Search results for: equestrian jumping tasks

Authors: Dean A. McCorkle, Ed W. Hellman, Rebekka M. Dudensing, Dan D. Hanselka

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The motivation for this study centers on the labor- and cost-intensive nature of wine and table grape production in the U.S., and the potential opportunities for precision mechanization using robotics to augment those production tasks that are labor-intensive. The objectives of this study are to evaluate the economic viability of grape production in five U.S. states under current operating conditions, identify common production challenges and tasks that could be augmented with new technology, and quantify a maximum price for new technology that growers would be able to pay. Wine and table grape production is primed for precision mechanization technology as it faces a variety of production and labor issues. Methodology: Using a grower panel process, this project includes the development of a representative wine grape vineyard in five states and a representative table grape vineyard in California. The panels provided production, budget, and financial-related information that are typical for vineyards in their area. Labor costs for various production tasks are of particular interest. Using the data from the representative budget, 10-year projected financial statements have been developed for the representative vineyard and evaluated using a stochastic simulation model approach. Labor costs for selected vineyard production tasks were evaluated for the potential of new precision mechanization technology being developed. These tasks were selected based on a variety of factors, including input from the panel members, and the extent to which the development of new technology was deemed to be feasible. The net present value (NPV) of the labor cost over seven years for each production task was derived. This allowed for the calculation of a maximum price for new technology whereby the NPV of labor costs would equal the NPV of purchasing, owning, and operating new technology. Expected Results: The results from the stochastic model will show the projected financial health of each representative vineyard over the 2015-2024 timeframe. Investigators have developed a preliminary list of production tasks that have the potential for precision mechanization. For each task, the labor requirements, labor costs, and the maximum price for new technology will be presented and discussed. Together, these results will allow technology developers to focus and prioritize their research and development efforts for wine and table grape vineyards, and suggest opportunities to strengthen vineyard profitability and long-term viability using precision mechanization.

Keywords: net present value, robotic technology, stochastic simulation, wine and table grapes

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Authors: Vaibhav Dalmia, Manoj Phirke, Renith G

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With the wide adoption of UAVs (unmanned aerial vehicles) in various industries by the government as well as private corporations for solving computer vision tasks it’s necessary that their potential is analyzed completely. Recent advances in Deep Learning have also left us with a plethora of algorithms to solve different computer vision tasks. This study provides a comprehensive survey on solving the Visual Object Tracking problem and explains the tradeoffs involved in building a real-time yet reasonably accurate object tracking system for UAVs by looking at existing methods and evaluating them on the aerial datasets. Finally, the best trackers suitable for UAV-based applications are provided.

Keywords: deep learning, drones, single object tracking, visual object tracking, UAVs

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Authors: Indu Gamage

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Though commonly utilized as a language improvement technique, reading has not been fully employed by both language teachers and learners to develop reading comprehension skills in English as a second language. In a Sri Lankan context, this area has to be delved deep into as the learners’ show more propensity to analyze. Reading comprehension is an area that most language teachers and learners struggle with though it appears easy. Most ESL learners engage in reading tasks without being properly aware of the objective of doing reading comprehension. It is observed that when doing reading tasks, the language learners’ concern is more on the meanings of individual words than on the overall comprehension of the given text. The passiveness with which the ESL learners engage themselves in reading comprehension makes reading a tedious task for the learner thereby giving the learner a sense of disappointment at the end. Certain reading tasks take the form of translations. The active cognitive participation of the learner in the mode of using productive strategies for predicting, employing schemata and using contextual clues seems quite less. It was hypothesized that the learners’ lack of knowledge of the productive strategies of reading was the major obstacle that makes reading comprehension a tedious task for them. This study is based on a group of 30 tertiary students who read English only as a fundamental requirement for their degree. They belonged to the Faculty of Humanities and Social Sciences of the University of Ruhuna, Sri Lanka. Almost all learners hailed from areas where English was hardly utilized in their day to day conversations. The study is carried out in the mode of a questionnaire to check their opinions on reading and a test to check whether the learners are using productive strategies of reading when doing reading comprehension tasks. The test comprised reading questions covering major productive strategies for reading. Then the results were analyzed to see the degree of their active engagement in comprehending the text. The findings depicted the validity of the hypothesis as grounds behind the difficulties related to reading comprehension.

Keywords: reading, comprehension, skills, reading strategies

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Authors: G. Kloudova, M. Stehlik

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Optimal human performance is a key goal in the professional setting of military pilots, which is a highly challenging atmosphere. The aviation environment requires substantial cognitive effort and is rich in potential stressors. Therefore, it is important to analyze variables such as mental workload to ensure safe conditions. Pilot mental workload could be measured using several tools, but most of them are very subjective. This paper details research conducted with military pilots using psychophysiological methods such as electroencephalography (EEG) and heart rate (HR) monitoring. The data were measured in a simulator as well as under real flight conditions. All of the pilots were exposed to highly demanding flight tasks and showed big individual response differences. On that basis, the individual pattern for each pilot was created counting different EEG features and heart rate variations. Later on, it was possible to distinguish the most difficult flight tasks for each pilot that should be more extensively trained. For training purposes, an application was developed for the instructors to decide which of the specific tasks to focus on during follow-up training. This complex system can help instructors detect the mentally demanding parts of the flight and enhance the training of military pilots to achieve optimal performance.

Keywords: cognitive effort, human performance, military pilots, psychophysiological methods

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Authors: Jonas De Kerf, Rein De Cooman, Sara De Gieter

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For many decades, scholars have aimed to understand how work can become more meaningful by maximizing both potential and enhancing feelings of satisfaction. One of the largest contributions towards such positive psychology was made with the introduction of the concept of ‘flow,’ which refers to a condition in which people feel intense engagement and effortless action. Since then, valuable research on work-related flow has indicated that this state of mind is related to positive outcomes for both organizations (e.g., social, supportive climates) and workers (e.g., job satisfaction). Yet, scholars still do not fully comprehend how such deep involvement at work is obtained, given the notion that flow is considered a short-term, complex, and dynamic experience. Most research neglects that people who experience flow ought to be optimally challenged so that intense concentration is required. Because attention is at the core of this enjoyable state of mind, this study aims to comprehend how elements that affect workers’ cognitive functioning impact flow at work. Research on cognitive performance suggests that working on mentally demanding tasks (e.g., information processing tasks) requires workers to concentrate deeply, as a result leading to flow experiences. Based on social facilitation theory, working on such tasks in an isolated environment eases concentration. Prior research has indicated that working at home (instead of working at the office) or in a closed office (rather than in an open-plan office) impacts employees’ overall functioning in terms of concentration and productivity. Consequently, we advance such knowledge and propose an interaction by combining cognitive task characteristics and work environments among part-time teleworkers. Hence, we not only aim to shed light on the relation between cognitive tasks and flow but also provide empirical evidence that workers performing such tasks achieve the highest states of flow while working either at home or in closed offices. In July 2022, an experience-sampling study will be conducted that uses a semi-random signal schedule to understand how task and environment predictors together impact part-time teleworkers’ flow. More precisely, about 150 knowledge workers will fill in multiple surveys a day for two consecutive workweeks to report their flow experiences, cognitive tasks, and work environments. Preliminary results from a pilot study indicate that on a between level, tasks high in information processing go along with high self-reported fluent productivity (i.e., making progress). As expected, evidence was found for higher fluency in productivity for workers performing information processing tasks both at home and in a closed office, compared to those performing the same tasks at the office or in open-plan offices. This study expands the current knowledge on work-related flow by looking at a task and environmental predictors that enable workers to obtain such a peak state. While doing so, our findings suggest that practitioners should strive for ideal alignments between tasks and work locations to work with both deep involvement and gratification.

Keywords: cognitive work, office lay-out, work location, work-related flow

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Authors: Wang Shuen-Tai, Lin Yu-Ching, Chang Hsi-Ya

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Cloud computing is the innovative and leading information technology model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort. In this paper, we aim at the development of workflow management system for cloud computing platforms based on our previous research on the dynamic allocation of the cloud computing resources and its workflow process. We took advantage of the HTML 5 technology and developed web-based workflow interface. In order to enable the combination of many tasks running on the cloud platform in sequence, we designed a mechanism and developed an execution engine for workflow management on clouds. We also established a prediction model which was integrated with job queuing system to estimate the waiting time and cost of the individual tasks on different computing nodes, therefore helping users achieve maximum performance at lowest payment. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for cloud computing platform. This development also helps boost user productivity by promoting a flexible workflow interface that lets users design and control their tasks' flow from anywhere.

Keywords: web-based, workflow, HTML5, Cloud Computing, Queuing System

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Authors: Robert Vanderburg, Michael Cowling, Nicholas Gibson

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Mathematics is one of the core subjects taught in the Australian K-12 education system and is considered an important component for future studies in areas such as engineering and technology. In addition to this, Australia has been a world leader in distance education due to the vastness of its geographic landscape. Despite this, research is still needed on distance math instruction. Even though delivery of curriculum has given way to online studies, and there is a resultant push for computer-based (PC, tablet, smartphone) math instruction, much instruction still involves practice problems similar to those original curriculum packs, without the ability for students to self-regulate their learning using the full interactive capabilities of these devices. Given this need, this paper addresses issues students have during online instruction. This study consists of 32 students struggling with mathematics enrolled in a math tutorial conducted in an online setting. The study used a case study design to understand some of the blockades hindering the students’ success. Data was collected by tracking students practice and quizzes, tracking engagement of the site, recording one-on-one tutorials, and collecting data from interviews with the students. Results revealed that when students have cognitively straining tasks in an online instructional setting, the first thing to dissipate was their ability to self-regulate. The results also revealed that instructors could ameliorate the situation and provided useful data on strategies that could be used for designing future online tasks. Specifically, instructors could utilize cognitive dissonance strategies to reduce the cognitive drain of the tasks online. They could segment the instruction process to reduce the cognitive demands of the tasks and provide in-depth self-regulatory training, freeing mental capacity for the mathematics content. Finally, instructors could provide specific scheduling and assignment structure changes to reduce the amount of student centered self-regulatory tasks in the class. These findings will be discussed in more detail and summarized in a framework that can be used for future work.

Keywords: digital education, distance education, mathematics education, self-regulation

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Authors: Roy. H. A. Lindelauf

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Cyberattacks are complex processes consisting of multiple interwoven tasks conducted by a set of agents. Interdictions and defenses against such attacks often rely on cyber kill chain (CKC) models. A CKC is a framework that tries to capture the actions taken by a cyber attacker. There exists a growing body of literature on CKCs. Most of this work either a) describes the CKC with respect to one or more specific cyberattacks or b) discusses the tools and technologies used by the attacker at each stage of the CKC. Defenders, facing scarce resources, have to decide where to allocate their resources given the CKC and partial knowledge on the tools and techniques attackers use. In this presentation CKCs are analyzed through the lens of covert projects, i.e., interrelated tasks that have to be conducted by agents (human and/or computer) with the aim of going undetected. Various aspects of covert project models have been studied abundantly in the operations research and game theory domain, think of resource-limited interdiction actions that maximally delay completion times of a weapons project for instance. This presentation has investigated both cooperative and non-cooperative game theoretic covert project models and elucidated their relation to CKC modelling. To view a CKC as a covert project each step in the CKC is broken down into tasks and there are players of which each one is capable of executing a subset of the tasks. Additionally, task inter-dependencies are represented by a schedule. Using multi-glove cooperative games it is shown how a defender can optimize the allocation of his scarce resources (what, where and how to monitor) against an attacker scheduling a CKC. This study presents and compares several cooperative game theoretic solution concepts as metrics for assigning resources to the monitoring of agents.

Keywords: cyber defense, cyber kill chain, game theory, information warfare techniques

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Supriya H. S., Chandrakala B. M.

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Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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Authors: Bing Xu, Kerry Lee, Jason M. Stephen

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Collaborative learning (CL) has been regarded as a way to facilitate students to gain knowledge and improve social skills. In China, lecturers in higher education institutions have commonly adopted CL in their daily practice. However, such a strategy could not be effective when it is designed and applied in an inappropriate way. Previous research hardly focused on how CL was applied in Chinese universities. This present study aims to gain a deep understanding of how Chinese lecturers design and implement CL tasks. The researchers interviewed ten lecturers from different faculties in various universities in China and usedGroup Learning Activity Instructional Design (GLAID) framework to analyse the data. We found that not all lecturers pay enough attention to eight essential components (proposed by GLAID) when they designed CL tasks, especially the components of Structure and Guidance. Meanwhile, only a small part of lecturers made formative assessment to help students improve learning. We also discuss the strengths and limitations and CL design and further provide suggestions to the lecturers who intend to use CL in class. Research Objectives: The aims of the present research are threefold. We intend to 1) gain a deep understanding of how Chinese lecturers design and implement collaborative learning (CL) tasks, 2) find strengths and limitations of CL design in higher education, and 3) give suggestions about how to improve the design and implement. Research Methods: This research adopted qualitative methods. We applied the semi-structured interview method to interview ten Chinese lecturers about how they designed and implemented CL tasks in their courses. There were 9 questions in the interview protocol focusing on eight components of GLAID. Then, underpinning the GLAID framework, we utilized the coding reliability thematic analysis method to analyse the research data. The coding work was done by two PhD students whose research fields are CL, and the Cohen’s Kappa was 0.772 showing the inter-coder reliability was good. Contribution: Though CL has been commonly adopted in China, few studies have paid attention to the details about how lecturers designed and implemented CL tasks in practice. This research addressed such a gap and found not lecturers were aware of how to design CL and felt it difficult to structure the task and guide the students on collaboration, and further ensure student engagement in CL. In summary, this research advocates for teacher training; otherwise, students may not gain the expected learning outcomes.

Keywords: collaborative learning, higher education, task design, GLAID framework

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Authors: Edwaldo R. B. Monteiro, Patricia D. M. Plentz, Edson R. De Pieri

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Mobile robotics is gaining an increasingly important role in modern society. Several potentially dangerous or laborious tasks for human are assigned to mobile robots, which are increasingly capable. Many of these tasks need to be performed within a specified period, i.e., meet a deadline. Missing the deadline can result in financial and/or material losses. Mechanisms for predicting the missing of deadlines are fundamental because corrective actions can be taken to avoid or minimize the losses resulting from missing the deadline. In this work we propose a simple but reliable deadline missing prediction mechanism for mobile robots through the use of historical data and we use the Pioneer 3-DX robot for experiments and simulations, one of the most popular robots in academia.

Keywords: deadline missing, historical data, mobile robots, prediction mechanism

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Authors: Dinesh Kumar Yadav

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Short stories for language development are deeply rooted elsewhere in any language syllabus. Its relevance is manifold. The short stories have the power to take the students to the target culture directly from the classroom. It works as a crucial factor in enhancing language skills in different ways. This article is an outcome of an experimental study conducted for a month on the 12th graders where they were engaged in different creative and critical-thinking activities along with various tasks that ranged from knowledge level to application level. The sole purpose was to build up their confidence in speaking in the classroom as well as develop all their language skills simultaneously. With the start of the class in August 2021, the students' speaking skill and their confidence in speaking in the class was tested. The test was abruptly followed by a presentation of a short story from their culture. The students were engaged in different tasks related to the story. The PowerPoint slides, handouts with the story, and tasks on photocopy were used as tools whenever needed. A one-month class exclusively on speaking skills through sharing stories was found to be very helpful in developing confidence in the learners. The result was very satisfactory. A large number of students became responsive in the class. The proficiency level was not satisfactory; however, their effort to speak in class showed a very positive sign in language development.

Keywords: short stories, relevance, language enhancement, language proficiency

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Authors: Seyed Yasin Yazdi-Amirkhiz, Azirah Hashim

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This study purported to comparatively investigate the influence of collaborative writing on the quality of individual writing of four female Iranian and four female Malaysian students. The first semester students at a private university in Malaysia, who were homogeneous in terms of age, gender, study discipline, and language proficiency, were divided into two Iranian and two Malaysian dyads. The dyads performed collaborative writing tasks for 15 sessions; after three consecutive collaborative writing sessions, each participant was asked to individually attempt a writing task. Both collaborative and individual writing tasks comprised isomorphic graphic prompts (IELTS Academic Module task 1). Writing quality of the five individually-produced texts during the study was scored in terms of task achievement (TA), cohesion/coherence (C/C), grammatical range/accuracy (GR/A), and lexical resources (LR). The findings indicated a hierarchy of development in TA and C/C among all the students, while LR showed minor improvement only among three of Malaysian students, and GR/A barely exhibited any progress among all the participants. Intermittent progressions and regressions were also discerned in the trajectory of their writing development. The findings are discussed in the light of the socio-cultural and emergentist perspectives, the typology of tasks used as well as the role of the participants’ level of language proficiency.

Keywords: collaborative writing, writing quality, individual writing, collaboration

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Authors: Tatiana N. Astakhova, Alexander E. Saprygin, Tatyana A. Golovko, Alexander N. Savostyanov, Mikhail S. Vlasov, Natalia V. Borisova, Alexandera G. Karpova, Urana N. Kavai-ool, Elena D. Mokur-ool, Nikolay A. Kolchanov, Lubomir I. Aftanas

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The study is dedicated to the research of brain activity in bilingual inhabitants of Siberia. We compared behavioral reactions and event-related potentials in Turkic-speaking inhabitants of Siberia (Tuvinians and Yakuts) and Russians. 63 healthy aboriginals of the Tyva Republic, 29 inhabitants of the Sakha (Yakutia) Republic, and 55 Russians from Novosibirsk participated in the study. All the healthy and right-handed participants, matched on age and sex, were students of different universities. EEG’s were recorded during the solving of linguistic tasks. In these tasks, participants had to find a syntax error in the written sentences. There were four groups of sentences: Russian, English, Tuvinian, and Yakut. All participants completed the tasks in Russian and English. Additionally, Tuvinians and Yakuts completed the tasks in Tuvinian or Yakut respectively. For Russians, EEG's were recorded using 128-channels according to the extended International 10-10 system, and the signals were amplified using “Neuroscan (USA)” amplifiers. For Tuvinians and Yakuts, EEG's were recorded using 64-channels and amplifiers Brain Products, Germany. In all groups, 0.3-100 Hz analog filtering and sampling rate 1000 Hz were used. As parameters of behavioral reactions, response speed and the accuracy of recognition were used. Event-related potentials (ERP) responses P300 and P600 were used as indicators of brain activity. The behavioral reactions showed that in Russians, the response speed for Russian was faster than for English. Also, the accuracy of solving tasks was higher for Russian than for English. The peak P300 in Russians were higher for English, the peak P600 in the left temporal cortex were higher for the Russian language. Both Tuvinians and Yakuts have no difference in accuracy of solving tasks in Russian and in their respective national languages. However, the response speed was faster for tasks in Russian than for tasks in their national language. Tuvinians and Yakuts showed bad accuracy in English, but the response speed was higher for English than for Russian and the national languages. This can be explained by the fact that they did not think carefully and gave a random answer for English. In Tuvinians, The P300 and P600 amplitudes and cortical topology were the same for Russian and Tuvinian and different for English. In Yakuts, the P300 and P600 amplitudes and topology of ERP for Russian were the same as what Russians had for Russian. In Yakuts, brain reactions during Yakut and English comprehension had no difference, and were reflected to foreign language comprehension - while the Russian language comprehension was reflected to native language comprehension. We found out that the Tuvinians recognized both Russian and Tuvinian as native languages, and English as a foreign language. The Yakuts recognized both English and Yakut as a foreign language, and only Russian as a native language. According to the inquirer, both Tuvinians and Yakuts use the national language as a spoken language, whereas they don’t use it for writing. It can well be a reason that Yakuts perceive the Yakut writing language as a foreign language while writing Russian as their native.

Keywords: EEG, ERP, native and foreign languages comprehension, Siberian inhabitants

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Authors: B. Sudarsan Baskar, S. Pooja Pragati, S. Raj Kumar

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The cost effectiveness in aircraft maintenance is of high privilege in the recent days. The cost effectiveness can be effectively made when line maintenance activities are incorporated at airports during Turn around time (TAT). The present work outcomes the shortcomings that affect the dispatching of the aircrafts, aiming at high fleet operability and low maintenance cost. The operational and cost constraints have been discussed and a suggestive alternative mechanism is proposed. The possible allocation of all deferred maintenance tasks to a set of all deferred maintenance tasks to a set of suitable airport resources have termed as alternative and is discussed in this paper from the data’s collected from the kingfisher airlines.

Keywords: decision support system, aircraft maintenance planning, maintenance-cost, RUL(remaining useful life), logistics, supply chain management

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Authors: Sakshi Gupta, Anupam Agrawal, Ekta Singla

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An exoskeleton design for rehabilitation purpose encounters many challenges, including ergonomically acceptable wearing technology, architectural design human-motion compatibility, actuation type, human-robot interaction, etc. In this paper, a passive architecture for upper limb exoskeleton is proposed for assisting in rehabilitation tasks. Kinematic modelling is detailed for task-based kinematic synthesis of the wearable exoskeleton for self-feeding tasks. The exoskeleton architecture possesses expansion and torsional springs which are able to store and redistribute energy over the human arm joints. The elastic characteristics of the springs have been optimized to minimize the mechanical work of the human arm joints. The concept of hybrid combination of a 4-bar parallelogram linkage and a serial linkage were chosen, where the 4-bar parallelogram linkage with expansion spring acts as a rigid structure which is used to provide the rotational degree-of-freedom (DOF) required for lowering and raising of the arm. The single linkage with torsional spring allows for the rotational DOF required for elbow movement. The focus of the paper is kinematic modelling, analysis and task-based synthesis framework for the proposed architecture, keeping in considerations the essential tasks of self-feeding and self-exercising during rehabilitation of partially healthy person. Rehabilitation of primary functional movements (activities of daily life, i.e., ADL) is routine activities that people tend to every day such as cleaning, dressing, feeding. We are focusing on the feeding process to make people independent in respect of the feeding tasks. The tasks are focused to post-surgery patients under rehabilitation with less than 40% weakness. The challenges addressed in work are ensuring to emulate the natural movement of the human arm. Human motion data is extracted through motion-sensors for targeted tasks of feeding and specific exercises. Task-based synthesis procedure framework will be discussed for the proposed architecture. The results include the simulation of the architectural concept for tracking the human-arm movements while displaying the kinematic and static study parameters for standard human weight. D-H parameters are used for kinematic modelling of the hybrid-mechanism, and the model is used while performing task-based optimal synthesis utilizing evolutionary algorithm.

Keywords: passive mechanism, task-based synthesis, emulating human-motion, exoskeleton

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Authors: A. Majidian

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The life prediction of thermal power plant components is necessary to prevent the unexpected outages, optimize maintenance tasks in periodic overhauls and plan inspection tasks with their schedules. One of the main critical components in a power plant is condenser because its failure can affect many other components which are positioned in downstream of condenser. This paper deals with factors affecting life of condenser. Failure rates dependency vs. these factors has been investigated using Artificial Neural Network (ANN) and fuzzy logic algorithms. These algorithms have shown their capabilities as dynamic tools to evaluate life prediction of power plant equipments.

Keywords: life prediction, condenser tube, neural network, fuzzy logic

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Authors: Kriuk Boris, Kriuk Fedor

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This paper presents a comparative study of fundamental similarity functions for Siamese networks in semantic textual similarity (STS) tasks. We evaluate various similarity functions using the STS Benchmark dataset, analyzing their performance and stability. Additionally, we introduce a multi-objective approach for optimal threshold selection. Our findings provide insights into the effectiveness of different similarity functions and offer a straightforward method for threshold selection optimization, contributing to the advancement of Siamese network architectures in STS applications.

Keywords: siamese networks, semantic textual similarity, similarity functions, STS benchmark dataset, threshold selection

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Authors: John Adeboye Oyeboade, Pius Olatunji Olaojo, Kuburay Folashade Yusuf, John Oluwaseye Adebayo

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Web-based Information Resources (WBIR) are increasingly becoming essential tools for students to accomplish academic tasks. Preliminary observation revealed that many polytechnic libraries in Southwestern Nigeria do not subscribe or renew subscriptions to WBIR academic databases, and students use free-based electronic resources. Hence, this study was carried out to investigate socioeconomic status and use of WBIR by public polytechnic students in Southwestern Nigeria. Six public polytechnics out of the 16 offerings of Higher National Diploma (HND) programs were selected by stratified random sampling to reflect federal and state polytechnics. A proportionate size sampling technique was used to select 1,463 HND students. The instruments used were Socioeconomic status (SeS) (α=0.81) and WBIR used for Academic Tasks (α=0.98) scales. Data were analyzed using descriptive statistics and Pearson’s product-moment correlation at a 0.05 level of significance. Students’ SeS ( =79.10) was moderate. Online reference sources ( =3.97), Web 2.0 ( =3.50), and social media ( =3.00) were regularly used WBIR. WBIR use ( =53.34) was moderate. The students used WBIR for project writing ( =3.46) and class assignments ( =3.42). The Students’ SeS (r=0.59) had significant relationships with WBIR use. Socioeconomic status directly influenced the use of WBIR for academic tasks. Management of polytechnics should provide WBIR subscriptions for students’ use in the polytechnic e-libraries.

Keywords: public polytechnic students, polytechnic libraries, socioeconomic status, Web-based information resources

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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: Karima Merchant

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The aim of this study was to analyze the impact of the Writing Eight Exercise, an exercise from the Brain Integration Therapy, with Kindergartners who are struggling with writing tasks in school. With the help of this exercise, children were able to cross the midline, an invisible line running from our brain to our feet, which separates the body’s right from left. Crossing the midline integrates the brain hemispheres, thus encouraging bilateral movement. The study was spread over 15 weeks where the children were required to do the Writing Eight Exercise 4 times a week. The data collection methods included observations, student work samples and feedback from teachers and parents. Based on the results of this study, it can be concluded that the Writing Eight Exercise had a positive impact on students’ approach towards writing tasks, letter formation, and fine motor skills.

Keywords: crossing the midline, fine motor skills, letter formation, writing

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Authors: Khushi Chhajed

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Context: Color has been found to have an impact on cognitive performance. Due to the negative connotation associated with red, it has been found to impair performance on intellectual tasks. Aim: This study aims to assess the effect of color on individuals' anagram solving ability. Methodology: An experimental study was conducted on 66 participants in the age group of 18–24 years. A self-made anagram assessment tool was administered. Participants were expected to solve the tool in three colors- red, blue and grey. Results: A lower score was found when presented with the color blue as compared to red. The study also found that participants took relatively greater time to solve the red colored sheet. However these results are inconsistent with pre-existing literature. Conclusion: Hence, an association between color and performance on cognitive tasks can be seen. Future directions and potential limitations are discussed.

Keywords: color psychology, experiment, anagram, performance

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Authors: Jernice S. Y. Tan

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Introduction: Reliability within and between testers is vital to ensure the accuracy of any motor assessment instrument. However, reliability checks of the Movement Assessment Battery for Children-2 (MABC-2) age band 3 using multiple testers assigned to different MABC-2 tasks for the same group of participants are uncommon. Multiple testers were not stated as a choice in the MABC-2 manual. Therefore, the purpose of this study was to determine the inter- and intra-tester reliability for using multiple testers to administer the test protocols of MABC-2 age band 3. Methods: Thirty volunteered adolescents (n = 30; 15 males, 15 females; age range: 13 – 16 years) performed the eight tasks in a randomised sequence at three different test stations for the MABC-2 task components (Manual Dexterity, Aiming and Catching, Balance). Ethics approval and parental consent were obtained. The participants were videotaped while performing the test protocols of MABC-2 age band 3. Five testers were involved in the data collection process. They were Sports Science graduating students doing their final year project and were supervised by experienced motor assessor. Inter- and intra-tester reliability checks using intra-class coefficient (ICC) were carried out using the videotaped data. Results: The inter-tester reliability between the five testers for the eight tasks ranged from rᵢcc = 0.705 to rᵢcc = 0.995. This suggests that the average agreement between them was considered good to excellent. With the exception of one tester who had rᵢcc = 0.687 for one of the eight tasks (i.e. zip-zap hopping), the intra-tester reliability within each tester ranged from rᵢcc = 0.728 to rᵢcc = 1.000, and this also suggested good to excellent consistency within testers. Discussion: The use of multiple testers with good intra-tester reliability for different test stations is feasible. This method allows several participants to be assessed concurrently at different test stations and saves overall data collection time. Therefore, it is recommended that the administering of MABC-2 with multiple testers should be extended to other age bands ensuring the feasibility of such method for other age bands.

Keywords: adolescents, MABC, motor assessment, motor skills, reliability

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Authors: Guanqiao Wang, Hongyang Yu

Abstract:

There is a lot of repetitive work in the traditional construction industry. These repetitive tasks can significantly improve production efficiency by replacing manual tasks with robots. There- fore, robots appear more and more frequently in the construction industry. Navigation and positioning are very important tasks for construction robots, and the requirements for accuracy of positioning are very high. Traditional indoor robots mainly use radiofrequency or vision methods for positioning. Compared with ordinary robots, the indoor plastering robot needs to be positioned closer to the wall for wall plastering, so the requirements for construction positioning accuracy are higher, and the traditional navigation positioning method has a large error, which will cause the robot to move. Without the exact position, the wall cannot be plastered, or the error of plastering the wall is large. A new positioning method is proposed, which is assisted by line lasers and uses image processing-based positioning to perform more accurate positioning on the traditional positioning work. In actual work, filter, edge detection, Hough transform and other operations are performed on the images captured by the camera. Each time the position of the laser line is found, it is compared with the standard value, and the position of the robot is moved or rotated to complete the positioning work. The experimental results show that the actual positioning error is reduced to less than 0.5 mm by this accurate positioning method.

Keywords: indoor plastering robot, navigation, precise positioning, line laser, image processing

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Authors: Zheng Baichuan, Li Shenghui, Li Bingqian, Zhang Ning, Chen Kai

Abstract:

Entity alignment (EA) tasks in knowledge graphs often play a pivotal role in the integration of knowledge graphs, where structural differences often exist between the source and target graphs, such as the presence or absence of attribute information and the types of attribute information (text, timestamps, images, etc.). However, most current research efforts are focused on improving alignment accuracy, often along with an increased reliance on specific structures -a dependency that inevitably diminishes their practical value and causes difficulties when facing knowledge graph alignment tasks with varying structures. Therefore, we propose a universal knowledge graph alignment approach that only utilizes the common basic structures shared by knowledge graphs. We have demonstrated through experiments that our method achieves state-of-the-art performance in fair comparisons.

Keywords: knowledge graph, entity alignment, transformer, deep learning

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Authors: Izabella Szollosi, Klara Marton

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Aphasia can be defined as a weakness in accessing linguistic information. Accessing linguistic information is strongly related to information processing, which in turn is associated with the cognitive control system. According to the literature, a deficit in the cognitive control system interferes with language processing and contributes to non-fluent speech performance. The aim of our study was to explore this hypothesis by investigating how cognitive control interacts with language performance in participants with non-fluent aphasia. Cognitive control is a complex construct that includes working memory (WM) and the ability to resist proactive interference (PI). Based on previous research, we hypothesized that impairments in domain-general (DG) cognitive control abilities have negative effects on language processing. In contrast, better DG cognitive control functioning supports goal-directed behavior in language-related processes as well. Since stroke itself might slow down information processing, it is important to examine its negative effects on both cognitive control and language processing. Participants (N=52) in our study were individuals with non-fluent Broca’s aphasia (N = 13), with transcortical motor aphasia (N=13), individuals with stroke damage without aphasia (N=13), and unimpaired speakers (N = 13). All participants performed various computer-based tasks targeting cognitive control functions such as WM and resistance to PI in both linguistic and non-linguistic domains. Non-linguistic tasks targeted primarily DG functions, while linguistic tasks targeted more domain specific (DS) processes. The results showed that participants with Broca’s aphasia differed from the other three groups in the non-linguistic tasks. They performed significantly worse even in the baseline conditions. In contrast, we found a different performance profile in the linguistic domain, where the control group differed from all three stroke-related groups. The three groups with impairment performed more poorly than the controls but similar to each other in the verbal baseline condition. In the more complex verbal PI condition, however, participants with Broca’s aphasia performed significantly worse than all the other groups. Participants with Broca’s aphasia demonstrated the most severe language impairment and the highest vulnerability in tasks measuring DG cognitive control functions. Results support the notion that the more severe the cognitive control impairment, the more severe the aphasia. Thus, our findings suggest a strong interaction between cognitive control and language. Individuals with the most severe and most general cognitive control deficit - participants with Broca’s aphasia - showed the most severe language impairment. Individuals with better DG cognitive control functions demonstrated better language performance. While all participants with stroke damage showed impaired cognitive control functions in the linguistic domain, participants with better language skills performed also better in tasks that measured non-linguistic cognitive control functions. The overall results indicate that the level of cognitive control deficit interacts with the language functions in individuals along with the language spectrum (from severe to no impairment). However, future research is needed to determine any directionality.

Keywords: cognitive control, information processing, language performance, non-fluent aphasia

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Authors: Anju Bala, Inderveer Chana

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Task scheduling is the key concern for the execution of performance-driven workflow applications. As efficient scheduling can have major impact on the performance of the system, task scheduling is often chosen for assigning the request to resources in an efficient way based on cloud resource characteristics. In this paper, priority based task scheduling algorithm has been proposed that prioritizes the tasks based on the length of the instructions. The proposed scheduling approach prioritize the tasks of Cloud applications according to the limits set by six sigma control charts based on dynamic threshold values. Further, the proposed algorithm has been validated through the CloudSim toolkit. The experimental results demonstrate that the proposed algorithm is effective for handling multiple task lists from workflows and in considerably reducing Makespan and Execution time.

Keywords: cloud computing, priority based scheduling, task scheduling, VM allocation

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Authors: J. D. Martínez-Vargas, C. Castro-Hoyos, G. Castellanos-Dominguez

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In this work, we propose a novel approach for measuring the stationarity level of a multichannel time-series. This measure is based on a stationarity definition over time-varying spectrum, and it is aimed to quantify the relation between local stationarity (single-channel) and global dynamic behavior (multichannel dynamics). To assess the proposed approach validity, we use a well known EEG-BCI database, that was constructed for separate between motor/imagery tasks. Thus, based on the statement that imagination of movements implies an increase on the EEG dynamics, we use as discriminant features the proposed measure computed over an estimation of the non-stationary components of input time-series. As measure of separability we use a t-student test, and the obtained results evidence that such measure is able to accurately detect the brain areas projected on the scalp where motor tasks are realized.

Keywords: stationary measure, entropy, sub-space projection, multichannel dynamics

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Authors: Tamer E. Yared

Abstract:

The use of driving simulators has made laboratory testing easier. It has been proven to be valid for testing driving ability by many researchers. One benefit of using driving simulators is keeping the human subjects away from traffic hazards, which drivers usually face in a real driving environment while performing a driving experiment. In this study, a driving simulator was developed with a navigation system using a game development software (Unity 3D) and C-sharp codes to measure and evaluate driving performance, safety, and workload for different driving tasks. The driving simulator hardware included a gaming steering wheel and pedals as well as a monitor to view the driving tasks. Moreover, driver distraction was evaluated by utilizing an eye-tracking system working in conjunction with the driving simulator. Twenty subjects were recruited to evaluate driver distraction, workload, driving safety, and performance, as well as provide their feedback about the driving simulator. The subjects’ feedback was obtained by filling a survey after conducting several driving tasks. The main question of that survey was asking the subjects to compare driving on the driving simulator with real driving. Furthermore, other aspects of the driving simulator were evaluated by the subjects in the survey. The survey revealed that the recruited subjects gave an average score of 7.5 out of 10 to the driving simulator when compared to real driving, where the scores ranged between 6 and 8.5. This study is a preliminary effort that opens the door for more improvements to the driving simulator in terms of hardware and software development, which will contribute significantly to driving ability testing.

Keywords: driver distraction, driving performance, driving safety, driving simulator, driving workload, navigation system

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