relations and brochure at the store as the most important factors. From the group discussion, the local community agreed that the brand for the community coconut sugar of Salapi community should be a picture of a green coconut tree and yellow color background. This brand implies the strength of community and authentic of the high quality natural product.

Keywords: coconut sugar, community brand, Samut Songkram, natural product

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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

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Authors: Y. N. Fung, R. Liu, T. M. Choi

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Over the past decades, previous studies have explored different consumers’ attitudes towards sustainable fashion and how these attitudes affect consumer behaviors. Researchers have attempted to provide solutions for product suppliers (e.g., retailers, designers, developers, and manufacturers) through studying consumers’ attitudes towards sustainable fashion. However, based on the studies of consumer attitudes, investigations on the sales and market share of sustainable sportswear products remain under-explored. Gaps may exist between the consumers’ expectations and the developed sustainable sportswear products. In this study, a novel study has been carried out to examine the attitude gaps existing between the sustainable sportswear suppliers’ (SSSs) and the sustainable sportswear consumers (SSCs). This study firstly identifies the key attitudes towards sustainable sportswear product development. It analyses how sustainable attitudes affect the products being developed, as well as the effects of the attitude’s difference between the SSSs and the SSCs on the consumers’ satisfaction towards sportswear product consumption. A gap analysis research framework is adopted with the use of collected questionnaire survey data. The results indicate that a significant difference exists between SSSs and SSCs’ attitudes towards sustainable design, manufacture, product features, and branding. Based on in-depth interviews, the major causes of the difference in attitudes are studied to provide managerial insights for sustainable sportswear product management and business development.

Keywords: sustainability, sportswear, attitude, gap analysis, suppliers, consumers

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Authors: Silvia Boschetti, Jakub Binter, Robin Kopecký, Lenka PříPlatová, Jaroslav Flegr

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A strict dichotomy was present between religion and science, but recently, cognitive science focusses on the impact of supernatural beliefs on cognitive processes such as pattern recognition. It has been hypothesized that cognitive and perceptual processes have been under evolutionary pressures that ensured amplified perception of patterns, especially when in stressful and harsh conditions. The pattern detection in religious and non-religious individuals after induction of negative, anxious mood shall constitute a cornerstone of the general role of anxiety, cognitive bias, leading towards or against the by-product hypothesis, one of the main theories on the evolutionary studies of religion. The apophenia (tendencies to perceive connection and meaning on unrelated events) and perception of visual patterns (or pateidolia) are of utmost interest. To capture the impact of culture and upbringing, a comparative study of two European countries, the Czech Republic (low organized religion participation, high esoteric belief) and Italy (high organized religion participation, low esoteric belief), are currently in the data collection phase. Outcomes will be presented at the conference. A battery of standardized questionnaires followed by pattern recognition tasks (the patterns involve color, shape, and are of artificial and natural origin) using an experimental method involving the conditioning of (controlled, laboratory-induced) stress is taking place. We hypothesize to find a difference between organized religious belief and personal (esoteric) belief that will be alike in both of the cultural environments.

Keywords: culture, esoteric belief, pattern perception, religiosity

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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

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Authors: Babatunde Olumide Olawale, Oyebode Olumide Oyediran

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The security safe is a place or building where classified document and precious items are kept. To prevent unauthorised persons from gaining access to this safe a lot of technologies had been used. But frequent reports of an unauthorised person gaining access into security safes with the aim of removing document and items from the safes are pointers to the fact that there is still security gap in the recent technologies used as access control for the security safe. In this paper we try to solve this problem by developing a multimodal biometric system for physical access control into a security safe using face and voice recognition. The safe is accessed by the combination of face and speech pattern recognition and also in that sequential order. User authentication is achieved through the use of camera/sensor unit and a microphone unit both attached to the door of the safe. The user face was captured by the camera/sensor while the speech was captured by the use of the microphone unit. The Scale Invariance Feature Transform (SIFT) algorithm was used to train images to form templates for the face recognition system while the Mel-Frequency Cepitral Coefficients (MFCC) algorithm was used to train the speech recognition system to recognise authorise user’s speech. Both algorithms were hosted in two separate web based servers and for automatic analysis of our work; our developed system was simulated in a MATLAB environment. The results obtained shows that the developed system was able to give access to authorise users while declining unauthorised person access to the security safe.

Keywords: access control, multimodal biometrics, pattern recognition, security safe

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Authors: Zuk Nechemia Turbovich

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This paper introduces DoD, a contextual spiral model that describes the lifecycle of products intended for manufacturing using Personal 3D Printers (P3DP). The study is based on a review of the desktop P3DPs market that shows that the combination of digital connectivity, coupled with the potential ownership of P3DP by home users, is radically changing the form of the product lifecycle, comparatively to familiar lifecycle paradigms. The paper presents the change in the design process, considering the characterization of product types in the P3DP market and the possibility of having a direct dialogue between end-user and product designers. The model, as an updated paradigm, provides a strategic perspective on product design and tools for success, understanding that design is subject to rapid and continuous improvement and that products are subject to repair, update, and customization. The paper will include a review of real cases.

Keywords: lifecycle, mass-customization, personal 3d-printing, user involvement

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Authors: Misganaw Abebe Baye, Ji-Woo Park, Beom-Soo Kang

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The product quality of multi-point dieless forming (MDF) is identified to be dependent on the process parameters. Moreover, a certain variation of friction and material properties may have a substantially worse influence on the final product quality. This study proposed on how to compensate the MDF product defects by minimizing the sensitivity of noise parameter variations. This can be attained by reliability-based robust optimization (RRO) technique to obtain the optimal process setting of the controllable parameters. Initially two MDF Finite Element (FE) simulations of AA3003-H14 saddle shape showed a substantial amount of dimpling, wrinkling, and shape error. FE analyses are consequently applied on ABAQUS commercial software to obtain the correlation between the control process setting and noise variation with regard to the product defects. The best prediction models are chosen from the family of metamodels to swap the computational expensive FE simulation. Genetic algorithm (GA) is applied to determine the optimal process settings of the control parameters. Monte Carlo Analysis (MCA) is executed to determine how the noise parameter variation affects the final product quality. Finally, the RRO FE simulation and the experimental result show that the amendment of the control parameters in the final forming process leads to a considerably better-quality product.

Keywords: dimpling, multi-point dieless forming, reliability-based robust optimization, shape error, variation, wrinkling

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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)

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Authors: Gowtham Kalkere Jayanna, Mohamad Nazri Husin

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Graph theory, chemistry, and technology are all combined in cheminformatics. The structure and physiochemical properties of organic substances are linked using some useful graph invariants and the corresponding molecular graph. In this paper, we study specific reverse topological indices such as the reverse sum-connectivity index, the reverse Zagreb index, the reverse arithmetic-geometric, and the geometric-arithmetic, the reverse Sombor, the reverse Nirmala indices for the bistar graphs B (n: m) and the corona product Kₘ∘Kₙ', where Kₙ' Represent the complement of a complete graph Kₙ.

Keywords: reverse topological indices, bistar graph, the corona product, graph

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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

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Authors: Mokhlisur Rahman

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Consumers have developed a sense of responsibility in the past decade, reflecting on their purchasing behavior after viewing an advertisement. Consumers tend to buy ideal products that enable them to be judged by their close network in the opinion world. In such value considerations, any information that feeds consumers' desire for social status helps, which becomes capital for educating consumers on the importance of purchasing green products for manufacturing companies. Companies' effort in manufacturing green products to get high conversion demands a good deal of promotion with quality information and engaging representation. Additionally, converting people from traditional to eco-friendly products requires innovative alternatives to replace the existing product. Considering consumers' understanding of products and their purchasing behavior, it becomes essential for the brands to know the extent to which consumers' level of awareness of the ecosystem is to make them more responsive to green products. Another is brand image plays a vital role in consumers' perception regarding the credibility of the claim regarding the product. Brand image is a significant positive influence on the younger generation, and younger generations tend to engage more in pro-environmental behavior, including purchasing sustainable products. For example, Adidas senses the necessity of satisfying consumers with something that brings more profits and serves the planet. Several of their eco-friendly products are already in the market, and one is UltraBOOST DNA parley, made from 3D-printed recycled ocean waste. As a big brand image, Adidas has leveraged an interest among the younger generation by incorporating sustainability into its advertising. Therefore, influential brands' effort in the sustainable revolution through engaging advertisement makes it more prominent by educating consumers about the reason behind launching the product. This study investigates younger consumers' attitudes toward sustainability, brand recognition, exposure to green advertising, willingness to receive more green advertising, purchasing green products, and motivation. The study conducts a market experiment by creating two video advertisements: a sustainable product video advertisement and a non-sustainable product video advertisement. Both the videos have similar content design and the same length of 2 minutes, but the messages are different based on the identical product type college bags. The first video advertisement promotes eco-friendly college bags made from biodegradable raw materials, and the second promotes non-sustainable college bags made from plastics. After viewing the videos, consumers make purchasing decisions and complete an online survey to collect their attitudes toward sustainable products. The study finds the importance of a sense of responsibility to the consumers for climate change issues. Also, it empowers people to take a step, even small, and increases environmental awareness. This study provides companies with the knowledge to participate in sustainable product launches by collecting consumers' perceptions and attitudes toward green products. Also, it shows how important it is to build a brand's image for the younger generation.

Keywords: brand-image, environment, green-advertising, sustainability, younger-consumer

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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

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Authors: Kawpong Polyorat

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Since the outbreak of mad cow disease and bird flu, consumers have become more concerned with meat quality and safety. As a result, meat traceability is adopted as one approach to handle consumers’ concern in this issue. Nevertheless, in Thailand, meat traceability is rarely used as a marketing tool to persuade consumers. As a consequence, the present study attempts to understand consumer trust in the meat traceability system by conducting a study in this country to examine the impact of three types of consumer knowledge on this trust. The study results reveal that out of three types of consumer knowledge, marketplace knowledge was the sole predictor of consumer trust in meat traceability and it has a positive influence. General product class knowledge and knowledge in meat products with traceability, however, did not significantly influence consumer trust. The research results provide several implications and directions for future study.

Keywords: consumer knowledge, marketing, product knowledge, traceability

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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

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Authors: M. L. Anitha, K. A. Radhakrishna Rao

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With the advent of modern computing technology, there is an increased demand for developing recognition systems that have the capability of verifying the identity of individuals. Recognition systems are required by several civilian and commercial applications for providing access to secured resources. Traditional recognition systems which are based on physical identities are not sufficiently reliable to satisfy the security requirements due to the use of several advances of forgery and identity impersonation methods. Recognizing individuals based on his/her unique physiological characteristics known as biometric traits is a reliable technique, since these traits are not transferable and they cannot be stolen or lost. Since the performance of biometric based recognition system depends on the particular trait that is utilized, the present work proposes a fusion approach which combines Inner knuckle print (IKP) trait of the middle, ring and index fingers with the geometrical features of hand. The hand image captured from a digital camera is preprocessed to find finger IKP as region of interest (ROI) and hand geometry features. Geometrical features are represented as the distances between different key points and IKP features are extracted by applying local binary pattern descriptor on the IKP ROI. The decision level AND fusion was adopted, which has shown improvement in performance of the combined scheme. The proposed approach is tested on the database collected at our institute. Proposed approach is of significance since both hand geometry and IKP features can be extracted from the palm region of the hand. The fusion of these features yields a false acceptance rate of 0.75%, false rejection rate of 0.86% for verification tests conducted, which is less when compared to the results obtained using individual traits. The results obtained confirm the usefulness of proposed approach and suitability of the selected features for developing biometric based recognition system based on features from palmar region of hand.

Keywords: biometrics, hand geometry features, inner knuckle print, recognition

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Authors: Sergejs Kolesovs, Armands Vigants

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The use of dairy industry by-products and wastewater as a cheap substrate for microalgal growth is gaining recognition. However, the mechanisms of lactose utilization remain understudied, limiting the potential of successful microalgal biomass production using various dairy by-products, such as whey and permeate. The necessity for microalgae to produce a specific enzyme, β-galactosidase, requires the selection of suitable strains. This study focuses on a freshwater microalgal isolate's ability to grow on a semi-synthetic medium supplemented with lactose. After 10 days of agitated cultivation, an axenic microalgal isolate achieved significantly higher biomass production under mixotrophic growth conditions (0.86 ± 0.07 g/L, dry weight) than heterotrophic growth (0.46 ± 0.04 g/L). Moreover, mixotrophic cultivation had significantly higher biomass production compared to photoautotrophic growth (0.67 ± 0.05 g/L). The activity of β-galactosidase was detected in both supernatant and microalgal biomass under mixotrophic and heterotrophic growth conditions, showing the potential of extracellular and intracellular mechanisms of enzyme production. However, the main limiting factor in this study was the increase of pH values during the cultivation, significantly reducing the activity of the β-galactosidase enzyme after 3rd day of cultivation. It highlights the need for stricter control of growth parameters to ensure the enzyme's activity. Further research will assess the isolate's suitability for dairy by-product bioconversion and biomass composition.

Keywords: microalgae, lactose, whey, permeate, beta-galactosidase, mixotrophy, heterotrophy

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Authors: Mekkaoui Soumiya, Sadki Assia, Ait Heda Abdellatif

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Territorial marketing is a crucial element in the improvement of the attractiveness and competitiveness of a region, city or country. It is important to identify the different tools that distinguish the area from the other places and use them in order to achieve territorial marketing objectives. This paper tries to present the assets of Argan oil, the endemic terroir product, in the development of the tourism sector in Souss Massa. Starting from the Argan tree forests to the final use of the oil, every stage of the process can be developed as a tourism product in order to make the region more appealing to tourists.

Keywords: territorial marketing, terroir product, rural tourism, ecotourism, Argan oil

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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

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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

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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

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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

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Authors: Mei-Yi Wu, Shang-Ming Huang

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The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system.

Keywords: mobile image retrieval, text mining, product information service system, online marketing

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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

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Authors: Berie Abebe Getahun

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The tourism sector has been identified by the Ethiopian government as one of the priority economic sectors and planned to make Ethiopia among the top five African destinations by 2020. It is obvious international tourism demand for Ethiopia lags behind other African countries like South Africa, Egypt, Morocco, Tanzania, and Kenya. Meanwhile, the number of international tourists’ arrival to Ethiopia increases continuously. The main purpose of this study was to find out potentials, challenges, and opportunities of Ethiopian Cultural Center for tourism product development. Therefore, an attempt has been made to identify potentials over which tourism product development can be enhanced, and opportunities that promote tourism product development in Ethiopia. To achieve this objective, data have been collected by using observation, interview and focus group discussion with selected informants working the ministry of tourism and culture. The collected data has been analyzed by transcribing materials, and by using thematic analysis method based on the research objective. Likewise, the analyzed data has been discussed in the context of prevailing literature. As revealed in finding, Ethiopian cultural center has untapped potential for tourism product development that includes: meetings, incentives, conferences, events, availability of concerned stakeholders and demand of visitors. On the other hand, lack of awareness about tourism product development, financial constraints, skilled manpower, absence of tour guiding service and interpretation of heritages have been identified as the major challenges that hindering tourism product development in the cultural center. Moreover, the growth of domestic tourism, distinctive presence and rich culture of Ethiopia, and policy of Ethiopia that promotes the growth and preservation of indigenous cultures are deemed important opportunities for tourism product development in the country. And lastly, conducting a research based on tourism product development, reviewing the existing marketing and promotion strategies, training manpower, working harmoniously with the concerned stakeholders, and a careful examination of opportunities present in order to best utilize resources were implications drawn for future intervention.

Keywords: challenges and opportunities of tourism, Ethiopian tourism potential, tourism product, tourism product development

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Authors: Shaode Yu, Jiajian Meng, Bing Zhu, Hang Yu, Qiurui Sun

Abstract:

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

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Authors: Anderson Rocha, Pedro Miguel de Figueiredo Dinis Oliveira Gaspar

Abstract:

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 123

Authors: Afshan Saad, Muhammad Saad, Shah Muhammad Emaduddin

Abstract:

Nowadays the business condition is so quick paced that enhancing ourselves consistently has turned into a huge factor for the presence of an undertaking. We can check this for structural building and significantly more so in the quick-paced universe of data innovation and programming designing. The lithe philosophies, similar to Scrum, have a devoted advance in the process that objectives the enhancement of the improvement procedure and programming items. Pivotal to process enhancement is to pick up data that grants you to assess the condition of the procedure and its items. From the status data, you can design activities for the upgrade and furthermore assess the accomplishment of those activities. This investigation builds a model that measures the product nature of the improvement procedure. The product quality is dependent on the useful and auxiliary nature of the product items, besides the nature of the advancement procedure is likewise vital to enhance programming quality. Utilitarian quality covers the adherence to client prerequisites, while the auxiliary quality tends to the structure of the product item's source code with reference to its practicality. The procedure quality is identified with the consistency and expectedness of the improvement procedure. The product quality model is connected in a business setting by social occasion the information for the product measurements in the model. To assess the product quality model, we investigate the information and present it to the general population engaged with the light-footed programming improvement process. The outcomes from the application and the client input recommend that the model empowers a reasonable evaluation of the product quality and that it very well may be utilized to help the persistent enhancement of the advancement procedure and programming items.

Keywords: Agile SDLC Tools, Agile Software development, business value, enterprise applications, IBM, IBM Rational Team Concert, RTC, software quality, software metrics

Procedia PDF Downloads 145

Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

Abstract:

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 215

Authors: Qura-tul-aain Khair

Abstract:

Purpose- The purpose of this paper is to empirically examining the strength of association of responsive market orientation and proactive market orientation with new product performance and exploring the possible moderating role of organizational learning based on contingency theory. Design/methodology/approach- Data for this study was collected from FMCG manufacturing industry and services industry, where customers are in contact frequently and responses are recorded on continuous basis. Sample was collected through convenience sampling. The data collected from different marketing department and sales personnel were analysed using SPSS 16 version. Findings- The paper finds that responsive market orientation is more strongly associated with new product performance. The moderator, organizational learning, plays it significant role on the relationship between responsive market orientation and new product performance. Research limitations/implications- this paper has taken sample from just FMCG industry and service industry, more work can be done regarding how different-markets require different market orientation behaviours. Originality/value- This paper will be useful for foreign business looking for investing and expanding in Pakistan, they can find opportunity to get sustained competitive advantage through exploring the proactive side of market orientation and importance of organizational learning.

Keywords: organizational learning, proactive market orientation, responsive market orientation, new product performance

Procedia PDF Downloads 347