Reviewerly/exHarmony huggingface dataset:
Quantum computation of reactions on surfaces using local embedding

Abstract Modeling electronic systems is an important application for quantum computers. In the context of materials science, an important open problem is the computational description of chemical reactions on surfaces. In this work, we outline a workflow to model the adsorption and reaction of molecules on surfaces using quantum computing algorithms. We develop and compare two local embedding methods for the systematic determination of active spaces. These methods are automated and based on the physics of molecule-surface interactions and yield systematically improvable active spaces. Furthermore, to reduce the quantum resources required for the simulation of the selected active spaces using quantum algorithms, we introduce a technique for exact and automated circuit simplification. This technique is applicable to a broad class of quantum circuits and critical to enable demonstration on near-term quantum devices. We apply the proposed combination of active-space selection and circuit simplification to the dissociation of water on a magnesium surface using classical simulators and quantum hardware. Our study identifies reactions of molecules on surfaces, in conjunction with the proposed algorithmic workflow, as a promising research direction in the field of quantum computing applied to materials science.
Fintech Application: Artificial Intelligence and Blockchain

From academia to manufacture, artificial intelligence has a wide application and influence. on financial market. Finance is one of the earliest industries have a great connection with artificial intelligence. Through accurate profiling, neural networks and a series of artificial intelligence technology apply to finance. The traditional financial products, service way, credit finance invest decisions, risk control, etc. will have an innovation. Analysis of base, impact mechanism, development directions, risks on combination between artificial intelligence and finance has great theoretical value and practical significance to promote further combination between artificial intelligence and finance. Blockchain, originated from the concept of digital currency, has an extensive application in series of industries. Governments, financial companies, technology enterprise all over the world show great interest in blockchains. Blockchain, a rising distributed database protocol, apply cryptography technology, time-stamped chain data structures and distributed consensus mechanisms, have achieved decentralization, immutability, easy traceability and many advantages. Blockchains have solved the problem, high cost and insecurity of traditional centralized system, which has broad application prospects. This article focuses on two representative technologies apply in finance, artificial intelligence and blockchains. Start with the definitions of artificial intelligence and blockchains. The significance part is analysis on application of these two technologies. It compares different charge of robo-advisor platform and analyze non-performing loans rate to show the advantage of intelligence risk control. It also introduces five types and characteristic of blockchains, and uses ripple as example to show application of blockchains in cross-broader payments.
KINERJA PERGURUAN TINGGI DALAM PERSPEKTIF KINERJA LAYANAN, STRATEGI PEMANFATAAN TEKNOLOGI DAN KOMPETENSI SUMBERDAYA MANUSIA

Abstrak&#x0D; Tantangan global dan digitalisasi menjadi fokus perguruan tinggi menuju internasionalisasi. Menjawab tantangan tersebut dibutuhkan sistem tata kelola yang baik dalam upaya mencapai efektif itas dan efisiensi pencapaian visi dan misi perguruan tinggi. Penelitian ini bertujuan menganalisis kinerja perguruan tinggi dalam persepktif kinerja layanan, strategi pemanfaatan teknologi informasi, dan kompetensi sumberdaya manusia. Teknik analisis dilakukan dengan mixed method. Pengujian kuatitatif dilakukan dengan sampel para pengelola program studi. Analisis kualitatif dilakukan berdasarkan hasil diskusi dengan para partisipan yang terdiri dari dari beberapa pimpinan perguruan tinggi dengan akreditasi unggul dan memiliki information technology awareness yang tinggi, pengelola admistrasi akademik dan human resource pada obyek penelitian. Hasil penelitian menunjukkan bahwa strategi pemanfaatan teknologi informasi dan kinerja layanan berpengaruh positif terhadap kinerja perguruan tinggi. Peningkatan kompetensi sumberdaya manusia berpengaruh terhadap meningkatnya kinerja layanan, serta berpengaruh terhadap kinerja perguruan tinggi, namun strategi pemanfaatan teknologi informasi tidak berpengaruh terhadap kinerja layanan.&#x0D; &#x0D; &#x0D; &#x0D; Abstract&#x0D; Global challenges and digitalization are the focus of higher education towards internationalization. Responding to these challenges requires a good governance system in an effort to achieve effectiveness and efficiency in achieving the vision and mission of higher education. This study aims to analyze the performance of universities in terms of service performance, information technology utilization strategies, and human resource competencies. The analysis technique was carried out using a mixed method. Qualitative testing was carried out with a sample of study program managers. Qualitative analysis was carried out based on the results of discussions with participants consisting of several university leaders with superior accreditation and having high information technology awareness, academic administration managers and human resources on the object of research. The results showed that the strategy of using information technology and service performance had a positive effect on university performance. Increasing the competence of human resources has an effect on increasing service performance, but has an effect on the performance of higher education institutions. The strategy of using information technology has no effect on service performance.&#x0D; Keywords:&#x0D; higher education performance, service performance, technology utilization strategy, human resource competency
Tsunami Disaster Risk Assessment Using a Geographic Information System for Puger Sub-District, Jember Regency

The southern region of East Java is located on the Indo-Australian plate. The shifting of these plates allows for earthquakes that trigger tsunamis to occur. The earthquake leads to the impact of a tsunami in several areas, one of which is Puger Sub-District, Jember Regency. The main economic activity of the Puger Sub-District is the fishery; hence significant local coastal communities are vulnerable to tsunami threats. This study aims to map the tsunami risk using a Geographic Information System. The tsunami hazard map used the analysis of the tsunami inundation map from the BMKG. Vulnerability and capacity maps were prepared based on BNPB Chief Regulations. Vulnerability is evaluated based on social, physical, environmental, and economic data. Capacity considers components of the institution, early warning and risk analysis or evaluation, disaster awareness education, reduction of basic risk, and preparedness. The hazard, vulnerability, and capacity maps are classified into five classes. The tsunami risk map is then derived by overlaying the three input maps. Results showed that the villages with very high risk are Puger Kulon and Mojosari at the coastal front areas, covering an area of 13.01% of the total regional area of the Puger Sub-District.
SIMULASI TRANSISI METAMORFOSIS BENTUK CITRA MODEL FRAKTAL DENGAN LIMA KOMPONEN KOLASE ARAH RADIAL DAN VERTIKAL

Metamorphic as a keyword has several implementations in digital era. The basic implementation is in image processing that can be extended to other fields. The metamorphic process in image processing as a series transition visualization of two source images can be simulated in fractal model. As long as a pair of fractal objects of the iterated function system model uses the affine coefficients as a result of transformations in initial state, so it can be transformed to other states easily just applying gradually manipulation on each set of coefficients based on the interpolation values between the source and destination objects. In this paper there are two kinds of metamorphic transition effects on two pairs of fractal objects with five collage components discussed. The first model exhibits the metamorphic transition effect in radial direction and the second one exhibits the metamorphic transition effect in vertical direction between the pair of similar objects.
Pengembangan Arsitektur Knowledge Management System Untuk Model Bisnis Pendidikan Tinggi

The purpose of this study is to design and develop architecture and application of Knowledge Management System (KMS) with a deep and comprehensive analysis at XYZ University. To get a deep and comprehensive analysis, several tools and methods are needed. The collaboration is contained in the stages of this study, starting from the business area analysis to map the subjects needed in making databases, current condition analysis by mapping the needs of knowledge and measuring KM Readiness with Rao scale. Both analyzes produce centralized KMS architectural recommendations, website -based KM application designs accompanied and cost benefits analysis. The conclusion obtained is the Knowledge Management System is one of the real solutions for the organization in giving contributions to improvement of governance and human resources in the organization, the readiness of the organization in implementing knowledge management also affects the process of developing knowledge management systems, technology is one aspect which contributes to the development of knowledge management, besides that the Knowledge Manage-Ment System can be developed into tools to assist management in assessing employee activity aspects.
Wavelength encoded single-shot high-spatiotemporal resolution all-optical probe

The laser probe is one of the main techniques for capturing ultrafast dynamic processes and has extensive applications in fields such as plasma physics, photochemistry, and biomedical science. In this work, a time-wavelength encoded optical probe generation scheme is proposed, which uses cascaded frequency doubling crystals with different phase-matching angles and independent delay lines to achieve time-wavelength encoding. This method offers single-shot high-spatiotemporal resolution, high frame rate, and a wide range of adjustable time windows. The temporal resolution of the optical probe depends on the pulse width of the second harmonic, which can be adjusted by changing the phase-matching angle of the frequency-doubling crystal. The time window of the optical probe is only related to the change in the delay line, which can be adjusted by changing the length of the delay line. Therefore, the time resolution and time window of the optical probe are independent of each other. An optical probe generation system is constructed with 247 fs temporal resolution, 4 μm spatial resolution, 4.05 THz maximal frame rate, and an adjustable time window from sub-picosecond to 3 ns. The three-dimensional spatiotemporal evolution process of plasma filaments is captured within a single shot by using the optical probe. The experimental results show that the ionization front of the plasma propagates forward at a velocity of &lt;inline-formula&gt;&lt;tex-math id="M2"&gt;\begin{document}$ {\left(2.963\pm 0.024\right)\times 10}^{8}\;{\rm{m}}/{\rm{s}} $\end{document}&lt;/tex-math&gt;&lt;alternatives&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="22-20230727_M2.jpg"/&gt;&lt;graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="22-20230727_M2.png"/&gt;&lt;/alternatives&gt;&lt;/inline-formula&gt;, which is consistent with the theoretical prediction. This demonstrates the feasibility of using the probe for capturing ultrafast events. In the part of discussion, we analyze that the key parameters of the optical probe can reach a maximum frame rate of 35.7 THz, a maximum time resolution of 28 fs, and a time window range that can be adjusted from hundreds of femtoseconds to tens of nanoseconds. Finally, the optimal design parameters of the optical probe are given for different application scenarios. The optical probe generation scheme has good scalability and versatility, and can be combined with any wavelength decoding device, diffraction imaging, holographic imaging, tomography scanning, and other technologies. The high spatiotemporal resolution of the optical probe and the independent adjustability of its parameters provide a feasible solution for single-shot high spatiotemporal resolution captures of ultrafast dynamic processes on a multiple time scale.
Integration of English ‘teaching-learning-assessing’ in Chinese High Schools: A Literature Review

Classroom assessment has always been the focus of research on foreign language teaching, and "integration of teaching and assessment" has become a heated topic in international second language teaching field, but this topic has not yet attracted the attention of some scholars. In result, this paper retrieves the papers published domestic and abroad between 2017 and 2023 focusing on the "integration of teaching and evaluation" in English subject as data sources and analyzes the research contents. The results show that the research type of "integration of teaching-learning-assessing" is mainly theoretical research, but the number of empirical research is quite small. Besides, the theoretical research also shows an upward trend. The research objects are mainly secondary school English teachers and students. The research content focuses on the following four aspects: the definition of "integration of teaching-learning-assessing"; the implementation path of "integration of teaching-learning-assessing" in the classroom; the application of "integration of teaching-learning-assessing" in specific subjects and the investigation of "integration of teaching-learning-assessing" in the classroom. The data collection methods were mainly questionnaires, interviews and classroom observations. In the end of this paper, the future research and the development trend of "integration of teaching-learning-assessing" are pointed out.
Analisis Komparasi Algoritma Machine Learning untuk Sentiment Analysis (Studi Kasus: Komentar YouTube “Kekerasan Seksual”)

Cases of sexual violence in the last decade have been rampant in Indonesia. Cases of sexual violence are increasingly exposed, along with the increasing use of social media. One of them is violence against women. Cases of sexual violence often cause various kinds of stigma in the community, so this study aims to determine the public's response to cases of sexual harassment using sentiment analysis. The data used is sourced from YouTube comments with the title "Kasus Bunuh Diri NW: Bripda Randy Tersangka, Penanganan Polisi Dikritik | Narasi Newsroom." The method used is Machine Learning algorithms such as the SVM algorithm, Naive Bayes, and Random Forest. The results of comparing the three Machine Learning algorithms, Random Forest, obtained the best accuracy rate of 78% compared to the other two algorithms in conducting sentiment analysis on YouTube comments about sexual harassment discussions.
Perancangan Aplikasi Penjualan Berbasis Client Server Pada Kedai WKWK Kota Purwokerto Menggunakan Metode Prototype

Sales processes such as ordering and paying at the WKWK Kedai Purwokerto are still very manual, as is still using written notes and payment transactions are still carried out by manual calculations, this can result in errors in making payment transactions, so a Client Server-based sales application is made. With the creation of this application, the needs of admins and cashiers can make the ordering and payment process easy and fast and efficient. Sales application at Kedai WKWK Purwokerto City that can provide convenience in placing orders, payment transactions and managing important data in order to convey data information quickly, accurately and integratedly. A food and beverage sales application that was built on a Client Server basis, using the MySQL Database, Apache Web Server and PHP programming language, which is designed to handle the processing and management of data so as to produce reports in the form of master data, normative (numbers) and the matrix at Kedai WKWK Purwokerto City.
To Explore the Current Situation of Self-efficacy and Strategies to Improve the Self-efficacy of Secondary Vocational Students

Secondary vocational school student; Self-efficacy; Enhance strategy
A Study on the Usefulness of Internships

The purpose of this study is to examine the issues of internships in the Japanese accommodation industry and clarify the needs of both lodging industry workers and university students. This research conducted two different questionnaires. The first is about the human resource elements that the hotel industry requires in university graduates, and the second is about the feedback from the university students who participated in a one-month internship program at accommodation facilities in Japan. These results showed that mid- to long-term internships designed through industry-academia collaboration are considered to play an important role in the purpose of acquiring the human resource elements essential for the accommodation industry.
An Abstractive Automatic Summarization Approach Based on a Text Comprehension Model of Cognitive Psychology

This paper proposes a new cognitive abstractive text summarization model. The proposed approach is a double-stage system. First, text segments are mapped to salient topics, and a saliency score is computed for every sentence. Next, the summarization task is formulated as a fuzzy logic problem. Sentences ensuring maximum coverage and fidelity are selected to be part of a pre-summary. Sentences of the first stage’s output are rephrased using a T5 transformer. Experimental results show that the proposed approach outperforms three state-of-the-art summarization protocols.
Efficient Association Rules Minimization Using a Double-Stage Quine-McCluskey-Based Approach

Association rules are used to identify relationships between variables in large datasets. They help us explain obtained results in a transaction database by uncovering associations between items. One major limitation of association rules is the combinatorial explosion that occurs when the number of constructed rules is enormous. Several state-of-the-art techniques try to define a given threshold to overcome this issue; Rules with scores below previously established thresholds are deleted. Nevertheless, those threshold-based strategies have often implied the loss of salient association rules, which have yet to be scored higher than the established threshold because their context of extraction is not recurrent. Ditto, thresholds are usually established in a quasi-arbitrary way. This paper proposes a novel Quine-McCluskey-based double-stage approach that effectively reduces the number of association rules. The Quine-McCluskey technique is widely used in simplifying Boolean logic expressions. First, the number of initial association rules is reduced through the Quine-McCluskey technique. Next, we optimize the salient information loss rate. Conducted experiments show that the proposed approach significantly reduces the number of rules while keeping salient information.
Measuring Gender: A Machine Learning Approach to Social Media Demographics and Author Profiling

Social media has become a preeminent medium of communication during the early 21st century, facilitating dialogue between the political sphere, businesses, scientific experts, and everyday people. Researchers in the social sciences are focusing their attention on social media as a central site of social discourse, but such approaches are hampered by the lack of demographic data that could help them connect phenomena originating in social media spaces to their larger social context. Computational social science methods which use machine learning and deep learning natural language processing (NLP) tools for the task of author profiling (AP) can serve as an essential complement to such research. One of the major demographic categories of interest concerning social media is the gender distribution of users. We propose an ensemble of multiple machine learning classifiers able to distinguish whether a user is anonymous with an F1 score of 90.24%, then predict the gender of the user based on their name, obtaining an F1 score of 89.22%. We apply the classification pipeline to a set of approximately 44,000,000 posts related to COVID-19 extracted from the social media platform Twitter, comparing our results to a benchmark classifier trained on the PAN18 Author Profiling dataset, showing the validity of the proposed approach. An n-gram analysis on the text of the tweets to further compare the two methods has been performed.
A Content-Based Group Recommender System Using Feature Weighting and Virtual Users Aggregation

Recommender systems (RSs) are tools that help users to make decisions, when they face overloaded domains, suggesting the best items according to their tastes and preferences. Content-based RSs (CBRSs) are one of the most popular types of RSs, which work with items’ descriptions and users’ profiles to make recommendations. Besides, group recommendation systems (GRSs) are another type of RS which are focused on user groups rather than individual users, providing recommendations based on the group preferences. The present work proposes a new method of content-based group recommendations (CB-GRSs), which represents a line of work scarcely addressed by the scientific community, with three main novelties: weighting of item features, integrating group profiles in the set of user profiles and selecting dynamically the best aggregation function depending on the size of the group. An experimental study is carried out to show the advantages of the proposal with respect to previous works.
Efficient Course Management using Moodle Meta Course and Collaborative Teaching Assistant Support for Information Literacy Education

Many universities have established compulsory subjects related to information in the first-year experience to acquire information (media) literacy. At Ochanomizu University, quarter classes “Exercises in Information Processing (1)” and “Exercises in Information Processing (2)” are compulsory subjects for all students. There are a total of 13 classes with the same subject name, and they are organized and implemented for each department. The total number of participants was approximately 500. In the present study, we report a case study of class management using the Moodle meta course as an efficient use of common materials for 13 classes. In addition, each of the 13 classes is supported by a different teaching assistant, and we also considered methods for class management to ensure collaborative support among teaching assistants.