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SSRN 2023年

作者： Ismail, Ahmad Muhaimin Hamid, Siti Hafizah Ab Sani, Asmiza Abdul Daud, Nur Nasuha Mohd Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia Faculty of Ocean Engineering Technology and Informatics University Malaysia Terengganu Kuala Terengganu Terengganu21030 Malaysia

ContextThe performance of the defect prediction model by using balanced and imbalanced datasets makes a big impact on the discovery of future defects. Current resampling techniques only address the imbalanced datasets without taking into consideration redundancy and noise inherent to the imbalanced *** address the imbalance issue, we propose Kernel Crossover Oversampling (KCO), an oversampling technique based on kernel analysis and cross-over interpolation. Specifically, the proposed technique aims to generate balanced datasets by increasing data diversity in order to reduce redundancy and *** first represents multidimensional features into two-dimensional features by employing Kernel Principal Component Analysis (KPCA). KCO then divides the plotted data distribution by deploying spectral clustering to select the best region for interpolation. Lastly, KCO generates the new defect data by cross-interpolating different data templates within the selected data *** to the prediction evaluation conducted, KCO consistently produced F-scores ranging from 21% to 63% across six datasets, on average. According to the experimental results presented in this study, KCO provides more effective prediction performance than other baseline *** experimental results show that KCO within project and cross project predictions especially consistently achieve higher performance of F-score results. © 2023, The Authors. All rights reserved.

关键词： Interpolation

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The State of Diversity and Inclusion in Apache: A Pulse Check

The State of Diversity and Inclusion in Apache: A Pulse Chec...

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ICSE Workshop on Cooperative and Human Aspects on Software engineering, CHASE

作者： Zixuan Feng Mariam Guizani Marco A. Gerosa Anita Sarma School of Electrical Engineering and Computer Science Oregon State University Corvallis Oregon USA School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff Arizona USA

Diversity and inclusion (D&I) in open source software (OSS) is a multifaceted concept that arises from differences in contributors’ gender, seniority, language, region, and other characteristics. D&I has received growing attention in OSS ecosystems and projects, and various programs have been implemented to foster contributor diversity. However, we do not yet know how the state of D&I is evolving. By understanding the state of D&I in OSS projects, the community can develop new and adjust current strategies to foster diversity among contributors and gain insights into the mechanisms and processes that facilitate the development of inclusive communities. In this paper, we report and compare the results of two surveys of Apache Software Foundation (ASF) contributors conducted over two years (n=624 & n=432), considering a variety of D&I aspects. We see improvements in engagement among those traditionally underrepresented in OSS, particularly those who are in gender minority or not confident in English. Yet, the gender gap in the number of contributors remains. We expect this study to help communities tailor their efforts in promoting D&I in OSS.

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Effects of personalized exercise prescriptions and social media delivered through mobile health on cancer survivors’physical activity and quality of life

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Journal of Sport and Health Science 2023年第6期12卷 705-714页

作者： Zan Gao Suryeon Ryu Wanjiang Zhou Kaitlyn Adams Mohamed Hassan Rui Zhang Anne Blaes Julian Wolfson Ju Sun School of Kinesiology University of MinnesotaMinneapolisMN 55455USA Department of Kinesiology Recreationand Sport StudiesThe University of TennesseeKnoxvilleTN 37996USA Department of Pharmaceutical Care&Health Systems and Institute for Health Informatics University of MinnesotaMinneapolisMN 55455USA Department of Hematology School of MedicineUniversity of MinnesotaMinneapolisMN 55455USA School of Public Health University of MinnesotaMinneapolisMN 55455USA Department of Computer Science&Engineering University of MinnesotaMinneapolisMN 55455USA

Purpose This study aimed to examine the effects of a multi-component mobile health intervention(wearable,apps,and social media)on cancer survivors’(CS')physical activity(PA),quality of life,and PA determinants compared to exercise prescription only,social media only,and attention control *** A total of 126 CS(age=60.37±7.41 years,mean±SD)were recruited from the United *** study duration was 6 months and participants were randomly placed into 4 *** participants received a Fitbit tracker and were instructed to install its companion app to monitor their daily ***(1)received previously established weekly personalized exercise prescriptions via email,(2)received weekly Facebook health education and interacted with one another,(3)received both Conditions 1 and 2,or(4)were part of the control condition,meaning they adopted usual *** PA daily steps,quality of life(i.e.,physical health and mental health),and PA determinants(e.g.,self-efficacy,social support)were measured at baseline,3 months,and 6 *** The final sample size included 123 *** results revealed only the multi-component condition had greater improvements in PA daily steps than the control condition post-intervention(95%confidence interval(95%CI):368–2951;p<0.05).Similarly,those in the multi-component condition had significantly greater increased physical health than the control condition(95%CI:–0.41 to–0.01;p<0.05)over *** addition,the social media condition had significantly greater increased perceived social support than the control condition(95%CI:0.01–0.93;p<0.05).No other significant differences on outcomes were *** The study findings suggest that the implementation of a multi-component mobile health intervention had positive effects on CS PA steps and physical ***,offering social media intervention has the potential to improve CS perceived social support.

关键词： Daily steps Exercise app Fitbit Health wearable Physical activity determinantsTagedAPTARAEnd

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Refining Word Embeddings for Funniness Predicting Sentimental Analysis Tasks 14

Refining Word Embeddings for Funniness Predicting Sentimenta...

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14th IEEE International Conference on computer Research and Development, ICCRD 2022

作者： Chen, Yanjin Chen, Duo Wang, Yifan Zhou, Zhicheng University of Virginia Computer Science department CharlottesvilleVA22904 United States Graduated from University of California Irvine IrvineCA92697 United States King's College London Faculty of Natural Mathematical Engineering Sciences Informatics Department London United Kingdom University of Birmingham School of Computer Science Birmingham United Kingdom

ISBN: (纸本)9781728177212

Sentiment analysis lies within one of the core fields for natural language processing. Concerning this field, word embeddings have been widely used as an effective way of representing words based on distributional semantics. In this paper, we focus on improving the GloVe embedding used for predicting the funniness of edited news headlines. The GloVe embedding of different dimensions is further tuned with the news headline dataset provided by SemEval, using the Continuous Bag of Words model and Skip-gram model, respectively. A recurrent neural network model is developed as the regression model for prediction task. A set of experiments are designed to evaluate the performance of various refined GloVe embeddings. We found out that original GloVe embedding and refined embeddings share similar performance in our current work. The prediction is more accurate for all refined embeddings when using 100 dimensions rather than 300 dimensions embeddings. © 2022 IEEE.

关键词： Forecasting

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Strained Elastic Surfaces with Adjustable-Modulus Edges (SESAMEs) for Soft Robotic Actuation

Strained Elastic Surfaces with Adjustable-Modulus Edges (SES...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Christopher J. Kimmer Michael Seokyoung Han Cindy K. Harnett Informatics School of Natural Science Indiana University Southeast New Albany IN US Department of Mechanical Engineering University of Louisville Louisville KY USA Department of Electrical and Computer Engineering University of Louisville Louisville KY USA

For robots to interact safely with humans and travel with minimal weight, low-density packable actuators are sought. Electronically-driven active materials like shape memory wire and other artificial muscle fibers offer solutions, but these materials need a restoring force. Moreover, if joint bending is required, the actuators must exert a bending moment around the joint. In this paper, we model the three-dimensional shapes of strained elastic surfaces with adjustable-modulus edges (SESAMEs), then implement SESAMEs by machine embroidering shape memory alloy wire onto stretched elastic fabric, showing a path to lightweight actuators that exert bending forces and have built-in restoring forces. SESAMEs start out planar, and upon release from the plane take on three-dimensional shapes thanks to the balance between bending energy in the boundary and strain energy in the elastic surface. The elastic creates both a restoring force to bring the boundary back to its original shape after actuation, and an out-of-plane structure for applying a bending moment. We demonstrate SESAMEs' properties as soft robotic actuators individually and in arrays, and coupled to flexible plastic frames during the planar fabrication process as bending actuators to switch bistable mechanical structures.

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Investigation of the acceleration influence on friction in bearings in dual-spin missile

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Materials Today: Proceedings 2023年 93卷 817-823页

作者： Ivana Todić Vladimir Kuzmanović University of Belgrade Faculty of Mechanical Engineering Weapon Systems Department Kraljice Marije 16 11120 Belgrade Serbia University of Belgrade Faculty of Mathematics Department for Computer Science and Informatics Studentski Trg 16 11000 Belgrade Serbia

Rockets and missiles fired from a tube usually have aerodynamic surfaces that are packed when the rocket is in the tube. One of the common fins folding solutions is the wrap-around fins. The wrap-around fins are usually separated from the rocket’s body by a bearing; thus the characteristics and the type of bearings used will have an effect on roll stabilization and the performance of roll stabilization autopilot. Also, during the flight, many forces act upon the missile thus affecting its exposed components. In turn, this may also affect the performance of the bearings that allow the wrap-around fins to rotate independently around the missile’s body. This dual-spin concept increases roll stabilization efficiency and reduces induced roll from lateral control. For this design to be effective and achieve the desired performance, it is critical to analyze how the movements of the missile affect the bearing separating the body from the wrap-around fins. Since the sections are separated by the bearing, various imperfections of the joint such as friction, misalignment, etc. combined with the acceleration of the missile may have a transitional influence on the performance of the wrap-around fins and thus roll stabilization. In this paper, we will first identify and explain the problem of acceleration influence on friction in bearings. Next, the laboratory equipment and experimental procedures for examining friction in bearings will be described in detail. We will then present and analyze the results obtained from the experiments. Finally, we will draw conclusions and present the design modification this investigation has led to as well as the improved roll autopilot performance achieved by using the appropriate bearing.

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Intake Monitoring in Free-Living Conditions: Overview and Lessons we Have Learned

arXiv

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arXiv 2022年

作者： Diou, Christos Kyritsis, Konstantinos Papapanagiotou, Vasileios Sarafis, Ioannis Department of Informatics and Telematics Harokopio University of Athens Greece Electrical and Computer Engineering Department Aristotle University of Thessaloniki Greece

The progress in artificial intelligence and machine learning algorithms over the past decade has enabled the development of new methods for the objective measurement of eating, including both the measurement of eating episodes as well as the measurement of in-meal eating behavior. These allow the study of eating behavior outside the laboratory in free-living conditions, without the need for video recordings and laborious manual annotations. In this paper, we present a high-level overview of our recent work on intake monitoring using a smartwatch, as well as methods using an in-ear microphone. We also present evaluation results of these methods in challenging, real-world datasets. Furthermore, we discuss use-cases of such intake monitoring tools for advancing research in eating behavior, for improving dietary monitoring, as well as for developing evidence-based health policies. Our goal is to inform researchers and users of intake monitoring methods regarding (i) the development of new methods based on commercially available devices, (ii) what to expect in terms of effectiveness, and (iii) how these methods can be used in research as well as in practical applications. © 2022, CC BY.

关键词： Monitoring

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3D Object Pose Estimation Using Local Features Based for Industrial Appliance

3D Object Pose Estimation Using Local Features Based for Ind...

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International Electronics Symposium (IES)

作者： Alfan Rizaldy Pratama Bima Sena Bayu Dewantara Dewi Mutiara Sari Dadet Pramadihanto Center for Research and Innovation on Advanced Transportation Electrification Politeknik Elektronika Negeri Surabaya Surabaya Indonesia Department of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Surabaya Indonesia

Object localization in the industrial field plays an important role to obtain the pose information of an object. For supporting the localization works, 3D point cloud data is used as its primacy containing the shape of an object. Despite its rapid development, the problems faced by each object used are heterogeneous. In this research, Time-of-Flight (ToF) camera is used to obtain the data considering its capability to provide a small form factor and sufficient point cloud data. As the one of most popular objects in the industrial field, fitting pipe is used in whole systems. Start from obtaining the data using a ToF camera, then followed by preprocessing which eliminate Non-measured data and point outside of the threshold range. Segmentation by separating the object with its planar, and separating each other into individual objects done by RAndom SAmple Consensus (RANSAC) and Density-based Spatial Clustering Application with Noise (DBSCAN). Before the pose estimation is applied, CNN is used to recognize the object. By using Fast Point Feature Histogram (FPFH) with SAmple Consensus Initial-Alignment (SAC-IA) as the coarse pose estimation and Iterative Closest Point (ICP) as the refinement pose estimation, average rotation error in Euclidean space (roll, pitch, yaw) as 0.47 degree, in translation is 4.17 mm. Also, we estimate the size of the pipe which has an average error of 5.30 mm.

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Spatial, Spatiotemporal, and Feature Analysis of Electroencephalogram During Imagined Speech with Visual vs Audio Cues

Spatial, Spatiotemporal, and Feature Analysis of Electroence...

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Electronic and Electrical engineering and Intelligent System (ICE3IS), International Conference on

作者： Nilam Fitriah Astri Budikayanti Hasballah Zakaria Tati Latifah Erawati Rajab Faculty of Computer Science Universitas Indonesia Depok Indonesia Department of Neurology Universitas Indonesia Jakarta Indonesia Department of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

People with speech disorders have difficulties in social life and welfare. To overcome this barrier, researchers have conducted studies to recognize imagined speech from biosignals. The essential biosignals in producing speech are brain signals. This study aimed to determine activated brain regions during the imagined speech by spatial and spatiotemporal analysis to assist feature selection in imagined speech recognition. We recorded the normal subjects' brain signals using electroencephalography (EEG) when they imagined saying a word without vocalization. The protocol ran in two different-time sessions to cover the EEG nonstationary. We utilized visual cues in the first sub-session and audio cues in the second one. One word per sub-session had seven trials, each consisting of a rest state and cue presentation, followed by four repetitions of the imagined speech state, each preceded by a preparation state. We calculated power spectral entropy (PSE) values from the acquired dataset and used them as a feature since they captured signals' activity. The normalized PSE above 0.5 (middle value) was considered as high activity. The results showed that repeated-trial protocol induced brain activity during imagined speech. For visual or audio-cued imagined speech, the selected channels were in the central and left frontal regions, with additional right temporal, left parietal, and left occipital regions for visual-cued imagined speech. The highest PSE was found in the central region. Meanwhile, the lowest PSE was shown in the preparation state, confirming that cue presentation was not affecting imagined speech states.

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Increasing Hosting Capacity of Uncontrollable Distributed Energy Resources in Isolated Power Systems

Increasing Hosting Capacity of Uncontrollable Distributed En...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Phivos Therapontos Andreas Stavrou Petros Aristidou Distribution System Operator Electricity Authority of Cyprus Nicosia Cyprus Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Transmission Network Owner Electricity Authority of Cyprus Nicosia Cyprus Dept. of Electrical & Computer Engineering & Informatics Cyprus University of Technology Limassol Cyprus

Due to the push for more sustainable generation, small-scale distributed energy resources (DERs) penetration has increased significantly. Most countries have no remote monitoring and control requirements for DERs below a certain size. Therefore, they can be labeled as uncontrollable DERs (UDERs). In isolated systems, the UDERs hosting capacity is limited due to frequency stability concerns, as it is impossible to modify or curtail their generation in a centralized manner. In this paper, we propose the utilization of the active power over-frequency reduction curve for increasing the hosting capacity of UDERs in isolated power systems. Cyprus’s power system has been used to evaluate the proposed solution’s performance. The optimal settings of the curve have been identified, and it was found that UDERs hosting capacity can be increased significantly with the proposed methodology.

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