Reviewerly/exHarmony huggingface dataset:
ANALISIS TINGKAT KESULITAN GURU DALAM PEMBELAJARAN BERBASIS TEKNOLOGI INFORMASI DAN KOMUNIKASI (TIK) PADA MASA PANDEMI COVID-19 DI SDN GUGUS III MATARAM

Direct teaching-learning process in classroom is not supported due to pandemic covid-19. One of the solution is online learning. Elementary schools at Gugus III Mataram are among of the schools that successfully utilize online learning during covid-19. In practice, it is important to conduct an analysis related to the teacher’s difficulties in current ICT-based learning.  This study aims at finding out the difficulties faced by teachers in planning, implementing, and assessing ICT-based learning during the pandemic Covid-19 at SDN Gugus III Mataram. This research is descriptive qualitative with descriptive methods. There were 8 teachers as the subject of this research. The data collection was done through questionnaires and interviews.  SPSS 16.0 used to analyze the data (menu: Analyze-Descriptive statistic-Descriptive). Related to the difficulties in planning of ICT-based learning during covid-19, the result of the research reveals that 14% of teachers said it was not difficult, 42% of them said it was quite difficult, 37% of them said it was difficult, and 7% of them said it was very difficult. In terms of implementation, 7.5% of the teachers said it was not difficult, 29.5% stated it was quite difficult, 37% said it was difficult, and 7% of them said it was very difficult. Whereas regarding to the assessment, 9% of the teachers said it was not difficult, 40.5% of them claimed it was quite difficult, 32% said it was difficult, and 18.5% of them said it was very difficult. Considering the result of this research, the teachers should be innovative and discuss the problems with their fellow, the principal should evaluate the implementation of ICT-based learning during the Covid-19 pandemic and provide training on the use of ICT applications in learning, and other researchers should prepare comprehensive instruments to find out solutions related to the problems faced by teachers
Fault-Tolerance Testing on Small Quantum Error-Correcting Codes

Quantum computers hold the promise to solve some hard problems that are intractable for even the most powerful current supercomputers. One of the most famous examples is Shor's algorithm for factorizing large numbers, which has exponential speedup compared to its best classical counterparts. However, running such an algorithm will require to build a large-scale quantum computer consisting of thousands or even millions of qubits that include quantum error correction (QEC) and fault-tolerant (FT) mechanisms. Quantum computing is already a reality with the so-called Noisy Intermediate-Scale Quantum (NISQ) processors, some of them available in the cloud. Noisy refers to the imperfect control over the qubits and intermediate-scale to the relatively low number of quits (from fifty to a few hundred). Although current and near-term quantum devices will not have enough qubits for implementing large and fully corrected quantum computations, the use of small quantum error correction codes may extend the computation lifetime of NISQ devices. In this context and as a first step, it is important to test and demonstrate the fault-tolerance of these QEC codes. In this thesis, we explore the fault-tolerance of two small quantum correction codes that are good candidates to be applied to NISQ processors, the [[4,2,2]] code and the [[7,1,3]] Steane code. To this purpose, by following the FT criterion prosed by Daniel Gottesman in 2016, we tested both codes using two simulators, the stabilizer formalism simulator that includes quite simple error models and a full density matrix simulator called quantumsim, which includes more realistic noise. The simulations are performed under reasonable noise parameter values. For the [[4,2,2]] code, 235 circuits are tested based on the two simulators. The results show that in the stabilizer formalism simulation, the FT criterion is satised for all circuits, while not fully satisfied in the full density matrix simulation. For the [[7,1,3]] Steane code, we use a parallel-flag error correction implementation which is tested using the full density matrix simulator. Our results show that without applying any QEC cycle, for all circuits (84 circuits for 1 logical qubit simulation and 452 circuits for 2 logical qubits simulation), the error rate of the encoded circuits is lower than the unencoded ones. Adding a quantum error correction (QEC) cycle will in general increase the error rate of the computation.
Progress towards enabling quantum engineering

Ongoing research at SUNY Polytechnic Institute to enable large scale fabrication of quantum devices with tightly controlled performance characteristics will be presented. Josephson junctions and transmon qubits patterned with 193 nm lithography will be used to illustrate how advanced process tools can control critical dimensions of devices, necessary for building larger ensembles of qubits. Advances in the CMOS industry enable superior surface roughness and interface quality to be achieved across the entire 300mm wafer – some examples will be presented. The integration of photonic circuits (waveguides and on-chip cryogenic IR emitters) with superconducting Josephson junctions to enable large-scale neuromorphic computing structures in the near future will be discussed. Ongoing work on developing materials and processes for UV-transparent photonic circuits at 300mm will be presented – such chips could be useful as part of the interface to trapped ion qubits. The talk will wrap up with a discussion of the synergies in technology development, and functionality integration that can be achieved using an advanced fabrication facility.
CONSTRAINED GAUSSIAN PROCESS REGRESSION: AN ADAPTIVE APPROACH FOR THE ESTIMATION OF HYPERPARAMETERS AND THE VERIFICATION OF CONSTRAINTS WITH HIGH PROBABILITY

This paper focuses on the Gaussian process regression (GPR) of nonlinear functions subject to multiple linear constraints such as boundedness, monotonicity or convexity. It presents an algorithm allowing for the optimization, in a concerted way, of the statistical moments of the Gaussian process used for the regression and the position of a reduced number of points where the constraints are required to hold, such that the constraints are verified in the whole input space, with high probability, at a reasonable computational cost. After having presented the theoretical bases and the numerical implementation of this algorithm, this paper illustrates its efficiency through the analysis of several test functions of increasing dimensions.
LAPORAN KERJA PRAKTEK BERLYAR PENGOPRASIAN DAN PERAWATAN FRESH WATER GENERATORDI PT. SAMUDERA INDONESIAMV. INTAN BARUNA

OPERATION AND MAINTENANCE OF FRESH WATER GENERATOR TO MEET THE NEEDS OF FRESH WATERON MV. INTAN BARUNAFresh Water Generator on board is one of the auxiliary machinery to convert sea water into fresh water through the refining process, namely, the evaporation in the evaporator and condensing within condenser. The air craft has very important role in the smooth operation of the ship, where the operation of the ship can not be separated from the need of fresh water.So, important is the role of Fresh Water Generator on board the need for check and maintenance in order to keep maximum performance. Maintenance of the valve’s vacuum, checking the ejector pump must be done to determine the low preasure of sea water. Cleaning uses chemical materials, clean the condenser from possible to be damaged when clogged dirt so cleaned and repaired immediately.The result obtained from this study is the cause of their impaired absorption of the heat on Fresh Water Generator because are planted in sea water was dirty and containing high levels of salt taht cause the crust and corrosion, so it does not reach the heat absorption normaly to reach the optimal result.Keyword : Fresh Water Generator, operation, maintenance.
Collision-Free Path Planning for Efficient Inspection of Free-Form Surface by Using a Trigger Probe

Measurement path planning plays an essential role in on-machine measurement, which is often required to be time-saving and collision-free. This paper proposes a novel path planning methodology and develops an automatic collision avoidance strategy for measurement. Measurement points are generated by Contour section sampling (CSS), Grid mesh sampling (GMS), and Locally dense sampling (LDS) on the free-form surface. Afterwards, a shortest path algorithm (SPA) and a non-interference path algorithm (NIPA) are developed respectively. The simulations show that the proposed method can reduce the total inspection distance to nearly 7.82% than the original one. The presented path planning method can measure the surface of large aerospace parts directly by using a trigger probe.
Scholarship Eligibility Decision Support Using Naive Bayes Case Study : Sandjojo Foundation Scholarship

Until now there are no basic rules to determine the candidates that worthy to receive Sandjojo Foundation scholarship at Soegijapranata Catholic University. Therefore, the scholarship’s recipients are not well-targeted.This project can help to solve problems by using Naive Bayes algorithm as a media for decision makers with criteria such as based on GPA of the students’ registran, total parents’ income, and must be an active student in organization. By using the registrant’s previous data, Naive Bayes algorithm can study the data for each criteria that are inputted to determine whether the applicant is eligble or not to receive the scholarship from Sandjojo Foundation. This project made using web base application and has been tested four (4) times with various kinds of test data and training data, with the accuracy results are around 50% until 65% and the time is lower than three (3) seconds.
Webinar Pengabdian: Meningkatkan Kreativitas Seni Siswa SD di Masa Pandemi melalui Pemanfaatan Barang Bekas di Rumah

The implementation of online learning during this pandemic has a huge impact on the sector of education, one of those is the implementation of education at UPTD SDN 1 Munjuljaya which is identical to its musical activities. The learning process which carried out by online, especially in practicing the art activities is very difficult to do because it requires practice directly, so it causes the art creativity of students can’t be optimally developed considering the increasing spread of the covid-19 virus. One of the things that can overcome this problem is we carried out a community service through webinar with the theme “Improving Elementary School Students Art Creativity during the Pandemic through Utilizing Secondhnd Goods at Home”. The method that used id an online webinar via Zoom Meeting platform which is attended by 70 participants including students in grade 3, 4, 5, and 6. Through this webinar, the students are very enthutiastic in developing art creativity by utilizing secondhand goods at home although this activity carried out online. In this webinar, the students practice a beat by following the instructions of the speaker, they are also assigned to make a work, so its helps students to increase their creativity in using second-hand goods
Autoencoder-Based Model for Detecting Accounting Statement Fraud

The past two decades have witnessed several captions with incidents of corporate financial frauds in India. There is huge destruction in the wealth of investors as well as the society due to financial frauds. Not only local but also direct foreign investors may also give a second thought before investing in Indian companies. As per the cases registered in the recent past, especially Satyam and Wipro-World Bank have made investors rethink about investing in Indian companies with regard to the Indian business framework. In parity with developing countries, there are several cases of fraud in developed countries too. These cases created the urgency to develop the mechanism of detecting financial fraud worldwide in advance. If the fraud can be detected at an early stage, then investors can protect themselves from financial losses. These cases emphasize the need for all stakeholders to protect their investments by discovering fraud in its primitive stages by distinguishing between truthful and false information. For the current study, the researcher has collected 1000 data points of Non-Fraudulent companies and 86 data points of Fraudulent companies for the period of 2008–2020 for Indian manufacturing companies listed on the Bombay Stock Exchange. Artificial Neural Network Autoencoder model has been trained to learn the representation of the data of Non-fraud companies. This learning has been used to classify the financial statements among fraud and non-fraud companies. To train the model, 800 data points of only non-fraudulent companies were used. However, 200 data points of non-fraudulent with 86 data points of fraudulent companies were used for testing the model. The researcher is able to achieve 98.95% accuracy in the classification of fraudulent as well as non-fraudulent companies.
A Blockchain-Enabled Fog Computing Model for Peer-To-Peer Energy Trading in Smart Grid

The advancement in renewable energy sources (RESs) technology have changed the role of traditional consumers to prosumers. In contrast to the traditional power grid, the Smart Grid (SG) network provides a platform for peer-to-peer (P2P) energy trading between prosumers to buy or sell energy according to their requirements. The potential benefits of P2P energy trading can be realized through an efficient service provider of the communication network infrastructure. However, the current communication network is a trustless environment and thereby is unable to fully support the P2P energy trading requirements. Existing techniques in P2P energy trading with blockchain suffers from large network delay due to large network size; this further affects the network performance for P2P trading. In this paper, we present a novel Blockchain-Based Smart Energy Trading (BSET) algorithm along with a Blockchain-Enabled Fog Computing Model (BFCM) for P2P energy trading in Smart Grid. The proposed BSET algorithm provides a fully trusted minimum latency communication network that enables the prosumers to trade energy within their local premises. The algorithm was implemented using iFogSim, Truffle, ATOM, Anaconda, and Geth and evaluated against state-of-the-art communication network models for P2P energy trading. The simulation results revealed the effectiveness in terms of secure trading and network latency.
Improved and Dynamic Distance Measure Algorithm to detect the Fake and Clone Social Networking Accounts

Social media is a fast growing field in present days and more data is generating day by day. Social media is a platform for users to communicate with each other from anywhere in the world. Millions of new people are joining in the social media platforms. Online social media sites (OSMS) such as Face book, Twitter are used by the users to store and share their personal information. With the generation of huge data everyday many fake users are creating fake or cloned profiles to damage the social networking platforms with these profiles. Fake or cloned profiles are detected based on the set of rules that can classify fake or genuine profiles. Many existing approaches are used to find the fake profiles such as C4.5 and Cloned detection indexes. With these systems there is a lack of accuracy in result analysis. To overcome this we have proposed a new approach called as Linear Support Vector Machine (SVM) which is a dynamic and improved approach to find the fake profiles in OSMS. To improve the performance of fake profile detection, a robust preprocessing is integrated to the Linear SVM. The dataset is collected from the kaggle website which consists of 5000 fake profiles. Results show the performance of proposed system.
VOICE BASED EMAIL SYSTEM FOR VISUALLY IMPAIRED

Internet is one of the basic luxury for daily living. Every person is using the facts and information on internet. On the other hand, blind people face difficulty in accessing the text resources. The development in computer based handy systems has opened up numerous opportunities for the visually disabled across.
Is Smaller Always Better? - Evaluating Video Compression Techniques for Simulation Ensembles

We provide an evaluation of the applicability of video compression techniques for compressing visualization image databases that are often used for in situ visualization. Considering relevant practical implementation aspects, we identify relevant compression parameters, and evaluate video compression for several test cases, involving several data sets and visualization methods; we use three different video codecs. To quantify the benefits and drawbacks of video compression, we employ metrics for image quality, compression rate, and performance. The experiments discussed provide insight into good choices of parameter values, working well in the considered cases.
HOLISTIC EDUCATIONAL APPROACH: COOPERATIVE LEARNING AND MINDFULNESS IN THE TRAINING OF FUTURE TEACHERS

Traditionaleducationalinstructionis being replaced by new, more holistic paradigms requiring both a methodological change and a new definition of the role of the teacher and students. This study proposes a new education paradigm based on active teamwork methodologies (such as cooperative learning)and mindfulness techniques. Cooperative learning is a well-known strategy that has obtained very positive results in the development of competences and skills. Mindfulness techniques favor the development of attitudes and values as well as increase dinner-calm, resulting in lower levels of stress and anxiety among both students and teachers. The proposed paradigm was implemented in a course of the master’s degree program for Secondary School Teachers at the University of Almeria (Spain). The results show that students were more engaged with the learning process and developeda greater sense of responsibility and empathy,not only towards their own learning but also to their classmates’ learning. The procedure included the application of the Mindful Attention Awareness Scale (MAAS) at the beginning and at the end of the course to measure the evolution of the students in different items related to mindfulness.
Secure the Big Data of Patient Health Care using IOT Sensor

Internet of Things consist of extending the internet connectivity isolated standard devices of digital gadgets such as smartphones, tablets and laptops, to wide range of traditionally dumb or non-internet-enabled of physical devices on everyday objects. With users shattering and stand in line up for the upcoming big thing, who identify that the setting is persistently updating, and recognise their responsibility preserve up. Entrenched with technology of devices can lead into over the internet, and they can be monitored and controlled. Despite of keep information safe has familiar with vulnerability assessment, ethical hacking, public key infrastructure (PKI) security, and wireless network security will be key performers. Most of the IOT devices will be perform through digital devices and smartphones. External hardware and sensors are involves to develop apps that can communicate even more.
Perbandingan Pemikiran Tokoh Dalam Novel Dahlan dan Novel Penakluk Badai Serta Relevansinya Terhadap Pembelajaran Sastra Berbasis Karakter di SMA

This study aims to describe the differences and similarities in the thoughts of the characters in the novel Dahlan by Haidar Musyafa and the novel Penakluk Badai by Aguk Irawan MN and the relevance of novel analysis to literary learning materials in class XII high school. This research was a qualitative research. This study used a comparative literature approach with Damono's theory. The data collection techniques used in this study were documentation techniques, reading techniques, and note-taking techniques. Data were analyzed qualitatively with descriptive data presentation. The data were obtained through the literature study method. The data in this study were analyzed by describing the similarities and differences. The results of the study indicated the differences and similarities in the thoughts of the characters in the novel Dahlan and the novel Penakluk Badai and their relevance to literary learning materials in high school. The findings of this study on its relevance to literary learning in high school by including the story text in literary learning materials and as an example before students write a literary work.
IMPLEMENTASI ALGORITMA APRIORI UNTUK MENGETAHUI POLA KORELASI ANTAR PARAMETER KUALITAS DAN HASIL PRODUKSI TANAMAN PADI

Department of Food Crops, horticulture and Bone plantation in particular the production part is a part that is responsible for the recording of food crop data that occurred in Bone District one of which is rice crop. The number of activities of rice crop logging in the Agriculture service of Bone District generates a pile of data that is increasingly larger and one of the problems faced is the processing of rice crop data. The data used in the research is a data factor that affects the quality and yield of rice production, which will discuss about the association relationship between a number of factors affecting the quality and yield of rice production. The algorithm used is a priori algorithm by analyzing high frequency patterns namely looking for a combination of items that meet the minimum support and minimum confidence values for the establishment of association rules. The sample Data used as many as 60 incidents occurred in Bone district. The result of the study of 60 event data is a combination of items or quality factors and the result of rice production with the associated value of 20% support and confidence value 90%, resulted in 11 association rules. Information with the known factors that affect the quality and yield of the most common rice production in Bone District can be used by the Department of Agriculture crops, horticulture and plantation as the basis for conducting Actions required.
Software engineering in the Philippines: A survey and analysis of the academe and industry practices

This paper studied the state of software engineering practices in the Philippines. Survey, analysis of projects and interviews were conducted in the industry as well as the academe. Based on the survey results, most companies use agile method with scrum as the most preferred variant. Waterfall, prototyping and timeboxing are also evident in these companies, at times used together (e.g agile scrum-waterfall). The most common method used by students in software development projects is waterfall, followed by prototyping. There is a general awareness of agile-scrum in the universities studied, with the method implemented in one of the student projects. For companies, time-constraint and re-work due to requirement change or additional requirement remains to be the most common challenge. Planning in using agile method and frequency of scrum meetings can also be improved. In the academe, risk management can be complemented with issue management as a way to handle realized risks.