Search results for: facial action

Authors: Cherish Romina Prajitno, Sunisa Thaichinda

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One indicator of facial aging is wrinkles. Not only that, but wrinkles are a key indicator in our world of facial aesthetics. Wrinkles occur where fault lines develop in aging skin. Nowadays, people are more motivated to keep up their appealing and young appearance. Many individuals are seeking a fast recovery time for their aesthetic procedures and are interested in non-invasive techniques that have a proven track record for successful outcomes. The purpose of this study is to see the efficacy of 100% (pure) grapeseed oil for reducing periorbital wrinkles. This study used the split-face, double-blind method, and this treatment was administered for three months at random to fifteen patients, with the grapeseed oil at one side of the face and the other side with the placebo. The main outcome measure was determined by conducting a comparative analysis of the participants' wrinkle results during each visit using the VIsioscan® VC98. Additionally, we evaluated the skin's elasticity and barrier function using the Cutometer® MP 530 and Tewameter® TM300. Furthermore, we administered a satisfaction score questionnaire to the patients in the 12th week. The findings of the study indicate that grapeseed oil exhibited a noteworthy effect in diminishing the appearance of wrinkles in the periorbital region, enhancing the viscoelastic properties of the periorbital skin, and improving the functionality of the skin barrier in the periorbital area.

Keywords: periorbital wrinkles, pure grapeseed oil, split-face method

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Authors: Kourosh Modarresi

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The abundance of media channels and devices has given users a variety of options to extract, discover, and explore information in the digital world. Since, often, there is a long and complicated path that a typical user may venture before taking any (significant) action (such as purchasing goods and services), it is critical to know how each node (media channel) in the path of user has contributed to the final action. In this work, the significance of each media channel is computed using statistical analysis and machine learning techniques. More specifically, “Regularized Singular Value Decomposition”, and “Sparse Principal Component” has been used to compute the significance of each channel toward the final action. The results of this work are a considerable improvement compared to the present approaches.

Keywords: multimedia attribution, sparse principal component, regularization, singular value decomposition, feature significance, machine learning, linear systems, variable shrinkage

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Authors: Brittany Richardson, Ying Wang

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For physical therapy, exercise prescription, athlete training, and regular fitness training, it is crucial to perform health assessments or fitness assessments periodically. An accurate assessment is propitious for tracking recovery progress, preventing potential injury and making long-range training plans. Assessments include necessary measurements, height, weight, blood pressure, heart rate, body fat, etc. and advanced evaluation, muscle group strength, stability-mobility, and movement evaluation, etc. In the current standard assessment procedures, the accuracy of assessments, especially advanced evaluations, largely depends on the experience of physicians, coaches, and personal trainers. And it is challenging to track clients’ progress in the current assessment. Unlike the tradition assessment, in this paper, we present a deep learning based face recognition algorithm for accurate, comprehensive and trackable assessment. Based on the result from our assessment, physicians, coaches, and personal trainers are able to adjust the training targets and methods. The system categorizes the difficulty levels of the current activity for the client or user, furthermore make more comprehensive assessments based on tracking muscle group over time using a designed landmark detection method. The system also includes the function of grading and correcting the form of the clients during exercise. Experienced coaches and personal trainer can tell the clients' limit based on their facial expression and muscle group movements, even during the first several sessions. Similar to this, using a convolution neural network, the system is trained with people’s facial expression to differentiate challenge levels for clients. It uses landmark detection for subtle changes in muscle groups movements. It measures the proximal mobility of the hips and thoracic spine, the proximal stability of the scapulothoracic region and distal mobility of the glenohumeral joint, as well as distal mobility, and its effect on the kinetic chain. This system integrates data from other fitness assistant devices, including but not limited to Apple Watch, Fitbit, etc. for a improved training and testing performance. The system itself doesn’t require history data for an individual client, but the history data of a client can be used to create a more effective exercise plan. In order to validate the performance of the proposed work, an experimental design is presented. The results show that the proposed work contributes towards improving the quality of exercise plan, execution, progress tracking, and performance.

Keywords: exercise prescription, facial recognition, landmark detection, fitness assessments

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Authors: Sudheer Dhume, T. Prasad

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There are distinct signs of Business Education losing its sheen. It is more so in developing countries. One of the reasons is the value addition at the end of 2 year MBA program is not matching with the requirements of present times and expectations of the students. In this backdrop, Pedagogy Innovation has become prerequisite for making our MBA programs relevant and useful. This paper is the description and analysis of innovative Action Learning pedagogical approach adopted by a group of faculty members at NITIE Mumbai. It not only promotes multidisciplinary research but also enhances integration of the functional areas skillsets in the students. The paper discusses the theoretical bases of this pedagogy and evaluates the effectiveness of it vis-à-vis conventional pedagogical tools. The evaluation research using Bloom’s taxonomy framework showed that this blended method of Business Education is much superior as compared to conventional pedagogy.

Keywords: action learning, blooms taxonomy, business education, innovation, pedagogy

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Authors: Chloe Shu-Hua Yeh

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Effects of videogame play on players cognitive abilities is a growing research field in the recent decades, however, little is known about how ‘out-of-school’ use of videogame influences creativity. This interdisciplinary research explores the cognitive and emotional effects of two different types of online videogames (an action videogame and a non-action videogame) on subsequent creativity performances using a within-participant design study with 36 participants. Results showed that after playing the action game participants performed higher originality, elaboration and flexibility than after playing the causal game. The results explored effects of emotional states elicited during playing the games suggesting that arousal may be a significant emotional factor which influence subsequent creativity performance. The cognitive and emotional effects of videogame were discussed followed with implications for emotion-creativity-videogame play research, game designers, educational practitioners and parents.

Keywords: attentional breadth, creativity, emotion, videogame play

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Authors: Nayra Martin-Key, Erich Graf, Wendy Adams, Graeme Fairchild

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Children and adolescents with Conduct Disorder (CD) have been shown to demonstrate impairments in emotion recognition, but it is currently unclear whether this deficit is related to specific emotions or whether it represents a global deficit in emotion recognition. An emotion recognition task with concurrent eye-tracking was employed to further explore this relationship in a sample of male and female adolescents with CD. Participants made emotion categorization judgements for presented dynamic and morphed static facial expressions. The results demonstrated that males with CD, and to a lesser extent, females with CD, displayed impaired facial expression recognition in general, whereas callous-unemotional (CU) traits were linked to specific problems in sadness recognition in females with CD. A region-of-interest analysis of the eye-tracking data indicated that males with CD exhibited reduced fixation times for the eye-region of the face compared to typically-developing (TD) females, but not TD males. Females with CD did not show reduced fixation to the eye-region of the face relative to TD females. In addition, CU traits did not influence CD subjects’ attention to the eye-region of the face. These findings suggest that the emotion recognition deficits found in CD males, the worst performing group in the behavioural tasks, are partly driven by reduced attention to the eyes.

Keywords: attention, callous-unemotional traits, conduct disorder, emotion recognition, eye-region, eye-tracking, sex differences

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Authors: Reka Zsuzsanna Mathe

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The globalization and the Europeanization have significantly contributed to a change in the role of the nation-states. The global economic crisis, the climate changes, and the recent refugee crisis, are just a few among many challenges that cannot be effectively addressed by the traditional role of the nation-states. One of the main roles of the states is to solve collective action problems, however due to their changing roles; apparently this is getting more and more difficult. Depending on political culture, collective action problems are solved either through cooperation or conflict. The political culture of Central and Eastern European (CEE) countries is marked by low civic participation and by a weak civil society. In this type of culture collective action problems are likely to be induced through conflict, rather than the democratic process of dialogue and any type of social change is probably to be introduced by social movements. Several studies have been conducted on the social movements of the CEE countries, yet, it is still not clear if the most significant social movements of the region tend to choose rather the cooperative or the conflictual way as action strategy. This study differentiates between a national and a European action field, having different social orders. The actors of the two fields are the broadly understood civil society members, conceptualized as social movements. This research tries to answer the following questions: a) What are the norms that best characterize the CEE countries’ social order? b) What type of actors would prefer a change and in which areas? c) Is there a significant difference between the main actors active in the national versus the European field? The main hypotheses are that there are conflicting norms defining the national and the European action field, and there is a significant difference between the action strategies adopted by social movements acting in the two different fields. In mapping the social order, the study uses data provided by the European Social Survey. Big data of the Global Data on Events, Location and Tone (GDELT) database offers information regarding the main social movements and their preferred type of action. The unit of the analysis is the so called ‘Visegrad 4’ countries: Poland, Czech Republic, Slovakia and Hungary and the research uses data starting from 2005 (after the European accession of these four countries) until May, 2017. According to the data, the main hypotheses were confirmed.

Keywords: big data, Central and Eastern Europe, civil society, GDELT, social movements

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Authors: Anoop T. R., Otman Basir, Robert F. Hess, Eileen E. Birch, Brooke A. Koritala, Reed M. Jost, Becky Luu, David Stager, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. We developed a two-stage method for strabismus detection and classification based on photographs of the face. The first stage detects the presence or absence of strabismus, and the second stage classifies the type of strabismus. The first stage comprises face detection using Haar cascade, facial landmark estimation, face alignment, aligned face landmark detection, segmentation of the eye region, and detection of strabismus using VGG 16 convolution neural networks. Face alignment transforms the face to a canonical pose to ensure consistency in subsequent analysis. Using facial landmarks, the eye region is segmented from the aligned face and fed into a VGG 16 CNN model, which has been trained to classify strabismus. The CNN determines whether strabismus is present and classifies the type of strabismus (exotropia, esotropia, and vertical deviation). If stage 1 detects strabismus, the eye region image is fed into stage 2, which starts with the estimation of pupil center coordinates using mask R-CNN deep neural networks. Then, the distance between the pupil coordinates and eye landmarks is calculated along with the angle that the pupil coordinates make with the horizontal and vertical axis. The distance and angle information is used to characterize the degree and direction of the strabismic eye misalignment. This model was tested on 100 clinically labeled images of children with (n = 50) and without (n = 50) strabismus. The True Positive Rate (TPR) and False Positive Rate (FPR) of the first stage were 94% and 6% respectively. The classification stage has produced a TPR of 94.73%, 94.44%, and 100% for esotropia, exotropia, and vertical deviations, respectively. This method also had an FPR of 5.26%, 5.55%, and 0% for esotropia, exotropia, and vertical deviation, respectively. The addition of one more feature related to the location of corneal light reflections may reduce the FPR, which was primarily due to children with pseudo-strabismus (the appearance of strabismus due to a wide nasal bridge or skin folds on the nasal side of the eyes).

Keywords: strabismus, deep neural networks, face detection, facial landmarks, face alignment, segmentation, VGG 16, mask R-CNN, pupil coordinates, angle deviation, horizontal and vertical deviation

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Authors: Lisa Wilderink, Ingrid Bakker, Albertine J. Schuit, Jacob C. Seidell, Carry M. Renders

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To ensure that health behavior interventions for children living in low socioeconomic position (SEP) neighborhoods are in line with children’s wishes and needs, participation of the children in the development, implementation, and evaluation is crucial. In this paper, we show how children living in three low-SEP neighborhoods in the Netherlands can be involved in Participatory Action Research (PAR) and what influences this participation process. The Photovoice method was used and provided comprehensive information from the children’s perspectives. With the help of the community workers, the children identified feasible actions. This paper shows that it is possible to involve children from low SEP neighborhoods in a meaningful way. We found that it is important to constantly discuss the process with participants, start with a concrete question or problem and adapt the project to the local context and skills of participants

Keywords: children, healthy behavior, participatory action research, socioeconomic health inequalities

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Authors: Deon de Jager, Yahya Zweiri, Dimitrios Makris

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The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.

Keywords: cognitive robotics, semantic memory, episodic memory, maximum entropy principle, particle swarm optimization

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Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf, Kamal Kharazi

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Research into long-term memory has demonstrated that the richness of the knowledge base cues in memory tasks improves retrieval process, which in turn influences learning and memory performance. The present research investigated the idea that adding cues connected to knowledge can affect memory performance in the context of action memory in children. In action memory studies, participants are instructed to learn a series of verb–object phrases as verbal learning and experience-based learning (learning by doing and learning by observation). It is well established that executing action phrases is a more memorable way to learn than verbally repeating the phrases, a finding called enactment effect. In the present study, a total of 410 students from four grade groups—2nd, 4th, 6th, and 8th—participated in this study. During the study, participants listened to verbal action phrases (VTs), performed the phrases (SPTs: subject-performed tasks), and observed the experimenter perform the phrases (EPTs: experimenter-performed tasks). During the test phase, cued recall test was administered. Semantic relational cues (i.e., well-integrated vs. poorly integrated items) were manipulated in the present study. In that, the participants were presented two lists of action phrases with high semantic integration between verb and noun, e.g., “write with the pen” and with low semantic integration between verb and noun, e.g., “pick up the glass”. Results revealed that experience-based learning had a better results than verbal learning for both well-integrated and poorly integrated items, though manipulations of semantic relational cues can moderate the enactment effect. In addition, children of different grade groups outperformed for well- than poorly integrated items, in flavour of older children. The results were discussed in relation to the effect of knowledge-based information in facilitating retrieval process in children.

Keywords: action memory, enactment effect, knowledge-based cues, school-aged children, semantic relational cues

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Authors: Ghazala Yaqub, Zubi Sadiq, Almas Hamid, Saira Iqbal

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This paper is the very first report of three dual action hybrids synthesized by covalent linkage of carbazole based novel antibacterial compounds with efflux pump inhibitors i.e., indole acetic acid/gallic acid. Novel carbazole based antibacterial compounds were prepared first and then these were covalently linked with efflux pump inhibitors which leads to the successful formation of hybrids. All prepared compounds were evaluated for their bacterial cell killing capability against Escherichia coli, Staphylococcus aureus, Pasteurella multocida and Bacillus subtilis. Compound were effective against all tested bacterial strains at different concentrations. But when these compounds were linked with efflux pump inhibitors they showed dramatic enhancement in their bacterial cell killing potential and minimum inhibitory concentration of all hybrids ranges from 7.250 µg/mL to 0.0283 µg/mL.

Keywords: antimicrobial assay, carbazole, dual action hybrids, efflux pump inhibitors

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Authors: Saleh Alkarri, Melinda Frame, Dimple Sharma, John Cairney, Lee Maddan, Jin H. Kim, Jonathan O. Rayner, Teresa M. Bergholz, Muhammad Rabnawaz

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Reported herein is an investigation of anti-bacterial and anti-virus properties, mode of action of Mg(OH)₂ and copper-infused Mg(OH)₂ nanoplatelets (NPs) on melt-compounded and thermally embossed polypropylene (PP) surfaces. The anti-viral activity for the NPs was studied in aqueous liquid suspensions against SARS-CoV-2, and the mode of action was investigated on neat NPs and PP samples that were thermally embossed with NPs. Anti-bacterial studies for melt-compounded NPs in PP confirmed approximately 1 log reduction of E. coli populations in 24 h, while for thermally embossed NPs, an 8 log reduction of E. coli populations was observed. In addition, the NPs exhibit anti-viral activity against SARS-CoV-2. Fluorescence microscopy revealed that reactive oxygen species (ROS) is the main mode of action through which Mg(OH)₂ and Cu-Infused Mg(OH)₂act against microbes. Plastics with anti-microbial surfaces from where biocides are non-leachable are highly desirable. This work provides a general fabrication strategy for developing anti-microbial plastic surfaces.

Keywords: anti-microbial activity, E. coli K-12 MG1655, anti-viral activity, SARS-CoV-2, copper-infused magnesium hydroxide, non-leachable, ROS, compounding, surface embossing, dyes

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Authors: Selvamuthukumaran Thirunavukkarasu, Arivudainambi Sundararajan

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The plant active molecules with their known mode of action are important leads to the development of newer insecticides. Lactone glycoside was identified earlier as the active principle in Cleistanthus collinus (Roxb.) Benth. (Fam: Euphorbiaceae). It possessed feeding deterrent, insecticidal and insect growth regulatory actions at varying concentrations. Deducing its mode of action opens a possibility of its further development. A no-choice leaf disc bioassay was carried out with lactone glycoside at different doses for different instars and Deterrence Indices were worked out. Using regression analysis concentrations imparting 10, 30 and 50 per cent deterrence (DI10, DI30 & DI50) were worked out. At these doses, effect on nutritional indices like Relative Consumption and Growth Rates (RCR & RGR), Efficiencies of Conversion of Ingested and Digested food (ECI & ECD) and Approximate Digestibility (AD) were worked out. The Relative Consumption and Growth Rate of control and lactone glycoside larva were compared by regression analysis. Regression analysis of deterrence indices revealed that the concentrations needed for imparting 50 per cent deterrence was 60.66, 68.47 and 71.10 ppm for third, fourth and fifth instars respectively. Relative consumption rate (RCR) and relative growth rate (RGR) were reduced. This confirmed the antifeedant action of the fraction. Approximate digestibility (AD) was found greater in treatments indicating reduced faeces because of poor digestibility and retention of food in the gut. Efficiency of conversion of both ingested and digested (ECI and ECD) food was also found to be greatly reduced. This indicated presence of toxic action. This was proved by comparing growth efficiencies of control and lactone glycoside treated larvae. Lactone glycoside was found to possess both feeding deterrent and toxic modes of action. Studies on molecular targets based on this preliminary site of action lead to new insecticide development.

Keywords: Spodoptera litura Fabricius, Cleistanthus collinus (Roxb.) Benth, feeding deterrence, mode of action

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Authors: Maria Hopkins, Sarah Koch, Fred Biasini

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Autism is lifelong disorder that affects one out of every 110 Americans. The deficits that accompany Autism Spectrum Disorders (ASD), such as abnormal behaviors and social incompetence, often make it extremely difficult for these individuals to gain functional independence from caregivers. These long-term implications necessitate an immediate effort to improve social skills among children with an ASD. Any technology that could teach individuals with ASD necessary social skills would not only be invaluable for the individuals affected, but could also effect a massive saving to society in treatment programs. The overall purpose of the first study was to develop, implement, and evaluate an avatar tutor for social skills training in children with ASD. “Face Say” was developed as a colorful computer program that contains several different activities designed to teach children specific social skills, such as eye gaze, joint attention, and facial recognition. The children with ASD were asked to attend to FaceSay or a control painting computer game for six weeks. Children with ASD who received the training had an increase in emotion recognition, F(1, 48) = 23.04, p < 0.001 (adjusted Ms 8.70 and 6.79, respectively) compared to the control group. In addition, children who received the FaceSay training had higher post-test scored in facial recognition, F(1, 48) = 5.09, p < 0.05 (adjusted Ms: 38.11 and 33.37, respectively) compared to controls. The findings provide information about the benefits of computer-based training for children with ASD. Recent research suggests the value of also using socially assistive robots with children who have an ASD. Researchers investigating robots as tools for therapy in ASD have reported increased engagement, increased levels of attention, and novel social behaviors when robots are part of the social interaction. The overall goal of the second study was to develop a social robot designed to teach children specific social skills such as emotion recognition. The robot is approachable, with both an animal-like appearance and features of a human face (i.e., eyes, eyebrows, mouth). The feasibility of the robot is being investigated in children ages 7-12 to explore whether the social robot is capable of forming different facial expressions to accurately display emotions similar to those observed in the human face. The findings of this study will be used to create a potentially effective and cost efficient therapy for improving the cognitive-emotional skills of children with autism. Implications and study findings using the robot as an intervention tool will be discussed.

Keywords: autism, intervention, technology, emotions

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Authors: Ali Almadan, Anoop Krishnan, Ajita Rattani

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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

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Authors: Shreyansh Singh, Afroz Ahmed

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Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. The total of this assumption over a populace addresses sentiment surveying and has various applications. Current text-based sentiment analysis depends on the development of word embeddings and Machine Learning models that take in conclusion from enormous text corpora. Sentiment Analysis from text is presently generally utilized for consumer loyalty appraisal and brand insight investigation. With the expansion of online media, multimodal assessment investigation is set to carry new freedoms with the appearance of integral information streams for improving and going past text-based feeling examination using the new transforms methods. Since supposition can be distinguished through compelling follows it leaves, like facial and vocal presentations, multimodal opinion investigation offers good roads for examining facial and vocal articulations notwithstanding the record or printed content. These methodologies use the Recurrent Neural Networks (RNNs) with the LSTM modes to increase their performance. In this study, we characterize feeling and the issue of multimodal assessment investigation and audit ongoing advancements in multimodal notion examination in various spaces, including spoken surveys, pictures, video websites, human-machine, and human-human connections. Difficulties and chances of this arising field are additionally examined, promoting our theory that multimodal feeling investigation holds critical undiscovered potential.

Keywords: sentiment analysis, RNN, LSTM, word embeddings

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Authors: M. P. Casiraghi, C. M. Quintella, P. Almeida

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Paraffinic oils were submitted to microbial action. The microorganisms consisted of bacteria of the genera Pseudomonas sp and Bacillus lincheniforms. The alterations in interfacial tension were determined using a tensometer and applying the hanging drop technique at room temperature (299 K ±275 K). The alteration in the constitution of the paraffins was evaluated by means of gas chromatography. The microbial activity was observed to reduce interfacial tension by 54 to 78%, as well as consuming the paraffins C19 to C29 and producing paraffins C36 to C44. The LIFirr technique made it possible to determine the microbial action quickly.

Keywords: paraffins, biosurfactants, LIFirr, microbial activity

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Authors: Prince Dacosta Aboagye, Ayyoob Sharifi

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Cities respond to climate concerns mainly through their climate action plans (CAPs). A comprehensive content analysis of the dynamics in existing urban CAPs is not well represented in the literature. This literature void presents a difficulty in appreciating the strengths and weaknesses of urban CAPs. Here, we perform a qualitative content analysis (QCA) on CAPs from 278 cities worldwide and use text-mining tools to map and visualize the relevant data. Our analysis showed a decline in the number of CAPs developed and published following the global COVID-19 lockdown period. Evidently, megacities are leading the deep decarbonisation agenda. We also observed a transition from developing mainly mitigation-focused CAPs pre-COP21 to both mitigation and adaptation CAPs. A lack of inclusiveness in local climate planning was common among European and North American cities. The evidence is a catalyst for understanding the trends in existing urban CAPs to shape future urban climate planning.

Keywords: urban, climate action plans, strengths, weaknesses

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Authors: Lilis Kistriyani, Dine Olisvia, Lutfa Rahmawati

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Facial mask is an important part of every beauty treatment because it will give a smooth and gentle effect on the face. This research is done to make edible film that will be applied for face mask. The main ingredient in making this edible film is purple sweet potato powder with the addition of glycerol as plasticizer. One of the ingredients in purple sweet potato is a flavonoid compound. The purpose of this study was to determine the effect of increasing the amount of glycerol to flavonoids release and the effect on the physical properties and biological properties of edible film produced. The stages of this research are the making of edible film, then perform some analysis, among others, spectrophotometer UV-vis analysis to find out how many flavonoids can be released into facial skin, tensile strength and elongation of break analysis, biodegradability analysis, and microbiological analysis. The variation of edible film is the volume of glycerol that is 1 ml, 2 ml, 3 ml. The results of spectrophotometer UV-vis analysis showed that the most flavonoid release concentration is 20.33 ppm in the 2 ml glycerol variation. The best tensile strength value is 8,502 N, and the greatest elongation of break value is 14% in 1 ml glycerol variation. In the biodegradability test, the more volume of glycerol added the faster the edible film is degraded. The results of microbiological analysis showed that purple sweet potato extract has the ability to inhibit the growth of Propionibacterium acnes seen in the presence of inhibiting zone which is 18.9 mm.

Keywords: face mask, edible film, plasticizer, flavonoid

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Authors: Meltem Kürtüncü, Işın Alkan

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Objective: This study was carried out with an experimental design in order to determine whether the lullaby, which was listened from mother’s voice and a stranger’s voice to the babies born at term and hospitalized in neonatal intensive care unit, had an effect on stress and relaxation symptoms of the infants. Method: Data from the study were obtained from 90 newborn babies who were hospitalized in Neonatal Intensive Care Unit of Zonguldak Maternity And Children Hospital between September 2015-January 2016 and who met the eligibility criteria. Lullaby concert was performed by choosing one of the suitable care hours. Stress and relaxation symptoms were recorded by the researcher on “Newborn response follow-up form” at pre-care and post-care. Results: After lullaby concert when stress symptoms compared to infants in the experimental and control groups before the care was not detected statistically significant difference between crying, contraction, facial grimacing, flushing, cyanosis and the rates of increase in temperature. After care, crying, contractions, facial grimacing, flushing, and restlessness revealed a statistically significant difference between the groups, but as the cyanosis and temperature increased stress responses did not result in a significant difference between the groups. In the control group babies the crying, contraction, facial grimacing, flushing, and restlessness behaviors rates were found to be significantly higher than experimental group babies. After lullaby concert when relaxation symptoms compared to infants in the experimental and control groups before the care, eye contact rates who listen to lullaby from mother’s voice was found to be significantly higher than infants who listen to lullaby from stranger’s voice and infants in the control group. After care as eye contact, smiling, sucking/searching, yawning, non-crying and sleep behaviors relaxation symptoms revealed statistically significant results. In the control group, these behaviors were found statistically lower degree than the experimental groups. Conclusion: Lullaby concerts as masking the ambient noise, reducing the stress symptoms and increasing the relaxation symptoms, and also for soothing and stimulant affects, due to ease the transition to the sleep state should be preferred in the neonatal intensive care units.

Keywords: lullaby, mother voice, relaxation, stress

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Authors: Jiahui Song, Ravindra P. Joshi

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The use of high-intensity, short-duration electric pulses is a promising development with many biomedical applications. The uses include irreversible electroporation for killing abnormal cells, reversible poration for drug and gene delivery, neuromuscular manipulation, and the shrinkage of tumors, etc. High intensity, short-duration electric pulses result in the creation of high-density, nanometer-sized pores in the cellular membrane. This electroporation amounts to localized modulation of the transverse membrane conductance, and effectively provides a voltage shunt. The electrically controlled changes in the trans-membrane conductivity could be used to affect neural traffic and action potential propagation. A rat was taken as the representative example in this research. The simulation study shows the pathway from the sensorimotor cortex down to the spinal motoneurons, and effector muscles could be reversibly blocked by using high-intensity, short-duration electrical pulses. Also, actual experimental observations were compared against simulation predictions.

Keywords: action potential, electroporation, high-intensity, short-duration

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Authors: Carolyn Cameron

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Stop Food Waste Australia is working with the industry to co-design sector action plans to prevent and reduce food waste across the supply chain. We are a public-private partnership, funded in 2021 by the Australian national government under the 2017 National Food Waste Strategy. Our partnership has representatives from all levels of government, industry associations from farm to fork, and food rescue groups. Like many countries, Australia has adopted the Sustainable Development Goal (SDG) target of 12.3 to halve food waste by 2030. A seminal 2021 study, the National Food Waste Feasibility Report, developed a robust national baseline, illustrating hotspots in commodities and across the supply chain. This research found that the consumption stages – households, food service, and institutions - account for over half of all food waste, and 22% of food produced never leaves the farm gate. Importantly the study found it is feasible for Australia to meet SDG 12.3, but it will require unprecedented action by governments, industry, and the community. Sector Action Plans (Plan) are one of the four main initiatives of Stop Food Waste Australia, including a voluntary commitment, a coordinated food waste communications hub, and robust monitoring and reporting framework. These plans provide a systems-based approach to reducing food loss and waste while realising multiple benefits for supply chain partners and other collaborators. Each plan is being co-designed with the key stakeholders most able to directly control or influence the root cause(s) of food waste hotspots and to take action to reduce or eliminate food waste in their value chain.  The initiatives in the Plans are fit-for-purpose, reflecting current knowledge and recognising priorities may refocus over time. To date, sector action plans have been developed with the Food Rescue, Cold Chain, Bread and Bakery, and Dairy Sectors. Work is currently underway on Meat and Horticulture, and we are also developing supply-chain stage plans for food services and institutions. The study will provide an overview of Australia’s food waste baseline and challenges, the important role of sector action plans in reducing food waste, and case studies of implementation outcomes.

Keywords: co-design, horticulture, sector action plans, voluntary

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Authors: Frederik Calsius, Mirela Popa, Alexia Briassouli

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In the field of machine learning, it is common practice to use benchmark datasets to prove the working of a method. The domain of action recognition in videos often uses datasets like Kinet-ics, Something-Something, UCF-101 and HMDB-51 to report results. Considering the properties of the datasets, there are no datasets that focus solely on very short clips (2 to 3 seconds), and on highly-similar fine-grained actions within one specific domain. This paper researches how current state-of-the-art action recognition methods perform on a dataset that consists of highly similar, fine-grained actions. To do so, a dataset of skateboarding tricks was created. The performed analysis highlights both benefits and limitations of state-of-the-art methods, while proposing future research directions in the activity recognition domain. The conducted research shows that the best results are obtained by fusing RGB data with OpenPose data for the Temporal Shift Module.

Keywords: activity recognition, fused deep representations, fine-grained dataset, temporal modeling

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Authors: José Batista de Souza Neto

Abstract:

This research project has as its theme the implementation of public policies to support micro and small businesses (MSEs). The research problem defined was how public policies for access to markets that drive the entrepreneurial ecosystem of MSEs are implemented. The general objective of this research is to understand the process of implementing a public policy to support the entrepreneurial ecosystem of MSEs by the Support Service for Micro and Small Enterprises of the State of São Paulo (SEBRAESP). Public policies are constituent elements of entrepreneurship ecosystems that influence the creation and development of ventures from the action of the entrepreneur. At the end of the research, it is expected to achieve the results for the following specific objectives: (a) understand how the entrepreneurial ecosystem of MSEs is constituted; (b) understand how market access public policies for MSEs are designed and implemented; (c) understand SEBRAE's role in the entrepreneurship ecosystem; and (d) offer an action plan and monitor its execution up to march, 2023. The field research will be conducted based on Action Research, with a qualitative and longitudinal approach to the data. Data collection will be based on narratives produced since 2019 when the decision to implement Comércio Brasil program, a public policy focused on generating market access for 4280 MSEs yearly, was made. The narratives will be analyzed by the method of document analysis and narrative analysis. It is expected that the research will consolidate the relevance of public policies to market access for MSEs and the role of SEBRAE as a protagonist in the implementation of these public policies in the entrepreneurship ecosystem will be demonstrated. Action research is recognized as an intervention method, it is expected that this research will corroborate its role in supporting management processes.

Keywords: entrepreneurship, entrepreneurship ecosystem, public policies, SEBRAE, action research

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Authors: Mohd Azraei Pangah Pa'at, Mohd Ruzlin Mohd Mokhtar, Norhidayu Rameli, Tashia Marie Anthony, Huzainie Shafi Abd Halim

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Partial Discharge (PD) diagnostic mapping testing is one of the main diagnostic testing techniques that are widely used in the field or onsite testing for underground power cable in medium voltage level. The existence of PD activities is an early indication of insulation weakness hence early detection of PD activities can be determined and provides an initial prediction on the condition of the cable. To effectively manage the results of PD Mapping test, it is important to have acceptable criteria to facilitate prioritization of mitigation action. Tenaga Nasional Berhad (TNB) through Distribution Network (DN) division have developed PD severity model name Severity Index (SI) for offline PD mapping test since 2007 based on onsite test experience. However, this severity index recommendation action had never been revised since its establishment. At presence, PD measurements data have been extensively increased, hence the severity level indication and the effectiveness of the recommendation actions can be analyzed and verified again. Based on the new revision, the recommended action to be taken will be able to reflect the actual defect condition. Hence, will be accurately prioritizing preventive action plan and minimizing maintenance expenditure.

Keywords: partial discharge, severity index, diagnostic testing, medium voltage, power cable

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Authors: Mukunda Bastola, Frank Nyame-Asiamah

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Economics explanation for privatisation, drawing on neo-liberal market structures and technical efficiency principles has failed to address social imbalance and, distribute the efficiency benefits accrued from privatisation equitably among service users and different classes of people in society. Stakeholders’ interest, which cover ethical values and changing human needs are ignored due to shareholders’ profit maximising strategy with higher service charges. The consequence of these is that, the existing justifications for privatisation have fallen short of customer quality expectations because the underlying plan-based models fail to account for the nuances of customer expectations. We draw on the theory of deferred action to develop a context-based privatisation model, the deferred-based privatisation model, to explain how privatisation could be strategised for the emergent reality of the wider stakeholders’ interests and everyday quality demands of customers which are unpredictable.

Keywords: privatisation, service quality, shareholders, deferred action, deferred-based privatisation model

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Authors: Bruno RamaëL, GwenaëL Page, Catherine Knopf-Lenoir, Olivier Baledent, Anne-Virginie Salsac

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No routine technique currently exists for clinicians to measure the mechanical properties of vascular walls non-invasively. Most of the data available in the literature come from traction or dilatation tests conducted ex vivo on native blood vessels. The objective of the study is to develop a non-invasive characterization technique based on Magnetic Resonance Imaging (MRI) measurements of the deformation of vascular walls under pulsating blood flow conditions. The goal is to determine the mechanical properties of the vessels by inverse analysis, coupling imaging measurements and numerical simulations of the fluid-structure interactions. The hyperelastic properties are identified using Solidworks and Ansys workbench (ANSYS Inc.) solving an optimization technique. The vessel of interest targeted in the study is the common carotid artery. In vivo MRI measurements of the vessel anatomy and inlet velocity profiles was acquired along the facial vascular network on a cohort of 30 healthy volunteers: - The time-evolution of the blood vessel contours and, thus, of the cross-section surface area was measured by 3D imaging angiography sequences of phase-contrast MRI. - The blood flow velocity was measured using a 2D CINE MRI phase contrast (PC-MRI) method. Reference arterial pressure waveforms were simultaneously measured in the brachial artery using a sphygmomanometer. The three-dimensional (3D) geometry of the arterial network was reconstructed by first creating an STL file from the raw MRI data using the open source imaging software ITK-SNAP. The resulting geometry was then transformed with Solidworks into volumes that are compatible with Ansys softwares. Tetrahedral meshes of the wall and fluid domains were built using the ANSYS Meshing software, with a near-wall mesh refinement method in the case of the fluid domain to improve the accuracy of the fluid flow calculations. Ansys Structural was used for the numerical simulation of the vessel deformation and Ansys CFX for the simulation of the blood flow. The fluid structure interaction simulations showed that the systolic and diastolic blood pressures of the common carotid artery could be taken as reference pressures to identify the mechanical properties of the different arteries of the network. The coefficients of the hyperelastic law were identified using Ansys Design model for the common carotid. Under large deformations, a stiffness of 800 kPa is measured, which is of the same order of magnitude as the Young modulus of collagen fibers. Areas of maximum deformations were highlighted near bifurcations. This study is a first step towards patient-specific characterization of the mechanical properties of the facial vessels. The method is currently applied on patients suffering from facial vascular malformations and on patients scheduled for facial reconstruction. Information on the blood flow velocity as well as on the vessel anatomy and deformability will be key to improve surgical planning in the case of such vascular pathologies.

Keywords: identification, mechanical properties, arterial walls, MRI measurements, numerical simulations

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Authors: Virginie Hergault, Siham Chebbah, Bertrand Frere

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Following in-house objectives, Central laboratory of Paris police Prefecture conducted a general review on models and Computational Fluid Dynamics (CFD) codes used to simulate pollutant dispersion in the atmosphere. Starting from that review and considering main features of Large Eddy Simulation, Central Laboratory Of Paris Police Prefecture (LCPP) postulates that the Fire Dynamics Simulator (FDS) model, from National Institute of Standards and Technology (NIST), should be well suited for air pollutant dispersion modeling. This paper focuses on the implementation and the evaluation of FDS in the frame of the European COST ES1006 Action. This action aimed at quantifying the performance of modeling approaches. In this paper, the CUTE dataset carried out in the city of Hamburg, and its mock-up has been used. We have performed a comparison of FDS results with wind tunnel measurements from CUTE trials on the one hand, and, on the other, with the models results involved in the COST Action. The most time-consuming part of creating input data for simulations is the transfer of obstacle geometry information to the format required by SDS. Thus, we have developed Python codes to convert automatically building and topographic data to the FDS input file. In order to evaluate the predictions of FDS with observations, statistical performance measures have been used. These metrics include the fractional bias (FB), the normalized mean square error (NMSE) and the fraction of predictions within a factor of two of observations (FAC2). As well as the CFD models tested in the COST Action, FDS results demonstrate a good agreement with measured concentrations. Furthermore, the metrics assessment indicate that FB and NMSE meet the tolerance acceptable.

Keywords: numerical simulations, atmospheric dispersion, cost ES1006 action, CFD model, cute experiments, wind tunnel data, numerical results

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Authors: Mei-Ying Liao, Lee-Ching Wei, Jung-Hsiang Tseng

Abstract:

The main purpose of this study was to explore the process of planning and execution of the music learning center in preschool. This study was conducted through a collaborative action research method. The research members included a university music professor, a teaching guide, a preschool director, and a preschool teacher, leading a class of 5-6-year-old children to participate in this study. Five teaching cycles were performed with a subject of bird. In the whole process that lasted three months, the research members would maintain the conversation, reflection, and revision repeatedly. A triangular validated method was used to collect data, including archives, interviews, seminars, observations, journals, and learning evaluations to improve research on the validity and reliability. It was found that a successful music learning center required comprehensive planning and execution. It is also important to develop good listening, singing, respect, and homing habits at the beginning of running the music learning center. By timely providing diverse musical instruments, learning materials, and activities according to the teaching goals, children’s desire to learning was highly stimulated. Besides, peer interactions improved their ensemble and problem-solving abilities. The collaborative action research enhanced the preschool teacher’s confidence and promoted professional growth of the research members.

Keywords: collaborative action research, case study, music learning center, music development

Procedia PDF Downloads 349