Reviewerly/exHarmony huggingface dataset:
GloDyNE: Global Topology Preserving Dynamic Network Embedding (Extended Abstract)

Dynamic Network Embedding (DNE) is attracting much attention due to the time-evolving nature of many real-world networks. The main objective of DNE is to efficiently update node embeddings while preserving network topology at each timestep. The idea of most existing DNE methods is to capture the topological changes at or around the most affected nodes (instead of all nodes) and accordingly update node embeddings. Unfortunately, this kind of approximation, although can improve efficiency, cannot effectively preserve the global topology of a dynamic network at each timestep, due to not considering the inactive sub-networks that receive accumulated topological changes propagated via the high-order proximity. To address this issue, we propose a new DNE method for better global topology preservation. Extensive experiments demonstrate the effectiveness and efficiency of the proposed method.
Credit Scoring Model of Small and Medium-sized Enterprises over Encrypted Data

Credit evaluation is important for the solution to financing difficulties of small and medium-sized enterprises (SMEs). Incomplete information brings some difficulties to credit evaluation of SMEs. Existing methods try to solve the problem of evaluation validity. However, they do not consider privacy leakage. Based on homomorphic encryption, our paper proposes a credit scoring model with privacy protection after constructing an indicator system from the aspects of transactions, profits and reputation. A user, such as a bank or an enterprise, encrypts sensitive data with his own public key and sends them to an evaluation institute. The institution integrates the data ciphertext into his evaluation model, and calculates the score ciphertext. In the scheme, homomorphic operation can effectively resist malicious attacks from inside and outside. Neither a user nor an institution obtains the other party's information. The experiments show the scheme has small computation overhead and large communication overhead. And it is suitable for the scenarios with good network bandwidth and privacy protection requirements.
What and Where to See: Deep Attention Aggregation Network for Action Detection

AbstractWith the development of deep convolutional neural networks, 2D CNN is widely used in action detection task. Although 2D CNN extracts rich features from video frames, these features also contain redundant information. In response to this problem, we propose Residual Channel-Spatial Attention module (RCSA) to guide the network what (object patterns) and where (spatially) need to be focused. Meanwhile, in order to effectively utilize the rich spatial and semantic features extracted by different layers of deep networks, we combine RCSA and deep aggregation network to propose Deep Attention Aggregation Network. Experiment resultes on two datasets J-HMDB and UCF-101 show that the proposed network achieves state-of-the-art performances on action detection. KeywordsAction detectionResidual channel-spatial attentionFeature aggregationDeep neural network
Implementasi Algoritma Naïve Bayes Untuk Menentukan Calon Penerima Beasiswa Di SMK YPM 14 Sumobito Jombang

Scholarships are grants in the form of financial assistance given to individuals that aim to be used for the continuation of the education achieved. With this scholarship program, it is hoped that it can help students who have problems in financing. The selection of scholarship recipients at SMK YPM 14 Sumobito still experiences problems in decision making, because the assessment process is not always decided based on definite considerations but the policy of the decision makers who ultimately determine the scholarship recipients. This is because there is no method that can predict prospective scholarship recipients. Eligibility of prospective scholarship recipients is determined by applying the Naïve Bayes method. This method was chosen because it was able to study the previous case data used as test data. After testing with the Naïve Bayes algorithm using the Rapidmaner tool, the results were 90.48% accuracy, 96.88% precision, 83.33% recall each. So that it can be said as a good key to apply for prospective scholarship recipients.
Integration of blockchain with IoT-enabled sensor networks for smart grids

This chapter emphasizes on the IoT, its mechanism, and significance with respect to the current trends. Sensors will be the medium to exchange information from one part of the location to different locations. Smart grids play a major role compared to conventional grid were the energy usage and controlling are critical. The later section of this chapter gives the complete picture of how these IoT-enabled networks will be the part of smart grids, its implementation challenges, and benefits.The role of blockchain in IoT is discussed. Various advantages and disadvantages or challenges faced in adopting blockchain in IoT are considered. The overall vulnerabilities of IoT environment is discussed in detail here.
Research on complex data analysis model based on distribution automation data

With the development of global information tech-nology, “Internet + distribution network” has been the direction of development, using digital, networked, intelligent and other technical needs and distribution automation data processing has become a pending problem. These problems can be solved by graph computing and graph data model technology. Graph data model can provide efficient data management means for distribution automation, and graph computing data model for distribution automation data can provide flexible visualization functions and powerful data analysis and management functions. In this paper, we briefly analyze the progress of graph computing and graph data model and distribution grid automation system research in recent years, and propose a graph computing model based on distribution grid automation data.
Implementation of Graphics Tilt Correction based on Enhanced Graphic Feature Preprocessing

Improper placement of pictures or inaccurate shooting angle will cause the angle of graphics in the photos to tilt. In order to pursue the high reliability and high recognition rate for subsequent operations such as feature extraction, graphics matching and character recognition, it is necessary to correct the tilt graphics in the photos in advance. This paper uses opencv library to process the tilt graphics in four steps, that is, enhance the graphic feature preprocessing, edge detection, find the maximum edge contour of the graphics, rotate and correct the graphics, and finally achieve the effect of correcting the graphic. Among them, the calculation the final deflection angle of the minimum circumscribed rotating rectangle of the contour is a key to the success or failure of the overall processing.
The Implementation of Information Services in the Prevention of Drugs Abuse in School

This study aims to describe the implementation of information services in the context of preventing drug abuse in schools. The type of this research is a qualitative approach with a descriptive study method. Informants in this study included school principals, deputy principals, heads of administrative affairs, counseling guidance teachers (counselors), and students. The research was carried out for 3 (three) consecutive months, namely June, July, and August 2021. The research data will be tested for credibility through diligent observation, triangulation, discussing research results, adequacy of references, and analysis of research cases. The results show that the implementation of information services in the context of preventing narcotics abuse in schools includes aspects of information service material (understanding, types, and factors of narcotics abuse) and information service methods (lectures, discussions, questions and answers, and the use of guide books). Supporting this implementation, it is hoped that there will be a strengthening of the concept and consistency of counselors (supervising teachers) and peer tutors in equipping students with insights, knowledge, skills, values and attitudes in implementing these information services through the effectiveness of training and deepening of information material.
A linking belief is not essential for reasoning

In reasoning, you acquire a new conclusion-attitude on the basis of premise-attitudes. It is commonly thought that an essential feature of reasoning is that you have a linking belief, which is a belief that the premises imply the conclusion. This paper shows that a linking belief is not essential for reasoning. A genuinely essential feature of reasoning is that you acquire the conclusion-attitude by following a rule. A linking belief may be a necessary feature of theoretical reasoning, because it may be a consequence of having the disposition to follow a rule. But it is not essential for reasoning, which is to say that it does not contribute to making the process reasoning. For other sorts of reasoning including practical reasoning, a linking belief is not even necessary.
Pembuatan Sistem Desalinasi Kapasitas 240 liter/jam di Dusun Bondan Kecamatan Kampung Laut Cilacap

Dusun Bondan is a district located in a tidal area. Various problems arise in Dusun Bondan because of the use of water that doesn’t meet the quality of sanitation water causing several diseases. The water crisis experienced by the residents of Dusun Bondan becomes the worst disaster especially in summer because the water at Dusun Bondan is salty with high total dissolved solids. A water desalination system has been made to produce sanitation water that meets the standard based on Minister of Health Regulation No. 32 of 2017. The methods used to overcome these problems are water source identification, design of desalination system, purchasing, fabrication and testing of desalinated water. The result of the activities is a desalination system which consists of pre-treatment using 4 filtration stages ended with reverse osmosis desalination using a special membrane. The result of desalinated water test shows that the water is odourless, tasteless, and other parameters meet the requirement of the standard.
Polarized single photons from a cavity-enhanced atom-light interface with coherent re-preparation

We propose a scheme to generate single photons from 87 Rb atoms. The com-bination of coherent STIRAP re-preparation and optical pumping allows for the efficient generation of streams of indistinguishable photons with promising use-cases.
Proof-of-Principle Laboratory Demonstration of Long-Baseline Interferometric Imaging Using Distributed Single-Photons

We report results of very-long-baseline interferometric imaging using distributed single photons. We demonstrate source autocorrelation reconstruction, and increased signal-to-noise ratio per detected coincidence compared to using classical states as phase reference.
Quantum Features of Broadband Multimode Bright Squeezed Vacuum for Quantum Metrology

We demonstrate quantum features in the transition from spontaneous parametric down conversion to bright squeezed vacuum that are relevant to multiphoton spectroscopy, enabling the use of higher flux sources for quantum metrology.
The National Broadcasting System in Israel as a media literacy agent for Hebrew and Arabic-speaking children during the Covid-19 pandemic

The COVID-19 pandemic led to the emergence of distance learning, with students across Israel having to learn from home starting in March 2020. In response, the Ministry of Education established the National Broadcasting System to help teachers with their online classes. Hundreds of lessons entailing media were recorded in a range of subjects, to be viewed by children of all ages via digital devices. Although television plays a role in socialization and education, the question is: can television at home substitute teachers in the classroom? This study examines the project for delivering prerecorded lessons in Hebrew and Arabic, which strove to provide an innovative means for enabling meaningful and enjoyable distance learning. The study found that teachers’ attitudes toward these recordings ranged from satisfaction, through indifference, to concern about their role as teachers and their use of digital media and technology. The study also found that the project provides a voice for the Arab minority.
The Distributed Digital Body Farm: Enabling the Analysis of Deleted File Decay Patterns

Estimating the rate and pattern of deleted file decay on digital media is of interest to digital forensic investigators. Understanding how deleted file contents decay and the factors that affect the process is useful in making decisions about artifact recovery during a forensic investigation. Although the mechanisms that cause deleted file content decay are well known, the actual decay behavior and patterns of decay are not well understood, and one cannot predict with certainty if some or all of a file may be recovered after it has been deleted. This work demonstrates a novel method for collecting data about deleted file content decay from real world systems, without violating user privacy. We present the design of the distributed digital body farm (DDBF) and demonstrate its application in collecting deleted file decay data from geographically dispersed computers. The DDBF is a remote software agent that collects content free and privacy preserving data about deleted file decay on an active computer system. The data collected is consolidated in a central repository and preliminary analysis is performed to reveal patterns in the data and show the value of the DDBF.
Context Matters: Accurately Measuring the Efficacy of Denial-of-Service Mitigations

Denial-of-Service (DoS) attacks remain a severe and constant threat to the Internet. While various mitigation strategies have been developed and deployed to defend against these attacks, the community lacks adequate metrics for quantifying their efficacy. Metrics used to quantify DoS attacks provide a solid starting point, but extending them to the domain of mitigations is non-trivial. Current metrics don’t account for a mitigation’s overhead outside periods of attack, and fail to capture important context – differences in attack rate, client behavior, network topology, and various other factors can all dramatically alter the impact of attacks and the efficacy of mitigations. This paper provides a methodology and novel suite of metrics designed to enable more meaningful and contextual measurement of DoS mitigations. To illustrate the benefits of these metrics we conduct experiments in the DeterLab network testbed measuring the efficacy of SYN Cookies, a well-known and widely used mitigation against the ubiquitous TCP SYN flood attack. We show that this mitigation is highly effective in certain contexts but can significantly degrade client quality of service in others. Our goal is to help device owners and network operators determine which mitigations are best suited for their particular context, and to help protocol designers and implementers develop a more DoS-resilient Internet.
A Comprehensive Study based on Human Facial Images

The human&#x2019;s facial image is a cumbersome research topic in computer vision or digital image processing. This paper tried to estimate the human gender and age that is too robust for different external environments. It gives an overview of facial recognition. There are the major applications as law enforcement, security, simulation on various areas to prevent the environmental condition. The common issues are occlusion, illumination, pose, imaging condition, facial expressions along with the facial features. More recently, the Convolution Neural Network (CNN) is a mostly used model to explore the current application background. The improved structure and learning method of the CNN network gives better performance and also the results are to be evaluated. The model predicts its human age and gender to classify the facial images.
Stacked Reconfigurable Optical Cavities for Smart Sensing Pixels

Photonic systems have seen a recent explosion of investigation for neuromorphic engineering and the execution of machine learning models, owing to the advantages of optics for communications and performing linear operations. Here, we present a novel architecture for executing reconfigurable multiwavelength photonic multiply-accumulate (MAC) operations based on all-solid-state vertically-integrated tunable cavities. We simulate this weighting action through full transfer-matrix calculations of a realistic candidate filter stack. By efficiently leveraging the out-of-plane dimension, we form a conceptual ‘smart pixel’ device that can achieve higher spectral channel count per area, or equivalently computational density, than comparable subpixel architectures and planar integrated photonic devices. While this technology is of use for neuromorphic photonic information processing, its usefulness extends to applications in sensing and communications by covering, for instance, high spatial resolution hyperspectral filters and reconfigurable routing.
Improved Feature-Level Fusion-Based Biometric System for Genuine and Imposter Identification

In this research work is divided into five sections: pre-processing, feature extraction, featurelevel fusion, imposter/ genuine classification, and male/female identification. The gathered raw data for palm print, dorsal vein, wrist vein, and palm vein are pre-processed with enhanced median filtering algorithms. The required features are then being extracted from the pre-processed images. Following that, an improved feature-level fusion technique is carried out based on the required security level. In the low security level, the certain image features are considered. Furthermore, if the medium security level is chosen, any two sets of attributes has been combined. If the high security level is chosen, all of the retrieved characteristics has been combined. Further, multiple classifications are carried out. It will determine whether the individual is genuine or an imposter. If it is an imposter, simply get rid of it. If the categorized result is genuine, it is reclassified as male or female.
An Analysis of Research Trends on Creative Teaching

Objectives The purpose of this study was to examine the studies on creative teaching published in Korean journals through the content analysis method and keyword network methods.&#x0D; Methods TThe final 77 papers among the papers searched as keywords for ‘creative teaching’ in Korean journals were targeted. For content analysis, the 77 papers were analyzed in terms of topics and research methods using an analysis frame. In addition, 216 keywords were derived for keyword network analysis, and frequency analysis and centrality analysis were conducted using textom programs and UCINET.&#x0D; Results First, before 2008 the main topic of creative teaching was creative teaching methods. From 2009 to 2014, in addition to creative teaching methods, various concepts such as creative teaching behavior, creative teaching beliefs, and creative teaching environment began to emerge, and after 2015, research on creative teaching behavior increased, and new concepts such as creative teaching competency and creative teaching efficacy were introduced. Also, from 2009 to 2104, most studies on creative teaching were conducted at universities, but after 2015, studies on creative teaching at universities and early childhood institutions increased. Second, the main keywords of creative teaching research were ‘teaching method’, ‘creative problem solving’, ‘child creativity’, and ‘teacher creativity’. As a result of network analysis, ‘creative teaching behavior’, ‘creativity’, and ‘creative teaching method’ were dominant keywords in degree centrality, closeness centrality, and mediation centrality.&#x0D; Conclusions This study reviewed systematically research on creative teaching by period, and explored the relationship between the variables related to creative teaching. Implications for the results and future studies were discussed.&#x0D; &#x0D;
The Effect on the Academic Persistence Intention by the School Belonging and the Professor Trust of University Students in Non-face-to-face Learning Environment due to COVID-19

Objectives The purpose of this study was to investigate the effect on the academic persistence intention by the school belonging and the professor trust of university students in non-face-to-face learning environment due to COVID-19.&#x0D; Methods A survey was held to the university students who have been non-face-to-face learning environment more than a semester in Seoul and Chungcheong cities from April 11 to April 18, 2022. 202 copies were in the final analysis for data analysis, t-test, ANOVA, Pearson’s Correlation Coefficient and Multiple regression was used.&#x0D; Results The school belonging, the professor trust, and the academic persistence intention of university students all showed significant positive correlations with one another. Number of meetings with professors in one semester, the school belonging, the professor trust, accounted for 40.8% of the total variance in the academic persistense intention among university students.&#x0D; Conclusions Therefore, this study could be used as a basic data for the development of student support programs that help students continue their studies by promoting a sense of belonging to their university and intimacy between professors.&#x0D; &#x0D;
A new two-dimensional coupled chaos and semi-tensor compressed sensing are used for joint compression encryption

In order to meet the requirements of high efficiency and security of data processing in wireless distributed transient pressure testing system, a new data compression and encryption acquisition method combining two-dimensional coupling cascade chaos map and semi-tensor compression sensing is proposed in this paper. Firstly, the cascade chaotic system based on sine function enhancement has better chaos complexity and larger chaos range than seed mapping. In this paper, a sinusoidal chaotic coupling cascade model is proposed. Secondly, the chaotic system is mapped to a compressed sensing observation matrix, and the dimension of the observation matrix in the sampling process is reduced by using semi-tensor theory. Finally, an experimental analysis of the 50psi measured shock wave combined compression encryption shows that the encrypted key space is 1064 with a compression ratio of 1∕4, the key sensitivity is 10-16, and the reconstruction error is less than 0.006 under the noise interference of 10dB, which meets the transmission requirements of wireless sensor networks.
Development and practical application of acmeological technologies of student assessment diagnose

In this article, the types and their classification according to the forms and stages of organization of acmeological diagnosis of primary school students’ mastery level are expressed. The article also contains suggestions and scientific recommendations on this issue.
On Barwise and Cooper’s “Generalized Quantifiers and Natural Language”

I review “Generalized Quantifiers and Natural Language”, 1981, by Jon Barwise and Robin Cooper. I focus on the flurry of activity triggered by their paper in the early 1980s and then focus on what I consider the two major innovations in their paper: direct interpretation of English, and hypothesized language universals. I document some of the related work done in the decades following their paper.
[Design and Application of Ultrasound Audit Workstation System].

According to the problems exist in the original ultrasound system, the study elaborates the design and application of the ultrasound audit workstation system, including the workflow, trace information recording, information management, audit data interaction, application effects, et al. This study points out that the system can optimize the ultrasound process, help to improve the quality and efficiency of ultrasound report audit as well as improve the efficiency of patients' ultrasound examination and medical treatment experience.