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Human-computer interaction-based robotic design and development and control system testing - Prototyping and implementation testing study of a robotic hand

Human-computer interaction-based robotic design and developm...

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2022 ieee asia-pacific conference on Image Processing, Electronics and computers, IPEC 2022

作者： Cai, Jiayi Cai, Jialiang Macau University of Science and Technology Faculty of Humanities and Arts China Macau University of Science and Technology Macao Institute of Materials Science and Engineering China

ISBN: (纸本)9781665409025

One of the most challenging issues in the development of existing robotic hand design and development based on existing policies and in everyday people's needs for interactive technologies that can assist patients who have lost hand manipulation due to neurological or stroke induced. This paper focuses on robotic hand designs aimed at assisting post-stroke patients with enhanced human-computer interaction, including four innovative research direction areas. a) Aesthetically, the four-piece human-computer interaction-based robotic hand design (i.e., internal mechanics, five elastic bands, electrodes, and soft skin-friendly material) looks more like sports equipment than a wearable machine. b) Inspired by human palm design engineering, the The human-computer assisted manipulator is an innovative form of mixing soft and hard components and materials, constructed from layers closest to the body made of soft, stretchable fabrics (i.e., neoprene and fly stitch fabric). 3D printed flexible TPU components, which use BOA dials to increase or decrease finger tension. c) For added strength, the product is worn on the palm of the hand, and then tightening the wrist strap prevents unwanted movement This is an innovative patent and is integrated into the glove. This is innovative and patented and the BOA dial integrated in the glove is attached to five elastic bands, one for each finger, which are secured in place by a channel placed on the TPU piece. This makes it lighter in weight. d) Intelligent. By being equipped with sensors, it can be intelligently sensed internally to properly release tension with promoting blood circulation in the wearer's hand, they push the BOA dial in and rotate it to increase tension, and to release tension, the user simply pulls the BOA dial upward. This will help the muscles relax and restore normal fluid movement. The data can be viewed in the accompanying app. After researching and investigating the existing human-machine interaction based robotic

关键词： Robotic arms

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Retail Analytics to anticipate Covid-19 effects Using Big data Technologies

Retail Analytics to anticipate Covid-19 effects Using Big Da...

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8th ieee asia-pacific conference on computer science and data engineering (ieee csde)

作者： Sharma, Jessica Sharma, Deepikesh Sharma, Krishneel Univ South Pacific Sch Informat Technol Engn Math & Phys Suva Fiji

ISBN: (纸本)9781665495523

Retail analytics helps a company gain a deeper understanding of customer demand, making shopping more relevant, personalized, and convenient and boosting sales using optimal pricing. This paper aims to demonstrate retail analytics through a prototype that uses big data technologies. Using the big data technologies, the raw data is stored, analyzed and visualized to get valuable decision-making insights. The project objective is to help companies get retail analytics from which they can make decisions to anticipate the Covid-19 effects. The design for the system includes Hadoop Distributed File System (HDFS), Apache Pig, Apache Hive, SparkSQL, Spark MLLib, and Apache Zeppelin. The prototype uses a dataset that contains information for the transactions in the United Kingdom. Therefore it does not relate to covid-19 retail data but helps answer relevant questions. The dataset is used to investigate revenue aggregate by the country for the top 5 countries, daily sales activity, hourly sales activity, basket size distribution, top 20 Items sold by frequency, and market basket analysis. This paper can be used to produce a production possibility curve, reduce shortage, avoid surplus, illustrate demand and supply curves, and detect current economic conditions. All these would help the decision-makers to develop strategies to help them anticipate the impacts of Covid-19.

关键词： HDFS Apache Pig Apache Hive SparkSQL Spark MLLib Apache Zeppelin Apache Sqoop

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Enhancing Cluster Quality of Numerical datasets with Domain Ontology

Enhancing Cluster Quality of Numerical Datasets with Domain ...

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Sudath Rohitha Heiyanthuduwage Md Anisur Rahman Md Zahidul Islam School of Computing Mathematics and Engineering Charles Sturt University Australia

Ontology-based clustering has gained attention in recent years due to the potential benefits of ontology. Current ontology-based clustering approaches have mainly been applied to reduce the dimensionality of attributes in text document clustering. Reduction in dimensionality of attributes using ontology helps to produce high quality clusters for a dataset. However, ontology-based approaches in clustering numerical datasets have not been gained enough attention. Moreover, some literature mentions that ontology-based clustering can produce either high quality or low-quality clusters from a dataset. Therefore, in this paper we present a clustering approach that is based on domain ontology to reduce the dimensionality of attributes in a numerical dataset using domain ontology and to produce high quality clusters. For every dataset, we produce three datasets using domain ontology. We then cluster these datasets using a genetic algorithm-based clustering technique called GenClust++. The clusters of each dataset are evaluated in terms of Sum of Squared-Error (SSE). We use six numerical datasets to evaluate the performance of our ontology-based approach. The experimental results of our approach indicate that cluster quality gradually improves from lower to the higher levels of a domain ontology.

关键词： computer science Clustering algorithms Ontologies data engineering data mining Genetic algorithms

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Implementation of an Automated Result Management System in a Developing Country

Implementation of an Automated Result Management System in a...

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Sonam Shivani Nair Neeraj Anand Sharma Department of Computer Science and Mathematics School of Science and Technology The University of Fiji Lautoka Fiji

Errors and omissions in the manual process of compiling student results in secondary schools in pacific Countries were examined in this research. To do that, preliminary research on the existing manual record-keeping system in Fiji was examined in a few chosen secondary schools. A new software application was designed to automate the processing of such results. This solved the issues with manual result processing. C# programming language as well as SQL-Server were used to create a software package. The system's anticipated outcomes demonstrate that educators are not required to record student tests, examinations, and calculation results because the system takes care of almost everything, relieving teachers of the stress of having to prepare students' results. Similarly, it is less expensive to print individual student results on A4-sized paper or imprinted cardboard material that resembles a certificate and has a more attractive appearance than it would be to create result booklets. By reducing the time and energy needed for result preparation, this program will reduce the stress associated with the teacher's work and free up a lot of time for teaching as well as other instructional concerns. The record-keeping and evaluation process capabilities of such a new system can be adjusted to fit the needs of both higher secondary schools whether private or public.

关键词： computer languages Visualization Structured Query Language Software packages Education Manuals C# languages

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IoT Cybersecurity: On the Use of Machine Learning Approaches for Unbalanced datasets

IoT Cybersecurity: On the Use of Machine Learning Approaches...

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8th ieee asia-pacific conference on computer science and data engineering (ieee csde)

作者： Azad, Salahuddin Naqvi, Syeda Salma Sabrina, Fariza Sohail, Shaleeza Thakur, Sweta Cent Queensland Univ Melbourne Vic Australia Kings Own Inst Sydney NSW Australia Cent Queensland Univ Sydney NSW Australia Univ Newcastle Sydney NSW Australia

ISBN: (纸本)9781665495523

Machine learning can effectively be used to detect cyberattacks in IoT networks by learning patterns from previous attack datasets. Unfortunately, datasets used for training machine learning models to detect cyberattacks are almost always unbalanced. As training methods usually try to minimise the loss function by correctly classifying the instances of the majority class, the minority class instances are more likely to be misclassified. This paper aims to develop an insight into the effectiveness of two different approaches for handling unbalanced datasets - weighted loss function, and synthetic minority oversampling technique (SMOTE) in enhancing the capacity of two machine learning algorithms - artificial neural network (ANN) and light gradient boosting model (LGBM) to correctly classify minority class instances. The results suggest that both SMOTE and weighted loss function enhance the recall rate for minority classes significantly, however, it comes at the cost of slightly reduced precision. Moreover, it is found that LGBM, being an ensemble classifier, has an inherent capacity of learning from unbalanced data and hence, outperforms ANN in detecting minority class instances.

关键词： artificial neural network gradient boosting unbalanced data oversampling weighted loss function cyberattack detection

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A fault diagnosis method based on data feature reconstruction and deep transfer learning

A fault diagnosis method based on data feature reconstructio...

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2022 ieee asia-pacific conference on Image Processing, Electronics and computers, IPEC 2022

作者： Wang, Zongyao Shangguan, Wei Peng, Cong Cai, Baigen School of Electronic and Information Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Rail Traffic Control Beijing China Beijing Engineering Research Center of Emc and Gnss Technology for Rail Transportation Beijing China

ISBN: (纸本)9781665409025

The ability to quickly and accurately diagnose the fault type of equipment is the key to ensure its safe and efficient operation. In this paper, a fault diagnosis method based on data feature reconstruction and deep transfer learning is proposed, and the feasibility of the proposed method is verified by using bearings as the experimental object. Firstly, the original bearing vibration signal is converted into a two-dimensional scalogram using wavelet transform;secondly, GoogLeNet is pre-trained using Image Net data, the network structure is fine-tuned using transfer learning, and the two-dimensional scalogram is used as the input of the deep neural network;finally, the model was validated and analyzed several times with the MFPT bearing fault data set, and the average diagnostic accuracy of the proposed method reached 99.4%, which verified its feasibility and superiority and provided a theoretical basis for guiding bearing maintenance decisions. © 2022 ieee.

关键词： Failure analysis

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Analysis of High Step-up Switched Capacitor DC-DC Converter Based on Coupled Inductors

Analysis of High Step-up Switched Capacitor DC-DC Converter ...

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2022 ieee Transportation Electrification conference and Expo, asia-pacific, ITEC asia-pacific 2022

作者： Liu, Hao Bai, Xuechen Gu, Jingyun Cai, Hongye Zhang, Xiangjun Xu, Dianguo Harbin Institute of Technology Hefei Power Supply Company Harbin China State Grid Anhui Electric Power Company Hefei Power Supply Company Harbin China Department of Electrical and Computer Engineering University of British Columbia Vancouver Canada School of Electrical Engineer and Automation Harbin Institute of Technology Harbin China

ISBN: (数字)9781665492065

ISBN: (纸本)9781665492065

A novel high step-up switched capacitor DC-DC converter based on coupled inductors is proposed in this paper. The proposed topology solves the problem of insufficient voltage on the switched capacitor, thus improves the traditional energy storage structure. Combined with the coupled inductor, which further improve the voltage gain characteristics and reduce the stress of the switching device. The operating principle and steady state analysis of the converter are introduced in details, and a 200W experimental prototype with an input voltage of25-45V and an output voltage of 380V is established in the laboratory to verify the feasibility of the converter. © 2022 ieee.

关键词： Gain measurement

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Performance Analysis of Verifiable data Registry Solutions for Decentralized Identifiers

Performance Analysis of Verifiable Data Registry Solutions f...

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computer science and data engineering (csde), ieee asia-pacific conference on

作者： Morteza Alizadeh Karl Andersson Olov Schelén Department of Computer Science Electrical and Space Engineering Luleå University of Technology Skellefteå Sweden Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

User identification in decentralized systems is a demanding task. Identification systems should work resiliently and have efficient performance. Moreover, identification systems should protect the data that they must store against hackers and saboteurs. Keeping a system with decentralized identification without any intervention in the middle has attracted attention to improve earlier centralized identification systems. Decentralized Identifiers (DIDs) constitute a solution for identification divided into different modules. The verifiable data registry is one of the main parts of this technology, which is distributed storage of identity properties. We analyze the decentralized identification data registry and compare the performance of verifiable data registry based on blockchain and the Distributed Hash Table (DHT) on different scales of systems. Our evaluation results show that DHT has better performance. Furthermore, a model based on DHT shows that in addition to immutable storage and faster query time, it makes systems handle or search in data storage with lower searching time compared to Ethereum Blockchain as another immutable secure technology. Finally, our results show that DHT is a better solution than other models in different scenarios. Although blockchain has promising results on a small scale, it still has problems with storage and query time in large-scale systems.

关键词： Sockets Memory management Reliability engineering data engineering data models Time measurement Blockchains

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Iterative Geometric Calibration Algorithm Based on Projection Point Correction 2

Iterative Geometric Calibration Algorithm Based on Projectio...

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2nd asia-pacific conference on Communications Technology and computer science, ACCTCS 2022

作者： Hu, Zeqin Li, Songfeng Zhu, Zefan Wei, Jun Lu, Yao School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Guangzhou Perception Vision Medical Technologies Co. Ltd. Guangzhou China

ISBN: (纸本)9781665400343

In the healthcare engineering field, the mobile X-ray system is becoming more and more popular in tomographic reconstruction and surgical navigation. The calibration of the geometric relationship between the X-ray source and detector is very important for tomographic reconstruction and surgical navigation. In this paper, an iterative geometric calibration algorithm based on projection point correction is proposed, and a double-layer calibration object is designed for calibration. Firstly, the geometric parameters are roughly estimated by using the geometric center point of the projection contour of the steel ball as the projection point. Then, through iteration, the projection points are corrected by using the relationship between the projection contour and internal parameters of the steel ball. The accuracy of our algorithm is proved by simulation and practical experiments. © 2022 ieee.

关键词： Calibration

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Australian COVID-19 data Visualisation and Forecast Modelling Performance Analysis

Australian COVID-19 Data Visualisation and Forecast Modellin...

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8th ieee asia-pacific conference on computer science and data engineering (ieee csde)

作者： Ali, Proma T. Reddy, Ayesha K. Univ Melbourne Software Engn Melbourne Vic Australia Univ Fiji Math & Phys Saweni Lautoka Fiji

ISBN: (纸本)9781665495523

The rise of the Coronavirus pandemic was unanticipated, and it turned into a very serious and catastrophically dangerous scenario especially in terms of financial balance, physical and mental health, population growth, socialization, and globalization. This paper considers Australian COVID-19 data from its beginning on the 25th of January to this date for experimental study. The popular Microsoft Power BI tool and Python coding language were primarily utilized to visualize the data sets and understand the depth of the COVID-19 situation in Australia. More specifically Python is primarily used in this study on the data to generate visualizations and forecasted models for effective interpretation of the ongoing medical peril. The plots and graphs created significantly extract trends for the accumulative infection rates ongoing in Australia from February 2020 to September 2021. Such important comprehensions of the numerical data set allowed for a graphical understanding and representation with data science applications. Statistical forecasting models such as the autoregressive integrated moving average (ARIMA) model and the long short-term memory (LSTM) model were applied to the time series data of Australian COVID-19 infection numbers to predict the future trends of COVID-19 cases in Australia. Finally, we feel this research can help the policymakers and health practitioners to manage such global medical issues more efficiently in the future with the help of data science technology and applications which is the uprising heart of our technological era.

关键词： COVID-19 Power BI Python Visualization Forecasting ARIMA LSTM

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