Search results for: speech emotion recognition

Authors: Katsumi Hirata

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To develop the useful acoustic environmental recognition system, the method of estimating 3D-position of a stationary random acoustic source using bispectral analysis of 4-point detected signals is proposed. The method uses information about amplitude attenuation and propagation delay extracted from amplitude ratios and angles of auto- and cross-bispectra of the detected signals. It is expected that using bispectral analysis affects less influence of Gaussian noises than using conventional power spectral one. In this paper, the basic principle of the method is mentioned first, and its validity and features are considered from results of the fundamental experiments assumed ideal circumstances.

Keywords: 4-point detection, a stationary random acoustic source, auto- and cross-bispectra, estimation of 3D-position

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Authors: Mark Omu

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Education has remained the greatest fulcrum on which the developmental aspirations of societies and the world over is Anchored. This has been the case from the antiquity. As a result of recognition of this fact, education occupies a crucial and centripetal position at different epochs of societal formation and transformation. This paper recognized the all-embracing role of education to society and it utilized the literary research and review of literature to espouse on the role of alternative sources of financing education. This position was borne out of the dwindling resources available to education. Especially to finance teaching, learning, research and retraining of staffers. This paper found among other things that alternative funding of education is possible and it can be achieved through selling of its research products like entrepreneurial skills, collaborative ventures in public private partnership, philanthropic of endowments, etc. These are capable of bridging the financial gap currently bedevilling the educational sectors.

Keywords: alternative sources, funding, tertiary, education, society, partnership, Nigeria

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Authors: Fernando Cabo Aseguinolaza, Víctor Bouzas Blanco, Alberto Martí Ezpeleta

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Santiago de Compostela became a stable object of literary representation during the period between 1840 and 1915, approximately. This study offers a partial cartographical look at this process, suggesting that a cultural space like Compostela’s becoming an object of literary representation paralleled the first stages of its becoming a tourist destination. We use maps as a method of analysis to show the interaction between a corpus of novels and the emerging tradition of tourist guides on Compostela during the selected period. Often, the novels constitute ways to present a city to the outside, marking it for the gaze of others, as guidebooks do. That leads us to examine the ways of constructing and rendering communicable the local in other contexts. For that matter, we should also acknowledge the fact that a good number of the narratives in the corpus evoke the representation of the city through the figure of one who comes from elsewhere: a traveler, a student or a professor. The guidebooks coincide in this with the emerging fiction, of which the mimesis of a city is a key characteristic. The local cannot define itself except through a process of symbolic negotiation, in which recognition and self-recognition play important roles. Cartography shows some of the forms that these processes of symbolic representation take through the treatment of space. The research uses GIS to find significant models of representation. We used the program ArcGIS for the mapping, defining the databases starting from an adapted version of the methodology applied by Barbara Piatti and Lorenz Hurni’s team at the University of Zurich. First, we designed maps that emphasize the peripheral position of Compostela from a historical and institutional perspective using elements found in the texts of our corpus (novels and tourist guides). Second, other maps delve into the parallels between recurring techniques in the fictional texts and characteristic devices of the guidebooks (sketching itineraries and the selection of zones and indexicalization), like a foreigner’s visit guided by someone who knows the city or the description of one’s first entrance into the city’s premises. Last, we offer a cartography that demonstrates the connection between the best known of the novels in our corpus (Alejandro Pérez Lugín’s 1915 novel La casa de la Troya) and the first attempt to create package tourist tours with Galicia as a destination, in a joint venture of Galician and British business owners, in the years immediately preceding the Great War. Literary cartography becomes a crucial instrument for digging deeply into the methods of cultural production of places. Through maps, the interaction between discursive forms seemingly so far removed from each other as novels and tourist guides becomes obvious and suggests the need to go deeper into a complex process through which a city like Compostela becomes visible on the contemporary cultural horizon.

Keywords: compostela, literary geography, literary cartography, tourism

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Authors: Louisa Han Lin Tan, Poh Sim Kang, Wei Ming Loi, Susan Jane Rickard Liow

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The efficacy of music for improving speech and language has been shown across ages and diagnoses. Across the world, the wide range of therapy settings and increasing number of children diagnosed with special needs demand more cost and time effective service delivery. However, research exploring co-treatment models on children other than those with Autism Spectrum Disorder remains sparse. The aim of this research was to determine the efficacy of music for improving language in children with special needs, and generalizability of therapy effects. 25 children (7 to 12 years) were split into three groups – A, B and control. A cross-over design with direct therapy (storytelling) with or without music, and indirect therapy was applied with two therapy phases lasting 6 sessions each. Therapy targeted three prepositions in each phase. Baseline language abilities were assessed, with re-assessment after each phase. The introduction of music in therapy led to significantly greater improvement (p=.046, r=.53) in associated language abilities, with case studies showing greater effectiveness in developmentally appropriate target prepositions. However, improvements were not maintained once direct therapy ceased. As such, the incorporation of music could lead to greater efficiency and effectiveness of language therapy in children with special needs, but sustainability and generalizability of therapy effects both require further exploration.

Keywords: music, language therapy, children, special needs

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Authors: Ji Eun Shin, Dong Hoon Lim

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Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

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Authors: Belaynesh Chekol, Numan Çelebi

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The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

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Authors: Yujun Liu, Maosheng Ran

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Background: Chinese rural-to-urban migrant workers’ mental health problems raise attentions from different social sectors. However, situation of present mental health services provided to this population has not been discovered. This study attempts to describe the current mental health service situation, identify the gaps and give the future directions based on the quantitative data. Methods: Questionnaire surveys were conducted among 2017 rural-to-urban migrant workers in 13 cities and 100 social work service organizations in 5 cities in 2014. Data was collected by face-to-face structured interview by trained interviewers. Findings: Migrant workers’ mental health status was not good. Compared to the severity of mental distress, mental health service for this population was lacking and insufficient, which accounted for only 14.4% of all services in our sample. And the group work and case work were the most frequently-used methods. By estimating a series of regression models, we revealed that life experiences and working conditions were significantly associated with migrant workers’ mental health status. Therefore, the macro social work practices aimed at this whole group were advocated to promote their mental wellbeing. That is, practitioners should not only focus on the improvement of migrant workers’ emotion management capacity, but also pay attention to raise awareness and improve their living and working condition; not only concentrate on the solving of individuals’ dilemma, but also promote gradual reformation of present labor regime and hukou system in China.

Keywords: Chinese rural-to-urban migrant workers, macro social work practice, mental health service needs, mental health status

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Authors: Yong-Kyu Jung

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The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).

Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity

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Authors: Sylwia Krawiec, Joanna Cabaj, Karol Malecha

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Nowadays, progress in the field of the analytical methods is of great interest for reliable biological research and medical diagnostics. Classical techniques of chemical analysis, despite many advantages, do not permit to obtain immediate results or automatization of measurements. Chemical sensors have displaced the conventional analytical methods - sensors combine precision, sensitivity, fast response and the possibility of continuous-monitoring. Biosensor is a chemical sensor, which except of conventer also possess a biologically active material, which is the basis for the detection of specific chemicals in the sample. Each biosensor device mainly consists of two elements: a sensitive element, where is recognition of receptor-analyte, and a transducer element which receives the signal and converts it into a measurable signal. Through these two elements biosensors can be divided in two categories: due to the recognition element (e.g immunosensor) and due to the transducer (e.g optical sensor). Working of optical sensor is based on measurements of quantitative changes of parameters characterizing light radiation. The most often analyzed parameters include: amplitude (intensity), frequency or polarization. Changes in the optical properties one of the compound which reacts with biological material coated on the sensor is analyzed by a direct method, in an indirect method indicators are used, which changes the optical properties due to the transformation of the testing species. The most commonly used dyes in this method are: small molecules with an aromatic ring, like rhodamine, fluorescent proteins, for example green fluorescent protein (GFP), or nanoparticles such as quantum dots (QDs). Quantum dots have, in comparison with organic dyes, much better photoluminescent properties, better bioavailability and chemical inertness. These are semiconductor nanocrystals size of 2-10 nm. This very limited number of atoms and the ‘nano’-size gives QDs these highly fluorescent properties. Rapid and sensitive detection of dopamine is extremely important in modern medicine. Dopamine is very important neurotransmitter, which mainly occurs in the brain and central nervous system of mammals. Dopamine is responsible for the transmission information of moving through the nervous system and plays an important role in processes of learning or memory. Detection of dopamine is significant for diseases associated with the central nervous system such as Parkinson or schizophrenia. In developed optical biosensor for detection of dopamine, are used graphene quantum dots (GQDs). In such sensor dopamine molecules coats the GQD surface - in result occurs quenching of fluorescence due to Resonance Energy Transfer (FRET). Changes in fluorescence correspond to specific concentrations of the neurotransmitter in tested sample, so it is possible to accurately determine the concentration of dopamine in the sample.

Keywords: biosensor, dopamine, fluorescence, quantum dots

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Authors: Leila Safazadeh, Brad Berron

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Self-assembled monolayers have tremendous impact in interfacial science, due to the unique opportunity they offer to tailor surface properties. Low-density self-assembled monolayers are an emerging class of monolayers where the environment-interfacing portion of the adsorbate has a greater level of conformational freedom when compared to traditional monolayer chemistries. This greater range of motion and increased spacing between surface-bound molecules offers new opportunities in tailoring adsorption phenomena in sensing systems. In particular, we expect low-density surfaces to offer a unique opportunity to intercalate surface bound ligands into the secondary structure of protiens and other macromolecules. Additionally, as many conventional sensing surfaces are built upon gold surfaces (SPR or QCM), these surfaces must be compatible with gold substrates. Here, we present the first stable method of generating low-density self assembled monolayer surfaces on gold for the analysis of their interactions with protein targets. Our approach is based on the 2:1 addition of thiol-yne chemistry to develop new classes of y-shaped adsorbates on gold, where the environment-interfacing group is spaced laterally from neighboring chemical groups. This technique involves an initial deposition of a crystalline monolayer of 1,10 decanedithiol on the gold substrate, followed by grafting of a low-packed monolayer on through a photoinitiated thiol-yne reaction in presence of light. Orthogonality of the thiol-yne chemistry (commonly referred to as a click chemistry) allows for preparation of low-density monolayers with variety of functional groups. To date, carboxyl, amine, alcohol, and alkyl terminated monolayers have been prepared using this core technology. Results from surface characterization techniques such as FTIR, contact angle goniometry and electrochemical impedance spectroscopy confirm the proposed low chain-chain interactions of the environment interfacing groups. Reductive desorption measurements suggest a higher stability for the click-LDMs compared to traditional SAMs, along with the equivalent packing density at the substrate interface, which confirms the proposed stability of the monolayer-gold interface. In addition, contact angle measurements change in the presence of an applied potential, supporting our description of a surface structure which allows the alkyl chains to freely orient themselves in response to different environments. We are studying the differences in protein adsorption phenomena between well packed and our loosely packed surfaces, and we expect this data will be ready to present at the GRC meeting. This work aims to contribute biotechnology science in the following manner: Molecularly imprinted polymers are a promising recognition mode with several advantages over natural antibodies in the recognition of small molecules. However, because of their bulk polymer structure, they are poorly suited for the rapid diffusion desired for recognition of proteins and other macromolecules. Molecularly imprinted monolayers are an emerging class of materials where the surface is imprinted, and there is not a bulk material to impede mass transfer. Further, the short distance between the binding site and the signal transduction material improves many modes of detection. My dissertation project is to develop a new chemistry for protein-imprinted self-assembled monolayers on gold, for incorporation into SPR sensors. Our unique contribution is the spatial imprinting of not only physical cues (seen in current imprinted monolayer techniques), but to also incorporate complementary chemical cues. This is accomplished through a photo-click grafting of preassembled ligands around a protein template. This conference is important for my development as a graduate student to broaden my appreciation of the sensor development beyond surface chemistry.

Keywords: low-density self-assembled monolayers, thiol-yne click reaction, molecular imprinting

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Authors: Xiao Chen, Xiaoying Kong, Min Xu

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This paper presents a road vehicle detection approach for the intelligent transportation system. This approach mainly uses low-cost magnetic sensor and associated data collection system to collect magnetic signals. This system can measure the magnetic field changing, and it also can detect and count vehicles. We extend Mel Frequency Cepstral Coefficients to analyze vehicle magnetic signals. Vehicle type features are extracted using representation of cepstrum, frame energy, and gap cepstrum of magnetic signals. We design a 2-dimensional map algorithm using Vector Quantization to classify vehicle magnetic features to four typical types of vehicles in Australian suburbs: sedan, VAN, truck, and bus. Experiments results show that our approach achieves a high level of accuracy for vehicle detection and classification.

Keywords: vehicle classification, signal processing, road traffic model, magnetic sensing

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Authors: Giuseppe Liverano

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Today’s school iscalledupon to take the lead role in supporting students towards the formation of conscious identity and a sense of responsible citizenship, through the development of key competencies for lifelong learning A rolethatrequiresit to be ready for change and to respond to the ever new needs of students, by adopting new pedagogical and didactic models and new didactic devices. Information and Communication Technologies, in this sense, reveal themselves to be usefulresourcesthatpermit to focus attention on the learning of eachindividualstudentunderstoodas a dynamic and relational process of constructing shared and participatedmeanings. The use of collaborative writing apps represents a democratic and shared knowledge way of constructionthroughICTs. It promotes the learning of reading-writing, literacy, and the development of transversal competencies in an inclusive perspective peer-to-peer comparison and reflectionthatstimulates the transfer of thought into speech and writing, the transformation of knowledge through a trialogicalapproach to learning generates enthusiasm and strengthensmotivationItrepresents a “different” way of expressing the training needs which come from several disciplinary fields of subjects with different cultures. The contribution aims to reflect on the formative value of collaborative writing through apps and analyse some proposals on line at school during the time of pandemic in order to highlight their critical aspects and pedagogical perspectives.

Keywords: collaborative writing, formative value, online, apps, pandemic

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Authors: Pannathorn Chachvarat, Smarnjit Piromrun

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Aging is the reality for the future world. An urgent priority for the development of the elderlies’ quality living is needed. The promotion of quality the elderly to live longer in their dignity and being independence are essential. The objective of this descriptive research was to study the self-care regarding to the valuable living in Thai elderly. The randomized sample was 100 elderly who live in Muang district of Phayao province. The tools included 2 parts; 1) Personal data (gender, age, income, occupation, marital status, living condition and disease), and 2) the self-care regarding to the valuable living questionnaire consisted of 3 domains, physical (21items), spiritual (13 items) and social domain (12 items). The content validity tool was tested the IOC ranged between 0.60 – 1.00 and the reliability test, Cronbach Alpha was 0.82. The research found that; The most participants were female (60 %), Farmer (37%), and underlying disease (65 %). The range of age was 68 years. Overall of the self-care regarding to the valuable living of physical, spiritual and social were at the high level.The highest level of physical activities was self-taking bath twice a day (morning and evening), and slept at least 5-6 hours at night time.The highest level of spirit activities was a good member of the family, contributions to persons in family, good emotion. Additionally were enjoyable, accepting changes in the body such as the dry skin and the blurred vision, accepting the roles and duties in taking care of house and grandchildren, selecting the applicable activities and practice according to religious Buddhateachingfor the happiness and meditated life.The highest of the social activities were the good relationship between other elderlies and family members, happy to help social activities as of their capacity, and being happy to help other people who have problems.

Keywords: self-care, valuable living, elderly, Thai

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Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

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The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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Authors: Mary Joy C. Montenegro, Voltaire M. Mistades

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This action research was implemented to enhance the teaching of linear motion and to improve students' conceptual understanding and engagement using a developed 7R-based module called 'module on vectors and one-dimensional kinematics' (MVOK). MVOK was validated in terms of objectives, contents, format, and language used, presentation, usefulness, and overall presentation. The validation process revealed a value of 4.7 interpreted as 'Very Acceptable' with a substantial agreement (0. 60) from the validators. One intact class of 46 Grade 12 STEM students from one of the public schools in Paranaque City served as the participants of this study. The students were taught using the module during the first semester of the academic year 2019–2020. Employing the mixed-method approach, quantitative data were gathered using pretest/posttest, activity sheets, problem sets, and survey form, while qualitative data were obtained from surveys, interviews, observations, and reflection log. After the implementation, there was a significant difference of 18.4 on students’ conceptual understanding as shown in their pre-test and post-test scores on the 24-item test with a moderate Hake gain equal to 0.45 and an effect size of 0.83. Moreover, the scores on activity and problem sets have a 'very good' to 'excellent' rating, which signifies an increase in the level of students’ conceptual understanding. There also exists a significant difference between the mean scores of students’ engagement overall (t= 4.79, p = 0.000, p < 0.05) and in the dimension of emotion (t = 2.51, p = 0.03) and participation/interaction (t = 5.75, p = 0.001). These findings were supported by gathered qualitative data. Positive views were elicited from the students since it is an accessible tool for learning and has well-detailed explanations and examples. The results of this study may substantiate that using MVOK will lead to better physics content understanding and higher engagement.

Keywords: conceptual understanding, engagement, linear motion, module

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Authors: Kamellia Reshadi, Pranav Ragji, Theodoros Soldatos

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Recent advancements in cloud computing and storage, along with rapid progress in artificial intelligence (AI), have transformed approaches to developing efficient, scalable applications. However, integrating AI with cloud computing poses challenges as these fields are often disjointed, and many advancements remain difficult to access, obscured in complex documentation or scattered across research reports. For this reason, we share experiences from prototype projects combining these technologies. Specifically, we focus on Google Cloud Platform (GCP) functionalities and describe vision and speech activities applied to labeling, subtitling, and urban traffic flow tasks. We describe challenges, pricing, architecture, and other key features, considering the goal of real-time performance. We hope our demonstrations provide not only essential guidelines for using these functionalities but also enable more similar approaches.

Keywords: artificial intelligence, cloud computing, real-time applications, case studies, knowledge management, research and development, text labeling, video annotation, urban traffic analysis, public safety, prototyping, Google Cloud Platform

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Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux

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In France, the railway network is one of the main transport infrastructures and is the second largest European network. Therefore, railway inspection is an important task in railway maintenance to ensure safety for passengers using significant means in personal and technical facilities. Artificial vision has recently been applied to several railway applications due to its potential to improve the efficiency and accuracy when analyzing large databases of acquired images. In this paper, we present a vision system able to detect fastening elements based on artificial vision approach. This system acquires railway images using a CCD camera installed under a control carriage. These images are stitched together before having processed. Experimental results are presented to show that the proposed method is robust for detection fasteners in a complex environment.

Keywords: computer vision, image processing, railway inspection, image stitching, fastener recognition, neural network

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Authors: Yaron Covo, Tamar Kofman, Shira Palti

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Over the recent decades, debates about the engagement of fans in football governance have focused on the club level and national level, emphasizing the significance of fans’ involvement in increasing the connection of clubs with the community, and in safeguarding the transparency, accountability, and clubs’ financial stability. This paper will offer a different conceptual justification for providing fans with access to decision-making processes in football. First, it will suggest that the participation of fans is necessary for addressing discriminatory practices against women in football stadiums. Second, it will argue that fans’ involvement in football governance is important not only at the club and national level but also at the global level, relying on the principles of Global Administrative Law. In contemporary men’s football, female fans face different forms of discrimination. Iranian women are still prohibited from attending football games at the domestic level; In Saudi Arabia, female fans are only permitted to enter designated family areas; Qatar – the host of the 2022 FIFA world cup – requires women to attend matches wearing modest clothing. Similarly, in Turkey, Lebanon, UAE, and Algeria, women face cultural barriers when attending men’s football games. In other countries, female fans suffer from subtle discrimination, including micro-aggressions, misogyny, sexism, and noninstitutionalized exclusion. Despite the vital role of fans in world football and the importance of football for many women’s lives, little has been done to address this problem. While FIFA recognizes that these discriminatory practices contradict its statutes, this recognition fails to materialize into meaningful change. This paper will argue that FIFA’s omission stems from two interrelated characteristics of world football: (1) the ultra-masculine nature of the game; (2) the insufficient recognition of fans’ significance. While fans have been given a voice in various football bodies on the domestic level, FIFA has yet to allow the representation of fans as stakeholders in world football governance. Since fans are a more heterogeneous group than players, the voices of those fans who do not fit the ultra-masculine model are not heard. Thus, by focusing mainly on male players, FIFA reproduces the hegemonic masculinity that feeds back into fan dynamics and marginalizes female fans. To rectify this problem, we will call on FIFA to provide fans and female fans in particular, with voice mechanisms and access to decision-making processes. In addition to its impact on the formation of fans’ identities, such a move will allow fans to demand better enforcement of existing anti-discrimination norms and new regulations to address their needs. The literature has yet to address the relationship between fans’ gender discrimination and global football governance. Building on Global Administrative Law scholarship and feminist theories, this paper will aim to fill this gap.

Keywords: fans, FIFA, football governance, gender discrimination, global administrative law, human rights

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Authors: Oliver Kinnane, Aidan Reilly, John Grimes, Sara Pavia, Rosanne Walker

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Unwanted sound reflection can create acoustic discomfort and lead to problems of speech comprehensibility. Contemporary building techniques enable highly finished internal walls resulting in sound reflective surfaces. In contrast, sustainable construction materials using natural and vegetal materials, are often more porous and absorptive. Hemp shiv is used as an aggregate and when mixed with lime binder creates a low-embodied-energy concrete. Cement replacements such as ground granulated blast slag (GGBS), a byproduct of other industrial processes, are viewed as more sustainable alternatives to high-embodied-energy cement. Hemp concretes exhibit good hygrothermal performance. This has focused much research attention on them as natural and sustainable low-energy alternatives to standard concretes. A less explored benefit is the acoustic absorption capability of hemp-based concretes. This work investigates hemp-lime-GGBS concrete specifically, and shows that it exhibits high levels of sound absorption.

Keywords: hemp, hempcrete, acoustic absorption, GGBS

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Authors: R. Gautam, P. Sastha Kanagasabai, G. N. Rathna

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The proposed healthcare system enables quadriplegic patients, people with severe motor disabilities to send commands to electronic devices and monitor their vitals. The growth of Brain-Computer-Interface (BCI) has led to rapid development in 'assistive systems' for the disabled called 'assistive domotics'. Brain-Computer-Interface is capable of reading the brainwaves of an individual and analyse it to obtain some meaningful data. This processed data can be used to assist people having speech disorders and sometimes people with limited locomotion to communicate. In this Project, Emotiv EPOC Headset is used to obtain the electroencephalogram (EEG). The obtained data is processed to communicate pre-defined commands over the internet to the desired mobile phone user. Other Vital Information like the heartbeat, blood pressure, ECG and body temperature are monitored and uploaded to the server. Data analytics enables physicians to scan databases for a specific illness. The Data is processed in Intel Edison, system on chip (SoC). Patient metrics are displayed via Intel IoT Analytics cloud service.

Keywords: brain computer interface, Intel Edison, Emotiv EPOC, IoT analytics, electroencephalogram

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Authors: André Augusto Ceballos Melo

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Design to facilitate the recognition of congruent prosthetic movements, context-to-motion translations guided by image, verbal prompt, users nonverbal communication such as facial expressions, gestures, paralinguistics, scene context, and object recognition contributes to this process though it can also be applied to other tasks, such as walking, Prosthetic limbs as assistive technology through gestures, sound codes, signs, facial, body expressions, and scene context The context-to-motion model is a machine learning approach that is designed to improve the control and dexterity of prosthetic limbs. It works by using sensory input from the prosthetic limb to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. This can help to improve the performance of the prosthetic limb and make it easier for the user to perform a wide range of tasks. There are several key benefits to using the context-to-motion model for prosthetic limb control. First, it can help to improve the naturalness and smoothness of prosthetic limb movements, which can make them more comfortable and easier to use for the user. Second, it can help to improve the accuracy and precision of prosthetic limb movements, which can be particularly useful for tasks that require fine motor control. Finally, the context-to-motion model can be trained using a variety of different sensory inputs, which makes it adaptable to a wide range of prosthetic limb designs and environments. Stable diffusion is a machine learning method that can be used to improve the control and stability of movements in robotic and prosthetic systems. It works by using sensory feedback to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. One key aspect of stable diffusion is that it is designed to be robust to noise and uncertainty in the sensory feedback. This means that it can continue to produce stable, smooth movements even when the sensory data is noisy or unreliable. To implement stable diffusion in a robotic or prosthetic system, it is typically necessary to first collect a dataset of examples of the desired movements. This dataset can then be used to train a machine learning model to predict the appropriate control inputs for a given set of sensory observations. Once the model has been trained, it can be used to control the robotic or prosthetic system in real-time. The model receives sensory input from the system and uses it to generate control signals that drive the motors or actuators responsible for moving the system. Overall, the use of the context-to-motion model has the potential to significantly improve the dexterity and performance of prosthetic limbs, making them more useful and effective for a wide range of users Hand Gesture Body Language Influence Communication to social interaction, offering a possibility for users to maximize their quality of life, social interaction, and gesture communication.

Keywords: stable diffusion, neural interface, smart prosthetic, augmenting

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Authors: Reut Lanyado, David Mendlovic

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Most biological methods for authentication require special equipment and, some of them are easy to fake. We proposed a method for authentication based on hand movement while typing a sentence with a regular camera. This technique uses the full video of the hand, which is harder to fake. In the first phase, we tracked the hand joints in each frame. Next, we represented a single frame for each individual using our Pose Agnostic Rotation and Movement (PARM) dimensional space. Then, we indicated a full video of hand movement in a fixed low dimensional space using this method: Fixed Dimension Video by Interpolation Statistics (FDVIS). Finally, we identified each individual in the FDVIS representation using unsupervised clustering and supervised methods. Accuracy exceeds 96% for 80 individuals by using supervised KNN.

Keywords: authentication, feature extraction, hand recognition, security, signal processing

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Authors: Abrar Hussain Qureshi

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Vocabulary has been highlighted as a key indicator in any foreign language learning program, especially English as a foreign language (EFL). It is often considered a potential tool in foreign language curriculum, and its deficiency impedes successful communication in the target language. The knowledge of the lexicon is very significant in getting communicative competence and performance. Nouns constitute a considerable bulk of English vocabulary. Rather, they are the bones of the English language and are the main semantic carrier in spoken and written discourse. As nouns dominate the bulk of the English lexicon, their role becomes all the more potential. The undertaken research is a systematic effort in this regard to work out a list of highly frequent list of Pakistani English nouns for the EFL learners at the secondary level. It will encourage autonomy for the EFL learners as well as will save their time. The corpus used for the research has been developed locally from leading English newspapers of Pakistan. Wordsmith Tools has been used to process the research data and to retrieve word list of frequent Pakistani English nouns. The retrieved list of core Pakistani English nouns is supposed to be useful for English language learners at the secondary level as it covers a wide range of speech events.

Keywords: corpus, EFL, frequency list, nouns

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Authors: Anna Amato

Abstract:

Every child needs communication. If spoken language is not or not fully available due to congenital or acquired limitations, those affected need appropriate ways. These can be found in many possibilities of Augmentative and Alternative Communications (AAC). In the communication promotion of severely impaired children, who can use their own body communication forms only to a limited extent for the differentiated understanding, computers with eye control play an essential role. It takes some time to understand the individual forms of communication of the child. Children who depend on the AAC need competent support to learn to communicate in a motivated way in their everyday life. The aim of the present parents' survey (n = 4), which was evaluated descriptively, is to demonstrate the development of communicative abilities as well as the motivation to use complex communication aids with eye control by patients with atypical Rett Syndrome. An increase in communication skills, well-being, self-reliance, and self-esteem, an improvement in social participation, as well as a reduction in anger and screaming events, were noted. The complex visual communication tools were available daily for 3 out of 4 patients with atypical Rett Syndrome. It raises research questions regarding speech understanding and the ability to drive eye control technology in a larger group of atypical Rett Syndrome patients.

Keywords: augmentative and alternative communications, AAC, atypical Rett-syndrome, children, development

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

Abstract:

Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. That is why the need for automation of this task is urgent. A lot of studies have investigated the subject using different standard image processing descriptors and sometimes hand-crafted ones.In this work, we make a comparative study between classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN, Autoencoders, Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches

Keywords: pollens identification, features extraction, pollens classification, automated palynology

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Authors: Muhammad Ammar, Talha Ali, Abdul Basit, Bakhtawar Rajput, Zobia Sohail

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Music note detection is an area of study for the past few years and has its own influence in music file generation from sheet music. We proposed a method to detect music notes on sheet music using basic thresholding and blob detection. Subsequently, we created a notes dictionary using a semi-supervised learning approach. After notes detection, for each test image, the new symbols are added to the dictionary. This makes the notes detection semi-automatic. The experiments are done on images from a dataset and also on the captured images. The developed approach showed almost 100% accuracy on the dataset images, whereas varying results have been seen on captured images.

Keywords: music note, sheet music, optical music recognition, blob detection, thresholding, dictionary generation

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Authors: Fatten F. Elkomy

Abstract:

The Syrian refugees are the largest refugee population since World War II. Mostly, children, these individuals were exposed to intense traumatic events in their homeland, throughout their journey, and during settlement in foreign lands. Art is a universal language to express feelings and tough human experiences. It is also a medium for healing and promoting creativity and resilience. Literature review was conducted to examine the use of art to facilitate psychiatric interviews, diagnosis, and therapy with traumatized children. Results show a severe impact of childhood trauma on the increased risk for abuse, neglect, and psychiatric disorders. Clinicians must recognize, evaluated and provide help for these children. In conclusion, drawings are used to tell a story, reflect deep emotions, and create a meaningful self-recognition and determination. Participants will understand art therapy using the expressive therapies continuum framework to evaluate drawings and to promote healing for refugee children.

Keywords: art therapy, children drawings, Syrian refugees, trauma in childhood

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Authors: Sara Namdarian, Hafez Salleh

Abstract:

This paper scrutinizes the circumstances of the application of Augmented Reality (AR) technology to enhance the adaptability of architecture classrooms in private Malaysian university classrooms. This study aims to indicate the constraints of mono-functional classrooms in comparison to the potentials of multi-functional classrooms derived from AR application through an exploratory mixed method strategy. This paper expects to contribute towards recognition of suitable AR techniques which can be applied in the development of Adaptive-AR-Classroom-Systems (AARCS) in architecture classrooms. The findings, derived from the analysis, show current classrooms have limited functional spaces, and concludes that AR application can be used in design classrooms to provide a variety of visuals and virtual objects that are required in conducting architecture projects in higher educational centers.

Keywords: design activity, space enhancement, design education, architectural design augmented reality

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Authors: Fitria Ningsih

Abstract:

This study concerns on the process of making corpus obtained from Indonesian year 4 students’ free writing compared to the vocabulary taught in English language textbooks. 369 students’ sample writings from 19 public elementary schools in Malang, East Java, Indonesia and 5 selected English textbooks were analyzed through corpus in linguistics method using AdTAT -the Adelaide Text Analysis Tool- program. The findings produced wordlists of the top 100 words most frequently used by students and the top 100 words given in English textbooks. There was a 45% match between the two lists. Furthermore, the classifications of the top 100 most frequent words from the two corpora based on part of speech found that both the Indonesian and English languages employed a similar use of nouns, verbs, adjectives, and prepositions. Moreover, to see the contextualizing the vocabulary of learning materials towards the students’ need, a depth-analysis dealing with the content and the cultural views from the vocabulary taught in the textbooks was discussed through the criteria developed from the checklist. Lastly, further suggestions are addressed to language teachers to understand the students’ background such as recognizing the basic words students acquire before teaching them new vocabulary in order to achieve successful learning of the target language.

Keywords: corpus, frequency, English, Indonesian, linguistics, textbooks, vocabulary, wordlists, writing

Procedia PDF Downloads 187

Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

Procedia PDF Downloads 175