Search results for: multimodal transformer autoencoder

Authors: Shao-Di Feng, Von-Wun Soo

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To generate symbolic music with specific emotions is a challenging task due to symbolic music datasets that have emotion labels are scarce and incomplete. This research aims to generate more refined emotions based on the training datasets that are only labeled with four quadrants in Russel’s 2D emotion model. We focus on the theory of Music Fadernet and map arousal and valence to the low-level attributes, and build a symbolic music generation model by combining transformer and GM-VAE. We adopt an in-attention mechanism for the model and improve it by allowing modulation by conditional information. And we show the music generation model could control the generation of music according to the emotions specified by users in terms of high-level linguistic expression and by manipulating their corresponding low-level musical attributes. Finally, we evaluate the model performance using a pre-trained emotion classifier against a pop piano midi dataset called EMOPIA, and by subjective listening evaluation, we demonstrate that the model could generate music with more refined emotions correctly.

Keywords: music generation, music emotion controlling, deep learning, semi-supervised learning

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Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

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Authors: Oluwatosin S. Adeoye

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The power quality issues in the world today are critical to the development of different nations. Prosperity of each nation depends on availability of constant power supply. Constant power supply is a major challenge in Africa particularly in Nigeria where the generated power is than thirty percent of the required power. The metrics of power quality are voltage dip, flickers, spikes, harmonics and interruptions. The level of interruptions in Ekiti State was examined through the investigation of the causes of power interruptions in the State. The method used was the collection of data from the Distribution Company, assessment through simple programming as a command for plotting the graphs through the use of MATLAB 2015 depicting the behavioural pattern of the interruption for a period of six months in 2016. The result shows that the interrelationship between the interruptions and development. Recommendations were suggested with the objective of solving the problems being set up by interruptions in the State and these include installation of reactors, automatic voltage regulators and effective tap changing system on the lines, busses and transformer substation respectively.

Keywords: development, frequency, interruption, power, quality

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Authors: D. Heinemann, S. Schramm, S. Knabner, D. Baumgarten

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Purpose: Applying solder paste to printed circuit boards (PCB) with stencils has been the method of choice over the past years. A new method uses a jet printer to deposit tiny droplets of solder paste through an ejector mechanism onto the board. This allows for more flexible PCB layouts with smaller components. Due to the viscosity of the solder paste, air blisters can be trapped in the cartridge. This can lead to missing solder joints or deviations in the applied solder volume. Therefore, a built-in and real-time inspection of the printing process is needed to minimize uncertainties and increase the efficiency of the process by immediate correction. The objective of the current study is the design of an optimal imaging system and the development of an automatic algorithm for the detection of applied solder joints from optical from the captured images. Methods: In a first approach, a camera module connected to a microcomputer and LED strips are employed to capture images of the printed circuit board under four different illuminations (white, red, green and blue). Subsequently, an improved system including a ring light, an objective lens, and a monochromatic camera was set up to acquire higher quality images. The obtained images can be divided into three main components: the PCB itself (i.e., the background), the reflections induced by unsoldered positions or screw holes and the solder joints. Non-uniform illumination is corrected by estimating the background using a morphological opening and subtraction from the input image. Image sharpening is applied in order to prevent error pixels in the subsequent segmentation. The intensity thresholds which divide the main components are obtained from the multimodal histogram using three probability density functions. Determining the intersections delivers proper thresholds for the segmentation. Remaining edge gradients produces small error areas which are removed by another morphological opening. For quantitative analysis of the segmentation results, the dice coefficient is used. Results: The obtained PCB images show a significant gradient in all RGB channels, resulting from ambient light. Using different lightings and color channels 12 images of a single PCB are available. A visual inspection and the investigation of 27 specific points show the best differentiation between those points using a red lighting and a green color channel. Estimating two thresholds from analyzing the multimodal histogram of the corrected images and using them for segmentation precisely extracts the solder joints. The comparison of the results to manually segmented images yield high sensitivity and specificity values. Analyzing the overall result delivers a Dice coefficient of 0.89 which varies for single object segmentations between 0.96 for a good segmented solder joints and 0.25 for single negative outliers. Conclusion: Our results demonstrate that the presented optical imaging system and the developed algorithm can robustly detect solder joints on printed circuit boards. Future work will comprise a modified lighting system which allows for more precise segmentation results using structure analysis.

Keywords: printed circuit board jet-printing, inspection, segmentation, solder paste detection

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Authors: Harpa Ragnarsdóttir, Magnús Kjartan Gíslason, Kristín Briem, Guðný Lilja Oddsdóttir

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Introduction: Whiplash-Associated Disorder (WAD) is a health problem characterized by motor, neurological and psychosocial symptoms, stressing the need for a multimodal treatment approach. To achieve individualized multimodal approach, prognostic factors need to be identified early using validated patient-reported and objective outcome measures. The aim of this study is to demonstrate the degree of association between patient-reported and clinical outcome measures of WAD patients in the subacute phase. Methods: Individuals (n=41) with subacute (≥1, ≤3 months) WAD (I-II), medium to high-risk symptoms, or neck pain rating ≥ 4/10 on the Visual Analog Scale (VAS) were examined. Outcome measures included measurements for movement control (Butterfly test) and cervical active range of motion (cAROM) using the NeckSmart system, a computer system using an inertial measurement unit (IMU) that connects to a computer. The IMU sensor is placed on the participant’s head, who receives visual feedback about the movement of the head. Patient-reported neck disability, pain intensity, general health, self-perceived handicap, central sensitization, and difficulties due to dizziness were measured using questionnaires. Excel and R statistical software were used for statistical analyses. Results: Forty-one participants, 15 males (37%), 26 females (63%), mean (SD) age 36.8 (±12.7), underwent data collection. Mean amplitude accuracy (AA) (SD) in the Butterfly test for easy, medium, and difficult paths were 2.4mm (0.9), 4.4mm (1.8), and 6.8mm (2.7), respectively. Mean cAROM (SD) for flexion, extension, left-, and right rotation were 46.3° (18.5), 48.8° (17.8), 58.2° (14.3), and 58.9° (15.0), respectively. Mean scores on the Neck Disability Index (NDI), VAS, Dizziness Handicap Inventory (DHI), Central Sensitization Inventory (CSI), and 36-Item Short Form Survey RAND version (RAND) were 43% (17.4), 7 (1.7), 37 (25.4), 51 (17.5), and 39.2 (17.7) respectively. Females showed significantly greater deviation for AA compared to males for easy and medium Butterfly paths (p<0.05). Statistically significant moderate to strong positive correlation was found between the DHI and easy (r=0.6, p=0.05), medium (r=0.5, p=0.05)) and difficult (r=0.5, p<0.05) Butterfly paths, between the total RAND score and all cAROMs (r between 0.4-0.7, p≤0.05) except flexion (r=0.4, p=0.7), and between the NDI score and CSI (r=0.7, p<0.01), VAS (r=0.5, p<0.01), and DHI (r=0.7, p<0.01) scores respectively. Discussion: All patient-reported and objective measures were found to be outside the reference range. Results suggest females have worse movement control in the neck in the subacute WAD phase. However, no statistical difference based on gender was found in patient-reported measures. Suggesting females might have worse movement control than males in general in this phase. The correlation found between DHI and the Butterfly test can be explained because the DHI measures proprioceptive symptoms like dizziness and eye movement disorders that can affect the outcome of movement control tests. A correlation was found between the total RAND score and cAROM, suggesting that a reduced range of motion affects the quality of life. Significance: The NeckSmart system can detect abnormalities in cAROM, fine movement control, and kinesthesia of the neck. Results suggest females have worse movement control than males. Results show a moderate to a high correlation between several patient-reported and objective measurements.

Keywords: whiplash associated disorders, car-collision, neck, trauma, subacute

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Authors: Yasunori Kobori, Murong Li, Feng Zhao, Shu Wu, Nobukazu Takai, Haruo Kobayashi

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This paper proposes an electrolytic capacitor-less transformer-less AC-DC LED driver with a current ripple canceller. The proposed LED driver includes a diode bridge, a buck-boost converter, a negative feedback controller and a current ripple cancellation circuit. The current ripple canceller works as a bi-directional current converter using a sub-inductor, a sub-capacitor and two switches for controlling current flow. LED voltage is controlled in order to regulate LED current by the negative feedback controller using a current sense resistor. There are two capacitors with capacitance of 5 uF. We describe circuit topologies, operation principles and simulation results for our proposed circuit. In addition, we show the line regulation for input voltage variation from 85V to 130V. The output voltage ripple is 2V and the LED current ripple is 65 mA which is less than 20% of the average of LED current of 350 mA.

Keywords: DC-DC buck converter, four-level output voltage, single inductor multi output (SIMO), switching converter

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Authors: David Julian Bernal Melgarejo

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Inland Waterway Transportation (IWT) is playing an important role in national transport systems, water transportation is considered to be safe, energy efficient and environmentally friendly mode of transport, considering all the benefits of IWT the Colombian government is planning to restore the Magdalena’s River navigability, embrace waterway transportation in Colombia could strength competitiveness while reduce most of the transport externalities. However, the current situation of the Magdalena deplorable, the most important river of Colombia has been abandoned for decades and the solution is beyond of a single administrative entity. This paper analyzes the outcomes of the Navigation And Inland Waterway Action and Development in Europe (NAIADES) program as a prospective to develop a sustainable program in Colombia. In order to guarantee the long-term future, and the adaptability of the program a research based on individual interviews with stakeholders and policy experts were carried out, findings support the idea of lack of integration within governmental institution, develop marketing strategies and human resources.

Keywords: inland waterway transportation, logistics, sustainability, multimodal transport systems, water transportation

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Authors: Artur Krukowski, Emmanouela Vogiatzaki

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The article presents an ongoing work in research projects such as SCAN4RECO or ARCH, both funded by the European Commission under Horizon 2020 program. The former one concerns multimodal and multispectral scanning of Cultural Heritage assets for their digitization and conservation via spatiotemporal reconstruction and 3D printing, while the latter one aims to better preserve areas of cultural heritage from hazards and risks. It co-creates tools that would help pilot cities to save cultural heritage from the effects of climate change. It develops a disaster risk management framework for assessing and improving the resilience of historic areas to climate change and natural hazards. Tools and methodologies are designed for local authorities and practitioners, urban population, as well as national and international expert communities, aiding authorities in knowledge-aware decision making. In this article we focus on 3D modelling of object geometry using primarily photogrammetric methods to achieve very high model accuracy using consumer types of devices, attractive both to professions and hobbyists alike.

Keywords: 3D modelling, UAS, cultural heritage, preservation

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Authors: M. Rahimi, F. Corman

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This paper study the travel behavior of passengers in a public transport disruption under information provision strategies. We develop a within-day approach for multi-agent simulation to evaluate the behavior of the agents, under comprehensive scenarios through various information exposure, equilibrium, and non-equilibrium scenarios. In particular, we quantify the effects of information strategies in disruption situation on passengers’ satisfaction, number of involved agents, and the caused delay. An agent-based micro-simulation model (MATSim) is applied for the city of Zürich, Switzerland, for the purpose of activity-based simulation in a multimodal network. Statistic outcome is analysed for all the agents who may be involved in the disruption. Agents’ movement in the public transport network illustrates agents’ adaptations to available information about the disruption. Agents’ delays and utility reveal that information significantly affects agents’ satisfaction and delay in public transport disruption. Besides, while the earlier availability of the information causes the fewer consequent delay for the involved agents, however, it also leads to more amount of affected agents.

Keywords: agent-based simulation, disruption management, passengers’ behavior simulation, public transport

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Authors: Shanhua Hu

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Social media as a critical propagandizing form of film, video games, and digital products has received substantial research attention, but there exists several critical barriers such as: (1) few studies exploring the internal and external connections of a product as part of the multimodal context that gives rise to readability and commercial return; (2) the lack of study of multimodal analysis in product’s official account of game publishers and its impact on users’ behaviors including purchase intention, social media engagement, and playing time; (3) no standardized ecologically-valid, game type-varying data can be used to study the complexity of official account’s postings within a time period. This proposed research helps to tackle these limitations in order to develop a model of readability study that is more ecologically valid, robust, and thorough. To accomplish this objective, this paper provides a more diverse dataset comprising different visual elements and messages collected from the official Twitter accounts of the Top 20 best-selling games of 2021. Video game companies target potential users through social media, a popular approach is to set up an official account to maintain exposure. Typically, major game publishers would create an official account on Twitter months before the game's release date to update on the game's development, announce collaborations, and reveal spoilers. Analyses of tweets from those official Twitter accounts would assist publishers and marketers in identifying how to efficiently and precisely deploy advertising to increase game sales. The purpose of this research is to determine how official game accounts use Twitter to attract new customers, specifically which types of messages are most effective at increasing sales. The dataset includes the number of days until the actual release date on Twitter posts, the readability of the post (Flesch Reading Ease Score, FRES), the number of emojis used, the number of hashtags, the number of followers of the mentioned users, the categorization of the posts (i.e., spoilers, collaborations, promotions), and the number of video views. The timeline of Twitter postings from official accounts will be compared to the history of pre-orders and sales figures to determine the potential impact of social media posts. This study aims to determine how the above-mentioned characteristics of official accounts' Twitter postings influence the sales of the game and to examine the possible causes of this influence. The outcome will provide researchers with a list of potential aspects that could influence people's judgments in limited-word posts. With the increased average online time, users would adapt more quickly than before in online information exchange and readings, such as the word to use sentence length, and the use of emojis or hashtags. The study on the promotion of official game accounts will not only enable publishers to create more effective promotion techniques in the future but also provide ideas for future research on the influence of social media posts with a limited number of words on consumers' purchasing decisions. Future research can focus on more specific linguistic aspects, such as precise word choice in advertising.

Keywords: engagement, official account, promotion, twitter, video game

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Authors: Vipresh Mehta , Aman Abhishek, Jatin Batra, Gautam Iyer

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Huge amount of solar radiation reaching the earth can be harnessed to provide electricity through Photo voltaic (PV) panels. The solar PV is an exciting technology but suffers from low efficiency. A study on low efficiency in multi MW solar power plants reveals that the electric yield of the PV modules is reduced due to reflection of the irradiation from the sun and when a module’s temperature is elevated, as there is decrease in the voltage and efficiency. We intend to alter the structure of the PV system, We also intend to improve the efficiency of the Solar Photo Voltaic Panels by active cooling to reduce the temperature losses considerably and decrease reflection losses to some extent. Reflectors/concentrators and anti-reflecting coatings are also used to intensify the amount of output produced from the system. Apart from this, transformer-less Grid-tied Inverter. And also, a T-LCL immitance circuit is used to reduce the harmonics and produce a constant output from the entire system.

Keywords: PV panels, efficiency improvement, active cooling, quantum dots, organic-inorganic hybrid 3D panel, ground water tunneling

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Authors: Suzi M. S. Cavalari, Tim Lewis

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Teletandem is a bilingual model of virtual exchange in which two partners from different countries( and speak different languages) meet synchronously and regularly over a period of 8 weeks to learn each other’s mother tongue (or the language of proficiency). At São Paulo State University (UNESP), participants should answer a questionnaire before starting the exchanges in which one of the questions refers to setting a goal to be accomplished with the help of the teletandem partner. In this context, the present presentation aims to examine the goal-setting activity of 79 Brazilians who participated in Portuguese-English teletandem exchanges over a period of four years (2012-2015). The theoretical background is based on goal setting and self-regulated learning theories that propose that appropriate efficient goals are focused on the learning process (not on the product) and are specific, proximal (short-term) and moderately difficult. The data set used was 79 initial questionnaires retrieved from the MulTeC (Multimodal Teletandem Corpus). Results show that only approximately 10% of goals can be considered appropriate. Features of these goals are described in relation to specificities of the teletandem context. Based on the results, three mechanisms that can help learners to set attainable goals are discussed.

Keywords: foreign language learning, goal setting, teletandem, virtual exchange

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Authors: Ola Hafez

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This study examines the way selected Egyptian digitally mediated memes utilize intertextuality as a means of expression. It is motivated by the emerging digital socio-political humorous practice using various forms of political commentary in Egyptian social media. One of these forms involves the use of memes incorporating (often doctored) video frames taken from Egyptian plays, films and songs, and relocated in a different socio-political context, often with a caption that re-appropriates the frame for the purpose of critical commentary, thus juxtaposing the socio-political phenomena being addressed and the Egyptian artistic and cultural heritage. The paper presents a discourse study of a convenience sample of a recent social media campaign and carries out two levels of analysis. At the micro level, the study pinpoints the various modes of intertextuality employed, including verbal as well as visual intertextuality in the light of the work of social semiotics by Kress and van Leeuwen. At the macro level, the paper sheds light on the socio-political implications of such practice in the light of Political Discourse Analysis.

Keywords: digitally mediated discourse, discourse analysis, Egyptian Arabic, intertextuality, memes, multimodality, political discourse analysis

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Authors: Sham Kidane, Fitsum Gaim, Ibrahim Abdella, Sirak Asmerom, Yoel Ghebrihiwot, Simon Mulugeta, Natnael Ambassager

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The lack of annotated datasets is a bottleneck to the progress of NLP in low-resourced languages. The work presented here consists of large-scale annotated datasets and models for the named entity recognition (NER) system for the Tigrinya language. Our manually constructed corpus comprises over 340K words tagged for NER, with over 118K of the tokens also having parts-of-speech (POS) tags, annotated with 12 distinct classes of entities, represented using several types of tagging schemes. We conducted extensive experiments covering convolutional neural networks and transformer models; the highest performance achieved is 88.8% weighted F1-score. These results are especially noteworthy given the unique challenges posed by Tigrinya’s distinct grammatical structure and complex word morphologies. The system can be an essential building block for the advancement of NLP systems in Tigrinya and other related low-resourced languages and serve as a bridge for cross-referencing against higher-resourced languages.

Keywords: Tigrinya NER corpus, TiBERT, TiRoBERTa, BiLSTM-CRF

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Authors: Georg Brunnthaller, Sandra Stein, Wilfried Sihn

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Logistics service providers are facing increasing volatility concerning future transport demand. Short-term planning horizons and planning uncertainties lead to reduced capacity utilisation and increasing empty mileage. To overcome these challenges, a model is proposed to continuously pre-plan future transport capacity in order to redesign and adjust the intermodal fleet accordingly. It is expected that the model will enable logistics service providers to organise more economically and ecologically sustainable transport chains in a more flexible way. To further describe such planning aspects, this paper gives a structured literature review on transport planning problems. The focus is on strategic and tactical planning levels, comprising relevant fleet-sizing-, network-design- and choice-of-carriers-problems. Models and their developed solution techniques are presented and the literature review is concluded with an outlook to our future research objectives

Keywords: choice of transport mode, fleet-sizing, freight transport planning, multimodal, review, service network design

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Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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Authors: Rodrigo Lentini, Beatrice Ionascu, Friederike A. Eyssel, Scandar Copti, Mohamad Eid

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The haptic modality has brought a new dimension to human computer interaction by engaging the human sense of touch. However, designing appropriate haptic stimuli, and in particular tactile stimuli, for various applications is still challenging. To tackle this issue, we present an intuitive system that facilitates the authoring of tactile gestures for various applications. The system transforms a hand gesture into a tactile gesture that can be rendering using a home-made haptic jacket. A case study is presented to demonstrate the ability of the system to develop tactile gestures that are recognizable by human subjects. Four tactile gestures are identified and tested to intensify the following four emotional responses: high valence – high arousal, high valence – low arousal, low valence – high arousal, and low valence – low arousal. A usability study with 20 participants demonstrated high correlation between the selected tactile gestures and the intended emotional reaction. Results from this study can be used in a wide spectrum of applications ranging from gaming to interpersonal communication and multimodal simulations.

Keywords: tactile stimulation, tactile gesture, emotion reactions, arousal, valence

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Authors: Georg Brunnthaller, Sandra Stein, Wilfried Sihn

Abstract:

Transportation service providers are facing increasing volatility concerning future transport demand. Short-term planning horizons and planning uncertainties lead to reduced capacity utilization and increasing empty mileage. To overcome these challenges, a model is proposed to continuously pre-plan future transportation capacity in order to redesign and adjust the intermodal fleet accordingly. It is expected that the model will enable logistics service providers to organize more economically and ecologically sustainable transport chains in a more flexible way. To further describe these planning aspects, this paper gives an overview on transportation planning problems in a structured way. The focus is on strategic and tactical planning levels, comprising relevant fleet-sizing, service-network-design and choice-of-carriers-problems. Models and their developed solution techniques are presented, and the literature review is concluded with an outlook to our future research directions.

Keywords: freight transportation planning, multimodal, fleet-sizing, service network design, choice of transportation mode, review

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Authors: Ma Lei-Lei, Zhou You

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Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.

Keywords: convolutional neural network, transformer, feature pyramid networks, loss function

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Authors: Azimeh Rajaee, Lingyun Zhao, Shi Wang, Yaqiang Liu

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In recent years many studies have been focused on bismuth-based nanoparticles as radiosensitizer and contrast agent in radiation therapy and imaging due to the high atomic number (Z = 82), high photoelectric absorption, low cost, and low toxicity. This study aims to introduce a new multifunctional bismuth-based nanoparticle as a theranostic agent for radiotherapy, computed tomography (CT) and magnetic resonance imaging (MRI). We synthesized bismuth ferrite (BFO, BiFeO3) nanoparticles by sol-gel method and surface of the nanoparticles were modified by Polyethylene glycol (PEG). After proved biocompatibility of the nanoparticles, the ability of them as contract agent in Computed tomography (CT) and magnetic resonance imaging (MRI) was investigated. The relaxation time rate (R2) in MRI and Hounsfield unit (HU) in CT imaging were increased with the concentration of the nanoparticles. Moreover, the effect of nanoparticles on dose enhancement in low energy was investigated by clonogenic assay. According to clonogenic assay, sensitizer enhancement ratios (SERs) were obtained as 1.35 and 1.76 for nanoparticle concentrations of 0.05 mg/ml and 0.1 mg/ml, respectively. In conclusion, our experimental results demonstrate that the multifunctional nanoparticles have the ability to employ as multimodal imaging and therapy to enhance theranostic efficacy.

Keywords: molecular imaging, nanomedicine, radiotherapy, theranostics

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Authors: A. Hassannia, S. Ramezani

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The technology of superconductivity has developed in many power system devices such as transmission cable, transformer, current limiter, motor and generator. Superconducting wires can carry high density current without loss, which is the capability that is used to design the compact, lightweight and more efficient electrical machines. Superconducting motors have found applications in marine and air propulsion systems as well as superconducting generators are considered in low power hydraulic and wind generators. This paper presents a rim-driven superconducting synchronous generator for hydraulic power plant. The rim-driven concept improves the performance of hydro turbine. Furthermore, high magnetic field that is produced by superconducting windings allows replacing the rotor core. As a consequent, the volume and weight of the machine is decreased significantly. In this paper, a 1 MW coreless rim-driven superconducting synchronous generator is designed. Main performance characteristics of the proposed machine are then evaluated using finite elements method and compared to an ordinary similar size synchronous generator.

Keywords: coreless machine, electrical machine design, hydraulic generator, rim-driven machine, superconducting generator

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Authors: C. J. Rossouw, T. I. van Niekerk

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The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

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Authors: Heejin Song

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Employing a critical action research approach that rejects essentialist onto-epistemological orientations to research in English language teaching (ELT) and interrogates the hegemonic relations in the knowledge construction and reconstruction processes, this study illuminates how an action research-informed pedagogical practice can transform the English for academic purposes (EAP) teaching to be more culturally and linguistically inclusive and critically oriented for English language learners’ advancement in academic literacies skills. More specifically, this paper aims to showcase the action research-informed pedagogical innovations that emphasize multilingual learners’ multiliteracies engagement and experiential education-oriented learning to facilitate the development of learners’ academic literacies, intercultural communicative competence, and inclusive global citizenship in the context of Canadian university EAP classrooms. The pedagogical innovations through action research embarked in response to growing discussions surrounding pedagogical possibilities of plurilingualism in ELT and synchronous online teaching. The paper is based on two iterations of action research over the pandemic years between 2020 and 2022. The data includes student work samples, focus group interviews, anonymous surveys, teacher feedback and comments on student work and teaching reflections. The first iteration of the action research focused on the affordances of multimodal expressions in individual learners’ academic endeavors for their literacy skills development through individual online activities such as ‘my language autobiography,’ ‘multimodal expression corner’ and public speeches. While these activities help English language learners enhance their knowledge and skills of English-spoken discourses, these tasks did not necessarily require learners’ team-based collaborative endeavors to complete the assigned tasks. Identifying this area for improvement in the instructional design, the second action research cycle/iteration emphasized collaborative performativity through newly added performance/action-based innovative learning tasks, including ‘situational role-playing’, ‘my cooking show & interview’, and group debates in order to provide learners increased opportunities to communicate with peers who joined the class virtually from different parts of the world and enhance learners’ intercultural competence through various strategic and pragmatic communicative skills to collaboratively achieve their shared goals (i.e., successful completion of the given group tasks). The paper exemplifies instances wherein learners’ unique and diverse linguistic and cultural strengths were amplified, and critical literacies were further developed through learners’ performance-oriented multiliteracies engagement. The study suggests that the action research-informed teaching practice that advocates for collaborative multiliteracies engagement serves to facilitate learners’ activation of their existing linguistic and cultural knowledge and contributes to the development of learners’ academic literacy skills. Importantly, the study illuminates that such action research-informed pedagogical initiatives create an inclusive space for learners to build a strong sense of connectedness as global citizens with increased intercultural awareness in their community of language and cultural practices, and further allow learners to actively participate in the construction of ‘collaborative relations of power’ with their peers.

Keywords: action research, EAP, higher education, multiliteracies

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Authors: Nuhi Arslani, Stojan Potrc, Timotej Mikuljan

Abstract:

Background: In Department of Abdominal and General Surgery of University Medical Centre Maribor, we treated 578 patients for rectal cancer between 2004 and 2014. During and after treatment we especially concentrated on monitoring local and systemic complications. Methods: For analysis, we used data gathered from preoperative diagnostic tests, reports gathered during operation, reports from the pathohistologic review, and reports on complications after surgery and follow up. Results: In the case of 573 (out of 578) patients (99.1%) we performed resection. R0 was achieved in 551 patients (96,1%). R1 was achieved in 8 patients (1,4%). R2 was achieved in 14 patients (2,4%). Local complications were reported in 78 (13.5%) patients and systemic complications were reported in 68 (11.7%). We would like to point out the low number of local and systemic complications. Conclusions: With advances in surgical techniques, with a multimodal-multidisciplinary approach and with the use of total mesorectal excision we experienced a significant improvement in reducing the number of local and systemic complications in patients with rectal cancer. However, there still remains the question for truly optimal care for each patient with rectal cancer and his quality of life after surgical treatment.

Keywords: local complications, rectal cancer, resection, systemic complications

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Authors: L. Wilkening, G. Ackermann, T. T. Do

Abstract:

This article presents an approach for stand-alone and grid-connected mode of a German low-voltage grid with high share of photovoltaic. For this purpose, suitable dynamic system models have been developed. This allows the simulation of dynamic events in very small time ranges and the operation management over longer periods of time. Using these simulations, suitable control parameters could be identified, and their effects on the grid can be analyzed. In order to validate the simulation results, a LV-grid test bench has been implemented at the University of Technology Hamburg. The developed control strategies are to be validated using real inverters, generators and different realistic loads. It is shown that a battery hybrid system installed next to a voltage transformer makes it possible to operate the LV-grid in stand-alone mode without using additional information and communication technology and without intervention in the existing grid units. By simulating critical days of the year, suitable control parameters for stable stand-alone operations are determined and set point specifications for different control strategies are defined.

Keywords: battery, e-mobility, photovoltaic, smart grid

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Authors: Fernanda Miranda da Cruz

Abstract:

This paper aims to systematize, descriptively and analytically, the relations between language, body and material world explored in a specific empirical context: everyday co-presence interactions between children diagnosed with Autistic Spectrum Disease ASD and various interlocutors. We will work based on 20 hours of an audiovisual corpus in Brazilian Portuguese language. This analysis focuses on 1) the analysis of daily interactions that have the presence/participation of subjects with a diagnosis of ASD based on an embodied interaction perspective; 2) the study of the status and role of gestures, body and material world in the construction and constitution of human interaction and its relation with linguistic-cognitive processes and Autistic Spectrum Disorders; 3) to highlight questions related to the field of videoanalysis, such as: procedures for recording interactions in complex environments (involving many participants, use of objects and body movement); the construction of audiovisual corpora for linguistic-interaction research; the invitation to a visual analytical mentality of human social interactions involving not only the verbal aspects that constitute it, but also the physical space, the body and the material world.

Keywords: autism spectrum disease, multimodality, social interaction, non-verbal interactions

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Authors: Kyung-Hoon Jang, Jae-Hyo Park, Kwang-Yeop Jang, Dongjin Kim

Abstract:

The Tesla coil is an electrical resonant transformer circuit designed by inventor Nikola Tesla in 1891. It is used to produce high voltage, low current and high frequency alternating current electricity. Tesla experimented with a number of different configurations consisting of two or sometimes three coupled resonant electric circuits. This paper focuses on development and high voltage education to apply a Tesla coil to cuisine for high quality flavor and taste conditioning as well as high voltage education under 50 kV corona discharge. The result revealed that the velocity of roasted black belly pork by Tesla coil is faster than that of conventional methods such as hot grill and steel plate etc. depending on applied voltage level and applied voltage time. Besides, carbohydrate and crude protein increased, whereas natrium and saccharides significantly decreased after lightning surge by Tesla coil. This idea will be useful in high voltage education and high voltage application.

Keywords: corona discharge, Tesla coil, high voltage application, high voltage education

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Authors: B. Kędra, R. Małkowski

Abstract:

This paper presents information on Power System Component Simulator – a device designed for LINTE^2 laboratory owned by Gdansk University of Technology in Poland. In this paper, we first provide an introductory information on the Power System Component Simulator and its capabilities. Then, the concept of the unit is presented. Requirements for the unit are described as well as proposed and introduced functions are listed. Implementation details are given. Hardware structure is presented and described. Information about used communication interface, data maintenance and storage solution, as well as used Simulink real-time features are presented. List and description of all measurements is provided. Potential of laboratory setup modifications is evaluated. Lastly, the results of experiments performed using Power System Component Simulator are presented. This includes simulation of under frequency load shedding, frequency and voltage dependent characteristics of groups of load units, time characteristics of group of different load units in a chosen area.

Keywords: power converter, Simulink Real-Time, Matlab, load, tap controller

Procedia PDF Downloads 220

Authors: Chaudhary Muhammad Aqdus Ilyas, Matthias Rehm, Kamal Nasrollahi, Thomas B. Moeslund

Abstract:

This paper presents the investigation of data collection procedures, associated with robots when placed with traumatic brain injured (TBI) patients for rehabilitation purposes through facial expression and mood analysis. Rehabilitation after TBI is very crucial due to nature of injury and variation in recovery time. It is advantageous to analyze these emotional signals in a contactless manner, due to the non-supportive behavior of patients, limited muscle movements and increase in negative emotional expressions. This work aims at the development of framework where robots can recognize TBI emotions through facial expressions to perform rehabilitation tasks by physical, cognitive or interactive activities. The result of these studies shows that with customized data collection strategies, proposed framework identify facial and emotional expressions more accurately that can be utilized in enhancing recovery treatment and social interaction in robotic context.

Keywords: computer vision, convolution neural network- long short term memory network (CNN-LSTM), facial expression and mood recognition, multimodal (RGB-thermal) analysis, rehabilitation, robots, traumatic brain injured patients

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Authors: Kunle Oparinde, Ernestina Maleshoane Rapeane-Mathonsi, Gift Mheta

Abstract:

Using Critical Discourse Analysis (CDA) and Multimodal Discourse Analysis (MDA), the research seeks to deconstruct politically-motivated discourse as observed from Nigerian politics. This is intended to be achieved by analysing linguistic (mis)representation and manipulation in Nigerian political settings, drawing from instances of language use as observed from different political campaigns. Since language in itself is generally meaningless without context, it is therefore paramount to analyse the (mis)representation and manipulation in Nigerian political sceneries within their contextual basis. The study focuses on political language used by Nigerian politicians emanating from printed and social media forms such as posters, pamphlets, speeches, billboards, and internet sources purposely selected across Nigeria. The research further aims at investigating the discursive strategies used by politicians to gain more audience, and, as a result, shape opinions that result in votes. The study employs a qualitative approach. Two parties are intentionally selected because they have been essentially strong at the national level namely: All Progressive Congress (APC) and the People’s Democratic Party (PDP). The study finds out that politicians in Nigeria, as in many parts of the world, use language to manipulate the electorate. Comprehensive discussion of these instances of political manipulation remains the thrust of this paper.

Keywords: communication, discourse, manipulation, misrepresentation

Procedia PDF Downloads 215