Search results for: controlled tasks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3739

Search results for: controlled tasks

3739 FESA: Fuzzy-Controlled Energy-Efficient Selective Allocation and Reallocation of Tasks Among Mobile Robots

Authors: Anuradha Banerjee

Abstract:

Energy aware operation is one of the visionary goals in the area of robotics because operability of robots is greatly dependent upon their residual energy. Practically, the tasks allocated to robots carry different priority and often an upper limit of time stamp is imposed within which the task needs to be completed. If a robot is unable to complete one particular task given to it the task is reallocated to some other robot. The collection of robots is controlled by a Central Monitoring Unit (CMU). Selection of the new robot is performed by a fuzzy controller called Task Reallocator (TRAC). It accepts the parameters like residual energy of robots, possibility that the task will be successfully completed by the new robot within stipulated time, distance of the new robot (where the task is reallocated) from distance of the old one (where the task was going on) etc. The proposed methodology increases the probability of completing globally assigned tasks and saves huge amount of energy as far as the collection of robots is concerned.

Keywords: energy-efficiency, fuzzy-controller, priority, reallocation, task

Procedia PDF Downloads 277
3738 A Case Study of Deep Learning for Disease Detection in Crops

Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

Abstract:

In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

Procedia PDF Downloads 218
3737 An Overview of Evaluations Using Augmented Reality for Assembly Training Tasks

Authors: S. Werrlich, E. Eichstetter, K. Nitsche, G. Notni

Abstract:

Augmented Reality (AR) is a strong growing research topic in different training domains such as medicine, sports, military, education and industrial use cases like assembly and maintenance tasks. AR claims to improve the efficiency and skill-transfer of training tasks. This paper gives a comprehensive overview of evaluations using AR for assembly and maintenance training tasks published between 1992 and 2017. We search in a structured way in four different online databases and get 862 results. We select 17 relevant articles focusing on evaluating AR-based training applications for assembly and maintenance tasks. This paper also indicates design guidelines which are necessary for creating a successful application for an AR-based training. We also present five scientific limitations in the field of AR-based training for assembly tasks. Finally, we show our approach to solve current research problems using Design Science Research (DSR).

Keywords: assembly, augmented reality, survey, training

Procedia PDF Downloads 234
3736 Efficient Rehearsal Free Zero Forgetting Continual Learning Using Adaptive Weight Modulation

Authors: Yonatan Sverdlov, Shimon Ullman

Abstract:

Artificial neural networks encounter a notable challenge known as continual learning, which involves acquiring knowledge of multiple tasks over an extended period. This challenge arises due to the tendency of previously learned weights to be adjusted to suit the objectives of new tasks, resulting in a phenomenon called catastrophic forgetting. Most approaches to this problem seek a balance between maximizing performance on the new tasks and minimizing the forgetting of previous tasks. In contrast, our approach attempts to maximize the performance of the new task, while ensuring zero forgetting. This is accomplished through the introduction of task-specific modulation parameters for each task, and only these parameters are learned for the new task, after a set of initial tasks have been learned. Through comprehensive experimental evaluations, our model demonstrates superior performance in acquiring and retaining novel tasks that pose difficulties for other multi-task models. This emphasizes the efficacy of our approach in preventing catastrophic forgetting while accommodating the acquisition of new tasks.

Keywords: continual learning, life-long learning, neural analogies, adaptive modulation

Procedia PDF Downloads 34
3735 In-Context Meta Learning for Automatic Designing Pretext Tasks for Self-Supervised Image Analysis

Authors: Toktam Khatibi

Abstract:

Self-supervised learning (SSL) includes machine learning models that are trained on one aspect and/or one part of the input to learn other aspects and/or part of it. SSL models are divided into two different categories, including pre-text task-based models and contrastive learning ones. Pre-text tasks are some auxiliary tasks learning pseudo-labels, and the trained models are further fine-tuned for downstream tasks. However, one important disadvantage of SSL using pre-text task solving is defining an appropriate pre-text task for each image dataset with a variety of image modalities. Therefore, it is required to design an appropriate pretext task automatically for each dataset and each downstream task. To the best of our knowledge, the automatic designing of pretext tasks for image analysis has not been considered yet. In this paper, we present a framework based on In-context learning that describes each task based on its input and output data using a pre-trained image transformer. Our proposed method combines the input image and its learned description for optimizing the pre-text task design and its hyper-parameters using Meta-learning models. The representations learned from the pre-text tasks are fine-tuned for solving the downstream tasks. We demonstrate that our proposed framework outperforms the compared ones on unseen tasks and image modalities in addition to its superior performance for previously known tasks and datasets.

Keywords: in-context learning (ICL), meta learning, self-supervised learning (SSL), vision-language domain, transformers

Procedia PDF Downloads 33
3734 Progress in Combining Image Captioning and Visual Question Answering Tasks

Authors: Prathiksha Kamath, Pratibha Jamkhandi, Prateek Ghanti, Priyanshu Gupta, M. Lakshmi Neelima

Abstract:

Combining Image Captioning and Visual Question Answering (VQA) tasks have emerged as a new and exciting research area. The image captioning task involves generating a textual description that summarizes the content of the image. VQA aims to answer a natural language question about the image. Both these tasks include computer vision and natural language processing (NLP) and require a deep understanding of the content of the image and semantic relationship within the image and the ability to generate a response in natural language. There has been remarkable growth in both these tasks with rapid advancement in deep learning. In this paper, we present a comprehensive review of recent progress in combining image captioning and visual question-answering (VQA) tasks. We first discuss both image captioning and VQA tasks individually and then the various ways in which both these tasks can be integrated. We also analyze the challenges associated with these tasks and ways to overcome them. We finally discuss the various datasets and evaluation metrics used in these tasks. This paper concludes with the need for generating captions based on the context and captions that are able to answer the most likely asked questions about the image so as to aid the VQA task. Overall, this review highlights the significant progress made in combining image captioning and VQA, as well as the ongoing challenges and opportunities for further research in this exciting and rapidly evolving field, which has the potential to improve the performance of real-world applications such as autonomous vehicles, robotics, and image search.

Keywords: image captioning, visual question answering, deep learning, natural language processing

Procedia PDF Downloads 41
3733 Freedom and the Value of Games: How to Overcome the Challenges in the Gamification of Necessary Learning Tasks

Authors: Jonathan May

Abstract:

This paper argues that the value of games relates to the sensation of freedom they create, and this in turn results from their nature as voluntary, non-necessary tasks. Attempts to gamify necessary learning tasks are therefore challenged to create this sensation of freedom and so they often fail to create the pleasure and value found in traditional games. It then demonstrates a route to creating this sensation of freedom through the maximization of varied and creative solutions to such problems.

Keywords: gamification, games, philosophy of games, freedom, voluntary action, necessity, motivation, value of games

Procedia PDF Downloads 121
3732 Mathematical Modeling of Switching Processes in Magnetically Controlled MEMS Switches

Authors: Sergey M. Karabanov, Dmitry V. Suvorov, Dmitry Yu. Tarabrin

Abstract:

The operating principle of magnetically controlled microelectromechanical system (MEMS) switches is based on controlling the beam movement under the influence of a magnetic field. Currently, there is a MEMS switch design with a flexible ferromagnetic electrode in the form of a fixed-terminal beam, with an electrode fastened on a straight or cranked anchor. The basic performance characteristics of magnetically controlled MEMS switches (service life, sensitivity, contact resistance, fast response) are largely determined by the flexible electrode design. To ensure the stable and controlled motion of the flexible electrode, it is necessary to provide the optimal design of a flexible electrode.

Keywords: flexible electrode, magnetically controlled MEMS, mathematical modeling, mechanical stress

Procedia PDF Downloads 143
3731 On the Significance of Preparing a Professional Literature Review in EFL Context

Authors: Fahimeh Marefat, Marzieh Marefat

Abstract:

The present research is inspired by the comment that “A substantive, thorough, sophisticated literature review is a precondition for doing substantive, thorough, sophisticated research”. This study is a report on an action research to solve my problem of preparing students to write a Literature Review (LR) that is more than mere cut and paste. More specifically, this study was initiated to discover whether there is an impact of equipping students with tools to write LR on the quality of research and on their view on LR significance. The participants were twenty-four Iranian TEFLers at Allameh Tabataba’i University. they were taking their advanced writing course with the lead researcher. We met once a week for 90 minutes for five weeks followed by individual consultations. Working through a process approach, and implementing tasks, the lead researcher ran workshops implementing different controlled assignments and subsequent activities to lead students to practice appropriate source use on multiple drafts: From choosing the topic, finding sources, forming questions, preparing quotation, paraphrase, and summary note cards, to outlining and most importantly introducing them the tools to evaluate prior research and offer their own take of it and finally synthesizing and incorporating the notes into the body of the LR section of their papers. The LR scoring rubric was implemented and a note was emailed to the students asking about their views. It was indicated that awareness raising and detailed explicit instruction improved the LR quality compared to their previous projects. Interestingly enough, they acknowledged how LR shaped all stages of their research, a further support for the notion of “being scholars before researchers”. The key to success is mastery over the literature which translates into extensive reading and critically appraising it.

Keywords: controlled tasks, critical evaluation, review of literature, writing synthesis

Procedia PDF Downloads 319
3730 Use and Effects of Kanban Board from the Aspects of Brothers Furniture Limited

Authors: Kazi Rizvan, Yamin Rekhu

Abstract:

Due to high competitiveness in industries throughout the world, every industry is trying hard to utilize all their resources to keep their productivity as high as possible. Many tools have been being used to ensure smoother flow of an operation, to balance tasks, to maintain proper schedules for tasks, to maintain proper sequence for tasks, to reduce unproductive time. All of these tools are used to augment productivity within an industry. Kanban board is one of them and of the many important tools of lean production system. Kanban Board is a visual depiction of the status of tasks. Kanban board shows the actual status of the tasks. It conveys the progress and issues of tasks as well. Using Kanban Board, tasks can be distributed among workers and operation targets can be visually represented to them. In this paper, an example of Kanban board from the aspects of Brothers Furniture Limited was taken and how the Kanban board system was implemented, how the board was designed and how it was made easily perceivable for the less literate or illiterate workers. The Kanban board was designed for the packing section of Brothers Furniture Limited. It was implemented for the purpose of representing the tasks flow to the workers and to mitigate the time that was wasted while the workers remained wondering about what task they should start after they finish one. Kanban board subsumed seven columns and there was a column for comments where if any problem occurred during working on the tasks. Kanban board was helpful for the workers as the board showed the urgency of the tasks. It was also helpful for the store section as they could understand which products and how much of them could be delivered to store at any certain time. Kanban board had all the information centralized which is why the work-flow got paced up and idle time was minimized. Regardless of many workers being illiterate or less literate, Kanban board was still explicable for the workers as the Kanban cards were colored. Since the significance of colors can be conveniently interpretable to them, colored cards helped a great deal in that matter. Hence, the illiterate or less literate workers didn’t have to spend time wondering about the significance of the cards. Even when the workers weren’t told the significance of the colored cards, they could grow a feeling about their meaning as colors can trigger anyone’s mind to perceive the situation. As a result, the board elucidated the workers about what board required them to do, when to do and what to do next. Kanban board alleviated excessive time between tasks by setting day-plan for targeted tasks and it also reduced time during tasks as the workers were acknowledged of forthcoming tasks for a day. Being very specific to the tasks, Kanban board helped the workers become more focused on their tasks helped them do their job with more perfection. As a result, The Kanban board helped achieve a 8.75% increase in productivity than the productivity before the Kanban board was implemented.

Keywords: color, Kanban Board, Lean Tool, literacy, packing, productivity

Procedia PDF Downloads 200
3729 Metaheuristics to Solve Tasks Scheduling

Authors: Rachid Ziteuni, Selt Omar

Abstract:

In this paper, we propose a new polynomial metaheuristic elaboration (tabu search) for solving scheduling problems. This method allows us to solve the scheduling problem of n tasks on m identical parallel machines with unavailability periods. This problem is NP-complete in the strong sens and finding an optimal solution appears unlikely. Note that all data in this problem are integer and deterministic. The performance criterion to optimize in this problem which we denote Pm/N-c/summs of (wjCj) is the weighted sum of the end dates of tasks.

Keywords: scheduling, parallel identical machines, unavailability periods, metaheuristic, tabu search

Procedia PDF Downloads 290
3728 Pre-Service Teachers’ Reasoning and Sense Making of Variables

Authors: Olteanu Constanta, Olteanu Lucian

Abstract:

Researchers note that algebraic reasoning and sense making is essential for building conceptual knowledge in school mathematics. Consequently, pre-service teachers’ own reasoning and sense making are useful in fostering and developing students’ algebraic reasoning and sense making. This article explores the forms of reasoning and sense making that pre-service mathematics teachers exhibit and use in the process of analysing problem-posing tasks with a focus on first-degree equations. Our research question concerns the characteristics of the problem-posing tasks used for reasoning and sense making of first-degree equations as well as the characteristics of pre-service teachers’ reasoning and sense making in problem-posing tasks. The analyses are grounded in a post-structuralist philosophical perspective and variation theory. Sixty-six pre-service primary teachers participated in the study. The results show that the characteristics of reasoning in problem-posing tasks and of pre-service teachers are selecting, exploring, reconfiguring, encoding, abstracting and connecting. The characteristics of sense making in problem-posing tasks and of pre-service teachers are recognition, relationships, profiling, comparing, laddering and verifying. Beside this, the connection between reasoning and sense making is rich in line of flight in problem-posing tasks, while the connection is rich in line of rupture for pre-service teachers.

Keywords: first-degree equations, problem posing, reasoning, rhizomatic assemblage, sense-making, variation theory

Procedia PDF Downloads 69
3727 The Mental Workload of ICU Nurses in Performing Human-Machine Tasks: A Cross-sectional Survey

Authors: Yan Yan, Erhong Sun, Lin Peng, Xuchun Ye

Abstract:

Aims: The present study aimed to explore Intensive Care Unit(ICU) nurses’ mental workload (MWL) and associated factors with it in performing human-machine tasks. Background: A wide range of emerging technologies have penetrated widely in the field of health care, and ICU nurses are facing a dramatic increase in nursing human-machine tasks. However, there is still a paucity of literature reporting on the general MWL of ICU nurses performing human-machine tasks and the associated influencing factors. Methods: A cross-sectional survey was employed. The data was collected from January to February 2021 from 9 tertiary hospitals in 6 provinces (Shanghai, Gansu, Guangdong, Liaoning, Shandong, and Hubei). Two-stage sampling was used to recruit eligible ICU nurses (n=427). The data were collected with an electronic questionnaire comprising sociodemographic characteristics and the measures of MWL, self-efficacy, system usability, and task difficulty. The univariate analysis, two-way analysis of variance(ANOVA), and a linear mixed model were used for data analysis. Results: Overall, the mental workload of ICU nurses in performing human-machine tasks was medium (score 52.04 on a 0-100 scale). Among the typical nursing human-machine tasks selected, the MWL of ICU nurses in completing first aid and life support tasks (‘Using a defibrillator to defibrillate’ and ‘Use of ventilator’) was significantly higher than others (p < .001). And ICU nurses’ MWL in performing human-machine tasks was also associated with age (p = .001), professional title (p = .002), years of working in ICU (p < .001), willingness to study emerging technology actively (p = .006), task difficulty (p < .001), and system usability (p < .001). Conclusion: The MWL of ICU nurses is at a moderate level in the context of a rapid increase in nursing human-machine tasks. However, there are significant differences in MWL when performing different types of human-machine tasks, and MWL can be influenced by a combination of factors. Nursing managers need to develop intervention strategies in multiple ways. Implications for practice: Multidimensional approaches are required to perform human-machine tasks better, including enhancing nurses' willingness to learn emerging technologies actively, developing training strategies that vary with tasks, and identifying obstacles in the process of human-machine system interaction.

Keywords: mental workload(MWL), nurse, ICU, human-machine, tasks, cross-sectional study, linear mixed model, China

Procedia PDF Downloads 60
3726 Simulation for Squat Exercise of an Active Controlled Vibration Isolation and Stabilization System for Astronaut’s Exercise Platform

Authors: Ziraguen O. Williams, Shield B. Lin, Fouad N. Matari, Leslie J. Quiocho

Abstract:

In a task to assist NASA in analyzing the dynamic forces caused by operational countermeasures of an astronaut’s exercise platform impacting the spacecraft, feedback delay, and signal noise were added to a simulation model of an active-controlled vibration isolation system to regulate the movement of the exercise platform. Previous simulation work was conducted primarily via MATLAB/Simulink. Two additional simulation tools used in this study were Trick and MBDyn, NASA co-developed software simulation environments. Simulation results obtained from these three tools were very similar. All simulation results support the hypothesis that an active-controlled vibration isolation system outperforms a passive-controlled system even with the addition of feedback delay and signal noise to the active-controlled system. In this paper, squat exercise was used in creating excited force to the simulation model. The exciter force from a squat exercise was calculated from the motion capture of an exerciser. The simulation results demonstrate much greater transmitted force reduction in the active-controlled system than the passive-controlled system.

Keywords: control, counterweight, isolation, vibration

Procedia PDF Downloads 72
3725 Preparation and Evaluation of Multiple Unit Tablets of Aceclofenac

Authors: Vipin Saini, Sunil Kamboj, Suman Bala, A. Pandurangan

Abstract:

The present research is aimed at fabrication of multiple-unit controlled-release tablet formulation of aceclofenac by employing acrylic polymers as the release controlling excipients for drug multi-particulates to achieve the desired objectives of maintaining the same controlled release characteristics as that prior to their compression into tablet. Various manufacturers are successfully manufacturing and marketing aceclofenac controlled release tablet by applying directly coating materials on the tablet. The basic idea behind development of such formulations was to employ aqueous acrylics polymers dispersion as an alternative to the existing approaches, wherein the forces of compression may cause twist of drug pellets, but do not have adverse effects on the drug release properties. Thus, the study was undertaken to illustrate manufacturing of controlled release aceclofenac multiple-unit tablet formulation.

Keywords: aceclofenac, multiple-unit tablets, acrylic polymers, controlled-release

Procedia PDF Downloads 394
3724 Algorithms for Run-Time Task Mapping in NoC-Based Heterogeneous MPSoCs

Authors: M. K. Benhaoua, A. K. Singh, A. E. Benyamina, P. Boulet

Abstract:

Mapping parallelized tasks of applications onto these MPSoCs can be done either at design time (static) or at run-time (dynamic). Static mapping strategies find the best placement of tasks at design-time, and hence, these are not suitable for dynamic workload and seem incapable of runtime resource management. The number of tasks or applications executing in MPSoC platform can exceed the available resources, requiring efficient run-time mapping strategies to meet these constraints. This paper describes a new Spiral Dynamic Task Mapping heuristic for mapping applications onto NoC-based Heterogeneous MPSoC. This heuristic is based on packing strategy and routing Algorithm proposed also in this paper. Heuristic try to map the tasks of an application in a clustering region to reduce the communication overhead between the communicating tasks. The heuristic proposed in this paper attempts to map the tasks of an application that are most related to each other in a spiral manner and to find the best possible path load that minimizes the communication overhead. In this context, we have realized a simulation environment for experimental evaluations to map applications with varying number of tasks onto an 8x8 NoC-based Heterogeneous MPSoCs platform, we demonstrate that the new mapping heuristics with the new modified dijkstra routing algorithm proposed are capable of reducing the total execution time and energy consumption of applications when compared to state-of-the-art run-time mapping heuristics reported in the literature.

Keywords: multiprocessor system on chip, MPSoC, network on chip, NoC, heterogeneous architectures, run-time mapping heuristics, routing algorithm

Procedia PDF Downloads 442
3723 The Mental Workload of Intensive Care Unit Nurses in Performing Human-Machine Tasks: A Cross-Sectional Survey

Authors: Yan Yan, Erhong Sun, Lin Peng, Xuchun Ye

Abstract:

Aims: The present study aimed to explore Intensive Care Unit (ICU) nurses’ mental workload (MWL) and associated factors with it in performing human-machine tasks. Background: A wide range of emerging technologies have penetrated widely in the field of health care, and ICU nurses are facing a dramatic increase in nursing human-machine tasks. However, there is still a paucity of literature reporting on the general MWL of ICU nurses performing human-machine tasks and the associated influencing factors. Methods: A cross-sectional survey was employed. The data was collected from January to February 2021 from 9 tertiary hospitals in 6 provinces (Shanghai, Gansu, Guangdong, Liaoning, Shandong, and Hubei). Two-stage sampling was used to recruit eligible ICU nurses (n=427). The data were collected with an electronic questionnaire comprising sociodemographic characteristics and the measures of MWL, self-efficacy, system usability, and task difficulty. The univariate analysis, two-way analysis of variance (ANOVA), and a linear mixed model were used for data analysis. Results: Overall, the mental workload of ICU nurses in performing human-machine tasks was medium (score 52.04 on a 0-100 scale). Among the typical nursing human-machine tasks selected, the MWL of ICU nurses in completing first aid and life support tasks (‘Using a defibrillator to defibrillate’ and ‘Use of ventilator’) was significantly higher than others (p < .001). And ICU nurses’ MWL in performing human-machine tasks was also associated with age (p = .001), professional title (p = .002), years of working in ICU (p < .001), willingness to study emerging technology actively (p = .006), task difficulty (p < .001), and system usability (p < .001). Conclusion: The MWL of ICU nurses is at a moderate level in the context of a rapid increase in nursing human-machine tasks. However, there are significant differences in MWL when performing different types of human-machine tasks, and MWL can be influenced by a combination of factors. Nursing managers need to develop intervention strategies in multiple ways. Implications for practice: Multidimensional approaches are required to perform human-machine tasks better, including enhancing nurses' willingness to learn emerging technologies actively, developing training strategies that vary with tasks, and identifying obstacles in the process of human-machine system interaction.

Keywords: mental workload, nurse, ICU, human-machine, tasks, cross-sectional study, linear mixed model, China

Procedia PDF Downloads 33
3722 Dual-Task–Immersion in the Interactions of Simultaneously Performed Tasks

Authors: M. Liebherr, P. Schubert, S. Kersten, C. Dietz, L. Franz, C. T. Haas

Abstract:

With a long history, dual-task has become one of the most intriguing research fields regarding human brain functioning and cognition. However, findings considering effects of task-interrelations are limited (especially, in combined motor and cognitive tasks). Therefore, we aimed at developing a measurement system in order to analyse interrelation effects of cognitive and motor tasks. On the one hand, the present study demonstrates the applicability of the measurement system and on the other hand first results regarding a systematization of different task combinations are shown. Future investigations should combine imagine technologies and this developed measurement system.

Keywords: dual-task, interference, cognition, measurement

Procedia PDF Downloads 496
3721 Design of a Virtual Reality System for Children with Developmental Coordination Disorder

Authors: Ya-Ju Ju, Li-Chen Yang, Yi-Chun Du, Rong-Ju Cherng

Abstract:

Introduction: It is estimated that 5-6% of school-aged children may be diagnosed to have developmental coordination disorder (DCD). Children with DCD are characterized with motor skill difficulty which cannot be explained by any medical or intellectual reasons. Such motor difficulties limit children’s participation to sports activity, further affect their physical fitness, cardiopulmonary function and balance, and may lead to obesity. The purpose of the project was to develop an exergaming system for children with DCD aiming to improve their physical fitness, cardiopulmonary function and balance ability. Methods: This study took five steps to build up the system: system planning, tasks selection, tasks programming, system integration and usability test. The system basically adopted virtual reality technique to integrate self-developed training programs. The training programs were developed to brainstorm among team members and after literature review. The selected tasks for training in the system were a combination of fundamental movement tor skill. Results and Discussion: Based on the theory of motor development, we design the training task from easy ones to hard ones, from single tasks to dual tasks. The tasks included walking, sit to stand, jumping, kicking, weight shifting, side jumping and their combination. Preliminary study showed that the tasks presented an order of development. Further study is needed to examine its effect on motor skill and cardiovascular fitness in children with DCD.

Keywords: virtual reality, virtual reality system, developmental coordination disorder, children

Procedia PDF Downloads 76
3720 Experimental Study of Upsetting and Die Forging with Controlled Impact

Authors: T. Penchev, D. Karastoyanov

Abstract:

The results from experimental research of deformation by upsetting and die forging of lead specimens wit controlled impact are presented. Laboratory setup for conducting the investigations, which uses cold rocket engine operated with compressed air, is described. The results show that when using controlled impact is achieving greater plastic deformation and consumes less impact energy than at ordinary impact deformation process.

Keywords: rocket engine, forging hammer, sticking impact, plastic deformation

Procedia PDF Downloads 334
3719 Workforce Optimization: Fair Workload Balance and Near-Optimal Task Execution Order

Authors: Alvaro Javier Ortega

Abstract:

A large number of companies face the challenge of matching highly-skilled professionals to high-end positions by human resource deployment professionals. However, when the professional list and tasks to be matched are larger than a few dozens, this process result is far from optimal and takes a long time to be made. Therefore, an automated assignment algorithm for this workforce management problem is needed. The majority of companies are divided into several sectors or departments, where trained employees with different experience levels deal with a large number of tasks daily. Also, the execution order of all tasks is of mater consequence, due to some of these tasks just can be run it if the result of another task is provided. Thus, a wrong execution order leads to large waiting times between consecutive tasks. The desired goal is, therefore, creating accurate matches and a near-optimal execution order that maximizes the number of tasks performed and minimizes the idle time of the expensive skilled employees. The problem described before can be model as a mixed-integer non-linear programming (MINLP) as it will be shown in detail through this paper. A large number of MINLP algorithms have been proposed in the literature. Here, genetic algorithm solutions are considered and a comparison between two different mutation approaches is presented. The simulated results considering different complexity levels of assignment decisions show the appropriateness of the proposed model.

Keywords: employees, genetic algorithm, industry management, workforce

Procedia PDF Downloads 119
3718 Resource Allocation and Task Scheduling with Skill Level and Time Bound Constraints

Authors: Salam Saudagar, Ankit Kamboj, Niraj Mohan, Satgounda Patil, Nilesh Powar

Abstract:

Task Assignment and Scheduling is a challenging Operations Research problem when there is a limited number of resources and comparatively higher number of tasks. The Cost Management team at Cummins needs to assign tasks based on a deadline and must prioritize some of the tasks as per business requirements. Moreover, there is a constraint on the resources that assignment of tasks should be done based on an individual skill level, that may vary for different tasks. Another constraint is for scheduling the tasks that should be evenly distributed in terms of number of working hours, which adds further complexity to this problem. The proposed greedy approach to solve assignment and scheduling problem first assigns the task based on management priority and then by the closest deadline. This is followed by an iterative selection of an available resource with the least allocated total working hours for a task, i.e. finding the local optimal choice for each task with the goal of determining the global optimum. The greedy approach task allocation is compared with a variant of Hungarian Algorithm, and it is observed that the proposed approach gives an equal allocation of working hours among the resources. The comparative study of the proposed approach is also done with manual task allocation and it is noted that the visibility of the task timeline has increased from 2 months to 6 months. An interactive dashboard app is created for the greedy assignment and scheduling approach and the tasks with more than 2 months horizon that were waiting in a queue without a delivery date initially are now analyzed effectively by the business with expected timelines for completion.

Keywords: assignment, deadline, greedy approach, Hungarian algorithm, operations research, scheduling

Procedia PDF Downloads 105
3717 Role of the Midwifery Trained Registered Nurse in Postnatal Units at Tertiary Care Hospitals in the Western Province of Sri Lanka: A Postal Survey

Authors: Sunethra Jayathilake, Vathsala Jayasuriya-Illesinghe, Kerstin Samarasinghe, Himani Molligoda, Rasika Perera

Abstract:

In Sri Lanka, postnatal care in the state hospitals is provided by different professional categories: Midwifery trained registered nurses (MTRNs), Registered Nurses (RNs) who do not have midwifery training, doctors and midwives. Even though four professional categories provide postnatal care to mothers and newborn babies, they are not aware of their own tasks and responsibilities in postnatal care. Particularly MTRN’s role in the postnatal unit is unclear. The current study aimed to identify nurses’ (both MTRN and RNs) perception on MTRN’s tasks and responsibilities in postnatal care. This is a descriptive cross sectional study using postal survey. All nurses who were currently working in postnatal units at five selected tertiary care hospitals in the Western Province at that time were invited to participate in the study. Accordingly, the pre evaluated self-administered questionnaire was sent to 201 nurses (53 MTRNs and 148 RNs) in the study setting. The number of valid return questionnaire was 166; response rate was 83%. Respondents rated the responsibility of four professional categories: MTRN, RN, doctor and midwife whether they are 'primarily responsible', 'responsible in absence' and 'not responsible', for each of 15 postnatal (PN) tasks which were previously identified from focus group discussions with care providers during the first phase of the study. Data were analyzed using SPSS version 20; descriptive statistics were calculated. Out of the 15 PN tasks, 13 were identified as MTRNs’ primary responsibilities by 71%-93% of respondents. The respondents also considered six (6) tasks out of 15 as primary responsibility of both MTRN and RN, seven (7) tasks as primary responsibility of MTRN, RN and doctor and the remaining two (2) tasks were identified as the primary responsibility of MTRN, RN and midwife. All 15 PN tasks overlapped with other professional categories. Overlapping tasks may create role confusion leading to conflicts among professional categories which affect the quality of care they provide, eventually, threaten the safety of the client. It is recommended that an official job description for each care provider is needed to recognize their own professional boundaries for ensuring safe, quality care delivery in Sri Lanka.

Keywords: overlapping, postnatal, responsibilities, tasks

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3716 The Effect of PETTLEP Imagery on Equestrian Jumping Tasks

Authors: Nurwina Anuar, Aswad Anuar

Abstract:

Imagery is a popular mental technique used by athletes and coaches to improve learning and performance. It has been widely investigated and beneficial in the sports context. However, the imagery application in equestrian sport has been understudied. Thus, the effectiveness of imagery should encompass the application in the equestrian sport to ensure its application covert all sports. Unlike most sports (e.g., football, badminton, tennis, ski) which are both mental and physical are dependent solely upon human decision and response, equestrian sports involves the interaction of human-horse collaboration to success in the equestrian tasks. This study aims to investigate the effect of PETTLEP imagery on equestrian jumping tasks, motivation and imagery ability. It was hypothesized that the use of PETTLEP imagery intervention will significantly increase in the skill equestrian jumping tasks. It was also hypothesized that riders’ imagery ability and motivation will increase across phases. The participants were skilled riders with less to no imagery experience. A single-subject ABA design was employed. The study was occurred over five week’s period at Universiti Teknologi Malaysia Equestrian Park. Imagery ability was measured using the Sport Imagery Assessment Questionnaires (SIAQ), the motivational measured based on the Motivational imagery ability measure for Sport (MIAMS). The effectiveness of the PETTLEP imagery intervention on show jumping tasks were evaluated by the professional equine rider on the observational scale. Results demonstrated the improvement on all equestrian jumping tasks for the most participants from baseline to intervention. Result shows the improvement on imagery ability and participants’ motivations after the PETTLEP imagery intervention. Implication of the present study include underlining the impact of PETTLEP imagery on equestrian jumping tasks. The result extends the previous research on the effectiveness of PETTLEP imagery in the sports context that involves interaction and collaboration between human and horse.

Keywords: PETTLEP imagery, imagery ability, equestrian, equestrian jumping tasks

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3715 What Constitutes Pre-School Mathematics and How It Look Like in the Classroom?

Authors: Chako G. Chako

Abstract:

This study reports on an ongoing research that explores pre-school mathematics. Participants in the study includes three pre-school teachers and their pre-school learners from one school in Gaborone. The school was purposefully selected based on its performance in Botswana’s 2019 national examinations. Specifically, the study is interested on teachers’ explanations of mathematics concepts embedded in pre-school mathematics tasks. The interest on explanations was informed by the view that suggests that, the mathematics learners get to learn, resides in teachers’ explanations. Recently, Botswana’s basic education has integrated pre-school education into the mainstream public primary school education. This move is part of the government’s drive to elevate Botswana to a knowledge-based-economy. It is believed that provision of pre-school education to all Batswana children will contribute immensely towards a knowledge-based-economy. Since pre-school is now a new phenomenon in our education, there is limited research at this level of education in Botswana. In particular, there is limited knowledge about what and how the teaching is conducted in Pre-Schools in Botswana. Hence, the study seeks to gain insight into what constitutes mathematics in tasks that learners are given, and how concepts are made accessible to Pre-school learners. The research question of interest for this study is stated as: What is the nature Pre-school teachers’ explanations of mathematics concepts embedded in tasks given to learners. Casting some light into what and how pre-school mathematics tasks are enacted is critical for policy and Pre-school teacher professional development. The sociocultural perspective framed the research. Adler and Rhonda’s (2014) notion of exemplification and explanatory communication are used to analyze tasks given to learners and teachers’ explanations respectively.

Keywords: classroom, explanation, mathematics, pre-school, tasks

Procedia PDF Downloads 114
3714 The Effect of Information vs. Reasoning Gap Tasks on the Frequency of Conversational Strategies and Accuracy in Speaking among Iranian Intermediate EFL Learners

Authors: Hooriya Sadr Dadras, Shiva Seyed Erfani

Abstract:

Speaking skills merit meticulous attention both on the side of the learners and the teachers. In particular, accuracy is a critical component to guarantee the messages to be conveyed through conversation because a wrongful change may adversely alter the content and purpose of the talk. Different types of tasks have served teachers to meet numerous educational objectives. Besides, negotiation of meaning and the use of different strategies have been areas of concern in socio-cultural theories of SLA. Negotiation of meaning is among the conversational processes which have a crucial role in facilitating the understanding and expression of meaning in a given second language. Conversational strategies are used during interaction when there is a breakdown in communication that leads to the interlocutor attempting to remedy the gap through talk. Therefore, this study was an attempt to investigate if there was any significant difference between the effect of reasoning gap tasks and information gap tasks on the frequency of conversational strategies used in negotiation of meaning in classrooms on one hand, and on the accuracy in speaking of Iranian intermediate EFL learners on the other. After a pilot study to check the practicality of the treatments, at the outset of the main study, the Preliminary English Test was administered to ensure the homogeneity of 87 out of 107 participants who attended the intact classes of a 15 session term in one control and two experimental groups. Also, speaking sections of PET were used as pretest and posttest to examine their speaking accuracy. The tests were recorded and transcribed to estimate the percentage of the number of the clauses with no grammatical errors in the total produced clauses to measure the speaking accuracy. In all groups, the grammatical points of accuracy were instructed and the use of conversational strategies was practiced. Then, different kinds of reasoning gap tasks (matchmaking, deciding on the course of action, and working out a time table) and information gap tasks (restoring an incomplete chart, spot the differences, arranging sentences into stories, and guessing game) were manipulated in experimental groups during treatment sessions, and the students were required to practice conversational strategies when doing speaking tasks. The conversations throughout the terms were recorded and transcribed to count the frequency of the conversational strategies used in all groups. The results of statistical analysis demonstrated that applying both the reasoning gap tasks and information gap tasks significantly affected the frequency of conversational strategies through negotiation. In the face of the improvements, the reasoning gap tasks had a more significant impact on encouraging the negotiation of meaning and increasing the number of conversational frequencies every session. The findings also indicated both task types could help learners significantly improve their speaking accuracy. Here, applying the reasoning gap tasks was more effective than the information gap tasks in improving the level of learners’ speaking accuracy.

Keywords: accuracy in speaking, conversational strategies, information gap tasks, reasoning gap tasks

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3713 Alexa (Machine Learning) in Artificial Intelligence

Authors: Loulwah Bokhari, Jori Nazer, Hala Sultan

Abstract:

Nowadays, artificial intelligence (AI) is used as a foundation for many activities in modern computing applications at home, in vehicles, and in businesses. Many modern machines are built to carry out a specific activity or purpose. This is where the Amazon Alexa application comes in, as it is used as a virtual assistant. The purpose of this paper is to explore the use of Amazon Alexa among people and how it has improved and made simple daily tasks easier for many people. We gave our participants several questions regarding Amazon Alexa and if they had recently used or heard of it, as well as the different tasks it provides and whether it successfully satisfied their needs. Overall, we found that participants who have recently used Alexa have found it to be helpful in their daily tasks.

Keywords: artificial intelligence, Echo system, machine learning, feature for feature match

Procedia PDF Downloads 78
3712 On Developing a Core Guideline for English Language Training Programs in Business Settings

Authors: T. Ito, K. Kawaguchi, R. Ohta

Abstract:

The purpose of this study is to provide a guideline to assist globally-minded companies in developing task-based English-language programs for their employees. After conducting an online self-assessment questionnaire comprised of 45 job-related tasks, we analyzed responses received from 3,000 Japanese company employees and developed a checklist that considered three areas: (i) the percentage of those who need to accomplish English-language tasks in their workplace (need for English), (ii) a five-point self-assessment score (task performance level), and (iii) the impact of previous task experience on perceived performance (experience factor). The 45 tasks were graded according to five proficiency levels. Our results helped us to create a core guideline that may assist companies in two ways: first, in helping determine which tasks employees with a certain English proficiency should be able to satisfactorily carry out, and secondly, to quickly prioritize which business-related English skills they would need in future English language programs.

Keywords: business settings, can-do statements, English language training programs, self-assessment, task experience

Procedia PDF Downloads 216
3711 Dynamic Ad-hoc Topologies for Mobile Robot Navigation Based on Non-Uniform Grid Maps

Authors: Peter Sauer, Thomas Hinze, Petra Hofstedt

Abstract:

To avoid obstacles in the surrounding environment and to navigate to a given target belong to the most important tasks for mobile robots. According to these tasks different data structures are suitable. To avoid near obstacles, occupancy grid maps are an ideal representation of the surroundings. For less fine grained tasks, such as navigating from one room to another in an apartment, pure grid maps are inappropriate. Grid maps are very detailed, calculating paths to navigate between rooms based on grid maps would take too long. Instead, graph-based data structures, so-called topologies, turn out to be a proper choice for such tasks. In this paper we present two methods to dynamically create topologies from grid maps. Both methods are based on non-uniform grid maps. The topologies are generated on-the-fly and can easily be modified to represent changes in the environment. This allows a hybrid approach to control mobile robots, where, depending on the situation and the current task, either the grid map or the generated topology may be used.

Keywords: robot navigation, occupancy grids, topological maps, dynamic map creation

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3710 Self-Supervised Pretraining on Sequences of Functional Magnetic Resonance Imaging Data for Transfer Learning to Brain Decoding Tasks

Authors: Sean Paulsen, Michael Casey

Abstract:

In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

Procedia PDF Downloads 52