Reviewerly/exHarmony huggingface dataset:
Quoka Atlas of Scholarly Knowledge Production: An Interactive Sensemaking Tool for Exploring the Outputs of Research Institutions

The vast amount of research produced at institutions world-wide is extremely diverse, and coarse-grained quantitative measures of impact often obscure the individual contributions of these institutions to specific research fields and topics. We show that by applying an information retrieval model to index research articles which are faceted by institution and time, we can develop tools to rank institutions given a keyword query. We present an interactive atlas, Quoka, designed to enable a user to explore these rankings contextually by geography and over time. Through a set of use cases we demonstrate that the atlas can be used to perform sensemaking tasks to learn and collect information about the relationships between institutions and scholarly knowledge production.
A study on cybersecurity awareness among students in Yobe: A quantitative approach

The emergence of the internet and also the use of various online applications and the exposure to the social platforms that are evolving day by day have positioned students to online risk. Online fraud, cyber-bully, phishing are among those risks students are exposed to in their daily activities. To find a solution to that, cybersecurity awareness can prepare them to protect themself against such risk. This research aims to investigate the students’ awareness of basic knowledge of cybersecurity. A quantitative approach was used for data collection using a set of designed questionnaires, this method was used to investigate the students’ cybersecurity knowledge and observe their behavior toward using the internet, from the survey a total of 201 Computer Science students in the Department of Computer Science at Yobe State University, Nigeria participated in the study. The research has encountered moderate responses from the students as all universities are close at this period due to the COVID 19 pandemic, only students living in urban were able to reach out in the study. The result obtained from the experiment were analyzed and it shows the University students' cybersecurity awareness is at a satisfactory level and more than average of the students are not well aware of how to protect their data. The research contribution is, there is no active cybersecurity awareness program in place, and also females’ students are more likely to be the victim of cyber-attack. Besides that, the survey also indicated a high enthusiasm for students to learn more about cybersecurity.
An analysis on the advancement of technologies and the presence of technological resources in teaching practice

Living in the 21st century, where Information and Communication Technologies, ICT, advance and become increasingly present in our daily life, it is expected that its use will extend to teaching practice and bring significant benefits in the teaching and learning process.In this article we have as objectives: to analyze the advancement of technologies; identify the main technological tools currently used by teachers in their pedagogical practice; to reflect on possible contributions that its use brings to the teaching and learning process and to point out the possible difficulties faced that still prevent its more effective use.For the formulation of this article, we initially used bibliographic research to give us a basis and then an online research, with teachers, regarding the use of technological resources in the classroom.As a theoretical contribution we use studies by authors such as Bruzzi (2016), Skinner (1972), Valente (1995), among others.We conclude, with this work, that the use of digital technologies in teaching practice exists yes, however several factors corroborate for its use to represent an improvement in the teaching and learning process.The use is conditioned to various factors such as equipment (hardware), software, teacher training, management, among others.The union of these elements or the lack of one of them makes success or not success happen.This leads us to a constant challenge of appropriating ICT in order to promote a quality education, which motivates people involved in the teaching and learning process to seek and participate in the construction of new knowledge.
발전 설비 지속 가능 운영 기술 연구

Purpose: It is important to operate safely and economically in obsolescent power plant facilities. Economical operation is related in the balance of the supply and demand. Safety operation predicts the possible risks in the facilities and then, takes measures to the facilities. For the monitoring of the power plant facilities, we needs several kinds of the sensing system. From the sensors data, we can predict the possible risk. Method: We installed the acoustic, vibration, electric and smoke sensors in the power plant facilities. Using the data, we developed 3 kinds of prediction models, such as, demand prediction, plant engine abnormal prediction model, and risk prediction model. Results: Accuracy of the demand prediction model is over 90%. The other models make a stable operation of the system. Conclusion: For the sustainable operation of the obsolescent power plant, we developed 3 kinds of AI prediction models. The model apply to JB company’s power plant facilities.
Using Internet of Things Determinants to direct towards e- learning in Sudanese universities

The current study aimed to identify the importance of the Internet of Things implementation in education, where the Internet of Things is the modern technological application that has captured the entire world by linking different beings with each other without human intervention. The study seeks to help the Ministry of Higher Education in Sudan to reduce the obstacles, difficulties and emergency conditions facing the educational process such as the Coronavirus pandemic, and to know the appropriate alternatives that can help in improving educational outcomes now and in the future. To achieve the goals of the study, a questionnaire was designed and distributed on a random sample consisting of (202) participants, representing the study community from faculty members in Sudanese Universities. The study relied on structural models because of its high validity tools, especially for qualitative data, for this reason, the AMOS statistical package was used. The study dealt with the determinants of the Internet of things represented in electronic platforms, virtual classes, and electronic obstacles. The study concluded that the obstacles have no effect in the model and that the effect size was weak reached 42%, which indicates that there are other variables that have a greater impact in the determinants of Internet of things. The study concluded that the Internet of Things provides many methods and tools that help faculty members to achieve valuable benefits for educational outcomes, thus facilitating their work and increasing student benefits. The study recommends conducting more studies and focusing on introducing the beneficiaries of the educational process (students) into the model.
MProve+ : Privacy Enhancing Proof of Reserves Protocol for Monero.

Proof of reserves protocols enable cryptocurrency exchanges to prove solvency, i.e. prove that they have enough reserves to meet their liabilities towards their customers. $\textsf{MProve}$ (EuroS&PW, 2019) was the first proof of reserves protocol for Monero which provided some privacy to the exchanges’ addresses. As the key images and the addresses are inherently linked in the $\textsf{MProve}$ proof, an observer could easily recognize the exchange-owned address when a transaction spending from it appears on the blockchain. This is detrimental for an exchange’s privacy and becomes a natural reason for exchanges to not adopt $\textsf{MProve}$ . To this end, we propose $\textsf{MProve}$ +, a Bulletproofs-based (S&P, 2018) NIZK protocol, which unlinks the key images and the addresses, thus alleviating the drawback of $\textsf{MProve}$ . Furthermore, $\textsf{MProve}$ + presents a promising alternative to $\textsf{MProve}$ due to an order of magnitude smaller proof sizes along with practical proof generation and verification times.
Using logic rules to achieve interpretable Convolutional Neural Network

Using logic rules in the Convolutional Neural Network (CNN) is helpful of CNN. The motivation of our paper is to show that there is a possibility to turn black box to white box. Moreover, in the proposed methodology, the output and output production (convolutional formula) will be interpretable. In our paper, it is shown that it would be possible to go from LCNN to CNN and vice versa. For this reason, score function is developed using quantum logic formula. Therefore, it is proven that there are some rules between input and output and the way of output production could be interpreted by the rules. This rules help us to understand CNN method.
Integration of geological and geophysical studies in order to mineral exploration at the Zaveh mineralization area, Khorasan Razavi Province, Iran

The copper deposit of Zaveh lies in the SE of the city of Torbat-e-Heydarieh and in middle of the Khaf-Kashmar-Bardaskan Magmatic Belt (KKBMB) in the Khorasan-e-Razavi Province. The lithology of the area consist of Jurassic and Cretaceous sedimentary rocks and Eocene volcanic units. Ore-formation is controlled by fault activity, representing vein-veinlet style E-W trending, formed within a conglomerate rich in quartz. Primary minerals are chalcopyrite, pyrite and arsenopyrite and secondary minerals contain malachite, azurite chalcocite, bornite, covellite, Cu sulphates, wad (Mn hydroxide), haematite, goethite, jarosite, limonite and (to a lesser extent) chrysocolla. The predominant alteration is silification which is associated with vein ore-formation. The volcanic units host propylitic, sericite, carbonate and silicification alterations. The ore-formation itself represents anomalies of Cu (2.1 % max), As (>1%), Sb (~105 gr/T), Pb (4371 gr/T) and Zn (1.1% max). Induced polarization and electrical resistivity (IP/RS) surveys unveil that the most chargeability anomaly corresponds to center of ore-forming vein and fault zone.The chargeability anomaly extends and amplifies with depth. The most amount of specific electrical resistance has been observed in the quartz-rich conglomerate. Interpretation of IP/RS data reveals that the chargeable source is extending in deeper beds (presumably sulphid ore-formation) which needs to be verified by boring operation. Geophysical surveys are significantly commensurate with field observations, ore-forming and geochemical data. Utilization Geophysical methods in different style of ore-deposits and interpretation of obtained information by means of geological, ore-forming and geochemistry data is considered to be a big step towards subterranean exploration and deposits modeling.
Homogeneous Architecture Augmentation for Neural Predictor

Neural Architecture Search (NAS) can automatically design well-performed architectures of Deep Neural Networks (DNNs) for the tasks at hand. However, one bottleneck of NAS is the prohibitively computational cost largely due to the expensive performance evaluation. The neural predictors can directly estimate the performance without any training of the DNNs to be evaluated, thus have drawn increasing attention from researchers. Despite their popularity, they also suffer a severe limitation: the shortage of annotated DNN architectures for effectively training the neural predictors. In this paper, we proposed Homogeneous Architecture Augmentation for Neural Predictor (HAAP) of DNN architectures to address the issue aforementioned. Specifically, a homogeneous architecture augmentation algorithm is proposed in HAAP to generate sufficient training data taking the use of homogeneous representation. Furthermore, the one-hot encoding strategy is introduced into HAAP to make the representation of DNN architectures more effective. The experiments have been conducted on both NAS-Benchmark-101 and NAS-Bench-201 dataset. The experimental results demonstrate that the proposed HAAP algorithm outperforms the state of the arts compared, yet with much less training data. In addition, the ablation studies on both benchmark datasets have also shown the universality of the homogeneous architecture augmentation.
의료시설 사업계획서의 건축사업비 산정에 관한 연구

Purpose: The purpose of this study is to provide an effective construction project cost estimation tool for preparing a business plan of healthcare facilities which can be practically used for development projects. Methods: In order to provide a tool for calculating construction project costs, this study analyzed the Building and Related Laws, the Building Technology Promotion Laws, the Ministry of Land, Infrastructure and Transport notifications and directives, the Ministry of Trade, Industry and Energy notifications, the detailed guidelines of the Ministry of Strategy and Finance, the Building Service Industry Promotion Acts, various certification standards, actual project budget calculation cases, etc. with advices from related experts. Results: 1) Construction cost is classified into construction costs, architectural design costs, supervision costs, incidental costs, and each sub-element. In particular, since there are many incidental cost items, essential items to be reviewed during planning are derived and costs are calculated according to appropriate consideration criteria. 2) Criteria for Payment calculation mainly applies the construction cost rate method or the actual cost fixed amount method in consideration of the characteristics and scope of work. Implications: There are many calculation factors that need to be applied to the construction project cost. Therefore, it is necessary to organize the calculation process more clearly.
La enseñanza de las matemáticas en un curso de formación en contexto de pandemia: la percepción de futuros profesores de matemáticas de Ecuador

The World has gone through a forced transformation process brought about by the sani- tary emergency that the Covid-19 pandemic caused. This situation trigged abrupt changes in all aspects of life, particularly, in education, where both teachers and students have not been equipped to face these conditions, as, suddenly, classrooms became improvised virtual learning environments. Under these circumstances, it has become significant to examine the perceptions that teacher-trainees at the Exact Sciences (Math and Physics) Pedagogy Major of Universidad de Cuenca have regarding the Math virtual classes that took place in their major during March and April, 2020. To attain this goal, a multiple-choice online question- naire was administered. The findings suggest that, although the major’s instructors apply some of the modern Math teaching and learning tendencies, several of them simply develop their traditional classes though a computer screen, without a significant methodological or strategical shift; this situation reveals a lack of training regarding the instrumental use of technological tools that support this new learning modality. Moreover, one can conclude that these virtual practices ought to be improved by means of new methodologies that prompt greater interaction among teachers and students.
A Fault Attack on the Family of Enocoro Stream Ciphers

A differential fault attack framework for the Enocoro family of stream ciphers is presented. We only require that the attacker can reset the internal state and inject a random byte-fault, in a random register, during a known time period. For a single fault injection, we develop a differential clocking algorithm that computes a set of linear equations in the in- and output differences of the non-linear parts of the cipher and relates them to the differential keystream. The usage of these equations is two-fold. Firstly, one can determine those differentials that can be computed from the faulty keystream, and secondly they help to pin down the actual location and timing of the fault injection. Combining these results, each fault injection gives us information on specific small parts of the internal state. By encoding the information we gain from several fault injections using the weighted Horn clauses, we construct a guessing path that can be used to quickly retrieve the internal state using a suitable heuristic. Finally, we evaluate our framework with the ISO-standardized and CRYPTREC candidate recommended cipher Enocoro-128v2. Simulations show that, on average, the secret key can be retrieved within 20 min on a standard workstation using less than five fault injections.
Chinese Language Learning and Mobile Technologies

China's global influence has increased with its spectacular economic development. With the growing trade and cultural exchange between China and other countries, there is a rapid rising need for Chinese language learning. Although Chinese language is challenging to learn due to its different intonations, complicated shapes, and considerable significance, it still attracts more individuals, organizations, and companies. Advances in mobile technologies provide new opportunities for language learning anytime and anywhere. To meet the diverse demands of students of language learning, many scholars have studied Chinese mobile language learning and developed many mobile applications to improve language learners' skills in listening, speaking, reading, and writing by leveraging the emerging mobile technologies. This chapter reviews earlier studies on mobile technologies employed in Chinese language learning and provides recommendations for future research.
Menimbang Preferensi Modalitas Belajar Pemelajar Nusa Tenggara Timur: Kajian Gaya Belajar Dan Strategi Belajar Bahasa

This research is about two learning preferences, namely learning styles and language learning strategies, in a group of learners who come from Nusa Tenggara Timur (NTT). The research objective is to describe the types of learning styles and the types of language learning strategies they used when learning Indonesian in tertiary institutions. The research data were obtained from students' answers to the statements listed in the VARK version 8.01 learning style questionnaire and the Oxford version 7.0 language learning strategy questionnaire, which was adapted in the context of learning Indonesian as a second language. The results showed that NTT students, who took Indonesian language courses at a private university in Yogyakarta, had one dominant learning style, namely the Kinestetic-Auditory [KA] type, and four types of language learning strategies, namely cognitive, metacognitive, affective and social strategies.
Case Role in the Urhobo Language

This paper examines case role in the Urhobo language. Case theory is used as theoretical frame work, the specific objectives is to investigate type of cases and to relate cases roles to argument structures in Urhobo. The study reveals that in the Urhobo language every lexically headed NP must receive case from a case assigner. The Case theory requires that the case assigner govern the NP to which its assigns case. Tense, verb and preposition are case assigners. The infinitive ‘to’ and the passive participles are not case assigners. Case assignment can take place only when the case assigner and the NP to which it assigns case bear a structural relation to one another. It also reveals that irrespective of the theory and its arguments, Urhobo verbs are the basses and centre of its expansion of its constructions. This research also finds out, that the argument structures identified in universal grammar (UG) align with the argument structure of the Urhobo language; the verb assigns arguments to the noun phrases in a sentence. This is traced to the structure of the Urhobo language which is subject-verb-object (SVO). Finally, the study reveals that the function of the nominative case is to mark the subject of the sentence; the vocative is the case of address; the accusative is used to mark the object of a transitive verb; the genitive is the case of possession, ablative case is to mark the instrument with which something is done and the dative case marks the indirect object in the Urhobo language.
JEM++: Improved Techniques for Training JEM

Joint Energy-based Model (JEM) is a recently proposed hybrid model that retains strong discriminative power of modern CNN classifiers, while generating samples rivaling the quality of GAN-based approaches. In this paper, we propose a variety of new training procedures and architecture features to improve JEM's accuracy, training stability, and speed altogether. 1) We propose a proximal SGLD to generate samples in the proximity of samples from the previous step, which improves the stability. 2) We further treat the approximate maximum likelihood learning of EBM as a multi-step differential game, and extend the YOPO framework to cut out redundant calculations during backpropagation, which accelerates the training substantially. 3) Rather than initializing SGLD chain from random noise, we introduce a new informative initialization that samples from a distribution estimated from training data. 4) This informative initialization allows us to enable batch normalization in JEM, which further releases the power of modern CNN architectures for hybrid modeling. Code: https://github.com/sndnyang/JEMPP
Innovative Learning through Fun Thinkers Media Based on Fill the Blank Question

Lack of student understanding of the material provided online by the teacher, students feel bored with monotonous learning using mobile phones, teachers provide materials and assignments through student books, the media used is still simple and less attractive. This study aims to develop media fun thinkers based on fill the blank questions for grade 1 elementary school students on theme 3 of my activities. Media development in this study is guided by the ADDIE model procedure which consists of several stages, namely analysis (Analyze), planning (Design), development (Development), implementation (Implementation), and evaluation (Evaluation). The trial subjects of this study consisted of 2 subject matter experts, 2 media experts, 2 practitioner responses, and 10 student responses (small groups). The data collected in this study, namely qualitative data and quantitative data. Data was collected using a questionnaire method with the distribution of rating scale instruments. The results showed that the average validity and reliability scores from the point of view of material experts were 4.3 with very valid qualifications and 93% with reliable qualifications, in terms of media experts it was 4.4 with very valid qualifications and 92% with reliable qualifications, from In terms of practitioner responses, it is 4.6 with very valid qualifications and 96% with reliable qualifications, and in terms of student responses it is 4.8 with very valid qualifications and 97% with reliable qualifications. This shows that the media fun thinkers based on fill the blank questions for elementary school students in grade 1 on theme 3 of my activities is declared suitable for use in learning. The implications of this research are expected to help students during online learning.
Quadratic-Curve-Lifted Reed-Solomon Codes

Lifted codes are a class of evaluation codes attracting more attention due to good locality and intermediate availability. In this work we introduce and study quadratic-curve-lifted Reed-Solomon (QC-LRS) codes, where the codeword symbols whose coordinates are on a quadratic curve form a codeword of a Reed-Solomon code. We first develop a necessary and sufficient condition on the monomials which form a basis the code. Based on the condition, we give upper and lower bounds on the dimension and show that the asymptotic rate of a QC-LRS code over $\mathbb{F}_q$ with local redundancy $r$ is $1-\Theta(q/r)^{-0.2284}$. Moreover, we provide analytical results on the minimum distance of this class of codes and compare QC-LRS codes with lifted Reed-Solomon codes by simulations in terms of the local recovery capability against erasures. For short lengths, QC-LRS codes have better performance in local recovery for erasures than LRS codes of the same dimension.