Search results for: speech recognition library
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2827

Search results for: speech recognition library

2437 Critical Discourse Analysis of President Mamnoon Hussain Speech in the Joint Session of Parliament.

Authors: Saeed Qaisrani

Abstract:

This article briefly reviews the rise of Critical Discourse Analysis about the Pakistani President Mamnoon Hussain speech which delivered in the joint session of Parliament and teases out a detailed analysis of the various critiques that have been levelled at CDA and its practitioners over the last twenty years, both by scholars working within the “critical” paradigm and by other critics. A range of criticisms are discussed which target the underlying premises, the analytical methodology and the disputed areas of reader response and the integration of contextual factors. Controversial issues such as the predominantly negative focus of much CDA scholarship, and the status of CDA as an emergent “intellectual orthodoxy”, are also reviewed. The conclusions offer a summary of the principal criticisms that emerge from this overview, and suggest some ways in which these problems could be attenuated. It also focused on the different views about president speech and how it is presented in the Pakistani print and electronic media.

Keywords: Critical Discourse Analysis, Analytical methodology, Corpus linguistics, Reader response theory, Critical paradigm, Contextualization.

Procedia PDF Downloads 456
2436 Face Recognition Using Body-Worn Camera: Dataset and Baseline Algorithms

Authors: Ali Almadan, Anoop Krishnan, Ajita Rattani

Abstract:

Facial recognition is a widely adopted technology in surveillance, border control, healthcare, banking services, and lately, in mobile user authentication with Apple introducing “Face ID” moniker with iPhone X. A lot of research has been conducted in the area of face recognition on datasets captured by surveillance cameras, DSLR, and mobile devices. Recently, face recognition technology has also been deployed on body-worn cameras to keep officers safe, enabling situational awareness and providing evidence for trial. However, limited academic research has been conducted on this topic so far, without the availability of any publicly available datasets with a sufficient sample size. This paper aims to advance research in the area of face recognition using body-worn cameras. To this aim, the contribution of this work is two-fold: (1) collection of a dataset consisting of a total of 136,939 facial images of 102 subjects captured using body-worn cameras in in-door and daylight conditions and (2) evaluation of various deep-learning architectures for face identification on the collected dataset. Experimental results suggest a maximum True Positive Rate(TPR) of 99.86% at False Positive Rate(FPR) of 0.000 obtained by SphereFace based deep learning architecture in daylight condition. The collected dataset and the baseline algorithms will promote further research and development. A downloadable link of the dataset and the algorithms is available by contacting the authors.

Keywords: face recognition, body-worn cameras, deep learning, person identification

Procedia PDF Downloads 142
2435 Analysis of Users’ Behavior on Book Loan Log Based on Association Rule Mining

Authors: Kanyarat Bussaban, Kunyanuth Kularbphettong

Abstract:

This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24 percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.

Keywords: behavior, data mining technique, a priori algorithm, knowledge discovery

Procedia PDF Downloads 380
2434 Pre-Analysis of Printed Circuit Boards Based on Multispectral Imaging for Vision Based Recognition of Electronics Waste

Authors: Florian Kleber, Martin Kampel

Abstract:

The increasing demand of gallium, indium and rare-earth elements for the production of electronics, e.g. solid state-lighting, photovoltaics, integrated circuits, and liquid crystal displays, will exceed the world-wide supply according to current forecasts. Recycling systems to reclaim these materials are not yet in place, which challenges the sustainability of these technologies. This paper proposes a multispectral imaging system as a basis for a vision based recognition system for valuable components of electronics waste. Multispectral images intend to enhance the contrast of images of printed circuit boards (single components, as well as labels) for further analysis, such as optical character recognition and entire printed circuit board recognition. The results show that a higher contrast is achieved in the near infrared compared to ultraviolet and visible light.

Keywords: electronics waste, multispectral imaging, printed circuit boards, rare-earth elements

Procedia PDF Downloads 397
2433 Speech Disorders as Predictors of Social Participation of Children with Cerebral Palsy in the Primary Schools of the Czech Republic

Authors: Marija Zulić, Vanda Hájková, Nina Brkić–Jovanović, Srećko Potić, Sanja Tomić

Abstract:

The name cerebral palsy comes from the word cerebrum, which means the brain and the word palsy, which means seizure, and essentially refers to the movement disorder. In the clinical picture of cerebral palsy, basic neuromotor disorders are associated with other various disorders: behavioural, intellectual, speech, sensory, epileptic seizures, and bone and joint deformities. Motor speech disorders are among the most common difficulties present in people with cerebral palsy. Social participation represents an interaction between an individual and their social environment. Quality of social participation of the students with cerebral palsy at school is an important indicator of their successful participation in adulthood. One of the most important skills for the undisturbed social participation is ability of good communication. The aim of the study was to determine relation between social participation of students with cerebral palsy and presence of their speech impairment in primary schools in the Czech Republic. The study was performed in the Czech Republic in mainstream schools and schools established for the pupils with special education needs. We analysed 75 children with cerebral palsy aged between six and twelve years attending up to sixth grade by using the first and the third part of the school function assessment questionnaire as the main instrument. The other instrument we used in the research is the Gross motor function classification system–five–level classification system, which measures degree of motor functions of children and youth with cerebral palsy. Funding for this study was provided by the Grant Agency of Charles University in Prague.

Keywords: cerebral palsy, social participation, speech disorders, The Czech Republic, the school function assessment

Procedia PDF Downloads 265
2432 Tensor Deep Stacking Neural Networks and Bilinear Mapping Based Speech Emotion Classification Using Facial Electromyography

Authors: P. S. Jagadeesh Kumar, Yang Yung, Wenli Hu

Abstract:

Speech emotion classification is a dominant research field in finding a sturdy and profligate classifier appropriate for different real-life applications. This effort accentuates on classifying different emotions from speech signal quarried from the features related to pitch, formants, energy contours, jitter, shimmer, spectral, perceptual and temporal features. Tensor deep stacking neural networks were supported to examine the factors that influence the classification success rate. Facial electromyography signals were composed of several forms of focuses in a controlled atmosphere by means of audio-visual stimuli. Proficient facial electromyography signals were pre-processed using moving average filter, and a set of arithmetical features were excavated. Extracted features were mapped into consistent emotions using bilinear mapping. With facial electromyography signals, a database comprising diverse emotions will be exposed with a suitable fine-tuning of features and training data. A success rate of 92% can be attained deprived of increasing the system connivance and the computation time for sorting diverse emotional states.

Keywords: speech emotion classification, tensor deep stacking neural networks, facial electromyography, bilinear mapping, audio-visual stimuli

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2431 Interactive Shadow Play Animation System

Authors: Bo Wan, Xiu Wen, Lingling An, Xiaoling Ding

Abstract:

The paper describes a Chinese shadow play animation system based on Kinect. Users, without any professional training, can personally manipulate the shadow characters to finish a shadow play performance by their body actions and get a shadow play video through giving the record command to our system if they want. In our system, Kinect is responsible for capturing human movement and voice commands data. Gesture recognition module is used to control the change of the shadow play scenes. After packaging the data from Kinect and the recognition result from gesture recognition module, VRPN transmits them to the server-side. At last, the server-side uses the information to control the motion of shadow characters and video recording. This system not only achieves human-computer interaction, but also realizes the interaction between people. It brings an entertaining experience to users and easy to operate for all ages. Even more important is that the application background of Chinese shadow play embodies the protection of the art of shadow play animation.

Keywords: hadow play animation, Kinect, gesture recognition, VRPN, HCI

Procedia PDF Downloads 375
2430 Optimization of Hate Speech and Abusive Language Detection on Indonesian-language Twitter using Genetic Algorithms

Authors: Rikson Gultom

Abstract:

Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.

Keywords: abusive language, hate speech, machine learning, optimization, social media

Procedia PDF Downloads 106
2429 Effective Stacking of Deep Neural Models for Automated Object Recognition in Retail Stores

Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

Abstract:

Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

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2428 Simultaneous Interpreting in the European Parliament: Linguistic Quality of the Political Discourse: An Empirical Analysis

Authors: Alicja Zapolnik-Plachetka

Abstract:

The paper examines the impact of the Members’ of the European Parliament (MEPs) language choice on the linguistic quality of their political discourse as delivered by the interpreters. The study, designed by the author, who is an EU interpreter herself, consisted of three phases. First, a number of speeches of Polish and Spanish MEPs were analyzed to determine whether the incidence of use of certain figures of speech depending on whether the speech had been delivered in English or their respective mother tongue. Then the use of figures of speech was also analyzed based on speeches by some British MEPs, in order to determine what was the incidence for the native users of English. Subsequently, the speeches were compared with their interpretations to find out whether the interpreters managed to convey accurately the means of oratory used by the MEPs. The final result shows that in case of institutional environments dependant on simultaneous interpretation the speakers’ choices can, in fact, influence the linguistic quality of the political communication.

Keywords: content accuracy, European Parliament, political discourse, simultaneous interpreting

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2427 Understanding the Motivations behind the Assassination of Turkish Armenian Journalist, Hrant Dink

Authors: Nusret Mesut Sahin

Abstract:

Hrant Dink, a prominent Turkish-Armenian journalist, and editor-in-chief of the bilingual Turkish-Armenian newspaper Agos was assassinated in Istanbul on January 19th, 2007 by a nationalist extremist, Ogun Samast. Dink had been voicing the atrocities against the Armenians between 1915 and 1922 during the Ottoman rule, and his comments on the issue appeared in the Turkish media many times before his assassination. It has been argued that the suffocating atmosphere created by the Turkish news media targeting Mr. Dink made him a target of an extremist Turkish juvenile. This study analyzes the media news to understand and explain why Hrant Dink became the target of a nationalist extremist. In this research, content analysis of news articles (N= 170) is conducted to identify whether there is a link between hate speech against Hrant Dink in the Turkish media and his assassination. The content of the newspaper articles is categorized and coded according to the hate language being used. The analysis suggested that Turkish media paved the way for Dink’s assassination. Hate speech against Hrant Dink on the media had risen gradually before the assassination. The study also found that the number of news stories covering hate speech and racist discourse against non-Muslim citizens of Turkey also increased dramatically before the assassination. Therefore, hate speech against minorities in media narratives and news reports should be monitored, and political figures or leaders of social groups who are targeted by some media outlets should be protected.

Keywords: Hrant Dink, assassination, Turkish Armenian journalist, media

Procedia PDF Downloads 137
2426 Evolution of the Environmental Justice Concept

Authors: Zahra Bakhtiari

Abstract:

This article explores the development and evolution of the concept of environmental justice, which has shifted from being dominated by white and middle-class individuals to a civil struggle by marginalized communities against environmental injustices. Environmental justice aims to achieve equity in decision-making and policy-making related to the environment. The concept of justice in this context includes four fundamental aspects: distribution, procedure, recognition, and capabilities. Recent scholars have attempted to broaden the concept of justice to include dimensions of participation, recognition, and capabilities. Focusing on all four dimensions of environmental justice is crucial for effective planning and policy-making to address environmental issues. Ignoring any of these aspects can lead to the failure of efforts and the waste of resources.

Keywords: environmental justice, distribution, procedure, recognition, capabilities

Procedia PDF Downloads 62
2425 Implementing Text Using Political and Current Issues to Create Choreography: “The Pledge 2.0”

Authors: Muhammad Fairul Azreen bin Mohd Zahid, Melissa Querk, Aimi Nabila bt Anizaim

Abstract:

For this particular research, the focus is based on the practice as research which will produce a choreography as the outcome. The ideas organically develop as an “epiphany” from the meeting, brainstorming, or situation that revolves around surroundings. In this study, the researchers are approaching the national pillar of Malaysia known as ‘Rukun Negara’ to develop a choreographic idea. The concept theory of Speech Act by J.L Austin is used to compose the choreography alongside with national pillar ‘Rukun Negara’ as a guideline for a contemporary work titled, The Pledge 2.0, besides fostering the spirit of unity. These approaches will offer flexibility in creating a choreography piece. The pledge has crossed the boundaries by using texts and heavy issues in choreography developments. It will emphasize the concept of delivering the speech via verbal and nonverbal body language. Besides using the Theory of Speech Acts, the development process of creating this piece will lay the bare normative structure implicit in performance practice. Converging current issues into the final choreographic piece for this research is vital as this research will explore a few choreography methods from different perspectives. Hence, the audience will be able to see the world of dance that always revolves in line with the diachronic process in many ways. The method used in this research is qualitative, which will be used in finding the movement that fits the given facts.

Keywords: performing arts, speech act, performative, nationalism, choreography, politic in dance

Procedia PDF Downloads 64
2424 Bug Localization on Single-Line Bugs of Apache Commons Math Library

Authors: Cherry Oo, Hnin Min Oo

Abstract:

Software bug localization is one of the most costly tasks in program repair technique. Therefore, there is a high claim for automated bug localization techniques that can monitor programmers to the locations of bugs, with slight human arbitration. Spectrum-based bug localization aims to help software developers to discover bugs rapidly by investigating abstractions of the program traces to make a ranking list of most possible buggy modules. Using the Apache Commons Math library project, we study the diagnostic accuracy using our spectrum-based bug localization metric. Our outcomes show that the greater performance of a specific similarity coefficient, used to inspect the program spectra, is mostly effective on localizing of single line bugs.

Keywords: software testing, bug localization, program spectra, bug

Procedia PDF Downloads 118
2423 Two Concurrent Convolution Neural Networks TC*CNN Model for Face Recognition Using Edge

Authors: T. Alghamdi, G. Alaghband

Abstract:

In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.

Procedia PDF Downloads 126
2422 Automatic Vowel and Consonant's Target Formant Frequency Detection

Authors: Othmane Bouferroum, Malika Boudraa

Abstract:

In this study, a dual exponential model for CV formant transition is derived from locus theory of speech perception. Then, an algorithm for automatic vowel and consonant’s target formant frequency detection is developed and tested on real speech. The results show that vowels and consonants are detected through transitions rather than their small stable portions. Also, vowel reduction is clearly observed in our data. These results are confirmed by the observations made in perceptual experiments in the literature.

Keywords: acoustic invariance, coarticulation, formant transition, locus equation

Procedia PDF Downloads 240
2421 Evaluation of Published Materials in Meeting the Information Needs of Students in Three Selected College Libraries in Oyo State, Nigeria

Authors: Rafiat Olasumbo Akande

Abstract:

Most college libraries in Oyo State show signs of unhealthy collection practices like the preponderance of non-recent collections and indiscriminate acquisition of sub-standard books from hawkers. The objective of this study, therefore, is to determine the extent at which available published materials in those college libraries are able to meet both knowledge and information needs of students in those institutions. A descriptive survey was conducted among 18 librarians and 21 library officers in three colleges purposively selected for the exercise using simple sampling technique. In all, 279 questionnaires were administered and out of those 279 administered, 265 were returned and analyzed using Statistical Package for Social Science (SPSS). Three College Librarian were also interviewed. Findings from the study showed that due to the paucity of funds, obsolete materials, and sub-standard materials being procured from roadside book hawkers hinders the college libraries in meeting the information needs of the students in these college libraries. It then concluded that only when there is standard procedure for collection management and acquisition of library materials that the knowledge and information needs of the students could be met. The study recommends that students and curriculum review committee members from various departments should always be involved in determining materials needed by the library to meet students information needs and that institution authority must fund, monitor and ensure compliance with the acquisition policy in place in the college libraries.

Keywords: libraries, published materials, information needs, college, evaluation, students

Procedia PDF Downloads 144
2420 Real-Time Recognition of Dynamic Hand Postures on a Neuromorphic System

Authors: Qian Liu, Steve Furber

Abstract:

To explore how the brain may recognize objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor~(DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network~(SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modeled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study's largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognize the postures with an accuracy of around 86.4% -only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much-improved cost to performance trade-off in its approach.

Keywords: spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system

Procedia PDF Downloads 443
2419 Pattern Recognition Search: An Advancement Over Interpolation Search

Authors: Shahpar Yilmaz, Yasir Nadeem, Syed A. Mehdi

Abstract:

Searching for a record in a dataset is always a frequent task for any data structure-related application. Hence, a fast and efficient algorithm for the approach has its importance in yielding the quickest results and enhancing the overall productivity of the company. Interpolation search is one such technique used to search through a sorted set of elements. This paper proposes a new algorithm, an advancement over interpolation search for the application of search over a sorted array. Pattern Recognition Search or PR Search (PRS), like interpolation search, is a pattern-based divide and conquer algorithm whose objective is to reduce the sample size in order to quicken the process and it does so by treating the array as a perfect arithmetic progression series and thereby deducing the key element’s position. We look to highlight some of the key drawbacks of interpolation search, which are accounted for in the Pattern Recognition Search.

Keywords: array, complexity, index, sorting, space, time

Procedia PDF Downloads 206
2418 Pattern Recognition Based on Simulation of Chemical Senses (SCS)

Authors: Nermeen El Kashef, Yasser Fouad, Khaled Mahar

Abstract:

No AI-complete system can model the human brain or behavior, without looking at the totality of the whole situation and incorporating a combination of senses. This paper proposes a Pattern Recognition model based on Simulation of Chemical Senses (SCS) for separation and classification of sign language. The model based on human taste controlling strategy. The main idea of the introduced model is motivated by the facts that the tongue cluster input substance into its basic tastes first, and then the brain recognizes its flavor. To implement this strategy, two level architecture is proposed (this is inspired from taste system). The separation-level of the architecture focuses on hand posture cluster, while the classification-level of the architecture to recognizes the sign language. The efficiency of proposed model is demonstrated experimentally by recognizing American Sign Language (ASL) data set. The recognition accuracy obtained for numbers of ASL is 92.9 percent.

Keywords: artificial intelligence, biocybernetics, gustatory system, sign language recognition, taste sense

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2417 Play-Based Approaches to Stimulate Language

Authors: Sherri Franklin-Guy

Abstract:

The emergence of language in young children has been well-documented and play-based activities that support its continued development have been utilized in the clinic-based setting. Speech-language pathologists have long used such activities to stimulate the production of language in children with speech and language disorders via modeling and elicitation tasks. This presentation will examine the importance of play in the development of language in young children, including social and pragmatic communication. Implications for clinicians and educators will be discussed.

Keywords: language development, language stimulation, play-based activities, symbolic play

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2416 Cinematic Liberty vs. Offending Social, Religious Beliefs: With Special Reference to the Controversial Contents in Cinema and Print Media

Authors: Govind Ji Pandey

Abstract:

The divergent opinions in the society are important for its development but with reasonable restrictions. The world recently witnessed one of the most violent protests by a group against the editor and publisher of the magazine ‘Charlie Hebdo’ for publishing cartoon of their religious leader. The supporter of freedom of speech and expression around the world were in shock and termed it the strongest attack against the free speech. People all around the world condemned the killing of the journalists but many soft voices from several corners were also coming for reasonable restrictions on the freedom of speech and expression. Of late, Indian society has witnessed many protests and supports of films with controversial content. It is the beauty of the Indian democracy which gives an opportunity to all for discussion and debate on any issue that challenges established social norms. However, many organizations as well as individuals misuse it for their personal benefits. There have been many film directors who faced protest from several quarters for their controversial themes. This research aims at analyzing the controversial contents published in print media and shown in films. To understand the nature and frequency of such media reports, content analysis technique is used. The research also highlights the perception of the public regarding the controversies. For getting the popular opinion on the coverage of controversial content in cinema and print media, five hundred people from Lucknow, UP, India were randomly selected. The findings of this research are important to understand the response of media and society towards the controversial content presented in cinema and print media. The research highlights that how a handful of people curb free speech in a democratic country like India.

Keywords: cinema, censor board, free speech, liberty, social-religious beliefs

Procedia PDF Downloads 237
2415 Defect Localization and Interaction on Surfaces with Projection Mapping and Gesture Recognition

Authors: Qiang Wang, Hongyang Yu, MingRong Lai, Miao Luo

Abstract:

This paper presents a method for accurately localizing and interacting with known surface defects by overlaying patterns onto real-world surfaces using a projection system. Given the world coordinates of the defects, we project corresponding patterns onto the surfaces, providing an intuitive visualization of the specific defect locations. To enable users to interact with and retrieve more information about individual defects, we implement a gesture recognition system based on a pruned and optimized version of YOLOv6. This lightweight model achieves an accuracy of 82.8% and is suitable for deployment on low-performance devices. Our approach demonstrates the potential for enhancing defect identification, inspection processes, and user interaction in various applications.

Keywords: defect localization, projection mapping, gesture recognition, YOLOv6

Procedia PDF Downloads 58
2414 E-Resource Management: Digital Environment for a Library System

Authors: Vikram Munjal, Harpreet Munjal

Abstract:

A few years ago we could hardly think of Libraries' strategic plan that includes the bold and amazing prediction of a mostly digital environment for a library system. However, sheer hard work by the engineers, academicians, and librarians made it feasible. However, it requires huge expenditure and now a day‘s spending for electronic resources (e-resources) have been growing much more rapidly than have the materials budgets of which such resources are usually a part. And many libraries are spending a huge amount on e-resources. Libraries today are in the midst of a profound shift toward reliance on e-resources, and this reliance seems to have deepened in recent years as libraries have shed paper journal subscriptions to help pay for online access. This has been exercised only to cater user behavior and attitudes that seem to be changing even more quickly in this dynamic scenario.

Keywords: radio frequency identification, management, scanning, barcodes, checkout and tags

Procedia PDF Downloads 381
2413 SCNet: A Vehicle Color Classification Network Based on Spatial Cluster Loss and Channel Attention Mechanism

Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

Abstract:

Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

Procedia PDF Downloads 148
2412 Affective Robots: Evaluation of Automatic Emotion Recognition Approaches on a Humanoid Robot towards Emotionally Intelligent Machines

Authors: Silvia Santano Guillén, Luigi Lo Iacono, Christian Meder

Abstract:

One of the main aims of current social robotic research is to improve the robots’ abilities to interact with humans. In order to achieve an interaction similar to that among humans, robots should be able to communicate in an intuitive and natural way and appropriately interpret human affects during social interactions. Similarly to how humans are able to recognize emotions in other humans, machines are capable of extracting information from the various ways humans convey emotions—including facial expression, speech, gesture or text—and using this information for improved human computer interaction. This can be described as Affective Computing, an interdisciplinary field that expands into otherwise unrelated fields like psychology and cognitive science and involves the research and development of systems that can recognize and interpret human affects. To leverage these emotional capabilities by embedding them in humanoid robots is the foundation of the concept Affective Robots, which has the objective of making robots capable of sensing the user’s current mood and personality traits and adapt their behavior in the most appropriate manner based on that. In this paper, the emotion recognition capabilities of the humanoid robot Pepper are experimentally explored, based on the facial expressions for the so-called basic emotions, as well as how it performs in contrast to other state-of-the-art approaches with both expression databases compiled in academic environments and real subjects showing posed expressions as well as spontaneous emotional reactions. The experiments’ results show that the detection accuracy amongst the evaluated approaches differs substantially. The introduced experiments offer a general structure and approach for conducting such experimental evaluations. The paper further suggests that the most meaningful results are obtained by conducting experiments with real subjects expressing the emotions as spontaneous reactions.

Keywords: affective computing, emotion recognition, humanoid robot, human-robot-interaction (HRI), social robots

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2411 Reading Behavior of Undergraduate Students at Suan Sunandha Rajabhat University

Authors: Ratanavadee Takerngsukvatana

Abstract:

The purposes of this research were to study reading behavior of undergraduate students at Suan Sunandha Rajabhat University. A stratified random sample of 380 participants was collected. A Likert five-scale questionnaire was developed to collect data and to obtain students’ opinions regarding their reading behavior. The findings revealed that the majority of respondents read mainly for academic purpose. They preferred to read magazines. The majority of respondents read an average of 3-7 pages a day. The places to read were home and library. Buying with their own money and borrowing from the library were two main sources of books. The suggested activity to promote is planning the curriculum to suit students’ reading behavior.

Keywords: reading, reading behavior, undergraduate students, Suan Sunandha Rajabhat University

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2410 Design and Development of Automatic Onion Harvester

Authors: P. Revathi, T. Mrunalini, K. Padma Priya, P. Ramya, R. Saranya

Abstract:

During the tough times of covid, those people who were hospitalized found it difficult to always convey what they wanted to or needed to the attendee. Sometimes the attendees might also not be there. In that case, the patients can use simple hand gestures to control electrical appliances (like its set it for a zero watts bulb)and three other gestures for voice note intimation. In this AI-based hand recognition project, NodeMCU is used for the control action of the relay, and it is connected to the firebase for storing the value in the cloud and is interfaced with the python code via raspberry pi. For three hand gestures, a voice clip is added for intimation to the attendee. This is done with the help of Google’s text to speech and the inbuilt audio file option in the raspberry pi 4. All the 5 gestures will be detected when shown with their hands via a webcam which is placed for gesture detection. A personal computer is used for displaying the gestures and for running the code in the raspberry pi imager.

Keywords: onion harvesting, automatic pluging, camera, raspberry pi

Procedia PDF Downloads 172
2409 Analyzing the Use of Augmented Reality and Image Recognition in Cultural Education: Use Case of Sintra Palace Treasure Hunt Application

Authors: Marek Maruszczak

Abstract:

Gamified applications have been used successfully in education for years. The rapid development of technologies such as augmented reality and image recognition increases their availability and reduces their prices. Thus, there is an increasing possibility and need for a wide use of such applications in education. The main purpose of this article is to present the effects of work on a mobile application with augmented reality, the aim of which is to motivate tourists to pay more attention to the attractions and increase the likelihood of moving from one attraction to the next while visiting the Palácio Nacional de Sintra in Portugal. Work on the application was carried out together with the employees of Parques de Sintra from 2019 to 2021. Their effect was the preparation of a mobile application using augmented reality and image recognition. The application was tested on the palace premises by both Parques de Sintra employees and tourists visiting Palácio Nacional de Sintra. The collected conclusions allowed for the formulation of good practices and guidelines that can be used when designing gamified apps for the purpose of cultural education.

Keywords: augmented reality, cultural education, gamification, image recognition, mobile games

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2408 The Effect of Experimentally Induced Stress on Facial Recognition Ability of Security Personnel’s

Authors: Zunjarrao Kadam, Vikas Minchekar

Abstract:

The facial recognition is an important task in criminal investigation procedure. The security guards-constantly watching the persons-can help to identify the suspected accused. The forensic psychologists are tackled such cases in the criminal justice system. The security personnel may loss their ability to correctly identify the persons due to constant stress while performing the duty. The present study aimed at to identify the effect of experimentally induced stress on facial recognition ability of security personnel’s. For this study 50, security guards from Sangli, Miraj & Jaysingpur city of the Maharashtra States of India were recruited in the experimental study. The randomized two group design was employed to carry out the research. In the initial condition twenty identity card size photographs were shown to both groups. Afterward, artificial stress was induced in the experimental group through the difficultpuzzle-solvingtask in a limited period. In the second condition, both groups were presented earlier photographs with another additional thirty new photographs. The subjects were asked to recognize the photographs which are shown earliest. The analyzed data revealed that control group has ahighest mean score of facial recognition than experimental group. The results were discussed in the present research.

Keywords: experimentally induced stress, facial recognition, cognition, security personnel

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