Reviewerly/exHarmony huggingface dataset:
PERANCANGAN APLIKASI ABSENSI KARYAWAN DENGAN MENGGUNAKAN QR CODE BERBASIS ANDROID

Employees are one of the most important assets for a company. With the satisfaction of employees for the company, it is possible for employees to provide the best for the company. Attendance is an important role in every work agency. Where attendance is one of the main supports that can support and motivate every work activity carried out in it. currently running an attendance system using manual attendance, namely using manual paper. This can result in several mistakes from both the shop and the employee, such as ineffectiveness due to using paper, forgetting the contents of the absence, not being recorded at the time of reporting in one month, or missing paper used. It can also cause carelessness for employees because of the risk of being absent when using manual attendance (paper) which causes manipulation of absent data. By using a QR Code, employees only need to print a QR code using a Smartphone or use a company device that employees can scan using a QR code. In this study, the method used is the waterfall method using Unified Modeling Language (UML) modeling. Then this application is designed with the help of tools from Android Studio and MySQL. This application was built with the aim of making it easier for store owners in attendance for their employees. Keywords: Employees, Attendance, QR Code, UML, Waterfall
Online portal for study and book donation

The point and object of this task are to set up an online gateway for the assortment of reading books so they can be given to the students who are out of luck. What this task will do is, gather the trade-in book from the understudy who has totally perused the book and completes his course effectively from the understudies and doesn't need the books any longer. After the assortment of these books, they would be given over to the NGOs which would check the books, and afterward whenever affirmed will be given to individuals straightforwardly or to the Government schools who will be giving out these books free of charge. Will the aggregate endeavors of the public authority, NGOs, and common society associations help in acquainting computerized activities with address the underlying difficulties and help in making learning seriously captivating and intriguing and simple to gather your books and In this project, we are also trying to cover the mode of online learning and preparation for higher study in village areas as well as city’s
Improving the Support Provided by a Collaboration Support System

Collaborative group projects can be messy and our students are often underprepared for them. The CoLab.online web application is designed to give project-based instructors the data and support they need to help their students develop the skills necessary for success. It's feature set includes weekly self- and peer-assessment with the results plotted on interactive charts for the instructor. It is interesting because it focuses students on reporting on the groups' internal dynamics rather than on evaluating their peers. A unique linked-slider interface makes the zero-sum approach clear by driving teammates sliders proportionally in the opposite direction of the one being moved. Furthermore, students are asked to assess their groups on a weekly basis, offering instructors a comprehensive picture, plotted on interactive graphs to help identify which teams are struggling such that the instructor can focus their team support efforts on teams that most need their help. The talk aims to enlist collaborators interested in developing our students' collaborative skills. The current effort focusing on improving the visualizations and the instructor experience to best provide the data, warning and tools necessary to develop our students team skills.
Opportunities for Remote Collaboration in a Social Web Search Model That Integrates Parents and Children: A Recent Advancement

Traditionally, search engines are designed to support a single user working alone. However, the construction of knowledge is enriched when one adds collaboration to search tasks. We identified opportunities for remote collaboration in a Social Web search model that integrates parents and children guided by 5W + 1H (who, what, where, when, why, how) dimensions. There are many good techniques in information retrieval for adults, but still not much scientific insight on how to design search engines for children in terms of both user interfaces and underlying algorithms. Our social search model aims at improving the search process for children. We found 7 opportunities for remote collaboration on the search process, based on implicit-explicit interactions. We propose to adapt the form of evaluation applied in Search Together to evaluate the prototype.
Android-Based Vehicle Collateral Storage Application at PT. Pegadaian (Persero)

The development of technology in this era of globalization is growing quite rapidly, one of which is a multi-functional device that is often used today is a mobile application as a medium for accessing information easily. PT. Pegadaian (Persero) is a credit institution that distributes credit on a legal basis for pawning. In the pawnshop line, Pegadaian can receive gold, electronic, and vehicle pawn services. For vehicle pawning, the validation process based on the condition of the car is still done manually using a checklist document, therefore the application is made using the Android Studio programming language to digitize the vehicle pawn process at Pegadaian which is designed using the Software Development Life Cycle (SDLC) method.
Problems and suggestions for improvement in technology and society division

While searching for lecture papers in the technical and social sectors, I found the lack of public information on the Japan Society of Mechanical Engineers department website. This is a matter that should be taken into consideration regarding the way the organization should be, and considering the impact of future departmental activities, we would like to make an immediate improvement proposal, and make a status report and an improvement proposal.
A polarization-based smoke removal method for surgical images

An improved smoke removal model for surgery is introduced with transmission parameters related to a medium’s optical depth rather than scene distance. Theoretical analysis and observation of experimental data shows that cross-polarized signals generated by multiple scattering are less affected by smoke compared to co-polarized signals. We analyze the transmission process of linearly polarized light interacting with different media, and then use polarization difference imaging and color channel information to detect smoke and estimate the transmission parameters. Several further processing procedures including parameter compensation and image smoothing are implemented to recover tissue visibility from surgical images.
Mercury vapour haloes in near-surface air above ore deposits and faults on Vancouver Island, British Columbia, Canada

&amp;lt;p&amp;gt;Volatile geogenic components, such as CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;, He, Rn, and Hg&amp;lt;sup&amp;gt;0&amp;lt;/sup&amp;gt;, form haloes in soil gas and near-surface air directly above mineral deposits. This contrasts with lithochemical, hydrochemical, and biochemical dispersion haloes that can be laterally displaced or obscured by transported overburden. Mercury vapour surveys have been used in exploration, because Hg occurs in most types of enogenic ore deposit types and is highly mobile. Low background concentrations in the atmosphere (1.2 to 1.5 ng/m&amp;lt;sup&amp;gt;3&amp;lt;/sup&amp;gt;) enable detecting even weak Hg emissions directly above buried ore deposits. In this study, we measured Hg vapour in air 1-50 cm above ground at 15 sites on Vancouver Island, British Columbia, Canada. To evaluate the effectiveness of the method across a range of settings, these sites include different types of known mineralized zones, barren rocks, and faults, both buried and exposed. The direct and continuous analysis via a portable RA-915M mercury analyzer reveals Hg vapour concentrations ranging from 0.5 to 54.4 ng/m&amp;lt;sup&amp;gt;3&amp;lt;/sup&amp;gt;. The highest Hg concentration was observed above tailings at the Bentley Au occurrence, possibly due to the amalgamation technique used for fine gold extraction between late 1800s and early 1900s. Prominent Hg vapour haloes mark shear-hosted Cu-Ag-Au sulphides at Mount Skirt (13.4x background Hg), epithermal Au-Ag-Cu at Mount Washington (8.9x background Hg), and sediment-covered polymetallic volcanogenic massive sulphides at the Lara-Coronation occurrence (4.2 to 6.6x background Hg). Basalt-hosted Cu-Ag-Au sulphide zones at the Sunro past producer are marked by weak Hg vapour anomalies relative to local background. Faults, including the Leech River fault, which was active in the Quaternary, are also marked by weak Hg vapour anomalies. The study confirms that, although the Hg level is influenced by weather, the real-time Hg vapour measurement of near-surface air can instantly delineate mineralized zones and fault structures that are buried under overburden 10s of m thick. In contrast to soil gas sampling, this simple and rapid technique can be applied to mineral exploration and geological mapping under overburden above any type of surface, including outcrops, talus, bogs, water bodies, snow, and permafrost.&amp;lt;/p&amp;gt;
PENGARUH METODE RESITASI TERHADAP PRESTASI BELAJAR SISWA PADA MATA PELAJARAN EKONOMI BISNIS

Abstract: Schools are institutions that provide learning, because learning processes can change a person's self to be better, the success or failure of learning requires a certain method. Providing appropriate and varied learning methods can be a motivational tool for students in a learning process, so that economic learning can be achieved, the right method is needed, not only students focus on the teacher, one of the right methods used in economic lessons is the recitation method, the recitation method is a teaching method in which the teacher assigns assignments to students and at the next meeting to be accountable for the results. The purpose of this researcher is to find out whether there is an effect of the recitation method on student achievement in economic subjects on the subject of class X MSMEs of SMK Al Fattah Kalitidu in the 2019/2020 academic year. In this study, researchers used quantitative research methods. By using the t-test formula to find the effect of the recitation method on learning achievement. Based on the results of the calculation of the hypothesis, it is known that the sig. (2-tailed) is 0.000 <0.05. Then H0 is accepted and Ha is rejected, so it can be concluded that there is an average difference between the pre-test and post-test, which means that there is an effect of using the recitation method on student achievement. Keywords: Resitation Method, Learning Achievement
Countering the Spread of Religious Extremism in Contemporary Society (the Case of the Federal List of Extremist Materials)

The article highlights the problems of countering religious extremism in Russia based on the results of the analysis of publications in the Federal List of Extremist Materials, which includes about 5 000 publications both in traditional print media and electronic materials posted on the Internet. The authors have analyzed editions covering religious issues from the viewpoint of lawfulness of recognizing them to be extremist ones. Main methods of studying religious materials to detect signs of extremism have been presented. The authors have identified the specificity of placing and distributing extremist religious information on the Internet, which is a source of spreading destructive ideas, ideologies, as well as a means of communication for extremist organizations. The paper briefly describes the activity of libraries working with the Federal List of Extremist Materials. Libraries receiving, storing and making literature available for public use should constantly analyze the information posted in the Federal List of Extremist Materials, and take appropriate measures to store and provide readers with documents of this kind in compliance with certain rules or to withdraw such materials from library collections. Thus, a library as a social institution counteracts the spread of extremist materials and, consequently, religious extremism in the society.
A PARALLEL HPC-BASED RESOURCE MANAGEMENT SYSTEM FOR BIG DATA APPLICATIONS

The amount of data produced in scientific and commercial fields is growing dramatically. Correspondingly, big data technologies, such as Hadoop and Spark, have emerged to tackle the challenges of collecting, processing, and storing such large-scale data.While the focus of big data applications is on handling enormous datasets, high-performance computing (HPC) focuses on performing computations as fast as possible. This is achieved by integrating heterogeneous hardware and crafting software and algorithms to exploit the parallelism provided by HPC. The performance capabilities afforded by HPC have made it an attractive environment for supporting scientific workflows and big data computing. This has led to a convergence of the HPC and big data fields.Unfortunately, there is usually a performance issue when running big data applications on HPC clusters because such applications are written in high-level programming languages. Such languages may be lacking in terms of performance and may not encourage or support writing highly parallel programs in contrast to some parallel programming models like Message Passing Interface (MPI). Furthermore, these platforms are designed as a distributed architecture, which differs from the architecture of HPC clusters.Alternately, the large volume of big data may hinder parallel programming models such as Message Passing Interface (MPI), Open Multi-Processing (OpenMP) and accelerator models (CUDA, OpenACC, OpenCL) from supporting high levels of parallelism. Based on the above-mentioned problems, there is a need to reduce the performance gap between HPC and big data applications while minimizing power consumption. To this end, this thesis puts forward the following research question: How can the performance of big data applications be enhanced on HPC clusters without sacrificing power consumption? A Hybrid Spark MPI OpenACC (HSMO) system is presented in this thesis as an answer to this question. HSMO relies on integrating Spark as a big data programming model with MPI and OpenACC as parallel programming models. Such integration brings together the advantages of each programming model and provides greater effectiveness. To enhance performance without sacrificing power consumption, the integration approach needs to exploit the hardware infrastructure in an intelligent manner. To do so, a mapping technique is proposed that is built based on the application’s virtual topology and the physical topology of the HPC resources. The presented approach in this thesis contributes to the domain of High-Performance Computing and Big Data and, more specifically, to resource management of HPC clusters, as well as to the areas of data locality and management of big data. The main contributions of this thesis include the novel integration and mapping approach itself, which supports big data applications on HPC clusters, the prototype implementation called HSMO, demonstrating the viability of the proposed approach, and a literature survey on relevant state-of-the-art research.
Multi-layer semantic interpretation of Aeronautical information

We present a hybrid architecture for knowledge extraction, in our future digital assistant for pilotsin commercial aircraft. We need to automatically decode aeronautical messages known as NOTAM(Notice to Airmen) and ATIS (Automatic terminal area information service). Those messagesinclude natural language sentences for operationally relevant information, particularly about theavailability of runways or taxiways, related limitations or procedures. For example, ILS APCHS INUSE RWY 36R, RNAV RWY 36L APCHS IN USE (“APCHS” stands for approaches, “RWY” standsfor runway). Such messages need to be reliably interpreted into a logical form, in order to: pushrelevant notifications to the pilot, answer his questions, or monitor flight’s compliance with applicableconstraints. Moreover, in case of pilot incapacitation during a single pilot flight, the aircraftshould be able to autonomously divert the flight.
Composite Re-Ranking for Efficient Document Search with BERT.

Although considerable efforts have been devoted to transformer-based ranking models for document search, the relevance-efficiency tradeoff remains a critical problem for ad-hoc ranking. To overcome this challenge, this paper presents BECR (BERT-based Composite Re-Ranking), a composite re-ranking scheme that combines deep contextual token interactions and traditional lexical term-matching features. In particular, BECR exploits a token encoding mechanism to decompose the query representations into pre-computable uni-grams and skip-n-grams. By applying token encoding on top of a dual-encoder architecture, BECR separates the attentions between a query and a document while capturing the contextual semantics of a query. In contrast to previous approaches, this framework does not perform expensive BERT computations during online inference. Thus, it is significantly faster, yet still able to achieve high competitiveness in ad-hoc ranking relevance. Finally, an in-depth comparison between BECR and other start-of-the-art neural ranking baselines is described using the TREC datasets, thereby further demonstrating the enhanced relevance and efficiency of BECR.
Are Indian Consumers Happy with Artificial Intelligence Enabled Personalized Customer Service

Both Indian and international businesses have adopted Artificial intelligence (AI) to provide customer services in the form of recommendation engines, chatbots, virtual assistants, etc across the Indian consumer market. Though advanced technologies lead to better services, customers’ perception of those services needs to be measured. This study surveys a sample of 1028 Indian consumers countrywide, their view on the AI-run customer services was measured via the questionnaire survey method by adopting convenience and snow-ball sampling techniques. Ten different viewpoints on the AI-run customer services were measured in both positive and negative aspects. Using Independent sample t-test and ANOVA, these variables were tested against the preferences for solving customer issues, demographics (gender, age, marital status), AI knowledge level, willingness to share personal data, and interaction with AI like chatbots and online virtual assistants. The results show that AI customer services are more appreciated by young consumers (25 years and below); male consumers; those who do not prefer human interaction for solving customer issues; those who have good knowledge about AI; those who are willing to share personal information and by those who have interacted with AI. Businesses need to upskill and invest in the right technology to provide a safe and personalized customer service to the end consumer. These results would benefit businesses to learn what the consumers really want and how to educate them to provide better services the way they want it by adopting new technology.
Quantum versus Randomized Communication Complexity, with Efficient Players

We study a new type of separations between quantum and classical communication complexity, separations that are obtained using quantum protocols where all parties are efficient, in the sense that they can be implemented by small quantum circuits, with oracle access to their inputs. Our main result qualitatively matches the strongest known separation between quantum and classical communication complexity Gavinsky (2016) and is obtained using a quantum protocol where all parties are efficient. More precisely, we give an explicit partial Boolean function f over inputs of length N, such that: Items (1), (2) qualitatively match the strongest known separation between quantum and classical communication complexity, proved by Gavinsky (2016). Item (3) is new. (Our result is incomparable to the one of Gavinsky. While he obtained a quantitatively better lower bound of $$\Omega\left(N^{1/2}\right)$$ in the classical case, the referee in his quantum protocol is inefficient). Exponential separations of quantum and classical communication complexity have been studied in numerous previous works, but to the best of our knowledge the efficiency of the parties in the quantum protocol has not been addressed, and in most previous separations the quantum parties seem to be inefficient. The only separations that we know of that have efficient quantum parties are the recent separations that are based on lifting Göös et al. (2017), Chattopadhyay et al. (2019a). However, these separations seem to require quantum protocols with at least two rounds of communication, so they imply a separation of two-way quantum and classical communication complexity, but they do not give the stronger separations of simultaneous-message quantum communication complexity vs. two-way classical communication complexity (or even one-way quantum communication complexity vs. two-way classical communication complexity). Our proof technique is completely new, in the context of communication complexity, and is based on techniques from Raz & Tal (2019). Our function f is based on a lift of the forrelation problem, using xor as a gadget.
Penggunaan Model Pembelajaran Problem Based Learning Untuk Meningkatkan Aktivitas dan Hasil Belajar Matematika Siswa Kelas VI Sekolah Dasar

This article aims to conceptually discuss the use of Problem Based Learning (PBL) learning models in student activities and learning outcomes in elementary schools, showing that with some efforts that have been made to improve learning activities and learning outcomes of grade VI students, but efforts have not been able to. running optimally, especially student activities that are decreasing, it is necessary to make efforts to improve the learning process, one of which is the Problem Based Learning (PBL) learning model. Based on observations, it shows that the Problem Based Learning (PBL) learning model has a good impact in terms of activities and learning outcomes, conceptually that the Problem Based Learning (PBL) learning model can be used as a model that is in line with improving the learning process which has a good impact on learning outcomes of students.
How Do You Prepare for the Unexpected Cyber Attack?

Last fall, in Northern California, the United States experienced its first ever deliberate large-scale and long-lasting blackout. Fueled by fears of increased devastating fires due to its century-old equipment, the region’s utility company shut off power to more than 1.5 million people forcing many evacuations. The impact was devastating; Michael Wara, a climate and energy expert at Stanford University, estimated the cost to California as up to $2.5 billion. For cybersecurity experts like myself, the blackout was a signal of just how precarious our reliance on electricity is, and how much we have to fear in cyberattacks. Think about what would happen if a cyberattack brought down the power grid in New York or even just a larger part of the country. As we saw in California, people could manage for a few hours -- maybe a few days -- but what would happen if the outage lasted for a week or more? If a larger population was targeted with a cyberattack on a utility, is an evacuation of millions of people feasible or desirable?