Reviewerly/exHarmony huggingface dataset:
Towards Privacy-Preserving Neural Architecture Search

Machine learning promotes the continuous development of signal processing in various fields, including network traffic monitoring, EEG classification, face identification, and many more. However, massive user data collected for training deep learning models raises privacy concerns and increases the difficulty of manually adjusting the network structure. To address these issues, we propose a privacy-preserving neural architecture search (PP-NAS) framework based on secure multi-party computation to protect users' data and the model's parameters/hyper-parameters. PP-NAS outsources the NAS task to two non-colluding cloud servers for making full advantage of mixed protocols design. Complement to the existing PP machine learning frameworks, we redesign the secure ReLU and Max-pooling garbled circuits for significantly better efficiency (3 ~ 436 times speed-up). We develop a new alternative to approximate the Softmax function over secret shares, which bypasses the limitation of approximating exponential operations in Softmax while improving accuracy. Extensive analyses and experiments demonstrate PP-NAS's superiority in security, efficiency, and accuracy.
Modular speaker design enabled by multi-material additive manufacturing

One of the most promising features of additive manufacturing is ability to reduce part count and assembly by printing complex shapes. This feature is further highlighted by utilizing multi-material printing in which stiff and compliant materials can be deposited by the same system. Air-acoustic speakers are traditionally comprised of several assembled components with different material properties including a stiff enclosure, stiff diaphragm, and compliant suspension. In this presentation, we will describe a modular acoustic speaker design. The design consists of fully printed structural components (which are threaded together, and assembled with a voice coil and magnet). The basic design as well as printing process will be described and acoustic measurements reported. A range of printed designs, which can be interchanged among each-other will be presented, and future design ideas which take advantage of the printing process explored.
Quizizz Application and understanding texts in English texts with the content of “Aprendo en Casa” Educational Platform

The objective of this research was to determine the results of the level of understanding texts in English with the content of “Aprendo en Casa” Educational Platform in second grade students at a Public School in Tacna by using Quizizz, 2020. The type of research that was used is experimental and the form was pre-experimental, the research method is hypothetico-deductive. The procedure for obtaining the data was through the application of pre and post-tests. The results indicate that after the post-test, 68.75% of students reached an outstanding level of achievement, 31.25% are at the expected level of achievement, 0% are at the process level, and at the beginning level. From the results obtained, it can be stated that the students from second grade managed to improve their level of understanding of English texts with the content of “Aprendo en Casa” Educational Platform through Quizizz.
Organizing Committee: Proceedings of the 8th Annual International Seminar on Trends in Science and Science Education (AISTSSE) 2021

First Page
Research of senior high school students’ economic culture formation in the conditions of development of the digital education environment

The work is devoted to the problem of finding approaches to assessing the level of formation of economic culture among high school students, as one of its important components. Recognition of the significance of the phenomenon in question in the educational sphere and the realization that the system of pedagogical support of continuous economic education in educational organizations is, somewhat, outdated requires their essential updating. In this regard, the problems of finding approaches to the study of ways of senior high school students’ economic culture formation in the context of the development of the digital educational environment of the region are becoming urgent, which requires the construction of the model itself. The aim of the work is to study, analyze the state and model of the process senior high school students’ economic culture formation. The main research methods are theoretical analysis of scientific, psychological and pedagogical literature on the research problem, study and generalization of experience on the problem; observation, questioning, conversation, qualimetry, testing, method of expert assessments; ascertaining and formative experiment; analysis of the study; methods for mathematical statistical processing, statistical processing empirical data. The study was conducted on the basis of Krasnoyarsk State Pedagogical University named after V. P. Astafiev with bachelor’s and master’s degree students, high school students, teachers from educational institutions, students of universities and secondary professional educational institutions of Krasnoyarsk and Krasnoyarsk Territory. The analysis of the state of the problem of high school students’ economic culture formation based on the diagnosed test tools revealed correctional dependences between the indicators of four components in the structure of high school students economic culture formation and the levels of this formation under the conditions of digital education environment development in the region. The obtained dependencies and research data made it possible to form a model of this process in the context of the development of the digital educational environment of the region, describing the degree of formation of each component at each level.
Developing A Web-Based Learning Media On Maharoh Istima In MAN 1 Kota Kediri

The use of learning media on Maharoh Istima is very essential to promote students’ listening skills. Learning media used by teachers used to be ineffective due to the students’ heterogenous listening proficiency. That’s why, it is needed to develop an autonomous and flexible learning media to promote students’ listening skill which can be implemented anytime and anywhere. This Research and Development study employed a developmental method called ADDIE. The media produced was validated by media and material experts using a Likert Scale for analysis. The study produced a website http://belajaristima.com/ validated by the media expert in 92,30% and the material expert in 97,27 %. From the validation, it is said that the media is valid and can be implemented as a learning media.
SISTEM INFORMASI PENCATATAN HUTANG DALAM PENGADAAN OBAT BERBASIS MULTIUSER (Studi Kasus Di RSUD Ambarawa)

The development of information technology is growing rapidly from day to day. This is supported by the presence of a computer as a data processing media that can assist the process of providing information. Computers are one of the basic needs for an agency or company to assist in recording and processing data in order to produce fast, precise and accurate information. The need for a computer is due to the number of transactions or important data of agencies or companies that are very diverse so that a database is needed that can store and process the data into information quickly, accurately, and can be used whenever needed This information is needed to help a company or agency in making the right decisions for the company's survival in the future. Likewise, the Ambarawa Regional General Hospital (RSUD) uses computers as a medium for recording and processing data to produce information.The Regional General Hospital (RSUD) Ambarawa is one of the institutions belonging to Semarang Regency which is engaged in public health services. Ambarawa Hospital is located at Jalan Kartini No. 101 Ambarawa. The beginning of its establishment was in 1930 in the form of a Private Hospital belonging to the Catholic Foundation and in 1945 the ownership of the Hospital was handed over to the Semarang Regency Government with management still carried out by the Catholic Foundation. Then in 1956 the ownership and management of the Hospital was completely handed over to the Semarang Regency Government. As of 2012, Ambarawa Hospital has been in the form of a Regional Public Service Agency (BLUD).
Performance Evaluation of Data Augmentation for Object Detection in XView Dataset

Object detection in overhead imagery is of great importance in computer vision. xView is one of the largest publicly available datasets of overhead imagery. Because limited amount of data/images is available for training, the performance of a typical object detection model is expected to be poor without enough training data. In this paper, data augmentation methods by changing/perturbing some of the properties of the images such as changing the color channel of the object, adding salt noise to the object, and enhancing contrast are applied to the xView dataset. Performance evaluation of object detection using YOLOv3 model and augmented data has been carried out. The results demonstrate that the effectiveness of the data augmentation methods depends on both the specific method and the object classes.
Minimum equalization for pedestrain re-identification

In order to solve the intelligent application of pedestrain re-identification technology in the actual monitoring scenes, the color and texture features are fused and some local blocks are used to extract image features by considering the changing shooting angle of pedestrian image. A method of histogram equalization before texture feature extraction is proposed to solve the problem of unclear pedestrian contour. By down sampling the image twice, the algorithm has better scale invariance. Compared with the existing re-identification method of cross-view quadratic discriminant analysis (XQDA) combined with local maximal occurrence (LOMO) characteristics, the experimental results show that the corresponding re-identification rate rank1 on the datasets of VIPeR, PUK-Reid and i-LIDS-VID is improved by 0.28%, 1.75% and 0.20%, respectively, which proves that the recognition rate of pedestrain re-identification with minimum equalization is improved.
Learning tenant behavior and evolutionary approach for demand response in colocation datacenters

This article addresses a relevant problem for super-computer and colocation datacenters that participate in energy-efficiency demand response programs. A combination of computational intelligence methods (artificial neural networks and evolutionary computation) is applied for computing accurate plannings to attend demand response events, while minimizing cost and quality of service degradation. Artificial neural networks are applied to predict the behavior of tenants within the demand response program and an evolutionary algorithm is applied to solve the underlying control/planning problem, considering the (fuzzy) neural network prediction as a surrogate of the unknown real function that models the behavior of tenants. Results computed for a case study modeling a realistic datacenter operation during a demand response event indicate that the proposed approach is able to compute accurate plannings, improving up to 71% over a Business as Usual method.
Investigation and Analysis on the Factors Affecting the Effect of College Students' Mobile Learning

With the development of network information technology and the popularity of mobile devices, college students have taken mobile learning as a new learning method, which has become a supplement to classroom formal learning and meets the needs of learners' informal learning.However, by reading a large number of relevant literature, it is found that the effect of College Students' mobile learning through mobile devices is not satisfactory.Starting with cognitive load theory, learning theory and learning motivation theory, this paper reads a large number of relevant references, systematically and deeply studies the factors affecting college students' mobile learning effect, puts forward the model of factors affecting college students' mobile learning effect, and then designs a targeted questionnaire to investigate college students with mobile learning experience, so as to make an empirical analysis of the theoretical model and research hypothesis.The research results of this paper prove that in the mobile learning environment, the quality of learning platform, the quality of learning resources, cognitive load and other factors will significantly affect the effect of learners' mobile learning.Finally, according to the results of research and practice, the paper puts forward relevant strategies and suggestions on how to improve the effect of College Students' mobile learning, hoping to promote people from all walks of life to improve the quality of mobile learning.
Research on the Design of Children's Stroller Based on User Experience

With the improvement of people's living standard, people put forward higher requirements for children's stroller.The children's stroller only with strong functionality and high safety can no longer meet the standard of good experience for users.This paper takes the user demand as the guide, finds the pain points and design opportunities of the children's stroller by establishing the user behavior map.Combined with the hierarchy of user experience needs, this paper makes a design and research on children's stroller, and finally puts forward a set of design scheme, which is expected to provide reference for the improvement of the user experience of children's stroller.
Sistem Pemesanan dan Pembayaran Menggunakan Teknologi Quick Response Code (QR Code) Berbasis Web pada Kedai Cangkir Gubug

The results of this study are in the form of a product, namely an android application, an ordering and payment system using Android-based QR Code technology. According to the research design, the research results go through two testing or validation processes, namely design validation by experts in this case expert lecturers in the computer field, and product validation by users.Validation is carried out using an assessment instrument in the form of a questionnaire or validation sheet. The questionnaire contains 10 questions that must be filled in with a value between 1 and 4. The total score will get a score of not good, enough, good, or very good. The final conclusion is a statement that the product must be replaced, can be used with many revisions, can be used with few revisions, or can be used without revision.The results of the design validation test by experts gave a total score of 37, included in the score indicator 31 n 40, namely "Very Good". The conclusion drawn by the expert for system design is "Can be Used Without Revision".The results of product validation testing by users give an average value of 35 so that it is in the indicator category and gets the "Very Good" predicate. The final conclusion of user validation is a product or prototype "Can Be Used Without Revision".This research was conducted in a restaurant, Restaurant isn’t just a place to eat something but also a place to relaxing, meet someone or hang out with friends or colagues. Service of the restaurant is the main factor to make customer feel comfortable and relax. Many restaurant make their own order and payment system for better service but they forgot about the speed of their services.Using research methods data collection, observation, and interviewin Kedai Cangkir Gubug, face to face service like greeting, take order, and serving order all of it is waiter’s job. All of that tasks need time at most that makes if the restaurant have many customers, every single customer have to wait for a longer time waiting for waiter that serving another customer. The payment method is quite troublesome for customer because they have to save order paper for payment in cashier later.The solution that writer’s made is to decrease the task of waiter so that services can be done equally with QRcode technology for ordering menu with the scanner is android smartphone. Payment only need name of customer or table number and customer can do it in cashier or they can request the bill at their table. Therefore waiter no need to take order one after another and customer can do payment easier.
Analysis of noun errors of Lao international students when learning Vietnamese

In second language acquisition, learning vocabulary is the most important thing for learners.Vocabulary is the key in the process of learning a foreign language because only when rich in vocabulary will not hinder communication in a foreign language.In fact, in learning Vietnamese as a foreign language, the language errors that Lao students make, lexical errors are quite common.In order to meet the requirements of Vietnamese vocabulary in teaching Vietnamese to Lao students international students, it is theoretically imperative to study errors and find solutions to overcome Vietnamese vocabulary errors of Lao students and practical applications.
Pengaruh Model Think Pair Share dengan Media Lagu Sahabat Sejati terhadap Kemampuan Menulis Cerpen Siswa Kelas XI MAS Proyek UNIVA Medan

&#x0D; &#x0D; &#x0D; &#x0D; This study aims to describe the ability to write short stories using the Think Pair Share learning model with the media song true friend of class XI MAS students in the UNIVA Medan project for the 2019 / 2020 academic year, to describe the ability to write short stories using the Think Pair Share learning model with video media for class XI MAS students. The UNIVA Medan project for the 2019 / 2020 academic year, to describe whether there is a significant influence on the ability to write short stories using the Think Pair Share learning model with the song media for the true friend of XI MAS students. The UNIVA Medan project for the 2019 / 2020 academic year. The sample in this study was 60 students. 2. From the results of data processing, the average value of the experimental class is 72.3 while the control class is 64.6. Thus it can be said that the results of learning to write short stories in the experimental class are higher than the control class. After testing the hypothesis, the value of tcount = 3.701 is then adjusted to ttable at a significant level = 5% with dk = (n1+n2) – 2 = (30+30 – 2) = 58, then the significant level is 5% = 2.002 ( by interpolation). Then compared between tcount and ttable, it was obtained that tcount 3.701 &gt; ttable 2.002 so that Ho (Nil Hypothesis) was rejected and Ha (Alternative Hypothesis) was accepted.&#x0D; &#x0D; &#x0D; &#x0D;
BoundaryFace: A Mining Framework with Noise Label Self-correction for Face Recognition

Face recognition has made tremendous progress in recent years due to the advances in loss functions and the explosive growth in training sets size. A properly designed loss is seen as key to extract discriminative features for classification. Several margin-based losses have been proposed as alternatives of softmax loss in face recognition. However, two issues remain to consider: 1) They overlook the importance of hard sample mining for discriminative learning. 2) Label noise ubiquitously exists in large-scale datasets, which can seriously damage the model’s performance. In this paper, starting from the perspective of decision boundary, we propose a novel mining framework that focuses on the relationship between a sample’s ground truth class center and its nearest negative class center. Specifically, a closed-set noise label self-correction module is put forward, making this framework work well on datasets containing a lot of label noise. The proposed method consistently outperforms SOTA methods in various face recognition benchmarks. Training code has been released at https://gitee.com/swjtugx/classmate/tree/master/OurGroup/BoundaryFace .
Maximum Margin Correlation Filter Based on Data Spatial Distribution Information

In the past decade, object localization and object classification using correlation filters, especially large margin correlation filters which combine with support vector machine (SVM), have become a hotspot. However, the large margin correlation filters do not consider the class distribution and the structural features within the class during training, which is easily affected by noise. This paper presents two methods to overcome this drawback: minimum class variance large margin correlation filter (MCVLMCF) and minimum class locality preserving variance correlation filter (MCLPVCF). First, the overall structure information of the target is obtained by the within-class scatter with MCVLMCF, and the spatial features of the sample are extracted by the intrinsic manifold structure of data with MCLPVCF. Then, we embed these two types of information into the optimal function of the large margin correlation filter, fuse the sample spatial features with the large margin principle and correlation filtering, and convert it to solve the filter in the frequency domain. Finally, object localization experiments in actual environments and classification experiments on different datasets demonstrate that our proposed methods can adapt to complex object changes and achieve better performances than some state-of-the-art methods.
Bocb: Performance Benchmarking by Analysing Impacts of Cloud Platforms on Consortium Blockchain

Consortium blockchain has recently witnessed unprecedented popularity due to its implicit features and potential capabilities. On the other hand, cloud computing has become a mature technology and has reshaped numerous other innovative technologies through its flexible and efficient on-demand computing services. Consortium blockchain's performance issues undermine its wider acceptance but unleashing the cloudâ€™s computing capabilities can help to develop the full potential of blockchain. In other words, cloud technology and blockchain's potential integration can be envisaged as a next-generation information technology, highly characterised by scalable and secure solutions, respectively. In this context, it is important to understand what benefits blockchain gains from cloud integration in terms of performance. This article presents a comprehensive, empirical analysis for an in-depth study of the performance of the blockchain, specifically consortium (but not limited to) implemented on the cloud, ranging from identifying potential performance bottlenecks, to configuring system parameters. Furthermore, this article presents a novel framework for blockchain on cloud benchmarking (BoCB), and implement it by a Hyperledger Fabric application on four different commercial Cloud platforms. The evaluation results of the blockchain performance on heterogeneous cloud platforms can help developers select the best possible configuration and resources to optimise their applications accordingly.