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QUADROTORS IN THE PRESENT ERA: A REVIEW 四旋翼飞行器在当今时代:回顾
Pub Date : 2021-02-28 DOI: 10.17762/ITII.V9I1.116
Ritika Thusoo, Sheilza Jain, S. Bangia
The advancement in the field of aerial robotics and control engineering has created many opportunities for the utilization of Unmanned Aerial Vehicles (UAVs).  Applications of UAVs from precision agriculture to delivering medicines and products at our doorsteps cannot be ignored. Quadrotors are the widely studied as sub-category of the rotor-type UAVs. Their ability to hover, vertical take-off and landing along with their small size and simple design make them suitable for many real-life applications like medicine delivery in containment zones struck with COVID-19. But under actuation caused due to four rotors to control six inputs creates instability in their flight. In this paper, Quadrotors and various Quadrotor applications are discussed. The various modeling and control techniques are discussed. Controlling techniques like LQR, LQG, PID and robust control is implemented for position, attitude and altitude control. Results for Proportional Integral and Derivative (PID) and Model Reference Adaptive Control (MRAC) of model generated using force-moment mathematical model are analyzed and compared using MATLAB Simulink. These control techniques are implemented for position, attitude and altitude control. In this paper, it has been concluded that MRAC performs better as compared to PID controller for position, attitude and Altitude control of Quadrotor.
航空机器人和控制工程领域的进步为无人驾驶飞行器的应用创造了许多机会。无人机从精准农业到在我们家门口运送药品和产品的应用不容忽视。作为旋翼型无人机的一个分支,四旋翼无人机得到了广泛的研究。它们能够悬停、垂直起飞和降落,体积小、设计简单,这使它们适用于许多现实生活中的应用,比如在受COVID-19袭击的遏制区运送药物。但在驱动下由于四个旋翼控制六个输入导致飞行不稳定。本文讨论了四旋翼飞行器和各种四旋翼飞行器的应用。讨论了各种建模和控制技术。采用LQR、LQG、PID和鲁棒控制技术对位置、姿态和高度进行控制。利用MATLAB Simulink对利用力-矩数学模型生成的模型进行比例积分与导数(PID)和模型参考自适应控制(MRAC)的结果进行了分析比较。这些控制技术用于位置、姿态和高度控制。本文的研究结果表明,与PID控制器相比,MRAC在四旋翼飞行器的位置、姿态和高度控制方面具有更好的性能。
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引用次数: 3
FLOWER POLLINATION ALGORITHM FOR MULTI LEVEL LOT SIZING OPTIMIZATION 多层次批量优化的花卉授粉算法
Pub Date : 2021-02-28 DOI: 10.17762/ITII.V9I1.110
V. Sahithi, M. S. Rao, C. Rao
In this competitive and constantly changing world, meeting the customer requirements within less time by providing less cost is extremely tricky task. This is only possible by optimizing all the different parameters in its life cycle. Here Optimizing the inventory plays a major role.Maintaining the exact amount of inventory, at proper place, in appropriate level is a challenging task for production managers. When we work on Multi level environments this problem becomes even more complex.So, to optimize this kind of problems we applied binary form of Flower Pollination algorithm to solve this complex problem. we solved different inventory lot sizing problems with this FP algorithm and compared the results with genetic algorithm and other algorithms. In all the scenarios our simulation results shown that FP algorithm is better than other algorithms.                       
在这个竞争激烈且不断变化的世界中,以更低的成本在更短的时间内满足客户需求是一项极其棘手的任务。这只能通过优化其生命周期中的所有不同参数来实现。在这里,优化库存起着重要作用。对生产经理来说,在适当的位置、适当的水平上保持准确的库存数量是一项具有挑战性的任务。当我们在多层环境中工作时,这个问题变得更加复杂。因此,为了优化这类问题,我们采用二进制形式的花授粉算法来解决这类复杂问题。用该算法求解了不同的库存批量问题,并将求解结果与遗传算法和其他算法进行了比较。在所有场景下,我们的仿真结果表明,FP算法优于其他算法。
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引用次数: 0
HEART DISEASE PREDICTION USING MACHINE LEARNING TECHNIQUES 利用机器学习技术预测心脏病
Pub Date : 2021-02-28 DOI: 10.17762/ITII.V9I1.120
K. Yadav, Anurag Sharma, Abhishek Badholia
In few previous decades around the globe the reason for extensive number of deaths is cardiovascular disease or Heart related disease and not only in India but all around the world has emerged as a life-threatening disease. So for the correct treatment and in time diagnosis for this disease the need of feasible, accurate and reliable system is encountered. For automation of analysis of the sophisticated and huge data, to the various medical dataset of Machine Learning techniques and methods are applied. In recent times many researchers for the health care industry assistance with the help of various techniques of Machine Learning, this in turn helps the professionals in the procedure of the heart related disease diagnosis. A survey of various models that accepts such techniques and algorithms and their performance analysis is presented in this paper. Within the researchers few very fashionable Model supported supervised learning algorithms are Random forest (RF), Decision Tree (DT), Naïve Bayes, ensemble models, K-Nearest Neighbour (KNN) and Support Vector Machine (SVM).  
在过去的几十年里,全球范围内大量死亡的原因是心血管疾病或心脏相关疾病,不仅在印度,而且在全世界都已成为一种危及生命的疾病。因此,要对本病进行正确的治疗和及时的诊断,就需要有一个可行、准确、可靠的系统。为了对复杂而庞大的数据进行自动化分析,对各种医疗数据集都应用了机器学习技术和方法。近年来,许多医疗保健行业的研究人员借助各种机器学习技术提供帮助,这反过来又帮助了心脏相关疾病诊断过程中的专业人员。本文综述了采用这种技术和算法的各种模型,并对其性能进行了分析。在研究人员中,一些非常流行的模型支持监督学习算法是随机森林(RF),决策树(DT), Naïve贝叶斯,集成模型,k -近邻(KNN)和支持向量机(SVM)。
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引用次数: 77
PREDICTIVE MODELLING AND ANALYTICS FOR DIABETES USING A MACHINE LEARNING APPROACH 使用机器学习方法对糖尿病进行预测建模和分析
Pub Date : 2021-02-28 DOI: 10.17762/ITII.V9I1.121
P. Mishra, D. Sharma, Abhishek Badholia
Adverse effects can be seen in the entire body due to the major disorders known as Diabetes. The risk of dangers like diabetic nephropathy, cardiac stroke and other disorders can increase severally because of the undiagnosed diabetes. Around the globe the people are suffering from this disease. For a healthy life early detection of this disease is very curtail. As the causes of the diabetes is increasing rapidly this disease might turn up as a reason for worldwide concern. Increasing the chances for a more accurate predictions and form experiences automatic learning by computational method may be provided by Machine Learning (ML). With the help of R data manipulation tool for trends development and with risk factor patterns detection in Pima Indian diabetes technique of machine learning is been used in the current researches. With the use of R data manipulation tool analysis and development five different predictive models is done for the categorization of patients into diabetic and non- diabetic.  supervised machine learning algorithms namely multifactor dimensionality reduction (MDR), k-nearest neighbor (k-NN), artificial neural network (ANN) radial basis function (RBF) kernel support vector machine and linear kernel support vector machine (SVM-linear) are used for this purpose.
由于被称为糖尿病的主要疾病,整个身体都可以看到不良反应。糖尿病肾病、心脏病和其他疾病的风险会因为未确诊的糖尿病而增加。世界各地的人们都在遭受这种疾病的折磨。为了健康的生活,早期发现这种疾病是非常困难的。由于糖尿病的病因正在迅速增加,这种疾病可能会引起全世界的关注。机器学习(ML)可以通过计算方法增加更准确的预测和形式经验自动学习的机会。借助R数据处理工具进行趋势发展,结合皮马印第安人糖尿病的危险因素模式检测,采用机器学习技术进行研究。利用R数据处理工具分析和开发了五种不同的预测模型,将患者分为糖尿病和非糖尿病。有监督的机器学习算法,即多因素降维(MDR)、k近邻(k-NN)、人工神经网络(ANN)径向基函数(RBF)核支持向量机和线性核支持向量机(SVM-linear)用于此目的。
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引用次数: 12
COVID-19 PANDEMIC AND HUMAN RESOURCE DEVELOPMENT PRACTICE IN NEPALESE COMMERCIAL BANKS COVID-19大流行与尼泊尔商业银行人力资源开发实践
Pub Date : 2021-02-18 DOI: 10.17762/ITII.V9I2.294
M. K. Chaudhary, Ajay Prasad Dhakal
A leadership style and its practice can be considered as the foundation of overall nations development. So, this paper majorly aims to explore the leadership style among academic leaders in his/her education sectors in overall. For this, a semi- structured interview questionnaire was applied to investigate and obtained opinion from the respondents. The results of this study exposed that extraordinary collaboration, responsibility, correspondence, and nurturing and strengthening are the major things that leads to the efficient academic operations. Thus, the paper concludes that academics of Nepal were favor of five leadership methods besides the task-oriented authority in Nepalese context. Finally, the finding of this research would anticipate a more extensive sense of direction towards successful academic’s sectors operations.  
一种领导风格及其实践可以被认为是国家整体发展的基础。因此,本文的主要目的是在整体上探讨其所在教育部门的学术领导者的领导风格。为此,我们采用半结构式访谈问卷进行调查,并征询受访者的意见。研究结果表明,卓越的合作、责任、沟通、培育和加强是导致高效学术运作的主要因素。因此,本文得出的结论是,尼泊尔学者赞成五种领导方法除了任务导向的权威在尼泊尔的语境。最后,这项研究的发现将为成功的学术部门运作提供更广泛的方向感。
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引用次数: 0
COVID-19 PANDEMIC AND HUMAN RESOURCE DEVELOPMENT PRACTICE IN NEPALESE COMMERCIAL BANKS COVID-19大流行与尼泊尔商业银行人力资源开发实践
Pub Date : 2021-02-18 DOI: 10.17762/itii.v9i1.88
Manoj Kumar Chaudhary, Ajay Prasad Dhakal
A leadership style and its practice can be considered as the foundation of overall nations development. So, this paper majorly aims to explore the leadership style among academic leaders in his/her education sectors in overall. For this, a semi-structured interview questionnaire was applied to investigate and obtained opinion from the respondents.  The results of this study exposed that extraordinary collaboration, responsibility, correspondence, and nurturing and strengthening   are the major things that leads to the efficient academic operations. Thus, the paper concludes that    academics of Nepal were favor of five leadership methods besides the task-oriented authority in Nepalese context. Finally, the finding of this research would anticipate a more extensive sense of direction towards successful academic’s sectors operations.  
一种领导风格及其实践可以被认为是国家整体发展的基础。因此,本文的主要目的是在整体上探讨其所在教育部门的学术领导者的领导风格。为此,采用半结构式访谈问卷进行调查,获取受访者的意见。研究结果表明,卓越的合作、责任、沟通、培育和加强是导致高效学术运作的主要因素。因此,本文得出的结论是,尼泊尔学者赞成五种领导方法除了任务导向的权威在尼泊尔的语境。最后,这项研究的发现将为成功的学术部门运作提供更广泛的方向感。
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引用次数: 0
Methods and Technologies for Protecting Pharmaceutical Products in Polymer Packaging from Counterfeiting 高分子包装药品防伪的方法与技术
Pub Date : 2021-01-01 DOI: 10.17762/itii.v7i3.72
Chistyakova T. B, Makaruk R. V, Sadykov I. A, Kohlert C
This article considers the problem of protecting pharmaceutical products with polymer packaging from counterfeiting. This issue has grown vital in almost the entire world, as the significant harm can come not only to the producer, but the legitimate producer, but the consumers as well. Due to this, the issue of protecting these products against forgery, and creating and improving existing approaches to anti-forgery protection, becomes a crucial one. The authors suggest methods and technologies for protecting pharmaceutical products’ polymer packaging based on modern ideas from IT and manufacturing such as image recognition, client-server software architecture, mobile apps, digital signatures, luminophores, and PVC film. Testing the authors’ approach showed the effectiveness of the presented methods and technologies. The results should be of interest to companies producing pharmaceuticals.
本文就聚合物包装药品防伪问题进行了探讨。这个问题几乎在整个世界都变得至关重要,因为严重的伤害不仅会对生产者,而且会对合法生产者,也会对消费者造成伤害。因此,保护这些产品免受伪造,创造和改进现有的防伪保护方法,成为一个至关重要的问题。作者根据IT和制造业的现代理念,提出了保护药品聚合物包装的方法和技术,如图像识别、客户端-服务器软件架构、移动应用程序、数字签名、发光团和PVC膜。对作者方法的测试表明了所提出的方法和技术的有效性。研究结果应该会引起制药公司的兴趣。
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引用次数: 0
Order Preserving Stream Processing in Fog Computing Architectures 雾计算体系结构中的保序流处理
Pub Date : 2021-01-01 DOI: 10.17762/ITII.V7I1.63
K. Vidyasankar
A Fog Computing architecture consists of edge nodes that generate and possibly pre-process (sensor) data, fog nodes that do some processing quickly and do any actuations that may be needed, and cloud nodes that may perform further detailed analysis for long-term and archival purposes. Processing of a batch of input data is distributed into sub-computations which are executed at the different nodes of the architecture. In many applications, the computations are expected to preserve the order in which the batches arrive at the sources. In this paper, we discuss mechanisms for performing the computations at a node in correct order, by storing some batches temporarily and/or dropping some batches. The former option causes a delay in processing and the latter option affects Quality of Service (QoS). We bring out the trade-offs between processing delay and storage capabilities of the nodes, and also between QoS and the storage capabilities.
雾计算架构由生成和预处理(传感器)数据的边缘节点、快速处理和执行可能需要的任何驱动的雾节点和可能执行长期和存档目的的进一步详细分析的云节点组成。一批输入数据的处理被分配到子计算中,这些子计算在体系结构的不同节点上执行。在许多应用程序中,期望计算保持批到达源的顺序。在本文中,我们讨论了在一个节点上以正确的顺序执行计算的机制,通过临时存储一些批次和/或删除一些批次。前者会导致处理延迟,后者会影响服务质量(QoS)。我们提出了处理延迟和节点存储能力之间的权衡,以及QoS和存储能力之间的权衡。
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引用次数: 0
Predictive Analysis using Convolution Network on Sentiment Analysis of Text Classification using Machine Learning 基于卷积网络的预测分析在机器学习文本分类情感分析中的应用
Pub Date : 2021-01-01 DOI: 10.17762/itii.v9i2.349
Vanitha kakollu, Et. al.
Today we have large amounts of textual data to be processed and the procedure involved in classifying text is called natural language processing. The basic goal is to identify whether the text is positive or negative. This process is also called as opinion mining. In this paper, we consider three different data sets and perform sentiment analysis to find the test accuracy. We have three different cases- 1. If the text contains more positive data than negative data then the overall result leans towards positive. 2. If the text contains more negative data than positive data then the overall result leans towards negative. 3. In the final case the number or positive and negative data is nearly equal then we have a neutral output. For sentiment analysis we have several steps like term extraction, feature selection, sentiment classification etc. In this paper the key point of focus is on sentiment analysis by comparing the machine learning approach and lexicon-based approach and their respective accuracy loss graphs.
今天,我们有大量的文本数据需要处理,而对文本进行分类的过程被称为自然语言处理。基本目标是确定文本是积极的还是消极的。这个过程也被称为意见挖掘。在本文中,我们考虑了三种不同的数据集,并进行情感分析来寻找测试的准确性。我们有三种不同的情况- 1。如果文本包含的正面数据多于负面数据,那么整体结果就倾向于正面。2. 如果文本包含的负面数据多于正面数据,则整体结果倾向于负面。3.在最后一种情况下,正负数据的数量几乎相等,那么我们有一个中性输出。对于情感分析,我们有几个步骤,如术语提取,特征选择,情感分类等。本文的重点是通过比较机器学习方法和基于词典的方法以及它们各自的准确性损失图来进行情感分析。
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引用次数: 0
Blockchain and Technologies Matching with the Case of Study of Vegetables Production 区块链与蔬菜生产配套技术研究
Pub Date : 2020-09-03 DOI: 10.36227/techrxiv.12911321
A. Massaro, Vincenzo Maritati, Nicola Savino, A. Galiano, Ugo Picciotti
The proposed work describes a new approach based on supply chain traceability by blockchain (BC). The basic BC network has been designed and applied for vegetables process monitoring and tracing. The paper proposes some results of an industry research project by describing the whole scenario, the architectures implementing BC, the sequence diagram principle, and the prototype network embedding blocks and transactions. The discussion is also addressed on the possibility to combine different technique such as artificial intelligence, and image processing to improve pre-cut vegetable quality. The paper proposed preliminary results proves that the adopted technologies and the methodologies found in the literature are suitable for the sanitation process certification and for quality traceability. The mentioned approaches are useful to apply the suggested frameworks for other supply chains.
提出的工作描述了一种基于区块链(BC)的供应链可追溯性的新方法。设计了基本BC网络,并将其应用于蔬菜生产过程监控与跟踪。本文通过描述整个场景、实现BC的体系结构、序列图原理以及嵌入块和事务的原型网络,给出了一个行业研究项目的一些成果。本文还讨论了结合人工智能和图像处理等不同技术来提高预切蔬菜质量的可能性。本文提出的初步结果证明,文献中所采用的技术和方法适用于卫生过程认证和质量追溯。上述方法有助于将建议的框架应用于其他供应链。
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引用次数: 2
期刊
Information Technology in Industry
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