Reviewerly/exHarmony huggingface dataset:
Video extensometer for structural steel using silhouette image from telecentric illumination system

Steel structures experience plastic deformation and damage during large earthquakes. The stress–strain (S–S) curve of structural steel can be used to develop a constitutive model to simulate its structural behavior. The S–S curve can be obtained by video extensometers, the efficiency of which with a telecentric lens and telecentric illumination remains unclear. The applicability of a telecentric lens and telecentric illumination system to video extensometers were investigated. Rigid-body motion and tensile testing were performed and the carrier of displacement of six gauge lengths was traced. Further, N images were obtained under a constant displacement/force and averaged to reduce the pseudo strain. Experimental results showed that the pseudo strain increases with the out-of-plane rigid displacement but remains unaffected by the in-plane rigid-body displacement. Tensile testing results showed an error difference of <10 % for the Young’s modulus obtained from the video extensometer and strain gauge.
A Study on the Development of Instruments to Measure Creative Convergence Capacity and Validation of the Instruments in College

The purpose of this study was to development of scales to measure ‘creative convergence capacity’ as the outcome of capstone class in college. Based on results from literature review and delphi survey, this study clarifies a theoretical ground for ‘creative convergence capacity’. Initial items to measure this concept were verified by content analysis and then finalized. After a pilot test done with 220 college students, gathered data were analyzed by item selection and exploratory factor analysis to verify their validity. Next, the main test implemented with 410 college students was analyzed with exploratory factor analysis using the method for rotation based on principle component analysis and varimax for validating the final items to measure ‘creative convergence capacity’. As a result, the scale for ‘creative convergence capacity’ consists of 34items to measure the following four factors: critical thinking, creative conception, collaborative activity, innovative problem solving. Criterion-related validity were performed at last to check this scale’s theoretical construct. In conclusion, this study concluded that the constructs for creative convergence capacity could be generalized and applicable to other samples.
Chaining Multiplications in Finite Fields with Chudnovsky-Type Algorithms and Tensor Rank of the k-Multiplication

We design a class of Chudnovsky-type algorithms multiplying k elements of a finite extension $${\text {I}\!\text {F}}_{q^n}$$ of a finite field $${\text {I}\!\text {F}}_q$$ , where $$k\ge 2$$ . We prove that these algorithms give a tensor decomposition of the k-multiplication for which the rank is in O(n) uniformly in q. We give uniform upper bounds of the rank of k-multiplication in finite fields. They use interpolation on algebraic curves which transforms the problem in computing the Hadamard product of k vectors with components in $${\text {I}\!\text {F}}_q$$ . This generalization of the widely studied case of $$k=2$$ is based on a modification of the Riemann-Roch spaces involved and the use of towers of function fields having a lot of places of high degree.
The Menzerath-Altmann law in the syntactic relations of the Chinese language based on Universal Dependencies (UD)

The Menzerath-Altmann law in the syntactic relations of the Chinese language based on Universal Dependencies (UD) was published in Quantitative Approaches to Universality and Individuality in Language on page 117.
Heaviside function as an activation function

Abstract The uniform closure of the neural networks with Heaviside activation is specified.
The Machine Learning Approach for Recommendation System Based on Online Review

For the past few years, various recommendation systems have been introduced that give recommendations and suggestions based on online user reviews. These recommenders provide valuable information from user-generated reviews through various processes. These systems use different techniques to extract the important information from the reviews that are valuable enough to give as suggestions to the users based on their interests. In this research, a portable recommender system has been developed based on the three Machine learning that recommend its user about different mobile phones available in the market and helps them select the best one based on the online user reviews.
Quality Evaluation of Wind Energy Data with Complete Linkage Clustering

Although wind is an important free energy and most investors or farmers would like to invest in wind energy projects, they sometimes lack of the wind quality data in alternative areas for making decision.It should be definitely good to have some simple methods to classify the quality of wind energy for alternative areas.In this study, Complete Linkage method combining with the Euclidean distance calculation, which is really a simple method for users, is introduced to cluster wind energy quality of alternative areas.In a case of 13 alternative areas in the south of Thailand, the data of average wind velocity along 12 months from the secondary data source can be used to generate the initial distance matrix before continuously improving with Complete Linkage method.Finally, these 13 alternative areas are suitable clustered at C.D. = 5.11 into 3 groups of the low wind quality area with I.D. = 1.21, the medium wind quality area with I.D. = 1.41 and the high wind quality area with I.D. = 1.45.
Artificial Intelligence-Based Defense Project Research on security vulnerabilities and countermeasures

This study examines the current state of artificial intelligence in the 4th Industrial Revolution, which is currently undergoing global development, and examines the systems that the United States and the Republic of Korea are incorporating into defense projects. The research was conducted to look at the security vulnerabilities identified to date and to suggest ways to compensate for the security vulnerabilities that may arise in the future development process.&#x0D; Because AI operates on the basis of superintelligence and hyper-connectivity, if a part is hacked, it can damage the entire system, and if the data built up is turned into misinformation by a hacker, the entire operating system can be crippled. The weapons systems of defense projects developed and operated for the purpose of war may have more serious consequences for society than AI-based equipment used by civilians.&#x0D; In this regard, we would like to explore the vulnerable areas that need to be supplemented and explore solutions based on the opinions of the literature and experts. We look forward to using it as a resource to help us now and in the future of leveraging artificial intelligence.
A Qualitative Study on the Direction of Learning Community Operation to Cultivate Teacher Professionalism : Focusing on Fisheries and Maritime High Schools

This study intends to suggest the direction of operation of the Fisheries and Maritime Teacher Learning Community(FMTLC) through the teachers" experiences. In order to overcome the geopolitical aspect, FMTLC is required to operate a blended teacher community that crosses online and offline, such as exchanging information with distant teachers on a daily basis through online community activities, and planning teacher Sports Day and Conference offline. In addition, by meeting with experienced senior teachers through FMTLC activities, teachers become more professional and motivated, which in turn will help them become more capable of interacting and teaching students. Ultimately, FMTLC will increase the friendship between teachers and establish a desirable identity as a teacher who practices quality education.
EXAMINING THE RELATIONSHIP BETWEEN GAMIFICATION USER TYPES AND FIVE PERSONALITY TYPES OF GENERATION Z TOURISM STUDENTS

Hotel businesses have a physical work environment where tourists and employees interact at the same time. As Gen Z grew up in the digitalized virtual world, their expectations from the business environment were different. At the beginning of these differences is the necessity of changing the traditional approaches to human resources management in hotels. Human resource management has turned to gamification applications as an innovative strategy. Human resources can place the right person in the right job as a result of matching personality and gamification user types. In addition, with the personality results obtained, it can enable us to make gamification designs suitable for the employees. This research aims to determine the gamification user types and five-factor personality types of Gen Z tourism students, who are current and potential employees, and to examine the relationship between them. The research was carried out using the quantitative method. The population of the research consists of 953 tourism faculty students' and a total of 449 participants were reached with the convenience sampling method. The data was collected on the online Question Pro platform using the survey method. A total of 280 usable questionnaires were included in the analysis. The mean and percentage values of the data obtained from the participants enabled the determination of the highest and lowest gamification and personality types. Research hypotheses were tested by correlation analysis. According to the research findings, the disruptive gamification user type and the responsible personality type were highest score among tourism students. As a result of the hypothesis tests, a negative relationship was determined between gamification user types and personality types. The results of the research reveal that creating personas and gamification designs within the framework of personality and gamification user types of employees in tourism and other sectors will play a key role in the success of the application. It has been concluded that the Gen Z exists with different personality types in the physical and virtual worlds.
Blockchain Stored Procedures and Optimization

This work was supported in part by the 2020 Industrial Internet Innovation and Development Project: Network Identifier Construction Project. The development of society and the progress of the times are inevitable for the continuation of human history, and the increasing innovation of Internet technology is one of the most important components. Data privacy protection has gradually entered the public's field of vision. Blockchain storage of data is a good way to solve the problem of privacy protection. Blockchain technology combines big data, cryptography, mathematics and other technologies. This article describes the In the process of storing data on the blockchain, an optimization mechanism for storing data is proposed to the storage problem, which effectively relieves the storage pressure and protects data privacy.
Memoryless Optimality: Neurons Do Not Need Adaptation to Optimally Encode Stimuli With Arbitrarily Complex Statistics

Abstract Our neurons seem capable of handling any type of data, regardless of its scale or statistical properties. In this letter, we suggest that optimal coding may occur at the single-neuron level without requiring memory, adaptation, or evolutionary-driven fit to the stimuli. We refer to a neural circuit as optimal if it maximizes the mutual information between its inputs and outputs. We show that often encountered differentiator neurons, or neurons that respond mainly to changes in the input, are capable of using all their information capacity when handling samples of any statistical distribution. We demonstrate this optimality using both analytical methods and simulations. In addition to demonstrating the simplicity and elegance of neural processing, this result might provide a way to improve the handling of data by artificial neural networks.
Kemampuan Mengenal Lambang Bilangan 1-5 Melalui Media Menjepit Angka Pada Anak Usia Dini

This research was carried out because of the low ability of children to recognize number symbols in TKIT MTA Karawang. For this reason, real action is needed in order to find the right solution related to the ability to recognize number symbols in children, namely through playing with number-clamping media. This study aims to determine whether children's ability to recognize number symbols can be increased through playing with number-clamping media in children aged 4-5 years at TKIT MTA Karawang. The researcher used this type of classroom action research as much as 2 cycles. The subjects in this study were children aged 4-5 years in class A, totaling 15 children, consisting of 11 girls and 4 boys. Based on the results of the study, it is known that there is an increase in the ability to recognize number symbols in children. In the pre-cycle the child's ability to recognize number symbols was 31.39% and increased by 32.52% in the first cycle to 63.91%, the increase again occurred from the first cycle to the second cycle by 18.68%. So that the increase that occurred from the pre-cycle to the second cycle was 82.59%. So it can be concluded that through the media clamping numbers can improve the ability to recognize number symbols.&#x0D;
Peningkatan Minat Membaca Anak melalui Modifikasi Media Pembelajaran Lantai Baca pada Anak Usia Dini

This study aims to increase reading interest in Chiqa Smart PAUD children. This type of research is classroom action research with two cycles. Research data through observation, observation and documentation of research subjects are children in group B1, totaling 10 children consisting of 5 boys and 5 girls. The results showed that the development of children's interest in reading in children increased after being given action through modification of the reading floor media that supports and children are free to choose and play so as to provide opportunities for children to understand and can foster children's interest in reading from an early age. This increase can be seen from the initial condition of the development of interest in reading. Group B1 children are in the criteria of not developing in cycle 1 with a percentage of 55% increasing to developing very well by taking action using modified reading floor media with children free to choose their own type of play to increase in cycle II with a percentage of 80%, where the modified reading floor media is made more interesting and fun and supports the criteria for developing very well. The children are able to ask questions and answer the explanation given, understand the articulation of letters clearly, correctly mention the initial letters of the picture, are able to read the letters that the children have arranged, mention the signs (the initial letters of the word), are able to tell stories and understand the contents of the story.
Digital Resources as a Way to Increase the Motivation of Economic Specialties Students in Studies of Mathematics

The purpose of the work is to analyze the technical, methodical and psychological aspects of digitalization in education and, in particular, the methods of ensuring the effectiveness of independent work of students in the conditions of e-learning. The main attention is paid to the problem of the influence of interactive educational technologies on the formation of external and internal motivation of students of economic specialties to study mathematical disciplines.&#x0D; Methodology. In the conditions of e-learning continuous monitoring of the success of students in mastering mathematical methods and their application to solve economic problems was carried out. The success of each student in performing each type of work separately, as well as his overall rating among other students in the group, were determined. These results were supplemented by the results of the students' questionnaire regarding their own attitude towards interactive technologies as a tool aimed at forming motivation for learning. &#x0D; Results. The virtual environment for e-learning was built using Moodle LMS and contained learning digital resources of various levels of interactivity, including electronic multimedia publications. This helped to fully meet the needs of the distance educational process. To form the student's external motivation, the authors used an electronic journal in which the types of current tasks, points for their completion, the student's rating for each type of tasks, as well as for all types of tasks in general, are defined. To support internal motivation, interactive learning elements were developed and implemented. The effectiveness of the use of digital resources was confirmed during the monitoring of students' success and by the results of the survey of the participants of the experiment. &#x0D; Conclusions. A significant advantage of the use of interactive components in the educational process should be considered the creation of conditions for a better understanding of theoretical material and using mathematical apparatus for solving real economic problems. The use of multi-level digital resources gives the student the opportunity to build an individual educational environment that increases internal motivation to study.
On-chip ultra-compact nonvolatile photonic synapse

The important research content of modern communication systems is to realize high-speed, stable, and intelligent information transmission and processing. All-optical neural networks based on the silicon integrated technology and phase change materials (PCMs) can realize picosecond-level modulation speed, faster processing speed, and lower energy consumption compared with the traditional electrical communication system. The photonic synapse is the core component of the all-optical neural network module, but the existing photonic synapses based on PCMs require a modulation distance (MD) of several micrometers or even ten micrometers to achieve a large output intensity range. In this paper, we propose an ultra-compact nonvolatile photonic synapse, in which MD can be shortened to 1 μm, breaking the record of the minimum signal MD of the silicon photonic synapse using the PCMs. At the same time, the output intensity range of our synapse is almost twice that of the existing research. Based on this photonic synapse, we analyze the relationship between the output response and incident wavelength, which can help to design an ultra-compact photonic convolutional neural network. This work has great potential in future photonic computing and photonic communication technologies.
EXPLORING THE REPRODUCTIVE BLACK MARKET: FERTILITY MEDICATIONS ON THE DARK WEB

This study aims to characterize the illegal trading of fertility medications on the dark web (a segment of the Internet not accessible by routine web browsers). Using specialized software, we reviewed anonymous marketplaces that sell illegal services/goods (e.g., forging documents, drugs, prescription medications, etc.) for the presence of fertility medications.
MACHINE-LEARNING ENABLED PREDICTION OF SUCCESSFUL SPERM RETRIEVAL FOR MICRODISSECTION TESTICULAR SPERM EXTRACTION

Successful sperm retrieval (SSR) for microdissection testicular sperm extraction (mTESE) is reported in only 50% of patients. Therefore, identifying demographic and clinical factors associated with SSR is essential to improve preoperative decision-making. We utilized machine learning (ML) to develop predictive models of SSR for mTESE. We retrospectively reviewed patients who underwent mTESE between 2002-2021. Demographic and clinical information including age, BMI, race/ethnicity, urologic history, semen volume, testis size, and preoperative testosterone, follicle stimulating hormone (FSH), and luteinizing hormone (LH) were collected. Univariate logistic regression was used to identify factors associated with SSR. Covariates with p<0.30 were included as inputs to each of five supervised ML models: elastic net-regularized logistic regression, random forest, support vector machine, neural network, and eXtreme gradient boosting (XGBoost). The dataset was partitioned into training (80%) and testing (20%) sets, and hyperparameter optimization was conducted in a 5-fold cross-validated fashion with training data. Lastly, models were assessed for accuracy, discrimination via area under the receiver operating characteristic curve (AUROC), calibration, and Brier score on the hold-out test set. 217 patients undergoing mTESE were included, of whom 123 (56.7%) had SSR. The random forest algorithm achieved the best performance in the hold-out test set (86% accuracy, 0.94 [95% CI 0.81-0.98] AUROC, calibration slope 1.33, calibration intercept 0.02, Brier score 0.10). The most important predictive factors associated with SSR in the ML model were preoperative FSH, preoperative LH, age at the time of mTESE, and preoperative semen volume. Per univariate logistic regression, preoperative FSH (OR 0.95, 95% CI 0.93-0.97, p<0.001), LH (OR 0.91, 95% CI 0.86-0.96, p=0.001), and semen volume (OR 0.67, 95% CI 0.55-0.80, p<0.001) were significantly inversely associated with SSR. Preoperative demographic and clinical factors, namely FSH, LH, preoperative semen volume, and patient age at time of mTESE, were utilized in ML models to accurately predict SSR for mTESE. This approach may improve prognostication for patients with male factor infertility.
Quantum approximate counting for Markov chains and collision counting

In this paper we show how to generalize the quantum approximate counting technique developed by Brassard, H{\o}yer and Tapp [ICALP 1998] to a more general setting: estimating the number of marked states of a Markov chain (a Markov chain can be seen as a random walk over a graph with weighted edges). This makes it possible to construct quantum approximate counting algorithms from quantum search algorithms based on the powerful ``quantum walk based search'' framework established by Magniez, Nayak, Roland and Santha [SIAM Journal on Computing 2011]. As an application, we apply this approach to the quantum element distinctness algorithm by Ambainis [SIAM Journal on Computing 2007]: for two injective functions over a set of $N$ elements, we obtain a quantum algorithm that estimates the number $m$ of collisions of the two functions within relative error $\epsilon$ by making $\tilde{O}\left(\frac{1}{\epsilon^{25/24}}\big(\frac{N}{\sqrt{m}}\big)^{2/3}\right)$ queries, which gives an improvement over the $\Theta\big(\frac{1}{\epsilon}\frac{N}{\sqrt{m}}\big)$-query classical algorithm based on random sampling when $m\ll N$.
Investigation of the Efficiency of Distance Learning in the Conditions of the Pandemic

In recent decades, the education system has been influenced by digital technologies, changing it. These changes had certainly been studied long before the pandemic, but the full transition to online learning occurred precisely in 2021 during the lockdown. The article analyzes and describes the trends in higher education that have tangibly and significantly affected its effectiveness under the conditions of the coronavirus pandemic. The tendencies that have been discussed and predicted by the scientific community require a deeper understanding from the standpoint of real pedagogical practice in order to resolve the consequences of the global educational crisis. The authors are convinced that education will not be the same as it was before the pandemic. We should evaluate the forms of online education and explore the motivation for learning since the education of the future depends on the search for new forms.