Reviewerly/exHarmony huggingface dataset:
Optical Convolutional Neural Network with Atomic Nonlinearity

An optical convolutional neural network is demonstrated in which linear operations are implemented by lenses and spatial light modulators, while an optical nonlinearity is realized by a cesium vapor cell as a saturable absorber.
LightHash: Experimental Evaluation of a Photonic Cryptocurrency

We propose LightHash , the first feasible photonic cryptographic hash function for blockchain technology using programmable photonic networks. We experimentally evaluate LightHash and assess whether photonic circuits can outperform digital competitors in latency and energy efficiency.
On-chip Training Silicon Photonic Circuits to Perform Digital and Analog Computing

We review our recent results on on-chip training silicon photonic circuits to perform digital (single and combinational Boolean logics) and analog (classification tasks in machine learning) computing.
Inference and Gradient Measurement for Backpropagation in Photonic Neural Networks

We experimentally demonstrate in situ backpropagation in a programmable nanophotonic interferometer network, achieving inference accuracies matching digital implementations. Error gradients are computed by simultaneously measuring optical interference at intermediate network components, eliminating expensive digital computations.
Help Not Wanted

Shows a photograph of the AgBot machine from AgWeed. It is designed to till, seed, feed, and weed plots of land.
Cryptocurrency and Global Practices: Lessons for Nigeria

This paper examined cryptocurrency and its global practices with particular reference to salient lessons for the Nigerian economy. The desk review methodology anchored on content analysis was used for the study. The paper identified distrust in political systems, weak domestic currency and high inflation rates as key factors fueling the growth of cryptocurrency usage in Nigeria thus motivating individuals to resort to cryptocurrencies as a tool for wealth preservation and inflation hedge. The study also found that the existence of trust deficit and challenges associated with privacy concerns, system uptime and stringent onboarding requirements were capable of derailing the success of the newly launched digital currency(‘e-naira’) issued by government to curtail cryptocurrency usage in Nigeria. The study concluded that cryptocurrencies and central bank issued digital currencies (CBDCs) are now part and parcel of the new economic order and represents the future of finance. It therefore recommended that nation states should work assiduously to develop uniformly agreed regulatory framework and global standards for the usage of cryptocurrencies.
The Linked Data Librarian – an emerging speciality or the new cataloguer

Purpose The purpose of this study is to come to an understanding of the role of the Linked Data Librarian as well as to explain why this librarian requires significant skills and knowledge in the area of creating and working with legacy library metadata. Design/methodology/approach Typical job positions for cataloguing and metadata librarians from two different librarian job posting websites were monitored and examined over the course of nearly three months. The findings from the analysis were compared with a new job posting for a Linked Data Librarian to answer the question regarding whether or not the Linked Data Librarian is just a new type of cataloguer or if the job posting represents a new speciality within librarianship. Findings The analysis found that in the early days the position of Linked Data Librarian will appear to be very much like a cataloguer and linked data librarian. As linked data technologies become established in libraries and Bibliographic Framework is eventually implemented, the position will take on its full Linked Data leadership role. Originality/value Seeing as the Linked Data Librarian position is a new one, little analysis of it and how it fits into the cataloguing and metadata department as well as the library in general exists. This paper seeks to fill that gap.
Perancangan Sistem Informasi Rekrutmen Karyawan Dengan Metode RUP

PT. Trikarya Cemerlang is one of the outsourcing companies whose business filed are provide janitor, security officers and others. PT. Trikarya Cemerlang has employee recruitment information system that is still manual or has not computerized yet. This system lack of effectiveness and efficiency. So we need a new employee recruitment information system design by using computerized system. By using web-based design new employee recruitment information system, hope it can help the company to recruit new employee, and also help the prospective employees to apply their application letter to the company. This research implement Rational Unified Process (RUP) methodology to develop the application. For the system design method is using the Object Oriented Analysis and Design method with UML diagram such as use case diagrams, activity diagrams, and sequence diagrams. As a result of the system, users easy to manage data, recruit employees, and process complete reports.
GLOBAL IMAGE IDENTIFIER

Many of the things, signs, and symbols we encounter when exploring the world might not be familiar to us. A global image identifier must be created to minimize confusion and misunderstanding. We shall use the less-than-universal traffic signs as an example. Road signs are strategically positioned to safeguard drivers’ and tourists' safety. Additionally, they offer instructions on when and where cars should turn or not turn. The traffic signs on the road express several cautions. In India, there are 400 traffic accidents per day, according to official statistics. Road signs ensure the safety of both automobiles and pedestrians by preventing accidents from occurring. Additionally, traffic signals reduce the incidence of traffic offences by ensuring that drivers follow certain laws. All users of the road, including pedestrians and automobiles, should give priority to traffic signals. For a multitude of reasons, including difficulty focusing, tiredness, and lack of sleep, we fail to see traffic signs. Other reasons for ignoring the indicators include impaired vision, the outside world's influence, and environmental factors. There is a critical need for a system that can recognize traffic lights automatically.
“Cum grano salis”

Abstract This short note is devoted to presentation of the essential points in the history of collaboration between the present-day Department of Computer Science and Artificial Intelligence of the University of Granada and the Systems Research Institute, Polish Academy of Science, with special emphasis on the place, taken in this collaboration by Control and Cybernetics . Thus, I mention encounters, conference meetings, jointly undertaken projects, as well as certain selected publications. In doing this, I also try to delineate the substance matter of the collaboration, which formed the backbone of it.
Axiological component in digitalization of health care and medicine

The basis of the modern industrial revolution is digitalization and artificial intelligence due to the influence of the digitalization process on all aspects of the economy, public life, including healthcare and education. The creation of a modernized healthcare system that would meet world standards implies an increase in both the quality and accessibility of medical care, which requires new technological solutions. The development of any new technology relies on digitalization, which has led to the creation of the Internet, robots, and artificial intelligence. Digital health is a new format for the medical industry to improve the efficiency and quality of medical care. The training of modern specialists provides for a significant change in teaching methods. The dependence of the quality of medical education on the multicomponent and increasingly digital nature of social reality is obvious. Additional special training of doctors for remote work is needed, the development of curricula taking into account the digitalization of healthcare. The relevance of the problem of digitalization of higher medical education involves an analysis of the state of modernization processes in medical universities, regulations on the electronic information educational environment of the university, including electronic information and educational resources, a set of information, telecommunication technologies and technological tools. The necessity of systematizing the social effects of the digitalization of higher education and conducting appropriate prolonged studies is substantiated.
Cyber ML-Based Cyberattack Prediction Framework in Healthcare Cyber-Physical Systems

Nowadays technologies play a major part in human lives and health. Machine Learning and related areas are booming and taking over the world right now. It is proved that Machine Learning often outdoes the humans in prediction of disease. Healthcare sector is getting benefited with the advancement in technologies. Cyber-physical system is a recent trend in technology advancement. Cyber-physical systems are the mechanisms which are controlled and monitored remotely. The proposed system considers the future critical concerns and challenges with cyber-physical systems and lists out such critical issues very elaborately. Machine Learning is the future of healthcare. It plays a major role in decision support system, enabling earlier prediction of disease and customized treatment plans to ensure the better performance and outcomes of the patients. Machine Learning in healthcare helps to analyze millions of patient data and provide suggested outcomes and defined resource allocation. Training a Machine Learning algorithm to predict the disease of the patients is a challenging task. A Machine Learning application does its job drastically to improve the health outcomes through algorithmic processes. In daily routine humans spend one-fourth of their work time on documentation related to regulatory and administrative process activities. Machine Learning algorithms could easily take over these routine tasks. Machine Learning in healthcare gets the highest score in sorting and classifying health data and supporting doctors’ clinical decisions and any kind of predictions that can save lives or make surgery less complicated.
Impact of COVID-19 on Students' Generic Skills - A Case Study in a University from a Developing Country

The education sector was considerably affected by the COVID-19 pandemic, risking the learning process and forcing governments to pull out contingency actions to ensure the students' development of generic and specific skills and guarantee education quality. These actions include the shift to online and hybrid (i.e., online and in-person) classes. This work assesses the pandemic effect on the generic skills of undergraduate students in a Colombian university. The study aims to determine the effect of COVID- 19 on the development of generic skills quantitatively. Two datasets were retrieved: i) A dataset with the scores obtained by the students in an institutional Generic Skills test and in the midterm tests; ii) A dataset with the students' scores in the Colombian standardized test for undergraduate students, called the Saber Pro test. Three analysis stages were performed: i) Univariate exploratory analysis; ii) Differential analysis to compare the No COVID vs. COVID scenarios; iii) A correlation analysis. Results showed that the scores of the Generic Skills and the Midterm tests increased significantly when comparing the two scenarios, except for the Written Communication. As for the Saber Pro test, only the scores for Written Comprehension, Quantitative Reasoning, and the global scores increased significantly. On the other hand, the correlation analysis showed a strong correlation only between the scores obtained at the Generic Skills and the Saber Pro tests for the English Proficiency skill. In addition, the analysis elucidated a weak correlation between the Generic Skills test's average and the Saber Pro's global score. Finally, the results prove that online education is a feasible alternative that offers students more flexibility to ensure the development of generic and specific skills.
Deep Learning with Electronic Health Record

This chapter discusses the evolution of electronic health record (EHR) and various applications of artificial intelligence (AI) and deep learning based on EHR in advancing drug research and development and providing better patient care. Three major types of real-world data include EHR, medical claim, and patient and disease registries. Various EHR data quality issues exist due to the observational nature of these data sets and complex data collection process and the use of various systems. The growing amount of EHR data and interoperability of various EHR systems, combined with AI and machine learning (ML) tools, present new opportunities for fresh insights about both patients and diseases. By using ML and data mining techniques, phenotyping algorithms can identify and characterize diseases, their subtypes, and clusters of comorbidities using EHRs, thereby enabling personalized healthcare. Risk prediction is an important step toward personalized medicine and patient-centric healthcare.
How cryptocurrencies get hacked

Digital currencies are designed to be “unhackable”, but that doesn't mean funds are safe from criminals, says Matthew Sparkes
Cash Information System Design Based on Website (Case Study on Café XYZ)

All human activities are very easy due to the rapid development of information technology. Website is a product of information technology. Currently, the use of websites has mushroomed everywhere as a promotional medium to other uses. Cafe XYZ is one of the sellers of various processed coffee drinks in Surabaya. Before the research was conducted, the cafe cashier's transaction process was still carried out in a conventional way only by relying on a notebook which was very inefficient. Not only that, it is also very difficult in the process of managing the data recap, the possibility of the data being lost is very high. The researcher offers a website-based information system design with the Laravel framework supported by a development method, namely SDLC (System Development Life Cycle) which is connected online on the internet so that it can be accessed by anyone and anywhere. With the design of this cashier website, it is hoped that it can help and simplify the transaction process, process product data collection, and also recap transaction data to be more effective and efficient and can save time and costs.
A Comprehensive Review and Analysis on Decentralized Payment Gateways

Blockchain technology has drawn enormous interest both in the academic and industrial sector. However, Blockchain technology is now used for a variety of experimental applications and explorations in the finance sector. Between centralized and Decentralized blockchain technology, Decentralized blockchain technology simplifies the transaction payment mechanism by establishing a decentralized general ledger to boost the regulatory capability by eliminating inefficient intermediates. In this study, We mainly focused on Decentralized Blockchain technology in the payment sector. Firstly, we briefly explored various decentralized application systems and analyzed current decentralized payment gateways, including their benefits and drawbacks. After that, analyse the blockchain technology for the payment system. Finally, we talk about different decentralization market clusters.
Study on Partial Discharge Information Entropy Characteristics in Oil-paper Insulation

The detection and characteristic of partial discharge of oil-paper insulation is an important means to detect the insulation status of converter transformers. In this paper, we simulate the actual operating environment of transformer, establish the oil-paper insulation needle-plate model, and obtain the partial discharge signal data under different conditions by changing the thickness of cardboard and the spacing between needle and plate. The feasibility of information entropy theory and application to partial discharge signal processing is analyzed. For the whole process of partial discharge, the characteristic parameters of the discharge signal are extracted and characterized according to the PRPD spectrogram and signal data. It provides an idea to explore more effective characteristic parameters to study the development characteristics of partial discharge of oil-paper insulation.
Open Source Solutions in Experimental Design: An Introduction to the Symposium

Abstract The Open Science movement has increased dramatically in popularity with deserved calls to action around transparency, access to resources, and inclusion in our field. However, its practical applications within experimental design have been slow to uptake, with researchers unsure where to even start with the dizzying array of open source hardware and software solutions available. The perceived time investment and unknown cost, especially in implementing open source hardware, has stagnated the implementation of inexpensive experimental solutions, but we sought to increase awareness to lower the barrier to participation in this space. While there are countless technical and financial advantages to integrating open source solutions into every biologist's experimental design, we put an emphasis on the “people” part of the equation in our symposium. This symposium championed innovative experimental designs by early career Society for Integrative and Comparative Biology researchers across all fields of biology, from plants to animals, in the lab or in the field, or even virtually engaging with the public and students. The Open Science movement operates within community norms that champion transparency, continuous development, and collaboration. These values are congruent with the priorities of reducing barriers to participation in science, and we hope our symposium's collection of open source solutions encourages readers to adopt these or other innovative designs into their own experimentation.
PENGARUH PENERAPAN SISTEM MOVING CLASS TERHADAP MOTIVASI BELAJAR SISWA PADA MATA PELAJARAN BAHASA JEPANG DI SMA CENDANA PEKANBARU

Various types of learning systems are implemented in schools depending on their respective policies. SMA Cendana Pekanbaru is one of the schools that uses a moving class learning system in the teaching and learning process. With this system, it is expected to improve the quality of the teaching and learning process, to increase student motivation and also to achieve student learning outcomes. The moving class system is a teaching and learning system characterized by students visiting the teacher in class. The purpose of this study was to find out how the moving class system was applied at Cendana High School Pekanbaru and how it affected students' learning motivation in Japanese subjects. This research is a descriptive research with the research subject is class XII students who take Japanese language specialization hours as many as 9 people. Data were taken by means of interviews, observations, documentation and questionnaires and then analyzed and drawn conclusions. The results of the analysis show that the teaching and learning process using the moving class system at SMA Cendana Pekanbaru has been going well and the moving class has a positive effect on students' learning motivation.
Searching for Axions with Superconducting Nanowires [Poster]

matching between the excited modes and the generated axion field. We also discuss the potential leakage noise effects and their mitigation, which is aided by O(GHz) separation between the spectator and signal frequencies.
Noun Incorporation in Bahasa Indonesia

Indonesian has always been ignored as a source of Noun Incorporation. This happens because of the agglutinative nature of Indonesian. This means that many words in Indonesian are formed by combining several morphemes. Even so, it is possible that in fact a lot of Noun Incorporation (IN) processes occur in Indonesian. This research uses Mithun and Rosen's approach in searching for Incorporation of Nouns in Indonesian. The results of this study reveal that the incorporation of nouns in Indonesian even though they are not productive, still occurs at level I and II. The incorporation of nouns of Mithun's ideas and also surprisingly (needs further investigation) occurs in two types of Rosen's ideas, namely Compounding Nominal Incorporation and Nominal Incorporation. Classifier. This research also reveals that many incorporation of nouns in Indonesian are idiomatic and according to (Mithun, 1986) this is common in several languages.
Case Analysis for Case Law Education Using Factors and Computational Argumentation Theory

In Chap. 4 , we proposed a new method of analyzing precedents by introducing the concept of legal topoi to the description of precedents based on factors, and at the same time, we conducted an analysis of 21 precedents on tax law intending to investigate the possibility of predicting judgments and showed that it is possible to observe the trend of judgments in tax law. However, the method in Chap. 4 could not sufficiently verify the logic of the precedents because the relationship between the claims of plaintiffs and defendants and the judgments of judges in the precedents depended on the hierarchical relationship of factors and legal topoi. Therefore, in this chapter, we will use computational argumentation theory to describe the claims of plaintiffs and defendants and the judgments of judges in an argumentation framework for further analysis and logical verification of precedents. Specifically, the bipolar argumentation framework (BAF), which is an extension of the argumentation framework (AF), and the extended argumentation framework (EAF) will be used together to look at the plaintiff and defendant from both sides, and at the same time, the court’s decision will be described and discussed in the form of an EAF.
Conclusion

In Chap. 3 , we proposed a method to automatically evaluate argumentation skills from the records of argumentation exercises. Using two scoring sheets Round A (competitive argumentations) and Round B (cooperative argumentations) of an intercollegiate negotiation competition as a reference, several evaluation items were selected for each type of argumentation (cooperative argumentation, competitive argumentation). We then asked the experts (A, B, and C) to score each of the sample argumentation documents subjectively, represented the individual argumentation records as a series of “speech acts + factors” (training data), and performed multiple regression analysis between the pattern of appearance of “speech acts + factors” in the training data and the scoring results. The scoring prediction model was constructed by performing multiple regression analysis between the pattern of occurrence of “speech act + factor” and the scoring results in the training data. This predictive model reveals what each scorer pays attention to when making evaluations. Using this model, we scored the argumentation records of the garbage house problem and found that the accuracy of judgments of high-scoring argumentations with a negotiation strategy score of 3.5 or higher was 80%, 70%, and 90% for scorers A, B, and C. The estimation accuracy of the record of high-scoring utterances with a good working relationship score of 3.5 or higher was as high as 90% for scorer A, 80% for scorer B, and 100% for scorer C. This indicates that it is possible to identify excellent answers with high accuracy even for evaluation items such as negotiation strategies and good working relationships, which are conventionally difficult to evaluate objectively.