Reviewerly/exHarmony huggingface dataset:
Domain Feature Alignment Based on Complement Foreground for Cross-domain Pedestrian Re-identification

Although significant progress has been made in supervised pedestrian re-identification (re-id), it is still challenging to extend the re-id model to new scenes due to the huge domain gap. Getting rid of domain-specific features and aligning domain features are the ideas to solve cross-domain problems. However, for the former, the existing schemes are often not thorough enough to get rid of the unique characteristics of the domain, and for the latter, domain feature alignment schemes try to align the background and other information that should not be aligned, so they fail to achieve ideal results. In this paper, we propose domain alignment based on complementary foreground. The scheme strips off background clutter thoroughly with the help of mask, and uses pedestrian attribute information and control factor to reduce the influence of background loss caused by masks. Finally, we measure the distribution difference between the two domains with maximum mean difference, and make the feature distribution farther or closer according to the different feature levels. Experiments on mainstream data show that our scheme is 13.9% higher than the benchmark, and extensive ablation experiments prove the effectiveness of our design.
A Corpus-Based Comparative Analysis of the Readability of Chinese Textbooks Used by the Preliminary Schools in Mainland China and Taiwan

Combined with the relevant research on the readability formula, this paper determines nine measurement indexes according to the key factors affecting text readability, and makes a quantitative analysis of the primary school Chinese textbooks printed by People's Education Press and Taiwan Hanlin Press. The study found that in terms of Chinese characters, the two editions of textbooks performed better in the coverage of commonly used Chinese characters, and the PEP textbooks have higher requirements for children's literacy skills. In terms of words, the vocabulary richness of the THP textbooks is relatively stable, and the vocabulary distribution is strongly linearly related to grades, while the PEP textbooks lack a reasonable gradient. In terms of sentences, the THP textbook sets higher requirements for the comprehension ability of senior students.
The Role of Positive 3-H Words in Peacebuilding and Engagement in EFL/ESL Classes

This review aimed at investigating the role of help, hope, and harmony formally known as positive 3H on students' engagement and peacebuilding. This topic has recently attracted attention since teachers and the way they treat students are said to play a paramount role in the learning process and as a result, peace can be built in the classroom and students also are more likely to be actively engaged in the tasks. To start with, a definition for positive 3-H was presented coupled with the role it plays in language learning contexts. Then the way both inner peace and interpersonal peace have been applied in the learning process to build peace is discussed. Following that, the effects of positive 3-H on students' engagement and peacebuilding through raising some relevant activities are dealt with. Finally, implications and further directions are put forward.
A Light-Weight Deployment Methodology for DNN Re-training in Resource-Constraint Scenarios

Wireless smart devices with restricted resources in the IoT may need to update DNNs due to environmental changes. In order to alleviate the computational complexity of DNN updates and stringent requirements on the size and distribution of datasets when re-training, Deep Transfer Learning (DTL) is proposed for transferring the knowledge that DNNs can learn from large standard datasets and reducing the number of DNN layers that need to be re-trained. However, previous work has rarely reconciled the needs of the computational process with the advantages of the computational platform, resulting in sub-optimal performance of the system. To address this problem, we propose a Light-weight Deployment Methodology, which targets for agile deployment of DNN re-training in resource-constraint scenarios. We design a Hybrid Precision Light-weight Strategy to distinguish the general feature extractor layer from the others so that the different light-weight mechanisms are utilized for efficient computing. Besides analyzing the system performance from aspects of information loss, computational throughput, and resource utilization, our design is able to generate a system configuration guidance with NSGA-II, which compromises DNN performance and system efficiency. The evaluation shows the throughput of the computation module guided by NSGA-II reach 39.30 and 35.04 GOPs respectively for each quantization mechanism, with the relative errors of only 2.52% and 4.60% from the theoretical values. And the model size is reduced by 34.72% without accuracy loss.
Are Collaboration Tools Safe? An Assessment of Their Use and Risks

The ongoing pandemic created uncertainty worldwide − stay-at-home orders, social distancing, and business closure or reorganization to protect the health of employees and maintain business continuity. For many organizations, this meant a shift from the office to the home and the adoption of collaboration tools for communications and the sustenance of productivity. Operating safely and securely in a virtual workplace, via collaboration tools, requires distinct security considerations and configurations. The rise in the use of video and conferencing meeting applications has increased network traffic and in turn, an attraction for cybercriminals. Four collaboration tools were analyzed to identify their cyber threats, vulnerabilities, and risks. We provide recommendations on how organizations and customers could mitigate risks and vulnerabilities, prevent cyberattacks, and operate securely in a virtual workspace.
Application Development 2013 Curriculum Report

In SMA Dian Indonesia the report card data entry process is still constrained by the complexity of the application flow that is used. Each subject teacher gives a grade to the homeroom teacher to be processed into a report card. This made it difficult for the homeroom teacher to process the data provided by the subject teacher so that the process of processing report cards was hampered."This study aims to determine the process of developing the 2013 Curriculum Report Card Processing Application at Dian Indonesia High School. Based on the results of the analysis, it was obtained 90% in the very feasible category by media experts, and from the teacher the average validity was obtained 80.7% with the feasible category. So it can be concluded that the development of the 2013 Curriculum Report Card Processing Application is very suitable for use at Dian Indonesia High School.
Linear Regression Model to Predict the Spread of COVID-19 in Tangerang City

The outbreak of acute respiratory syndrome virus disease in China at the end of 2019 has caused a global epidemic as well as high mortality rates in affected countries. This research aimed at examining the extent of the spread of confirmed Covid-19 cases in Tangerang City. The data used included the data of confirmed Covid-19 patients. Such data was integrated with geospatial data found in 13 sub-districts in Tangerang City. The prediction of the spread of confirmed Covid-19 cases was made by using Linear Regression model. The results of the MAPE calculation with a value below 10% in 13 districts resulted in a very good predictive value. This prediction resulted in a graph and was connected to each other in a thematic map coordinate point system. The results of the Covid-19 spread prediction were divided into several districts and indicated with different color variations. Therefore, the darker the resulting color on the thematic map visualization, indicates an increase in Covid-19 cases that have occurred.
FastShare: Scalable Secret Sharing by Leveraging Locality

Shamir's secret sharing scheme is widely used in many cryptographic protocols such as secure multi-party computation. It allows a secret to be distributed to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n$</tex> parties such that any <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$t$</tex> parties learn no information about the secret, whereas any <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$t+1$</tex> parties can recover the secret. However, the worst-case recovery guarantees come at the price of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$O(n^{2})$</tex> computation cost. This quadratic cost limits its scalability to applications involving only a small number of participants. This paper presents a framework, called FastShare, for designing secret sharing schemes that ensures worst-case security guarantees at a lower computation cost by relaxing the recovery constraint from worst-case to average-case in a statistical sense. In particular, FastShare considers the setup where each party takes part in the recovery process with some probability <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\rho$</tex> , independently of others. The core idea of FastShare is to construct a ‘signal’ using the secret and random masks by inserting zeros at judiciously chosen locations, and take its finite field fast Fourier transform (FFT) to generate the shares. We present a scheme designed using FastShare where the judicious zero placement ensures that the shares form a codeword of a locally recoverable code. The locality property along with the FFT allows us to recover the secret with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$O(n\log n)$</tex> computational complexity, from a ‘random’ subset of shares of large enough size. We analyze its security and recovery thresholds, and characterize a trade-off between <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\rho$</tex> and the probability of successfully recovering the secret. Further, we carry out numerical simulations to demonstrate the applicability of the proposed scheme for a wide range of values of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n$</tex> .
Component analysis of matrix pattern on RGB images for image stegano-key in MATLAB

Steganography is quite possibly the best procedures to shroud the presence of concealed data inside a cowl thing. Pictures are the notable cowl things for Steganography and in this work, picture Steganography is embraced. Implanting secret information based interior pictures calls for concentrated calculation, and thus equipment based Steganography usage increases fundamental interest of Steganography based calculation. There are a few techniques to shroud inside recorded cover-photographs. The spatial area strategies control the duvet-photograph pixel-bit esteems to insert the mystery data. The mystery pieces are composed quickly to the duvet picture pixel bytes. Thusly, the spatial territory procedures are basic and simple to execute. The Least Significant Bit (LSB) based picture steganography is one of the significant systems in spatial area photograph Steganography. In this work, a shiny new strategy for LSB Steganography has been suggested that is an extemporized model of 1 bit LSB technique.
Influence of Cascaded Multi-task Design Based on Shannon Form of Fitts' Law in One-Dimensional Movement on Guidance of Visual Flow

In the graphic design of interaction, multi-task interface design has been a topic of discussion for a long time. There are many kinds of multi-task design methods. As a classic multi-task design, the layout and method of multi task design are constantly updated. In the calculation of Shannon’s formula of one-dimensional motion, the distribution of visual flow is observed by visual movement experiment, and the reasonable layout of stacked multi-task design on mobile devices with interaction on devices with plane surface is discussed. This paper also hopes to provide a useful reference for future multi-task design.
Modified Leader Algorithm for Under-Sampling the Imbalanced Dataset for Classification

Data classification with a standard classifier automates the manual classification process in many fields. In a two-class dataset, when the number of samples in one class is more in number than the other class, namely, imbalanced, then the performance of a classifier gets degraded due to the limited availability of the training instances in a particular class. To overcome the problems with the imbalanced datasets, a new under-sampling method has been proposed with the baseline idea of an incremental clustering technique. Clusters are formed from the sum of features of the instances instead of finding distance between patterns. Representatives of the clusters are average of the instances of the cluster. Proposed algorithm has the ability to solve the problems than the existing under-sampling approaches with k-means algorithm and leader algorithm. The results produced through the proposed algorithm work better during the classification with good accuracy and reduced misclassification rate in both major and minor classes.
Basic Consideration of Voice Coil Type Multiple-Degree-of-Freedom Actuator

Space recognition is a crucial task for autonomous systems such as robots and unmanned aerial vehicles. These systems necessary to get information using a camera while moving. However, the decrease of the recognition accuracy attributed to an image quality deterioration due to vibration and the increase of the system size have become problems. To solve these problems, we focused on multiple-degree-of-freedom (DOF) actuators. However, conventional multiple-DOF actuators require a large number of components, and the control device is large in size. Thus, we propose a novel multiple-DOF actuator that can be driven by a simple control device with a small number of components. First, a 2DOF actuator driven by a 3-phase half-bridge circuit is described. Next, a 3DOF actuator driven by a 4-phase half-bridge circuit is presented. The basic performance is evaluated by a magnetic field analysis using a three-dimensional finite element method. The analysis results show that the proposed actuator can be driven by the proposed operating principle and magnetic structure.
MULTICHANNEL CONVERTION OF RANDOM DATA WITH THE PAIR-ELEMENTS OF ORDERED SAMPLES

The concept of multichannel parallel converting of probability density function (pdf) of random data was previously used for single-element pdf-converters. In development of this concept, here we investigate converting properties of spdf-converters channels formed by the sum of the ​​pairs of ordered sample elements (order statistics). The characteristics of the conversion results as dependencies on the size of the samples and the displacement of the channels relative to the median of the samples were obtained for data with a uniform distribution density. Also where excluded the areas of mutual dependence of the density functions of the summed elements, which further where normalized together with approximating them functions. Despite the apparent structural differences, the goal of this study still was to determine the closeness of the converted data with some standard functions of the probability distribution density, in particular, with the normal distribution law. As before, the estimates of the closeness of the spdf-converter channels were obtained using the chi-square criteria. The results of the research were used to determine the size and location of the statistical closeness windows, and to construct spdf-converters statistical model. References 20, figures 14.
Customizable Camera Verification for Media Forensic

This paper presents our research work in camera verification. We expanded a convolutional network-based feature extraction/verification network to a multi-patch input and addressed the concerns over memory limitation and overfitting issue. We have also made careful consideration for custom model training and provided strong results showing promising potential for real-world application of detecting scene text repurposing.
Neyman’s Smoothness Test: A Trade-Off Between Moment-Based and Distribution-Based Leakage Detections

Leakage detection tests have become an indispensable tool for testing implementations featuring side channel countermeasures such as masking. Whilst moment-based techniques such as the Welch’s t-test are universally powerful if there is leakage in a central moment, they naturally fail if this is not the case. Distribution-based techniques such as the χ2-test then come to the rescue, but they have shown not to be robust with regards to noise. In this paper, we propose a novel leakage detection technique based on Neyman’s smoothness test. We find that our new test is robust with respect to noise (similar to the merit of Welch’s t-test), and can pick up on leakage that is not located in central moments (similar to the merit of the χ2-test). We also find that there is a sweet-spot where Neyman’s test outperforms both the t-test and the χ2-test. Realistic measurements confirm that such a sweet-spot is relevant in practice for detecting implementation flaws.
Video summary generation based on density peaks clustering with temporal characteristics

Video summary is a new content-based video compression technology, which can effectively find important information from the video and eliminate redundant data in video. The density peaks clustering (DPC) can quickly find the density peaks of datasets of arbitrary shapes and efficiently allocate data. In order to apply it to video summary generation, we consider the temporal characteristics of the video, and introduce it into the DPC algorithm, and propose an improved DPC algorithm with temporal characteristics (called T-DPC), which is applied for the Hue histogram clustering of video frames, and the video shot is segmented based on the clustering results. In the keyframe selection stage, calculate the similarity between each frame and its cluster center, and the entropy of each frame, then select the frame with the largest linear combination of entropy and similarity in each category as the keyframe. At the same time, the histogram intersection method is employed to remove similar frames in the keyframes to generate video summary. The proposed method in this paper is evaluated with 50 videos in the open video library. The experimental results show that the accuracy of the video summary generated by our method is higher than that of OV, STIMO, and VSUMM1, but not as good as DT and VSUMM2. The recall rate is higher than the OV, DT, and VSUMM2, the same as the STIMO, and slightly lower than the VSUMM1. The F values are all higher than the comparison algorithms OV, DT, STIMO, VSUMM1 and VSUMM2.
“Free Creativity” as Means to Overcome Urgent Problem of Estrangement in the Modern World

The paper aims to identify the role of free creativity as a means to overcome the problem of estrangement relevant to the modern society. The article traces evolution of the notion “estrangement” introduced by G. Hegel, developed by K. Marx and E. Fromm and still considered relevant in the XXI century. Scientific originality of the study lies in the fact that free creativity, as distinguished from creative work, is considered as a means to solve the problem of estrangement. As a result, the authors conclude that free creativity, not focused on satisfying essential human needs, helps to solve the problem of estrangement and to strengthen an individual’s social identity.
Launching Adversarial Label Contamination Attacks Against Malicious URL Detection

Web addresses, or Uniform Resource Locators (URLs), represent a vector by which attackers are able to deliver a multitude of unwanted and potentially harmful effects to users through malicious software. The ability to detect and block access to such URLs has traditionally been enabled through reactive and labour intensive means such as human verification and whitelists and blacklists. Machine Learning has shown great potential to automate this defence and position it as proactive through the implementation of classifier models. Work in this area has produced numerous high-accuracy models, though the algorithms themselves remain fragile to adversarial manipulation if implemented without consideration being given to their security. Our work aims to investigate the robustness of several classifiers for malicious URL detection by randomly perturbing samples in the training data. It is shown that without a measure of defence to adversarial influence, highly accurate malicious URL detection can be significantly and adversely affected at even low degrees of training data perturbation.
The level of C3 and C4 complement components in rats after the administration of myasthenogenic sera with different cytotoxicity

International scientific and practical conference «The concept of modern pharmacy and medicine in Ukraine and EU countries» : conference proceedings, July 9–10, 2021. Wloclawek : «Baltija Publishing», 2021. 170 pages.
Dependent Dirichlet Processes for Analysis of a Generalized Shared Frailty Model

Bayesian paradigm takes advantage of well-fitting complicated survival models and feasible computing in survival analysis owing to the superiority in tackling the complex censoring scheme, compared with the frequentist paradigm. In this chapter, we aim to display the latest tendency in Bayesian computing, in the sense of automating the posterior sampling, through a Bayesian analysis of survival modeling for multivariate survival outcomes with the complicated data structure. Motivated by relaxing the strong assumption of proportionality and the restriction of a common baseline population, we propose a generalized shared frailty model which includes both parametric and nonparametric frailty random effects to incorporate both treatment-wise and temporal variation for multiple events. We develop a survival-function version of the ANOVA dependent Dirichlet process to model the dependency among the baseline survival functions. The posterior sampling is implemented by the No-U-Turn sampler in Stan, a contemporary Bayesian computing tool, automatically. The proposed model is validated by analysis of the bladder cancer recurrences data. The estimation is consistent with existing results. Our model and Bayesian inference provide evidence that the Bayesian paradigm fosters complex modeling and feasible computing in survival analysis, and Stan relaxes the posterior inference.
Improved analysis of measurement-device-independent quantum key distribution with non-phase-randomized coherent states

Measurement-device-independent quantum key distribution (MDI-QKD) can remove all detector side-channel attacks, which can be implemented with phase-randomized coherent states (PRCS) or non-phase-randomized coherent states (NPRCS). In this paper, we focus on the MDI-QKD protocol with NPRCS and provide an improved analysis. In contrast with the original MDI-QKD with NPRCS which modulates the same intensity of coherent states in the key and test bases, we propose to modulate different intensities of coherent states in the key and test bases. Simulation results show that the secret key rate and transmission distance of MDI-QKD with NPRCS can be significantly improved. Furthermore, it is noteworthy that the modulation of different intensities does not bring extra complexity for experimental researchers, which can be easily done by adding an intensity modulator.