Reviewerly/exHarmony huggingface dataset:
Schrödinger-cat-like states with dressed photons in renormalized adiabatic approximation for generalized quantum Rabi Hamiltonian with quadratic interaction

We give a mathematical procedure to obtain the renormalized adiabatic approximation for the generalized quantum Rabi Hamiltonian with a quadratic interaction. The Hamiltonian describes the energy of the interaction system of a two-level artificial atom and a one-mode microwave photon. Using the renormalized adiabatic approximation in the deep-strong coupling regime, we study the appearance of the Schrödinger-cat-like states with dressed photons in the eigenstates of the generalized quantum Rabi Hamiltonian with the quadratic interaction.
MODELING AND MANAGING MEDICAL DATA

The article describes a statistical method for analyzing medical data based on the comparison of binary samples. Processing data that is accumulated in transactional medical information systems, based on the analysis of binary samples, allows you to determine the indicators of laboratory research and diagnoses that are characteristic of harmful production factors. This will contribute to the development of digital technologies in healthcare, which will improve both diagnostics and treatment methods, as well as facilitate the adoption of competent management decisions. The research results were converted to binary form by comparing them with the statistical norm interval. Diagnoses were considered initially as a binary variable. The samples obtained as a result of binarization for two groups, the first group includes people whose production activities contain harmful factors, and the second – those who do not have these factors, were compared with each other. The initial group turned out to be heterogeneous in relation to the other group, so it was decided to conduct a further study based on the development and testing of methods for adjusting samples in order to achieve uniformity while maximizing the preservation of medical data used for analysis.
Resident Data Pattern Analysis Using Sector Clustering for Storage Drive Forensics

Storage drives are huge reservoirs of digital evidence. The acquisition and examination of storage drives for evidentiary artifacts require enormous amounts of manual effort and computing resources, leading to huge case backlogs. This chapter describes a forensic triage methodology that leverages random sampling and unsupervised clustering to provide insights about the regions of interest on a storage drive. The number of sector samples to be evaluated during triage for legitimate inferences to be drawn about drive content is also discussed. Experiments involving storage drives of various capacities illustrate the effectiveness and utility of the extracted patterns for rapid drive triage.
"L'aglio mettilo tagliato": definire il participio passato predicativo attraverso la lingua della cucina

The 'predicative' function of Italian past participles is dealt with in this article, a function that has not yet been taken into account in Italian grammars. More precisely, we analyse constructions like l’aglio mettilo tagliato (‘add the sliced garlic’). As some constituency tests clearly show, such participles neither fall under the definition of «attributive» participles, nor under the «circumstantial» function: they rather behave as modifiers of the verbal phrase. Within the frame of secondary predication studies, the participles under consideration can be counted among the «depictives». Depictive predicative participles recur very often in the language of cookbooks and recipes: therefore we use such texts as a source for our purpose.
LibGuides: Data Resources for Poltical Science and Political Scientists: Help with R/SAS/SPSS/Stata

Guides and introductions to using various programs for statistical analysis. No statistical program will provide you with an emotionally-rewarding relationship, but these guides will help make the couples therapy more productive.
Photon-Number Resolution Using Superconducting Tapered Nanowire Detector

We show that a superconducting nanowire with an integrated impedance-matching taper can resolve photon numbers. The taper increases the nanowire detector’s output amplitude and makes it sensitive to the number of single-photon-induced hotspots.
Extended quasi-cyclic constructions of quantum codes and entanglement-assisted quantum codes

Construction of quantum codes and entanglement-assisted quantum codes with good parameters via classical codes is an important task for quantum computing and quantum information. In this paper, by a family of one-generator quasi-cyclic codes, we provide quasi-cyclic extended constructions that preserve the self-orthogonality to obtain stabilizer quantum codes. As for the computational results, some binary and ternary stabilizer codes with good parameters are constructed. Moreover, we present methods to construct maximal-entanglement entanglement-assisted quantum codes by means of the class of quasi-cyclic codes and their extended codes. As an application, some good maximal-entanglement entanglement-assisted quantum codes are obtained and their parameters are compared.
The Usage of Vlog in Combat Coronavirus News Reporting—A Case Study of “Wuhan: My Dairy of Combating Coronavirus”

On the logical starting point of log news report, this paper takes "Wuhan: My Dairy of Combating Coronavirus"as an example, discusses the innovative practice of Vlog in Combat Coronavirus News Reporting and considers the path change for news production in the ear of Web 2.0.
Real-time Facial Expression Recognition using 3D Appearance and Geometric Network for Public Security

Facial expression recognition is a promising technology that can be used in various fields of artificial intelligence.There are several challenges to deal this task, one of which is recognizing a facial expression in sequential input data for real-time recognition.Many types of convolutional neural networks have been proposed to consider temporal information together.Typically, there are appearance networks that utilize facial appearance information, geometric networks that use facial landmark points, and hybrid approaches that combined these two networks.In this paper, we compare various methods proposed so far and identify the best approach for each network.We also have an experiment the initial architecture of our proposed 3D appearance and geometric network based on these researches and validate that its 97.22% accuracy on CK+ dataset is comparable to state-of-the-art techniques.
Application of on-site EEW technology in South Korea.

&amp;lt;p&amp;gt;The potential seismic hazard in South Korea is known to be that mid-sized earthquakes could occur nationwide. Because the damages of mid-sized earthquake are concentrated only in the vicinity of the epicenter, on-site EEW technology is known to be effective as a means to reduce absence of alarm near the epicenter and to ensure safety from earthquake threat. This study aims to simulate on-site EEW suitable for South Korea's seismic observation environment and verify its reliability. Seismic observations of 267 events occurred in South Korea, have been collected over the past five years for the simulation . Filter Picker was utilized to detect P-wave features from more than 37,000 data sets using a time window suitable for mid-sized earthquakes. The ground noises are removed from the detected P-waves, and a linear empirical relationship between the maximum P-wave amplitudes in vertical direction and observed PGVs on the base rock are derived. Convert the forecasted and observed PGVs to MMI, respectively. Assuming a successful prediction within the MMI&amp;amp;#177;1 margin of error by comparing the two values, the results of this study showed an 80% success rate in the range above MMI 4. Through this study, feasibility and performance of on-site EEWS using domestic earthquake records were verified in South Korea. It is expected that this will contribute to the reduction of earthquake damage near the epicenter through an on-site warning in Korea.&amp;lt;/p&amp;gt;
Energy efficiency of microgrid and the application of blockchain in microgrid

Abstract Blockchain has the characteristics of reliability, encryption, non-tampering and traceability, which can effectively solve many problems such as data isolation and uneven distribution and energy waste in China’s microgrid. Both have the characteristics of decentralization, security, transparency and intelligence, which provide a basis for the combination of the two. The exploration of the integration of the blockchain’s own characteristics with the technology of the microgrid illustrates the advantages and feasibility of the blockchain in current transactions.
Radon and CO2 tracer for radioxenon subsurface sampling in the On Site Inspection

&amp;lt;p&amp;gt;The detection of anomalous concentration of Xenon radiosotopes in the subsurface gases during an On Site Inspection (OSI) is a strong indicator of a suspicious underground nuclear explosion. This implies that the sampling methodology ensure the collection of a reliable representative subsurface gaseous sample, avoiding the mixing with atmospheric gases. Radioxenon sampling in shallow layers can provide reliable results for desert areas, but different local geological features could result in more complex migration of subsurface gases to the very near superficial layers affecting the representativeness of the sample.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Radon is currently use as tracer to reveal the effective sampling of gases form the deep surface, so its measurement is coupled with the collection of radioxenon subsurface gases. The detection of radon anomalous concentration in subsurface gases could indicate different causes: high Radon content in subsurface indicate high radon concentration underground caused by the accumulation in an underground and confined cavity; on the other side, low radon detection in subsurface indicate low radon concentration underground that can be indicative of the absence of an underground cavity or the presence of rocks in the cavity absorbing radon. This lead to the consideration that radon is not a univocal tracer for Xe surface sampling in the OSI. A portable isotopic analyzer (that measures d13C and CO2) could be used to localize the faults and fracturing that could lead to a seeping of the subsurface gases. Therefore, this technique could be proposed as an auxiliary equipment for a preliminary activity during an OSI and a monitoring tool during subsurface gas sampling.&amp;lt;/p&amp;gt;
Pemodelan dan Simulasi Monte Carlo dalam Meningkatkan Pendapatan Penjualan Peralatan Motor (Studi Kasus : Bengkel AMI Motor)

AMI Motor shop is a various shop that is engaged in sales by selling various motorcycle equipment. Sales transactions vary in stores, but almost all products have increased and decreased, so it is necessary to know how the product data is related to consumer demand. Sales simulation is an estimate that can provide benefits in making decisions to increase sales revenue. The purpose of this study is to predict what motorcycle equipment stock should be increased and decreased in sales in the following year. The data used is motor equipment sales data in 2018 and 2019 which are processed using the Monte Carlo method. In speeding up data processing, this system is applied to a web-based system using the PHP (Hypertext Processor) programming language. Based on the results of testing prediction levels of motorcycle equipment sales, average accuracy is 95,92%, making it easier for company leaders to make decisions on developing business strategies to increase sales revenue.
A novel action recognition system for smart monitoring of elderly people using Action Pattern Image and Series CNN with transfer learning

Falling of elderly people who are staying alone at home leads to health risks. If they are not attended immediately even it may lead to fatal danger to their life. In this paper a novel computer vision-based system for smart monitoring of elderly people using Series Convolutional Neural Network (SCNN) with transfer learning is proposed. When CNN is trained by the frames of the videos directly, it learns from all pixels including the background pixels. Generally, the background in a video does not contribute anything in identifying the action and actually it will mislead the action classification. So, we propose a novel action recognition system and our contributions are 1) to generate more general action patterns which are not affected by illumination and background variations of the video sequences and eliminate the obligation of image augmentation in CNN training 2) to design SCNN architecture and enhance the feature extraction process to learn large amount of data, 3) to present the patterns learnt by the neurons in the layers and analyze how these neurons capture the action when the input pattern is passing through these neurons, and 4) to extend the capability of the trained SCNN for recognizing fall actions using transfer learning.
The Round Complexity of Secure Computation Against Covert Adversaries

We investigate the exact round complexity of secure multiparty computation (MPC) against covert adversaries who may attempt to cheat, but do not wish to be caught doing so. Covert adversaries lie in between semi-honest adversaries who follow protocol specification and malicious adversaries who may deviate arbitrarily. Recently, two round protocols for semi-honest MPC and four round protocols for malicious-secure MPC were constructed, both of which are optimal. While these results can be viewed as constituting two end points of a security spectrum, we investigate the design of protocols that potentially span the spectrum. Our main result is an MPC protocol against covert adversaries with variable round complexity: when the detection probability is set to the lowest setting, our protocol requires two rounds and offers same security as semi-honest MPC. By increasing the detecting probability, we can increase the security guarantees, with round complexity five in the extreme case. The security of our protocol is based on standard cryptographic assumptions. We supplement our positive result with a negative result, ruling out strict three round protocols with respect to black-box simulation.
TiVGAN: Text to Image to Video Generation with Step-by-Step Evolutionary Generator

Advances in technology have led to the development of methods that can create desired visual multimedia. In particular, image generation using deep learning has been extensively studied across diverse fields. In comparison, video generation, especially on conditional inputs, remains a challenging and less explored area. To narrow this gap, we aim to train our model to produce a video corresponding to a given text description. We propose a novel training framework, Text-to-Image-to-Video Generative Adversarial Network (TiVGAN), which evolves frame-by-frame and finally produces a full-length video. In the first phase, we focus on creating a high-quality single video frame while learning the relationship between the text and an image. As the steps proceed, our model is trained gradually on more number of consecutive frames.This step-by-step learning process helps stabilize the training and enables the creation of high-resolution video based on conditional text descriptions. Qualitative and quantitative experimental results on various datasets demonstrate the effectiveness of the proposed method.
자기주도학습 교육 향상을 위한 확산적·수렴적 사고기법 활용 연구 - 시각디자인 전공 중심으로 -

The role of design and designer is changing as we enter the era of the Fourth Industrial Revolution, which is based on creativity and convergence. New design types of names have been created and the design process, which could be solved by itself, is now essential to cooperate and collaborate with other majors. Therefore, the competence of today's designers wants talent with creative thinking and application skills that reflect the various values demanded by the knowledge society. In this study, based on the integrated thinking of Divergent Thinking·Convergent, which is necessary for the design problem-solving process for self-directed learning, we propose an educational methodology for self-directed learning and seek ways to utilize it. The type of integration of the Divergent·Convergent Thinking Techniques is an educational model that focuses on bringing one's ideas freely through two thoughts within a given format, through topics that can be observed in everyday life. Based on the existing prior research, the research method for the verification of the education model was integrated and applied CPSS types based on the design thinking, and items of Learner Satisfaction, Self-Efficiency, Idea Expression, and Presentation Skill were extracted to verify the effectiveness of the self-directed learning. The extracted items were conducted as experimental studies to verify the relationship of influence between the CPSS. In the future, we hope to cultivate future talents who can naturally solve problems together in collaboration with other major fields, and that the DPS education model will be applied to educators and students in the self-directed learning effect.
Recent Trends in the Use of Deep Learning Models for Grammar Error Handling

Grammar error handling (GEH) is an important topic in natural language processing (NLP). GEH includes both grammar error detection and grammar error correction. Recent advances in computation systems have promoted the use of deep learning (DL) models for NLP problems such as GEH. In this survey we focus on two main DL approaches for GEH: neural machine translation models and editor models. We describe the three main stages of the pipeline for these models: data preparation, training, and inference. Additionally, we discuss different techniques to improve the performance of these models at each stage of the pipeline. We compare the performance of different models and conclude with proposed future directions.
KOEFISIEN LIMPASAN PERMUKAAN PADA PERKERASAN PAVING BLOCK BERPORI

The use of pavement is increasing, especially in urban areas. Various types of pavement are used including asphalt, concrete and paving blocks. The use of pavements tightens the filtration and increases the volume of surface runoff. One of the pavements used to reduce runoff is paving blocks. The open area between paving blocks is the most influential factor in increasing water infiltration in paving blocks. The larger the opening area in the paving, the more water absorption capacity will be. This research uses infall simulator to model rain. The pavement used is a square porous paving block with a size of 20 x 10 x 8 cm. Variations in the number of pores are 3 holes, 5 holes and 9 holes. The area comparisons between paving blocks and pore holes were 99.4% and 0.6%, 99% and 1%, 98.2% and 1.8%, respectively. Measurements taken are the measurement of rain intensity, runoff volume, infiltration volume and surface break-even coefficient (C). The results showed that the addition of pore holes had an effect on the surface runoff coefficient. In square paving blocks without pores, the coefficient value is greater. Poreless square paving blocks have the highest runoff coefficient with values ranging from 0.41 to 0.45, square paving blocks with 3 porico holes, runoff efficiency ranges from 0.39 to 0.43, paving blocks with 5 pore runoff coefficients range from 0.38 - 0.42, and a square paving block with 9 pore holes, the smallest runoff coefficient ranges from 0.37 to 0.41.
Discussion on the application of energy microgrid integrated with blockchain technology

Abstract Based on the technical characteristics of the blockchain, the credibility, fit, architecture, and main business models of the data processing of the energy microgrid integrated with the blockchain technology are analyzed and discussed. It shows the feasibility and necessity of implementation, and puts forward a targeted solution to the current situation. Blockchain is very promising to promote the development of energy microgrid.
Are L2 adversarial examples intrinsically different?

Deep Neural Network (DDN) has achieved notable success in various tasks, including many security concerning scenarios. However, a considerable amount of work has proved its vulnerability to adversaries. We unravel the properties that can intrinsically differentiate adversarial examples and normal inputs through theoretical analysis. That is, adversarial examples generated by $L_2$ attacks usually have larger input sensitivity which can be used to identify them efficiently. We also found that those generated by $L_\infty$ attacks will be different enough in the pixel domain to be detected empirically. To verify our analysis, we proposed a \textbf{G}uided \textbf{C}omplementary \textbf{D}efense module (\textbf{GCD}) integrating detection and recovery processes. When compared with adversarial detection methods, our detector achieves a detection AUC of over 0.98 against most of the attacks. When comparing our guided rectifier with commonly used adversarial training methods and other rectification methods, our rectifier outperforms them by a large margin. We achieve a recovered classification accuracy of up to 99\% on MNIST, 89\% on CIFAR-10, and 87\% on ImageNet subsets against $L_2$ attacks. Furthermore, under the white-box setting, our holistic defensive module shows a promising degree of robustness. Thus, we confirm that at least $L_2$ adversarial examples are intrinsically different enough from normal inputs both theoretically and empirically. And we shed light upon designing simple yet effective defensive methods with these properties.
LibGuides: Return to Library 2021: Online Resources

This guide provides information for library users on returning to the library in the academic year 2020/2021.
On the Design and Implementation of Higher Mathematics Problem Teaching

Based on the analysis of the shortcomings of traditional teaching methods of higher mathematics, this paper expounds the significance of problem-based teaching, and makes in-depth thinking and research on the design principles, contents and implementation of higher mathematics problem-based teaching, which will provide useful reference for promoting the reform of higher mathematics teaching and improving the quality of personnel training.
VANDALISME DALAM PEMANFAATAN LAYANAN INFORMASI PERPUSTAKAAN

The purpose of this research is to know the factors that cause vandalism in the library. The research object discusses the importance of preventing vandalism as well as understanding the causes. The scope of research is focused on the basis for the creation of library services, so that a positive image of the library can be realized. The historical conceptual application of thought is critically analyzed realistically, in research methodit is called a historical approach and primary data is the primary source of information. The data collection method is library research. The research analysis is descriptive qualitative and content analysis to analyze the meaning of all the notions of deviant behavior, the factors that cause vandalism and its application to library institutions. Utilization of observation as a complement to support theoretical construction. The results of the study are the factors that cause vandalism in the library are: (1). Factors from users consist of; (a). Disappointment with library services, (b). There is an intention, (c). There is an opportunity, (d). Lack of awareness of library users, (e). Stress. (2). Factors from the library consist of; (a). Loose supervision, (b). Unprofessional Officers. (3). Environmental factors consist of; (a) The economic conditions of library users, (b). Social factors of library users, (c). The library room management is incorrect. (4). Communication deadlock. Keyword : Vandalism, Library Collection; Deviant Behavior