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A Literature Review on Technology-Based Problem-Posing Strategies in Academia 学术界基于技术的问题提出策略研究综述
Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399595
P. V. Elizabeth Vinitha, V. G. Renumol
Problem-posing (PP) is an act by a learner to gain knowledge by generating new problems or questions in a given scenario. Studies have proved that PP is an effective student-centered method for learning. Moreover, it helps students to understand complex concepts and improve their learning outcomes. Many researchers have tried to develop technology-based learning systems using PP strategy in various domains and technology tools are playing a major role in education, in this digital era. Hence, the main objectives of this study are: a) To identify the strategies used to implement problem-posing based on technology and b) To identify the advantages of technology-based PP strategies over conventional problem-posing methods. To achieve these objectives we have conducted a literature review on 67 papers. The study has identified collaborative mobile learning, com-puter-based group activities, gaming activities, web-ap-plication-based activities and tablet-PC based activities as technology-based PP strategies. It has also identified that there are limited researches on PP in domains such as STEM, Nursing, English, and Biochemistry. We found that technology-based PP strategies have various advantages. They help students to acquire knowledge, make an impressive change in their learning outcomes, improve students' motivation and responsibility by engaging them in the learning process, improve collaborative skills and lower their cognitive load.
问题提问(problem - posed,简称PP)是学习者在给定情境中通过提出新问题或疑问来获取知识的一种行为。研究证明,PP是一种有效的以学生为中心的学习方法。此外,它有助于学生理解复杂的概念,提高他们的学习成果。许多研究者已经尝试在各个领域使用PP策略开发基于技术的学习系统,技术工具在这个数字时代的教育中发挥着重要作用。因此,本研究的主要目标是:a)确定用于实施基于技术的问题提出的策略;b)确定基于技术的PP策略相对于传统问题提出方法的优势。为了达到这些目标,我们对67篇论文进行了文献综述。该研究将协作式移动学习、基于计算机的小组活动、游戏活动、基于web应用程序的活动和基于平板电脑的活动确定为基于技术的PP策略。研究还发现,在STEM、护理、英语和生物化学等领域,PP研究有限。我们发现,以技术为基础的PP策略具有多种优势。它们帮助学生获得知识,使他们的学习成果产生令人印象深刻的变化,通过让学生参与学习过程来提高他们的动机和责任感,提高他们的协作技能,降低他们的认知负荷。
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引用次数: 0
Real Time Electric Light Control using EOG Signals 使用EOG信号的实时电灯控制
Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399605
R. Anuradha, G. Rathi, A. GraceSelvarani, N. Gokul, M. S. Dhakshata
Aiding the disabled persons pose as a major challenge in the technology realm. A technology that would assist them to control the lights without the need to establish a physical touch to the switch would be highly beneficial. This paper describes the method to control the electrical lights in real time using electro-oculogram. The light ON OFF action was controlled by detecting the EOG signals which represents the blinking action and transferring the findings to a microcontroller.
帮助残疾人是技术领域的一项重大挑战。如果有一种技术可以帮助他们控制电灯,而不需要对开关进行物理触摸,那将是非常有益的。本文介绍了利用眼电图对电灯进行实时控制的方法。通过检测代表闪烁动作的EOG信号并将结果传输到微控制器来控制灯的ON - OFF动作。
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引用次数: 1
Assessment Methods and Interventions to Develop Computational Thinking — A Literature Review 发展计算思维的评估方法和干预措施-文献综述
Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399606
V.V. Vinu Varghese, V. G. Renumol
Computational Thinking (CT) allows us to solve complex problems by expressing it in a way that computers, humans, or both, can understand. CT is closely related to problem solving and critical thinking, which are actively used in STEM education. Research on CT has gained steady momentum recently, and many of the institutions around the world have adopted CT into their curriculum. This paper presents a literature review conducted to identify the interventions used to develop CT skills and the methods used to assess CT skills. The review explored various publications on CT and identified that curriculum-based interventions and workshops are the primary interventions used for introducing CT in the educational sector. During the analysis, we have also identified a handful of assessment tools used for measuring CT skills, but they are not standardized assessment tools. Hence, we plan to analyze the existing assessment methods and propose a new sophisticated tool for evaluating CT skills as our future work.
计算思维(computer Thinking, CT)允许我们用计算机、人类或两者都能理解的方式来解决复杂的问题。CT与解决问题和批判性思维密切相关,这在STEM教育中得到了积极的应用。近年来,计算机科学的研究取得了稳定的发展势头,世界上许多机构都将计算机科学纳入了他们的课程。本文介绍了一篇文献综述,旨在确定用于发展CT技能的干预措施以及用于评估CT技能的方法。本综述探讨了有关CT的各种出版物,并确定以课程为基础的干预措施和讲习班是在教育部门引入CT的主要干预措施。在分析过程中,我们还确定了一些用于测量CT技能的评估工具,但它们不是标准化的评估工具。因此,我们计划分析现有的评估方法,并提出一种新的复杂的评估CT技能的工具作为我们未来的工作。
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引用次数: 3
Graph Grammar for Parikh Word Representable Graphs Parikh词可表示图的图语法
Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399604
V. Jayakrishna, Lisa Mathew, Nobin Thomas, K. Subramanian, J. Mathew
Graph grammars are capable of modelling the generation of various families of graphs. Graph rewriting has basically two different approaches namely, node replacement and edge replacement rewriting. A variant of node replacement graph grammar called $nc-eNCE$ graph grammars was introduced recently. Recently, a special kind of graph, called Parikh word representable graph was introduced and its properties were studied. The problem of generation of graph structures using graph grammars has been considered in many studies. Here we generate the Parikh word representable graphs using $nc-eNCE$ graph grammars.
图语法能够对各种图族的生成进行建模。图重写基本上有两种不同的方法,即节点替换和边缘替换重写。最近引入了节点替换图语法的一种变体,称为$nc-eNCE$图语法。最近,引入了一类特殊的图——Parikh词可表示图,并对其性质进行了研究。利用图语法生成图结构的问题已经在许多研究中得到了考虑。这里我们使用$nc-eNCE$图语法生成Parikh词可表示的图。
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引用次数: 0
Future Predicting Intelligent Camera Security System 未来预测智能摄像头安全系统
Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399597
Merin Abraham, Nikita Suryawanshi, Nevin Joseph, Dhanashree Hadsul
The need for continuous human supervision, i.e. these systems are unable to perform certain functions without any operator monitoring the cctv video, is one of the major disadvantages of any camera-based monitoring system. An individual can hold his/her focus on the screen feed for a limited number of hours and not be distracted. Such poor monitoring could lead to a reduction in the effectiveness of the human operator's immediate action against a potential threat if detected on the screen. Therefore, the unique features of future prediction through the live video analysis method would have a huge effect on the surveillance system-based industries in order to address the limitations of the human attention span. The proposed system would be able to process the live stream from the cctv camera and generate output that will warn the operator of any possible danger that appears to occur or is occurring. For this method, a deep learning architectural approach is used with Convolutional Neural Networks. In this way, the surveillance camera system can detect an individual and identify and recognize those items carried by him or her on the basis of the level of danger. Similarly, the system can also identify and classify those acts that occur in the video feed into three distinct categories: natural, suspicious, malicious (based on the threat level) and send an alert to the respective human operator. Thus, the system will be able to help companies overcome security surveillance challenges and protect themselves from theft or any act of violence taking place in the area surrounding cctv.
需要持续的人工监控,即这些系统在没有操作员监控闭路电视视频的情况下无法执行某些功能,这是任何基于摄像机的监控系统的主要缺点之一。一个人可以把他/她的注意力集中在屏幕上几个小时,而不会分心。如果在屏幕上检测到潜在威胁,这种糟糕的监测可能会导致操作员立即采取行动的有效性降低。因此,通过实时视频分析方法预测未来的独特功能将对基于监控系统的行业产生巨大影响,以解决人类注意力持续时间的局限性。拟议的系统将能够处理来自闭路电视摄像机的实时流,并生成输出,警告操作员任何可能发生或正在发生的危险。对于这种方法,深度学习架构方法与卷积神经网络一起使用。通过这种方式,监控摄像系统可以检测到个人,并根据危险程度识别和识别他或她携带的物品。同样,系统还可以识别并将视频馈送中的行为分为三种不同的类别:自然、可疑、恶意(基于威胁级别),并向相应的人工操作员发送警报。因此,该系统将能够帮助公司克服安全监控方面的挑战,并保护自己免受盗窃或发生在cctv周围地区的任何暴力行为。
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引用次数: 1
Automated Question Answering Assistant 自动问答助手
Pub Date : 2021-02-11 DOI: 10.1109/icitiit51526.2021.9399601
Rutuja Kitukale, Nachiketh Pai, P. Nerkar, Archana Shirke, J. Jose
IT firms have a number of clients from various sectors. These vendors have many questions or queries which are to be answered manually. Also the amount of questions asked are huge in numbers approximately in the club of 500 to 600. This includes reading the document thoroughly and extracting all the related information regarding the question and then representing the data in appropriate format required. Answering all such questions manually in a limited period of time is quite a tedious task. This leads to more time consumption and increases the human labour behind it. The project aims at developing an automated system which would create a deep learning model that will input the questions present in any format and answer them automatically with the help of the algorithm and give the output in the required format, thus simplifying the work of searching the answers in a given extract and finding the least error prone answer to the question thus increasing the accuracy. This will also reduce time required behind studying any document and framing the answers from them. This system will be able to answer all types of questions. The system can be used for generating answer keys for online exams. The system will encourage the research that returns answers directly instead of keyword extraction from the documents with ample number of queries. Even it can be used for open domain searching of information over the internet.
IT公司有许多来自不同行业的客户。这些供应商有许多问题或查询需要手动回答。此外,问题的数量也很大,大约在500到600个俱乐部。这包括彻底阅读文档并提取有关问题的所有相关信息,然后以所需的适当格式表示数据。在有限的时间内手动回答所有这些问题是一项相当乏味的任务。这导致了更多的时间消耗,并增加了背后的人力劳动。该项目旨在开发一个自动化系统,该系统将创建一个深度学习模型,该模型将以任何格式输入问题,并在算法的帮助下自动回答问题,并以所需格式输出,从而简化在给定摘录中搜索答案的工作,并找到最不容易出错的问题答案,从而提高准确性。这也将减少研究任何文件并从中构建答案所需的时间。这个系统将能够回答所有类型的问题。该系统可用于生成在线考试的答案键。该系统将鼓励直接返回答案的研究,而不是从大量查询的文档中提取关键字。它甚至可以用于互联网上信息的开放领域搜索。
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引用次数: 0
Application of Artificial Intelligence for Maintenance Modelling of Critical Machines in Solid Tire Manufacturing 人工智能在实心轮胎制造关键机械维修建模中的应用
Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399600
R. Jayasuriya, P. A. G. M. Amarasinghe, S. Abeygunawardane
Machine maintenance is a challenging task in the manufacturing industry. The reliability and maintenance scheduling of continuously running machines are essential for the performance of manufacturing plants. In this paper, an artificial intelligence-based machine maintenance management system is proposed for a tire manufacturing plant. The proposed system consists of two main subsystems: dynamically updating maintenance scheduler and machine troubleshooter. The maintenance schedular is implemented using an Artificial Neural Network (ANN) whereas the machine troubleshooter is based on an expert system. The ANN-based maintenance schedular provides the optimum time frame to plan the preventive maintenance of critical machines based on the condition monitoring data and production data. The ANN is validated using validation performance charts and regression state charts obtained from the Matlab runtime environment. It is found that the R-squared value of the ANN is 0.998. On the other hand, a rule-based inference system is used in the machine troubleshooter. The expert system is validated by evaluating the maturity of the knowledge base. The percentage maturity of the expert system is reached to a level of 90% within 3 months.
在制造业中,机器维护是一项具有挑战性的任务。连续运行机器的可靠性和维护计划对制造工厂的性能至关重要。针对某轮胎制造厂,提出了一种基于人工智能的机器维修管理系统。该系统由两个主要子系统组成:动态更新维护调度和机器故障排除。维修计划使用人工神经网络(ANN)实现,而机器故障诊断则基于专家系统。基于人工神经网络的维修计划提供了基于状态监测数据和生产数据的关键机器预防性维修计划的最佳时间框架。使用从Matlab运行时环境中获得的验证性能图和回归状态图对人工神经网络进行验证。结果表明,人工神经网络的r平方值为0.998。另一方面,将基于规则的推理系统应用到机器故障诊断中。通过知识库的成熟度对专家系统进行验证。专家系统在3个月内达到90%的成熟度水平。
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引用次数: 0
Pedestrian Counting Using Yolo V3 使用Yolo V3进行行人计数
Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399607
Aiswarya Menon, Bini Omman, Asha S
Object detection is the process of determining the presence, location, and type or class of at least one object using a bounding box. The person detection process produces a bounding box and allot a class label as a person based on YOLO v3. In YOLO v3 the features are learned, divides the image cells and each cell says a bounding box and entity classification directly. There could be more than one bounding box per person, but the system makes use of non-maximum suppression to reduce the number of bounding boxes to one per person. Finally, the number of persons in the image and video are calculated using the count of the bounding boxes. The dataset used for static pedestrian detection is the INRIAdataset and ShanghaiTech dataset. Yolo_Mark is used for marking bounding boxes of persons and gets its annotation files using 243 images from the INRIA dataset. Darknet is used as the framework for implementing YOLOv3. From INRIA Dataset 120 images are used for testing purposes. Testing on the INRIA dataset resulted in an accuracy of 96.1%. From the Shanghai tech-B, dataset 56 images are used for testing. Testing resulted in an accuracy of 87.3%.
对象检测是使用边界框确定至少一个对象的存在、位置和类型或类别的过程。人员检测过程生成一个边界框,并根据YOLO v3为人员分配一个类标签。在YOLO v3中,特征被学习,分割图像单元格,每个单元格直接表示一个边界框和实体分类。每个人可能有多个边界框,但系统使用非最大抑制将边界框的数量减少到每个人一个。最后,利用边界框的计数计算图像和视频中的人数。静态行人检测使用的数据集是INRIAdataset和ShanghaiTech数据集。Yolo_Mark用于标记人的边界框,并使用来自INRIA数据集的243幅图像获取其注释文件。暗网被用作实现YOLOv3的框架。来自INRIA数据集的120幅图像用于测试目的。在INRIA数据集上进行测试,准确率达到96.1%。来自上海tech-B的数据集56图像用于测试。测试结果的准确率为87.3%。
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引用次数: 5
Improved RSSI based Vehicle Localization using Base Station 改进的RSSI基于基站的车辆定位
Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399596
Debajyoti Biswas, S. Barai, B. Sau
The physical position of the vehicles is vital information for the tracking operation. The vehicles localization have several benefits and support for safety, comfort, and reliability in future transportation systems. Thus the vehicular localization has investigated, where the base station (BS) will track the target vehicles. This paper mainly addresses a new localization scenario on distributing the coverage area based on the received signal strength indicator (RSSI). The RSSI measured in regular operation and consume minimum energy. However, wireless RSSI suffers from various interference in dynamic environments. For solving these issues, several methods have been proposed in the literature, including the signal intensity attenuation model (SIAM). This paper incorporates the fact that the motion of vehicles satisfies environmental constraints to improve the accuracy of RSSI-based localization by a new model, namely the gaussian signal attenuation model (GSAM) using most likely RSSIs. Numerical results demonstrate that the proposed method considerably outperforms the existing methods in terms of dynamic positioning accuracy.
车辆的物理位置是跟踪操作的重要信息。车辆的国产化对未来交通系统的安全性、舒适性和可靠性有许多好处和支持。这样就研究了车辆定位问题,基站(BS)将跟踪目标车辆。本文主要研究一种基于接收信号强度指标(RSSI)分配覆盖区域的定位新方案。在正常运行时测量的RSSI,能耗最小。然而,无线RSSI在动态环境中会受到各种干扰。为了解决这些问题,文献中提出了几种方法,包括信号强度衰减模型(SIAM)。本文结合车辆运动满足环境约束的事实,提出了一种基于最可能rssi的高斯信号衰减模型(GSAM),提高了基于rssi的定位精度。数值结果表明,该方法在动态定位精度上明显优于现有方法。
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引用次数: 5
Performance Investigation of Capacitive Wireless Charging Topologies for Electric Vehicles 电动汽车电容式无线充电拓扑性能研究
Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399608
S. Kodeeswaran, M. Nandhini Gayathri
This paper investigates the performance of wireless charging topologies in a Capacitive Power Transfer system (CPT). CPT technology is one of the best Electric Vehicle (EV) wireless charging method, in which electric fields between metal plates used to transfer. To realize high power and long-distance power transfer for Electric Vehicle, double-sided LC, LCL and LCLC compensation circuits were used in this research work. By analyzing and comparing the performance and efficiency of these three topologies a one suitable topology is identified for the compensation circuit to use in MATLAB Simulink. The compensation circuit provides resonances with the coupling capacitance, and increase the voltage level on metal plates.
研究了电容式功率传输系统(CPT)无线充电拓扑结构的性能。CPT技术是利用金属板之间的电场进行转移的一种最佳的电动汽车无线充电方法。为了实现电动汽车大功率、远距离的电力传输,本研究采用了双面LC、LCL和LCLC补偿电路。通过分析和比较这三种拓扑的性能和效率,确定了一种适用于MATLAB Simulink中补偿电路的拓扑结构。补偿电路与耦合电容产生共振,并提高金属板上的电压水平。
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引用次数: 8
期刊
2021 International Conference on Innovative Trends in Information Technology (ICITIIT)
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