Search results for: automatic recognition of speech

Authors: Rangika Perera, Shyamani Hettiarachchi, Fran Hagstrom

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Dyslexia is the most common reading reading-related difficulty among the school school-aged population and currently, 5-10% are showing the features of dyslexia in Sri Lanka. As there is an insufficient number of speech and language pathologists in the country and few speech and language pathologists working in government mainstream school settings, these children who are at risk of dyslexia are not receiving enough quality early intervention services to develop their reading skills. As teachers are the key professionals who are directly working with these children, using them as the primary facilitators to improve their reading skills will be the most effective approach. This study aimed to identify the efficacy of a two and half a day of intensive training provided to fifteen mainstream government school teachers of grade two classes. The goal of the training was to enhance their knowledge of dyslexia and provide full classroom skills training that could be used to support the development of the students’ reading competencies. A closed closed-ended multiple choice questionnaire was given to these teachers pre and -post-training to measure teachers’ knowledge of dyslexia, the areas in which these children needed additional support, and the best strategies to facilitate reading competencies. The data revealed that the teachers’ knowledge in all areas was significantly poorer prior to the training and that there was a clear improvement in all areas after the training. The gain in target areas of teaching skills selected to improve the reading skills of children was evaluated through peer feedback. Teachers were assigned to three groups and expected to model how they were going to introduce the skills in recommended areas using researcher developed, validated and reliability reliability-tested materials and the strategies which were introduced during the training within the given tasks. Peers and the primary investigator rated teachers’ performances and gave feedback on organizational skills, presentation skills of materials, clarity of instruction, and appropriateness of vocabulary. After modifying their skills according to the feedback the teachers received, they were expected to modify and represent the same tasks to the group the following day. Their skills were re-evaluated by the peers and primary investigator using the same rubrics to measure the improvement. The findings revealed a significant improvement in their teaching skills development. The data analysis of both knowledge and skills gains of the teachers was carried out using quantitative descriptive data analysis. The overall findings of the study yielded promising results that support intensive training as a method for improving teachers’ knowledge and teaching skill development for use with children in a whole class intervention setting who are at risk of dyslexia.

Keywords: Dyslexia, knowledge, teaching skills, training program

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Authors: Tommy Krieger, Klaus Gruendler

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We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its flexibility it is also a valuable tool for comparison studies.

Keywords: democracy, democracy index, machine learning, support vector machines

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Authors: Ghassan Kbar, Shady Aly, Ibrahim Alsharawy, Akshay Bhatia, Nur Alhasan, Ronaldo Enriquez

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The Smart Help for persons with disability (PWD) is a part of the project SMARTDISABLE which aims to develop relevant solution for PWD that target to provide an adequate workplace environment for them. It would support PWD needs smartly through smart help to allow them access to relevant information and communicate with other effectively and flexibly, and smart editor that assist them in their daily work. It will assist PWD in knowledge processing and creation as well as being able to be productive at the work place. The technical work of the project involves design of a technological scenario for the Ambient Intelligence (AmI) - based assistive technologies at the workplace consisting of an integrated universal smart solution that suits many different impairment conditions and will be designed to empower the Physically disabled persons (PDP) with the capability to access and effectively utilize the ICTs in order to execute knowledge rich working tasks with minimum efforts and with sufficient comfort level. The proposed technology solution for PWD will support voice recognition along with normal keyboard and mouse to control the smart help and smart editor with dynamic auto display interface that satisfies the requirements for different PWD group. In addition, a smart help will provide intelligent intervention based on the behavior of PWD to guide them and warn them about possible misbehavior. PWD can communicate with others using Voice over IP controlled by voice recognition. Moreover, Auto Emergency Help Response would be supported to assist PWD in case of emergency. This proposed technology solution intended to make PWD very effective at the work environment and flexible using voice to conduct their tasks at the work environment. The proposed solution aims to provide favorable outcomes that assist PWD at the work place, with the opportunity to participate in PWD assistive technology innovation market which is still small and rapidly growing as well as upgrading their quality of life to become similar to the normal people at the workplace. Finally, the proposed smart help solution is applicable in all workplace setting, including offices, manufacturing, hospital, etc.

Keywords: ambient intelligence, ICT, persons with disability PWD, smart application, SHW

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Authors: Elham Shirvani-Ghadikolaei

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In this paper, we examine the connection between the human mind and body within the framework of Merleau-Ponty's phenomenology. We study the role of this connection in designing more efficient learning environments, alongside the findings in physical recognition and educational neuroscience. Our research shows the interplay between the mind and the body in the external world and discusses its implications. Based on these observations, we make suggestions as to how the educational system can benefit from taking into account the interaction between the mind and the body in educational affairs.

Keywords: educational neurosciences, embodied cognition, pedagogical neurosciences, phenomenology

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Authors: Ghasem Yazadani, Hamidreza Ahmadi, Masoud Ahmadi, Sajad Rezazadeh

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In this paper with designing and proposing a compound of a heating and cooling system has been tried to show effect of this system on preventing esophagus cancer that can be caused by hot and cold drinks such as tea, coffee and ice water. This system has been simulated mechanically by fluent software and also has been validated by experimental way and a comprehensive result has been presented. Both of solution ways show that this system can reduce or increase temperature of drink to safe very dramatically and it can be a huge step toward consuming drinks safely and also it can be efficient about time issues. The system consists of a temperature sensor and an electronic controller that has a computer program to act automatically this task. Also this system has been presented after many different simulations and has been tried to find the best one in the point view of velocity of heating and cooling.

Keywords: fluent, heat transfer, controller, esophagus cancer

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Authors: Daniia Nigmatullina, Vlada Kugurakova, Maxim Talanov

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We present a methodology and our plans of anthropomorphic social agent visualization. That includes creation of three-dimensional model of the virtual companion's head and its facial expressions. Talking Head is a cross-disciplinary project of developing of the human-machine interface with cognitive functions. During the creation of a realistic humanoid robot or a character, there might be the ‘uncanny valley’ problem. We think about this phenomenon and its possible causes. We are going to overcome the ‘uncanny valley’ by increasing of realism. This article discusses issues that should be considered when creating highly realistic characters (particularly the head), their facial expressions and speech visualization.

Keywords: anthropomorphic social agent, facial animation, uncanny valley, visualization, 3D modeling

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Authors: Y. Kourd, D. Lefebvre, N. Guersi

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. In this paper we propose a method of fault diagnosis based on neuro-fuzzy technique and the choice of a threshold. The validation of this method on a test bench "Actuator Electro DAMADICS Benchmark". In the first phase of the method, we construct a model represents the normal state of the system to fault detection. With residuals analysis generated and the choice of thresholds for signatures table. These signatures provide us with groups of non-detectable faults. In the second phase, we build faulty models to see the flaws in the system that are not located in the first phase.

Keywords: residuals analysis, threshold, neuro-fuzzy system, residual evaluation

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Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: Gaokai Liu

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Automatic defect detection for nanomaterial images is widely required in industrial scenarios. Deep learning approaches are considered as the most effective solutions for the great majority of image-based tasks. In this paper, an edge guidance network for defect segmentation is proposed. First, the encoder path with multiple convolution and downsampling operations is applied to the acquisition of shared features. Then two decoder paths both are connected to the last convolution layer of the encoder and supervised by the edge and segmentation labels, respectively, to guide the whole training process. Meanwhile, the edge and encoder outputs from the same stage are concatenated to the segmentation corresponding part to further tune the segmentation result. Finally, the effectiveness of the proposed method is verified via the experiments on open nanofibrous datasets.

Keywords: deep learning, defect detection, image segmentation, nanomaterials

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Authors: Nora Geczy

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In today’s architectural practice, during the process of designing public, educational, healthcare and cultural space, human-centered architectural designs helping spatial orientation, safe space usage and the appropriate spatial sequence of actions are gaining increasing importance. Related to the methodology of designing public buildings, several scientific experiments in spatial recognition, spatial analysis and spatial psychology with regard to the components of space producing mental and physiological effects have been going on at the Department of Architectural Design and the Interdisciplinary Student Workshop (IDM) at the Széchenyi István University, Győr since 2013. Defining the creation of preventive, anticipated spatial design and the architectural tools of spatial comfort of public buildings and their practical usability are in the limelight of our research. In the experiments applying eye-tracking cameras, we studied the way public spaces are used, especially concentrating on the characteristics of spatial behaviour, orientation, recognition, the sequence of actions, and space usage. Along with the role of mental maps, human perception, and interaction problems in public spaces (at railway stations, galleries, and educational institutions), we analyzed the spatial situations influencing psychological and ergonomic factors. We also analyzed the eye movements of the experimental subjects in dynamic situations, in spatial procession, using stairs and corridors. We monitored both the consequences and the distorting effects of the ocular dominance of the right eye on spatial orientation; we analyzed the gender-based differences of women and men’s orientation, stress-inducing spaces, spaces affecting concentration and the spatial situation influencing territorial behaviour. Based on these observations, we collected the components of creating public interior spaces, which -according to our theory- contribute to the optimal usability of public spaces. We summed up our research in criteria for design, including 10 points. Our further goals are testing design principles needed for optimizing orientation and space usage, their discussion, refinement, and practical usage.

Keywords: architecture, eye-tracking, human-centered spatial design, public interior spaces, visual perception

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Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

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Authors: Lilia Edit Aparicio Pico, Paulo Cesar Coronado Sánchez, Roberto Ferro Escobar

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This paper presents the implementation of telemedicine services for physiotherapy, occupational therapy, and speech therapy rehabilitation, utilizing telebroadcasting of audiovisual content to enhance comprehensive patient recovery in rural areas of San Vicente del Caguán municipality, characterized by high levels of social conflict in Colombia. The region faces challenges such as dysfunctional problems, physical rehabilitation needs, and a high prevalence of hearing diseases, leading to neglect and substandard health services. Limited access to healthcare due to communication barriers and transportation difficulties exacerbates these issues. To address these challenges, a research initiative was undertaken to leverage information and communication technologies (ICTs) to improve healthcare quality and accessibility for this vulnerable population. The primary objective was to develop a tele-rehabilitation system to provide asynchronous online therapies and teleconsultation services for patient follow-up during the recovery process. The project comprises two components: Communication systems and human development. A technological component involving the establishment of a wireless network connecting rural centers and the development of a mobile application for video-based therapy delivery. Communications systems will be provided by a radio link that utilizes internet provided by the Colombian government, located in the municipality of San Vicente del Caguán to connect two rural centers (Pozos and Tres Esquinas) and a mobile application for managing videos for asynchronous broadcasting in sidewalks and patients' homes. This component constitutes an operational model integrating information and telecommunications technologies. The second component involves pedagogical and human development. The primary focus is on the patient, where performance indicators and the efficiency of therapy support were evaluated for the assessment and monitoring of telerehabilitation results in physical, occupational, and speech therapy. They wanted to implement a wireless network to ensure audiovisual content transmission for tele-rehabilitation, design audiovisual content for tele-rehabilitation based on services provided by the ESE Hospital San Rafael in physiotherapy, occupational therapy, and speech therapy, develop a software application for fixed and mobile devices enabling access to tele-rehabilitation audiovisual content for healthcare personnel and patients and finally to evaluate the technological solution's contribution to the ESE Hospital San Rafael community. The research comprised four phases: wireless network implementation, audiovisual content design, software application development, and evaluation of the technological solution's impact. Key findings include the successful implementation of virtual teletherapy, both synchronously and asynchronously, and the assessment of technological performance indicators, patient evolution, timeliness, acceptance, and service quality of tele-rehabilitation therapies. The study demonstrated improved service coverage, increased care supply, enhanced access to timely therapies for patients, and positive acceptance of teletherapy modalities. Additionally, the project generated new knowledge for potential replication in other regions and proposed strategies for short- and medium-term improvement of service quality and care indicators

Keywords: e-health, medical informatics, telemedicine, telerehabilitation, virtual therapy

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Authors: Bruno T. Gomes, José A. Menezes, Giordano Cabral

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With the popularity of smartphones, mobile apps emerge to meet the diverse needs, however the resources at the disposal are limited, either by the hardware, due to the low computing power, or the software, that does not have the same robustness of desktop environment. For example, in automatic audio classification (AC) tasks, musical information retrieval (MIR) subarea, is required a fast processing and a good success rate. However the mobile platform has limited computing power and the best AC tools are only available for desktop. To solve these problems the fast classifier suits, to mobile environments, the most widespread MIR technologies, seeking a balance in terms of speed and robustness. At the end we found that it is possible to enjoy the best of MIR for mobile environments. This paper presents the results obtained and the difficulties encountered.

Keywords: audio classification, audio extraction, environment mobile, musical information retrieval

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Authors: Svetlana L. Mishlanova, Evgeniia V. Ermakova, Mariia E. Timirkina

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The paper is concerned with the study of metaphor production in essays written by Russian and English native speakers in the framework of cognitive metaphor theory. It considers metaphorical competence as individual’s ability to recognize, understand and use metaphors in speech. The work analyzes the influence of visual metaphor on production and density of conventional and novel verbal metaphors. The main methods of research include experiment connected with image interpretation, metaphor identification procedure (MIPVU) and visual conventional metaphors identification procedure proposed by VisMet group. The research findings will be used in the project aimed at comparing metaphorical competence of native and non-native English speakers.

Keywords: metaphor, metaphorical competence, conventional, novel

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Authors: Bala Adamu Malami

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The necessity of low-cost electronic vehicle/car security designed in coordination with other security measures is always there in our society to reduce the risk of vehicle intrusion. Keeping this problem in mind, we are designing an automatic GPS system which is technology to build an integrated and fully customized vehicle to detect the movement of the vehicle and also serve as a security system at a reasonable cost. Users can locate the vehicle's position via GPS by using the Google Maps application to show vehicle coordinates on a smartphone. The tracking system uses a Global System for Mobile Communication (GSM) modem for communication between the mobile station and the microcontroller to send and receive commands. Further design can be improved to capture the vehicle movement range and alert the vehicle owner when the vehicle is out of range.

Keywords: electronic, GPS, GSM modem, communication, vehicle

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Authors: Ssu-Han Chen, Der-Baau Perng

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Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded, defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.

Keywords: molding surface, machine vision, statistical texture, discrete Fourier transformation

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Authors: Alan C. Lin, Tran Anh Son

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This study proposes an approach to determine the undercut regions and their releasing directions for slider design of complex parts represented by the file format of STL (STereoLithography). In order to delineate the border of undercut regions, orthogonal cutting planes are firstly employed to automatically find the inner loops of a part model. To discover the facets belonging to undercut regions, attributes are then assigned to the facets of the part model based on the topological relationship of adjacent facets of each inner loop. After that, the undercut regions are separated from other facets in the model. Through the recognized facets of the undercut regions, the concept of 'visibility map (V-map)' is further applied to determine feasible releasing directions for each of the undercut regions. The undercut regions having the same releasing direction are finally grouped to form a slider in the injection mold.

Keywords: solid model, STL data, injection mold design, visibility map

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Authors: Tomáš Bublík, Miroslav Virius

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This paper presents general results on the Java source code snippet detection problem. We propose the tool which uses graph and sub graph isomorphism detection. A number of solutions for all of these tasks have been proposed in the literature. However, although that all these solutions are really fast, they compare just the constant static trees. Our solution offers to enter an input sample dynamically with the Scripthon language while preserving an acceptable speed. We used several optimizations to achieve very low number of comparisons during the matching algorithm.

Keywords: AST, Java, tree matching, scripthon source code recognition

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Authors: Glenda Wrenn, Juliet Muzere, Meldra Hall, Allyson Belton, Kisha Holden, Chanita Hughes-Halbert, Martha Kent, Bekh Bradley

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Understanding the help seeking decision making process and experiences of health disparity populations with posttraumatic stress disorder (PTSD) is central to development of trauma-informed, culturally centered, and patient focused services. Yet, little is known about the decision making process among adult Black women who are non-treatment seekers as they are, by definition, not engaged in services. Methods: Audiotaped interviews were conducted with 30 African American adult women with clinically significant PTSD symptoms who were engaged in primary care, but not in treatment for PTSD despite symptom burden. A qualitative interview guide was used to elucidate key themes. Independent coding of themes mapped to theory and identification of emergent themes were conducted using qualitative methods. An existing quantitative dataset was analyzed to contextualize responses and provide a descriptive summary of the sample. Results: Emergent themes revealed that active mental avoidance, the intermittent nature of distress, ambivalence, and self-identified resilience as undermining to help seeking decisions. Participants were stuck within the help-seeking phase of ‘recognition’ of illness and retained a sense of “it is my decision” despite endorsing significant social and environmental negative influencers. Participants distinguished ‘help acceptance’ from ‘help seeking’ with greater willingness to accept help and importance placed on being of help to others. Conclusions: Elucidation of the decision-making process from the perspective of non-treatment seekers has implications for outreach and treatment within models of integrated and specialty systems care. The salience of responses to trauma symptoms and stagnation in the help seeking recognition phase are findings relevant to integrated care service design and community engagement.

Keywords: culture, help-seeking, integrated care, PTSD

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Authors: Sergei Aleinik, Mikhail Stolbov

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In this work, a method of time delay estimation for dual-channel acoustic signals (speech, music, etc.) recorded under reverberant conditions is investigated. Standard methods based on cross-correlation of the signals show poor results in cases involving strong reverberation, large distances between microphones and asynchronous recordings. Under similar conditions, a method based on cross-correlation of temporal envelopes of the signals delivers a delay estimation of acceptable quality. This method and its properties are described and investigated in detail, including its limits of applicability. The method’s optimal parameter estimation and a comparison with other known methods of time delay estimation are also provided.

Keywords: cross-correlation, delay estimation, signal envelope, signal processing

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Authors: Americo Pereira, Ricardo Carvalho, Pedro Carvalho, Luis Corte-Real

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Generating 3D content is a task mostly done by hand. It requires specific knowledge not only on how to use the tools for the task but also on the fundamentals of a 3D environment. In this work, we show that automatic generation of content can be achieved, from a scene script, by leveraging existing tools so that non-experts can easily engage in a 3D content generation without requiring vast amounts of time in exploring and learning how to use specific tools. This proposal carries several benefits, including flexible scene synthesis with different levels of detail. Our preliminary results show that the automatically generated content is comparable to the content generated by users with low experience in 3D modeling while vastly reducing the amount of time required for the generation and adds support to implement flexible scenarios for visual scene visualization.

Keywords: 3D virtualization, multimedia, scene script, synthesis

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Authors: Yuri Boiko, Iluju Kiringa, Tet Yeap

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Current drainage attack suggested previously is further studied in regular settings of closed-loop controlled Brushless DC (BLDC) motor with Kalman filter in the feedback loop. Modeling and simulation experiments are conducted in a Matlab environment, implementing the closed-loop control model of BLDC motor operation in position sensorless mode under Kalman filter drive. The current increase in the motor windings is caused by the controller (p-controller in our case) affected by false data injection of substitution of the angular velocity estimates with distorted values. Operation of multiplication to distortion coefficient, values of which are taken from the distortion function synchronized in its periodicity with the rotor’s position change. A saw function with a triangular tooth shape is studied herewith for the purpose of carrying out the bias injection with current drainage consequences. The specific focus here is on how the asymmetry of the tooth in the saw function affects the flow of current drainage. The purpose is two-fold: (i) to produce and collect the signature of an asymmetric saw in the attack for further pattern recognition process, and (ii) to determine conditions of improving stealthiness of such attack via regulating asymmetry in saw function used. It is found that modification of the symmetry in the saw tooth affects the periodicity of current drainage modulation. Specifically, the modulation frequency of the drained current for a fully asymmetric tooth shape coincides with the saw function modulation frequency itself. Increasing the symmetry parameter for the triangle tooth shape leads to an increase in the modulation frequency for the drained current. Moreover, such frequency reaches the switching frequency of the motor windings for fully symmetric triangular shapes, thus becoming undetectable and improving the stealthiness of the attack. Therefore, the collected signatures of the attack can serve for attack parameter identification via the pattern recognition route.

Keywords: bias injection attack, Kalman filter, BLDC motor, control system, closed loop, P-controller, PID-controller, current drainage, saw-function, asymmetry

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Authors: Minh-Thuan Nguyen, Phuong-Thai Nguyen, Van-Vinh Nguyen, Quang-Minh Nguyen

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Research on automatically generating descriptions for e-commerce products is gaining increasing attention in recent years. However, the generated descriptions of their systems are often less informative and attractive because of lacking training datasets or the limitation of these approaches, which often use templates or statistical methods. In this paper, we explore a method to generate production descriptions by using the GPT-2 model. In addition, we apply text paraphrasing and task-adaptive pretraining techniques to improve the qualify of descriptions generated from the GPT-2 model. Experiment results show that our models outperform the baseline model through automatic evaluation and human evaluation. Especially, our methods achieve a promising result not only on the seen test set but also in the unseen test set.

Keywords: GPT-2, product description, transformer, task-adaptive, language model, pretraining

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Authors: Retno Supriyanti, Ays Rahmadian Subhi, Yogi Ramadhani, Haris B. Widodo

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Alzheimer is one type of disease in the elderly that may occur in the world. The severity of the Alzheimer can be measured using a scale called Clinical Dementia Rating (CDR) based on a doctor's diagnosis of the patient's condition. Currently, diagnosis of Alzheimer often uses MRI machine, to know the condition of part of the brain called Hippocampus and Ventricle. MRI image itself consists of 3 slices, namely Coronal, Sagittal and Axial. In this paper, we discussed the measurement of the area of the ventricle especially in the Coronal slice based on the severity level referring to the CDR value. We use Active Contour method to segment the ventricle’s region, therefore that ventricle’s area can be calculated automatically. The results show that this method can be used for further development in the automatic diagnosis of Alzheimer.

Keywords: Alzheimer, CDR, coronal, ventricle, active contour

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Authors: Afaneen Anwer, Samara M. Kamil

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Load Forecast required prediction accuracy based on optimal operation and maintenance. A good accuracy is the basis of economic dispatch, unit commitment, and system reliability. A good load forecasting system fulfilled fast speed, automatic bad data detection, and ability to access the system automatically to get the needed data. In this paper, the formulation of the load forecasting is discussed and the solution is obtained by using artificial neural network method. A MATLAB environment has been used to solve the load forecasting schedule of Iraqi super grid network considering the daily load for three years. The obtained results showed a good accuracy in predicting the forecasted load.

Keywords: load forecasting, neural network, back-propagation algorithm, Iraqi power system

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Authors: Sultana Afrin Nipa

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Life on Earth cannot thrive or survive without water. Water is intimately tied with community, culture, spirituality, identity, socio-economic progress, security, self-determination, and livelihood. Thus, access to water is a United Nations recognized human right due to its significance in these realms. However, there is often conflict between those who consider water as the spiritual and cultural value and those who consider it an economic value thus being threatened by economic development, corporate exploitation, government regulation, and increased privatization, highlighting the complex relationship between water and culture. The Colorado River basin is home to over 29 federally recognized tribal nations. To these tribes, it holds cultural, economic, and spiritual significance and often extends to deep human-to-non-human connections frequently precluded by the Westphalian regulations and settler laws. Despite the recognition of access to rivers as a fundamental human right by the United Nations, tribal communities and their water rights have been historically disregarded through inter alia, colonization, and dispossession of their resources. Law of the River such as ‘Winter’s Doctrine’, ‘Bureau of Reclamation (BOR)’ and ‘Colorado River Compact’ have shaped the water governance among the shareholders. However, tribal communities have been systematically excluded from these key agreements. While the Winter’s Doctrine acknowledged that tribes have the right to withdraw water from the rivers that pass through their reservations for self-sufficiency, the establishment of the BOR led to the construction of dams without tribal consultation, denying the ‘Winters’ regulation and violating these rights. The Colorado River Compact, which granted only 20% of the water to the tribes, diminishes the significance of international legal frameworks that prioritize indigenous self-determination and free pursuit of socio-economic and cultural development. Denial of this basic water right is the denial of the ‘recognition’ of their sovereignty and self-determination that questions the effectiveness of the international law. This review assesses the international legal frameworks concerning indigenous rights and water justice and aims to pinpoint gaps hindering the effective recognition and protection of Indigenous water rights in Colorado River Basin. This study draws on a combination of historical and qualitative data sets. The historical data encompasses the case settlements provided by the Bureau of Reclamation (BOR) respectively the notable cases of Native American water rights settlements on lower Colorado basin related to Arizona from 1979-2008. This material serves to substantiate the context of promises made to the Indigenous people and establishes connections between existing entities. The qualitative data consists of the observation of recorded meetings of the Central Arizona Project (CAP) to evaluate how the previously made promises are reflected now. The study finds a significant inconsistency in participation in the decision-making process and the lack of representation of Native American tribes in water resource management discussions. It highlights the ongoing challenges faced by the indigenous people to achieve their self-determination goal despite the legal arrangements.

Keywords: colorado river, indigenous rights, law of the river, water governance, water justice

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Authors: Aprilia, Wei Liang Keith Nguyen, Shu Beng Tor, Gerald Gim Lee Seet, Chee Kai Chua

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Automated remanufacturing process is of great interest in today’s marine and offshore industry. Most of the current remanufacturing processes are carried out manually and hence they are error prone, labour-intensive and costly. In this paper, a conceptual framework for automated remanufacturing is presented. This framework involves the integration of 3D non-contact digitization, adaptive surface reconstruction, additive manufacturing and machining operation. Each operation is operated and interconnected automatically as one system. The feasibility of adaptive surface reconstruction on marine and offshore engineering components is also discussed. Several engineering components were evaluated and the results showed that this proposed system is feasible. Conclusions are drawn and further research work is discussed.

Keywords: adaptive surface reconstruction, automated remanufacturing, automatic repair, reverse engineering

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Authors: Labane Chrif

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A nonlinear approach to the automatic pitch attitude control problem for aircraft transportation is presented. A nonlinear model describing the longitudinal equations of motion in strict feedback form is derived. Backstepping is utilized for the construction of a globally stabilizing controller with a number of free design parameters. The controller is evaluated using the aircraft transportation. The adaptation scheme proposed allowed us to design an explicit controller with a minimal knowledge of the aircraft aerodynamics. Finally, the simulation results will show that backstepping controller have better dynamic performance, simpler design, higher precision, easier implement, etc. At the same time, the control effect will be significantly improved. In addition, backstepping control is superior in short transition, good stability, anti-disturbance and good control.

Keywords: nonlinear control, backstepping, aircraft control, Lyapunov function, longitudinal model

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Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

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Automatic text classification applies mostly natural language processing (NLP) and other AI-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: machine learning, text classification, NLP techniques, semantic representation

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Authors: Robert Krause

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Primary progressive aphasia (PPA) is a neurodegenerative disease similar to frontotemporal and semantic dementia, while having a different clinical image and anatomic pathology topography. Nonetheless, they are often included under an umbrella term: frontotemporal lobar degeneration (FTLD). In the study, examples of diagnosing PPA are presented through the multidisciplinary lens of specialists from different fields (neurologists, psychiatrists, clinical speech therapists, clinical neuropsychologists and others) using a variety of diagnostic tools such as MR, PET/CT, genetic screening and neuropsychological and logopedic methods. Thanks to that, specialists can get a better and clearer understanding of PPA diagnosis. The study summarizes the concrete procedures and results of different specialists while diagnosing PPA in a patient of younger middle age and illustrates the importance of multidisciplinary approach to differential diagnosis of PPA.

Keywords: primary progressive aphasia, etiology, diagnosis, younger middle age

Procedia PDF Downloads 170