Search results for: automated written corrective feedback

Authors: Mami Miyasaka, Kaichi Yanaoka

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Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity; symptoms often manifest during childhood. In children with ADHD, the development of inhibitory processes is impaired. Inhibitory control allows people to avoid processing unnecessary stimuli and to behave appropriately in various situations; thus, people with ADHD require interventions to improve inhibitory control. Positive or negative reinforcements (i.e., reward or punishment) help improve the performance of children with such difficulties. However, in order to optimize impact, reward and punishment must be presented immediately following the relevant behavior. In regular elementary school classrooms, such supports are uncommon; hence, an alternative practical intervention method is required. One potential intervention involves setting goals to keep children motivated to perform tasks. This study examined whether goal setting improved inhibitory performances, especially for children with severe ADHD-related symptoms. We also focused on giving feedback on children's task performances. We expected that giving children feedback would help them set reasonable goals and monitor their performance. Feedback can be especially effective for children with severe ADHD-related symptoms because they have difficulty monitoring their own performance, perceiving their errors, and correcting their behavior. Our prediction was that goal setting by itself would be effective for children with mild ADHD-related symptoms, and goal setting based on feedback would be effective for children with severe ADHD-related symptoms. Japanese elementary school children and their parents were the sample for this study. Children performed two kinds of go/no-go tasks, and parents completed a checklist about their children's ADHD symptoms, the ADHD Rating Scale-IV, and the Conners 3rd edition. The go/no-go task is a cognitive task to measure inhibitory performance. Children were asked to press a key on the keyboard when a particular symbol appeared on the screen (go stimulus) and to refrain from doing so when another symbol was displayed (no-go stimulus). Errors obtained in response to a no-go stimulus indicated inhibitory impairment. To examine the effect of goal-setting on inhibitory control, 37 children (Mage = 9.49 ± 0.51) were required to set a performance goal, and 34 children (Mage = 9.44 ± 0.50) were not. Further, to manipulate the presence of feedback, in one go/no-go task, no information about children’s scores was provided; however, scores were revealed for the other type of go/no-go tasks. The results revealed a significant interaction between goal setting and feedback. However, three-way interaction between ADHD-related inattention, feedback, and goal setting was not significant. These results indicated that goal setting was effective for improving the performance of the go/no-go task only with feedback, regardless of ADHD severity. Furthermore, we found an interaction between ADHD-related inattention and feedback, indicating that informing inattentive children of their scores made them unexpectedly more impulsive. Taken together, giving feedback was, unexpectedly, too demanding for children with severe ADHD-related symptoms, but the combination of goal setting with feedback was effective for improving their inhibitory control. We discuss effective interventions for children with ADHD from the perspective of goal setting and feedback. This work was supported by the 14th Hakuho Research Grant for Child Education of the Hakuho Foundation.

Keywords: attention deficit disorder with hyperactivity, feedback, goal-setting, go/no-go task, inhibitory control

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Authors: Nwauzoma Ohale Rowland, Bright Ugochukwu Umunna

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The world has been referred to as a global village for decades, adapting various technological and digital innovations to progress along the lines of development. Different continents have fully automated processes and procedures in the various sectors of their economies. This paper attempts to ascertain why the West African sub-continent while displaying a slow progression, has also joined the race toward having a fully automated process, albeit only in certain areas of its economy. Different reasons for this have been posited and will be discussed in this work. These reasons include high illiteracy rates and poor acceptance of new technologies. Studies were carried out that involved interactions with different business sectors and also a secondary-level investigation of experiments to ascertain the impact of automation in supply chain management on the West African market. Our reports show remarkable growth in businesses and sectors that have automated their processes. While this is the case, other results have also confirmed as due to the high illiteracy rates; the labour force has also been affected.

Keywords: Africa, automation, business, innovation, supply chain management, technology

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Authors: Sungho Kim, Jaechoul Shin, Yujin Baek, Nakseok Kim, Kyungnam Kim, Shinhaeng Jo

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The climate change and increase in heavy traffic have been accelerating damages that cause the problems such as pothole on asphalt pavement. Pothole causes traffic accidents, vehicle damages, road casualties and traffic congestion. A quick and efficient maintenance method is needed because pothole is caused by stripping and accelerates pavement distress. In this study, we propose a rapid and systematic pothole management by developing a pothole automated repairing equipment including a volume measurement system of pothole. Three kinds of cold mix asphalt mixture were investigated to select repair materials. The materials were evaluated for satisfaction with quality standard and applicability to automated equipment. The volume measurement system of potholes was composed of multi-sensor that are combined with laser sensor and ultrasonic sensor and installed in front and side of the automated repair equipment. An algorithm was proposed to calculate the amount of repair material according to the measured pothole volume, and the system for releasing the correct amount of material was developed. Field test results showed that the loss of repair material amount could be reduced from approximately 20% to 6% per one point of pothole. Pothole rapid automated repair equipment will contribute to improvement on quality and efficient and economical maintenance by not only reducing materials and resources but also calculating appropriate materials. Through field application, it is possible to improve the accuracy of pothole volume measurement, to correct the calculation of material amount, and to manage the pothole data of roads, thereby enabling more efficient pavement maintenance management. Acknowledgment: The author would like to thank the MOLIT(Ministry of Land, Infrastructure, and Transport). This work was carried out through the project funded by the MOLIT. The project name is 'development of 20mm grade for road surface detecting roadway condition and rapid detection automation system for removal of pothole'.

Keywords: automated equipment, management, multi-beam sensor, pothole

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Authors: D. Gvozdikov

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The purpose of this study is an attempt to describe an online action as a system that combines disjointed events and behavioral chains into a whole. The research focuses on patterns of naturally-formed chains of actions united by an orientation towards the online environment. A key characteristic of the system of online action is that it acts as an attractor for separate actions and chains of behavioral repertoire accumulating time and efforts made by users. The article demonstrates how the chains of online-offline actions are combined into a single pattern due to a simple identifiable mechanism, a positive feedback system. Using methods of digital ethnography and analyzing the content of the Instagram application and media blogs, the research reveals how through the positive feedback mechanism the entire system of online action acquires stability and can expand involving new spheres of human activity.

Keywords: digital anthropology, internet studies, systems theory, social media

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Authors: Florian Tille, Heide Weishaar, Bernhard Gibis, Susanne Schnitzer

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Introduction: The quality of patient-doctor communication and of written health information is central to organizational health literacy (HL). Whether patients understand their doctors’ explanations and textual material on health, however, is understudied. This study identifies the overall levels of patient understanding of health information and its associations with patients’ social characteristics in outpatient health care in Germany. Materials & Methods: This analysis draws on data collected via a 2017 national health survey with a sample of 6,105 adults. Quality of communication was measured for consultations with general practitioners (GPs) and specialists (SPs) via the Ask Me 3 program questions, and through a question on written health material. Correlations with social characteristics were explored employing bivariate and multivariate logistic regression analyses. Results: Over 90% of all respondents reported that they had understood their doctors’ explanations during the last consultation. Failed understanding was strongly correlated with patients’ very poor health (Odds Ratio [OR]: 5.19; 95% confidence interval [CI]: 2.23–12.10; ref. excellent/very good health), current health problem (OR: 6.54, CI: 1.70–25.12; ref. preventive examination) and age 65 years and above (OR: 2.97, CI: 1.10–8.00; ref. 18 to 34 years). Fewer patients answered they understood written material well (86.7% for las visit at GP, 89.7% at SP). Understanding written material poorly was highly associated with basic education (OR: 4.20, CI: 2.76–6.39; ref. higher education) and 65 years old and above (OR: 2.66, CI: 1.43–4.96). Discussion: Overall ratings of oral patient-doctor communication and written communication of health information are high. Yet, a considerable share of patients reports not-understanding their doctors and poor understanding of the written health-related material. Interventions that can contribute to improving organizational HL in outpatient care in Germany include HL training for doctors, reducing system barriers to easily-accessible health information for patients and combining oral and written health communication means. Conclusion: This work adds to the study of organizational HL in Germany. To increase patient understanding of health-relevant information and thereby possibly reduce health disparities, meeting the communication needs especially of persons in different age groups, with basic education and in very poor health is suggested.

Keywords: health survey, organizational health literacy, patient-doctor communication, social characteristics, outpatient care, Ask Me 3

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Authors: Lidia N. Hernández-Piña, Carlos R. Jaimez-González

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Interoperability in distributed systems is an important feature that refers to the communication of two applications written in different programming languages. This paper presents a serializer and a de-serializer of PHP objects to and from XML, which is an independent library written in the PHP programming language. The XML generated by this serializer is independent of the programming language, and can be used by other existing Web Objects in XML (WOX) serializers and de-serializers, which allow interoperability with other object-oriented programming languages.

Keywords: interoperability, PHP object serialization, PHP to XML, web objects in XML, WOX

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Authors: Thelma Palaoag, Melanie Basa, Jezreel Mark Panilo

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Checking short-answer questions and essays, whether it may be paper or electronic in form, is a tiring and tedious task for teachers. Evaluating a student’s output require wide array of domains. Scoring the work is often a critical task. Several attempts in the past few years to create an automated writing assessment software but only have received negative results from teachers and students alike due to unreliability in scoring, does not provide feedback and others. The study aims to create an application that will be able to check short-answer questions which incorporate information extraction. Information extraction is a subfield of Natural Language Processing (NLP) where a chunk of text (technically known as unstructured text) is being broken down to gather necessary bits of data and/or keywords (structured text) to be further analyzed or rather be utilized by query tools. The proposed system shall be able to extract keywords or phrases from the individual’s answers to match it into a corpora of words (as defined by the instructor), which shall be the basis of evaluation of the individual’s answer. The proposed system shall also enable the teacher to provide feedback and re-evaluate the output of the student for some writing elements in which the computer cannot fully evaluate such as creativity and logic. Teachers can formulate, design, and check short answer questions efficiently by defining keywords or phrases as parameters by assigning weights for checking answers. With the proposed system, teacher’s time in checking and evaluating students output shall be lessened, thus, making the teacher more productive and easier.

Keywords: information extraction, short-answer question, natural language processing, application

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Authors: Kazuma Okada, Tomoaki Hashimoto, Hirokazu Tahara

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Recently, the effectiveness of random dither quantization method for linear feedback control systems has been shown in several papers. However, the random dither quantization method has not yet been applied to nonlinear feedback control systems. The objective of this paper is to verify the effectiveness of random dither quantization method for nonlinear feedback control systems. For this purpose, we consider the attitude stabilization problem of satellites using discrete-level actuators. Namely, this paper provides a control method based on the random dither quantization method for stabilizing the attitude of satellites using discrete-level actuators.

Keywords: quantized control, nonlinear systems, random dither quantization

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Authors: Amit Bhanushali

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In the ever-changing landscape of software development, automated software testing has emerged as a critical component of the Software Development Life Cycle (SDLC). This research undertakes a comparative study of three major automated testing tools -UFT, Selenium, and RPA- evaluating them on usability, maintenance, and effectiveness. Leveraging existing JAVA-based applications as test cases, the study aims to guide testers in selecting the optimal tool for specific applications. By exploring key features such as source and licensing, testing expenses, object repositories, usability, and language support, the research provides practical insights into UFT, Selenium, and RPA. Acknowledging the pivotal role of these tools in streamlining testing processes amid time constraints and resource limitations, the study assists professionals in making informed choices aligned with their organizational needs.

Keywords: software testing tools, software development lifecycle (SDLC), test automation frameworks, automated software, JAVA-based, UFT, selenium and RPA (robotic process automation), source and licensing, object repository

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Authors: Radhey Sham Rajoria

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Pressure to increase the competitiveness in the manufacturing sector and for the survival in the market has led to the development of machining centres, which enhance productivity, improve quality, shorten the lead time, and reduce the manufacturing cost. With the innovation of machining centres in the manufacturing sector the production lines have been replaced by these machining centers, having the ability to machine various processes and multiple tooling with automatic tool changer (ATC) for the same part. Also the process plans can be easily generated for complex components. Some means are required to utilize the machining center at its best. The present work is concentrated on the automated part program generation, and in turn automated process plan generation for the turned components on Denford “MIRAC” 8 stations ATC lathe machining centre. A package in C++ on DOS platform is developed which generates the complete CNC part program, process plan and process sequence for the turned components. The input to this system is in the form of a blueprint in graphical format with machining parameters and variables, and the output is the CNC part program which is stored in a .mir file, ready for execution on the machining centre.

Keywords: CNC, MIRAC, ATC, process planning

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Authors: Monika Benedek

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This paper intends to present a pilot study of blended ear-training course at a Finnish university. The course ran for ten weeks and included both traditional (offline) group lessons for 90 minutes each week and an online learning platform. Twelve students majored in musicology and music education participated in the course. The aims of pilot research were to develop a new blended ear-training course at university level, to determine the ideal amount of workload in each part of the blended instruction (offline and online) and to develop the course material. The course material was selected from the Classical period in order to develop students’ aural skills together with their stylistic knowledge. Students were asked to provide written feedback of the course content and learning approaches of face-to-face group lessons and online learning platform each week during the course. Therefore, the teaching material is continuously planned for each week. This qualitative data collection and weekly analysis of data are on progress. However, based on the teacher-researcher’s experiences and the students’ feedback already collected, it could be seen that the blended instruction would be an ideal teaching strategy for ear-trainging at the music programmes of universities to develop students’ aural skills and stylistic knowledge. It is also presumed that such blended instruction with less workload would already improve university students’ aural skills and related musicianship skills. The preliminary findings of research also indicated that students generally found those ear-training tasks the most useful to learn online that combined listening, singing, singing and playing an instrument. This paper intends to summarise the final results of the pilot study.

Keywords: blended-learning, ear-training, higher music education, online-learning, pilot study

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Authors: Blerim Olluri

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A forensic science laboratory in Kosovo has never been organized at the level of most modern forensic science laboratories. This was made possible after the war of 1999 with the help and support from the United States. The United States Government/ICITAP provided 9.5 million dollars to support this project, this support have greatly benefitted law enforcement in Kosovo. With the establishment of Operative Procedures of Work and the law for Kosovo Agency of Forensic, the accreditation with ISO/IEC 17025 of the KAF labs it becomes mandatory. Since 2012 Laboratory’s DNA/Serology and Narcotics has begun reviewing and harmonizing their procedures according to ISO/IEC 17025. The focus of this work was to create quality manuals, procedures, work instructions, quality documentation and quality records. Furthermore, during this time is done the validation of work methods from scientific qualified personnel of KAF, without any help from other foreign agencies or accreditation body.In October 2014 we had the first evaluation based on ISO 17025 standards. According to the initial report of this assessment we have non conformity in test and Calibration methods method’s, and accommodation and environmental conditions. We identified several issues that are of extreme importance to KAF. One the most important issue is to create a professional group with experts of KAF, which will work in all the obligations, requested from ISO/IEC 17025. As conclusions that we earn in this path of accreditation, are that laboratory’s need to take corrective action, and all nonconformance’s must be addressed and corrective action taken before accreditation can be granted.

Keywords: accreditation, assessment, narcotics, DNA

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Authors: Kemka Ihemelandu, Chukwuemeka Ihemelandu

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Melanoma remains a public health crisis, with incidence rates increasing rapidly in the past decades. Improving diagnostic accuracy to decrease misdiagnosis using Artificial intelligence (AI) continues to be documented. Unfortunately, unintended racially biased outcomes, a product of lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone, have increasingly been recognized as a problem.Resulting in noted limitations of the accuracy of the Convolutional neural network (CNN)models. CNN models are prone to biased output due to biases in the dataset used to train them. Our aim in this study was the optimization of convolutional neural network algorithms to mitigate bias in the automated diagnosis of melanoma. We hypothesized that our proposed training algorithms based on a data augmentation method to optimize the diagnostic accuracy of a CNN classifier by generating new training samples from the original ones will reduce bias in the automated diagnosis of melanoma. We applied geometric transformation, including; rotations, translations, scale change, flipping, and shearing. Resulting in a CNN model that provided a modifiedinput data making for a model that could learn subtle racial features. Optimal selection of the momentum and batch hyperparameter increased our model accuracy. We show that our augmented model reduces bias while maintaining accuracy in the automated diagnosis of melanoma.

Keywords: bias, augmentation, melanoma, convolutional neural network

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Authors: Ying Su, Morgan C. Wang

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Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

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Authors: Kuei-Chun Liu, Yu-Yu Lai, Ching-Hong Wu

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A good automated testing tool could reduce as much as possible the manual work done by testers. Traditional record-replay testing tool provides an automated testing solution by recording mouse coordinates as test scripts, but it will be easily broken if any change of resolutions. Therefore, more and more testers design multiple test scripts to automate the testing process for different devices. In order to improve the traditional record-replay approach and reduce the effort that the testers spending on writing test scripts, we propose an approach for generating the Android application test scripts based on accessibility service without connecting to a computer. This approach simulates user input actions and replays them correctly even at the different conditions such as the internet connection is unstable when the device under test, the different resolutions on Android devices. In this paper, we describe how to generate test scripts automatically and make a comparison with existing tools for Android such as Robotium, Appium, UIAutomator, and MonkeyTalk.

Keywords: accessibility service, Appium, automated testing, MonkeyTalk, Robotium, testing, UIAutomator

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Authors: Diane M. Bender

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In architecture and design education, students learn and understand their discipline through lecture courses and within studios. A studio is where the instructor works closely with students to help them understand design by doing design work. The final jury is the culmination of the studio learning experience. It’s value and significance are rarely questioned. Students present their work before their peers, instructors, and invited reviewers, known as jurors. These jurors are recognized experts who add a breadth of feedback to students mostly in the form of a verbal critique of the work. Since the design review or jury has been a common element of studio education for centuries, jurors themselves have been instructed in this format. Therefore, they understand its value from both a student and a juror perspective. To better understand how these reviewers see the value of a studio review, a survey was distributed to reviewers at a multi-disciplinary design school within the United States. Five design disciplines were involved in this case study: architecture, graphic design, industrial design, interior design, and landscape architecture. Respondents (n=108) provided written comments about their perceived value of the studio review system. The average respondent was male (64%), between 40-49 years of age, and has attained a master’s degree. Qualitative analysis with thematic coding revealed several themes. Reviewers view the final jury as important because it provides a variety of perspectives from unbiased external practitioners and prepares students for similar presentation challenges they will experience in professional practice. They also see it as a way to validate the assessment and evaluation of students by faculty. In addition, they see a personal benefit for themselves and their firm – the ability to network with fellow jurors, professors, and students (i.e., future colleagues). Respondents also provided additional feedback about the jury system and studio education in general. Typical responses included a desire for earlier engagement with students; a better explanation from the instructor about the project parameters, rubrics/grading, and guidelines for juror involvement; a way to balance giving encouraging feedback versus overly critical comments; and providing training for jurors prior to reviews. While this study focused on the studio review, the findings are equally applicable to other disciplines. Suggestions will be provided on how to improve the preparation of guests in the learning process and how their interaction can positively influence student engagement.

Keywords: assessment, design, jury, studio

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Authors: Manana Rusieshvili, Rusudan Dolidze

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This paper aims at 1) investigating the ways in which a traditional, monomodal written verbal metaphor can be transposed as a monomodal non-verbal (visual) or multimodal (aural and -visual) filmic metaphor ; 2) exploring similarities and differences in the process of encoding and decoding of monomodal and multimodal metaphors. The empiric data, on which the research is based, embrace three sources: the novel by Harry Gray ‘The Hoods’, the script of the film ‘Once Upon a Time in America’ (English version by David Mills) and the resultant film by Sergio Leone. In order to achieve the above mentioned goals, the research focuses on the following issues: 1) identification of verbal and non-verbal monomodal and multimodal metaphors in the above-mentioned sources and 2) investigation of the ways and modes the specific written monomodal metaphors appearing in the novel and the script are enacted in the film and become visual, aural or visual-aural filmic metaphors ; 3) study of the factors which play an important role in contributing to the encoding and decoding of the filmic metaphor. The collection and analysis of the data were carried out in two stages: firstly, the relevant data, i.e. the monomodal metaphors from the novel, the script and the film were identified and collected. In the second, final stage the metaphors taken from all of the three sources were analysed, compared and two types of phenomena were selected for discussion: (1) the monomodal written metaphors found in the novel and/or in the script which become monomodal visual/aural metaphors in the film; (2) the monomodal written metaphors found in the novel and/or in the script which become multimodal, filmic (visual-aural) metaphors in the film.

Keywords: encoding, decoding, filmic metaphor, multimodality

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Authors: Nikhil Verma, Akshay Kant Mishra, Rishabh Rastogi, Bikarama Prasad Yadav

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Emerging fire incidents are the protuberant contributor out turning into life loss, property damage and importantly firefighters. It insinuates that a firefighting and rescue operation of the existing equipment or apparatus and their proficiency is limited, particularly in annihilating firefighting environments. The proposed methodology will help in developing a technology which can be useful in minimizing the risks and losses due to fire. In this paper, design and development of combat mini vehicle comprising of multi-purpose nozzle system is proposed which can target diverse fires simultaneously at distinct time and location. Basically, the system is semi-automated type protection system which can be manoeuvred by controller. Designing of robust vehicle based on semi-automated protection type system is consummated using SolidWorks platform. Concept of developing a robust vehicle will help to fight fires in multiple directions reducing the time required to douse multiple fires.

Keywords: fire douse vehicle, multiple fires, multi-purpose nozzle, semi-automated system

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Authors: Maria-Agori Gravvani

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The part of communication holds a significant place in human life. From the early beginning of human history, humans tried to communicate orally with other people in order to survive and to communicate their needs. The level of education that the majority of the Athenean citizens had the opportunity to acquire in the Classic period was very low. Only the wealthy ones had the opportunity of the upper form of education that led them to a career in politics, while the other ones struggled for their daily survival. In the corpus of Euripides' and Sophocles' tragedies, the type of communication is written, too. Not only in the Iphigenia's tragedies of Euripides but also in the Sophocles' Trachiniae, the use of δέλτος bonds significant messages with people. Those written means of private communication play an important role in the plot of the tragedy and have hidden private messages from their owners. The main aim of this paper is to analyze the power of the deltos' written text in the tragedies of Euripides Ifigenia Taurica and Ifigenia Aulidensis and Sophocles' Trachiniae.

Keywords: deltos, ancient greek tragedy, sophocles, euripides

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Authors: Keaghan Brown

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The prioritization of drug resistance mutations impacting protein folding or protein-drug and protein-DNA interactions within macromolecular systems is critical to the success of treatment regimens. With a continual increase in computational tools to assess these impacts, the need for scalability and reproducibility became an essential component of computational analysis and experimental research. Here it introduce a bioinformatics pipeline that combines several structural analysis tools in a simplified workflow, by optimizing the present computational hardware and software to automatically ease the flow of data transformations. Utilizing preestablished software tools, it was possible to develop a pipeline with a set of pre-defined functions that will automate mutation introduction into the HIV-1 Integrase protein structure, calculate the gain and loss of polar interactions and calculate the change in energy of protein fold. Additionally, an automated molecular dynamics analysis was implemented which reduces the constant need for user input and output management. The resulting pipeline, Automated Mutation Introduction and Analysis (AMIA) is an open source set of scripts designed to introduce and analyse the effects of mutations on the static protein structure as well as the results of the multi-conformational states from molecular dynamic simulations. The workflow allows the user to visualize all outputs in a user friendly manner thereby successfully enabling the prioritization of variant systems for experimental validation.

Keywords: automated workflow, variant prioritization, drug resistance, HIV Integrase

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Authors: Cristian Păuna

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After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

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Authors: Paul Lam, Kevin Wong, Chi Him Chan

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Constant practicing and accurate, immediate feedback are the keys to improving students’ speaking skills. However, traditional oral examination often fails to provide such opportunities to students. The traditional, face-to-face oral assessment is often time consuming – attending the oral needs of one student often leads to the negligence of others. Hence, teachers can only provide limited opportunities and feedback to students. Moreover, students’ incentive to practice is also reduced by their anxiety and shyness in speaking the new language. A mobile app was developed to use artificial intelligence (AI) to provide immediate feedback to students’ speaking performance as an attempt to solve the above-mentioned problems. Firstly, it was thought that online exercises would greatly increase the learning opportunities of students as they can now practice more without the needs of teachers’ presence. Secondly, the automatic feedback provided by the AI would enhance students’ motivation to practice as there is an instant evaluation of their performance. Lastly, students should feel less anxious and shy compared to directly practicing oral in front of teachers. Technically, the program made use of speech-to-text functions to generate feedback to students. To be specific, the software analyzes students’ oral input through certain speech-to-text AI engine and then cleans up the results further to the point that can be compared with the targeted text. The mobile app has invited English teachers for the pilot use and asked for their feedback. Preliminary trials indicated that the approach has limitations. Many of the users’ pronunciation were automatically corrected by the speech recognition function as wise guessing is already integrated into many of such systems. Nevertheless, teachers have confidence that the app can be further improved for accuracy. It has the potential to significantly improve oral drilling by giving students more chances to practice. Moreover, they believe that the success of this mobile app confirms the potential to extend the AI-assisted assessment to other language skills, such as writing, reading, and listening.

Keywords: artificial Intelligence, mobile learning, oral assessment, oral practice, speech-to-text function

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Authors: Omid Kalatpour, Mohammadreza Ajdari

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This article studied the possible causes of human error-induced incidents in the petrochemical industry maintenance activities by using Human Factors Analysis and Classification System (HFACS). The purpose of the study was anticipating and identifying these causes and proposing corrective and preventive actions. Maintenance department in a petrochemical company was selected for research. A checklist of human error-induced incidents was developed based on four HFACS main levels and nineteen sub-groups. Hierarchical task analysis (HTA) technique was used to identify maintenance activities and tasks. The main causes of possible incidents were identified by checklist and recorded. Corrective and preventive actions were defined depending on priority. Analyzing the worksheets of 444 activities in four levels of HFACS showed 37.6% of the causes were at the level of unsafe actions, 27.5% at the level of unsafe supervision, 20.9% at the level of preconditions for unsafe acts and 14% of the causes were at the level of organizational effects. The HFACS sub-groups showed errors (24.36%) inadequate supervision (14.89%) and violations (13.26%) with the most frequency. According to findings of this study, increasing the training effectiveness of operators and supervision improvement respectively are the most important measures in decreasing the human error-induced incidents in petrochemical industry maintenance.

Keywords: human error, petrochemical industry, maintenance, HFACS

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Authors: Flavio O. Torres, Maria J. Castilla, Rodrigo A. Augsburger, Pedro I. Cachana, Katherine S. Reyes

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In this paper, we present a scene-based nonuniformity correction method using a modified recursive least square algorithm with a feedback system on the updates. The feedback is designed to remove impulsive noise contamination images produced by a recursive least square algorithm by measuring the output of the proposed algorithm. The key advantage of the method is based on its capacity to estimate detectors parameters and then compensate for impulsive noise contamination image in a frame by frame basics. We define the algorithm and present several experimental results to demonstrate the efficacy of the proposed method in comparison to several previously published recursive least square-based methods. We show that the proposed method removes impulsive noise contamination image.

Keywords: infrared focal plane arrays, infrared imaging, least mean square, nonuniformity correction

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Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

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Authors: Kaoutar Ben Azzou, Hanaa Talei

Abstract:

Human resources is an important department in each organization as it manages the life cycle of employees from recruitment training to retirement or termination of contracts. The recruitment process starts with a job opening, followed by a selection of the best-fit candidates from all applicants. Matching the best profile for a job position requires a manual way of looking at many CVs, which requires hours of work that can sometimes lead to choosing not the best profile. The work presented in this paper aims at reducing the workload of HR personnel by automating the preliminary stages of the candidate screening process, thereby fostering a more streamlined recruitment workflow. This tool introduces an automated system designed to help with the recruitment process by scanning candidates' CVs, extracting pertinent features, and employing machine learning algorithms to decide the most fitting job profile for each candidate. Our work employs natural language processing (NLP) techniques to identify and extract key features from unstructured text extracted from a CV, such as education, work experience, and skills. Subsequently, the system utilizes these features to match candidates with job profiles, leveraging the power of classification algorithms.

Keywords: automated recruitment, candidate screening, machine learning, human resources management

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Authors: Bjørn Salskov, Nicolaj Bang, Charlotte Falko

Abstract:

Future labour markets demand employees that can carry out a non-linear task which is still not possible for computers. This means that employees must have well-developed soft-skills to perform at high levels in such a work environment. One of these soft-skills is presenting a message effectively. To be able to present a message effectively, one needs to practice this. To practice effectively, the trainee needs feedback on the current performance. Here VR environments can be used as a practice tool because it gives the trainee a sense of presence and reality. VR environments are becoming a cost-effective training method since it does not demand the presence of an expert to provide this feedback. The research article analysed in this study suggests that VR environment can be used and are able to provide the necessary feedback to the trainee which in turn will help the trainee become better at the task. The research analysed in this review does, however, show that there is a need for a study with larger sample size and a study which runs over a longer period.

Keywords: training, presentation, presentation skills, VR training, VR as a training tool, VR and presentation

Procedia PDF Downloads 90

Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

Abstract:

Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Cheng Shuk Ling

Abstract:

This paper examines the English syntactic errors and their patterns in the written assignments of a General Education course at City University of Hong Kong. Subjects are 60 local and non-local (exchange) undergraduate students who are all EFL learners and L2 users with diversified education and disciplinary background (i.e. their major of study), which are unrelated to English language studies. The objective of this paper brings to the foreground a broad discussion of EFL/L2 undergraduate learners’ average syntactic ability in terms of written assessment. This paper is an attempt in classifying the patterns and categories of syntactic errors committed by students who were brought up and educated in non-native English-speaking countries. Thus, pedagogical recommendations are offered for both EFL/L2 learners and educators in tertiary education settings in such ways as to calibrate how and in what manner English language as the medium of instruction can lead to more enduring effects in learners within non-native English-speaking countries.

Keywords: syntactic errors, english as a foreign language, second language users, pedagogy

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Authors: Marios Papaevripidou, Yvoni Pavlou, Zacharias Zacharia

Abstract:

Embodied cognition and additional (touch) sensory channel theories indicate that physical manipulation is crucial to learning since it provides, among others, touch sensory input, which is needed for constructing knowledge. Given these theories, the use of Physical Manipulatives (PM) becomes a prerequisite for learning. On the other hand, empirical research on Virtual Manipulatives (VM) (e.g., simulations) learning has provided evidence showing that the use of PM, and thus haptic sensory input, is not always a prerequisite for learning. In order to investigate which means of experimentation, PM or VM, are required for enhancing student science learning at the kindergarten level, an empirical study was conducted that sought to investigate the impact of haptic feedback on the conceptual understanding of pre-school students (n=44, age mean=5,7) in three science domains: beam balance (D1), sinking/floating (D2) and springs (D3). The participants were equally divided in two groups according to the type of manipulatives used (PM: presence of haptic feedback, VM: absence of haptic feedback) during a semi-structured interview for each of the domains. All interviews followed the Predict-Observe-Explain (POE) strategy and consisted of three phases: initial evaluation, experimentation, final evaluation. The data collected through the interviews were analyzed qualitatively (open-coding for identifying students’ ideas in each domain) and quantitatively (use of non-parametric tests). Findings revealed that the haptic feedback enabled students to distinguish heavier to lighter objects when held in hands during experimentation. In D1 the haptic feedback did not differentiate PM and VM students' conceptual understanding of the function of the beam as a mean to compare the mass of objects. In D2 the haptic feedback appeared to have a negative impact on PM students’ learning. Feeling the weight of an object strengthen PM students’ misconception that heavier objects always sink, whereas the scientifically correct idea that the material of an object determines its sinking/floating behavior in the water was found to be significantly higher among the VM students than the PM ones. In D3 the PM students outperformed significantly the VM students with regard to the idea that the heavier an object is the more the spring will expand, indicating that the haptic input experienced by the PM students served as an advantage to their learning. These findings point to the fact that PMs, and thus touch sensory input, might not always be a requirement for science learning and that VMs could be considered, under certain circumstances, as a viable means for experimentation.

Keywords: haptic feedback, physical and virtual manipulatives, pre-school science learning, science experimentation

Procedia PDF Downloads 112