Reviewerly/exHarmony huggingface dataset:
Pengembangan Flipbook Berbasis Think Pair Share Pada Materi Pertumbuhan dan Perkembangan Pada Tumbuhan

Learning basically involves teachers and students as components of the audience. Professional teachers should be able to develop teaching materials independently according to the needs of students. However, teachers at Baiturrohmah Islamic High School Malang have not done this. Teachers still use worksheets on the market. Teachers have not used media that are able to motivate students in learning. The solution to this problem as well as the aim of the research is to develop a flipbook based on the Think Pair Share (TPS) model on plant growth and development materials. The research method uses R&amp;D with a 4D development model consisting of define, design, develop, and disseminate. The research instrument used a questionnaire. This research is limited to the develop stage. The results showed that the percentage was 87.5% (material expert assessment), 80% percentage (media expert assessment), 97.6 percentage (teacher assessment), 87.5 percentage (student readability test). Overall the product is ready to be used in learning
Correction to: FPGA Implementation of Optimized Code Converters with Reversible Logic Gates

Correction to: Chapter “FPGA Implementation of Optimized Code Converters with Reversible Logic Gates” in: D. Gupta et al. (eds.), Pattern Recognition and Data Analysis with Applications, Lecture Notes in Electrical Engineering 888, https://doi.org/10.1007/978-981-19-1520-8_26
Gold-bearing dolomite veins reveal multiple events as the cause of giant Au deposits

Giant ore deposit formation has commonly been considered to result from a single tectonic-hydrothermal event.A major weakness of this hypothesis is that such a large concentration of metals requires a huge flux over a long period, which is not common in geological processes.Here, we present dolomite U-Pb age data for multiple stages of formation and refinement in the production of the giant Zaozigou orogenic Au-Sb deposit in China.Disseminated (invisible) Au mineralization formed at 211 Ma during collision between the South China and North China blocks.Vein-style (native) Au-Sb ores formed at ca. 137 Ma, closely timed with reactivated compression between the South China and North China blocks.Refinement of gold occurred at ca. 89 Ma, coincident with orogenic collapse.Using this evidence, we propose a multi-stage model for Zaozigou.Multiple transient orogenic mineralization events can evolve throughout an entire collisional regime.Earlier orogenic mineralization at Zaozigou provided a favorable physical and chemical setting for later orogenic mineralization.Subsequent orogenic collapse triggers the pressure dissolution of the dolomite and quartz in auriferous veins, liberating metals from gangue minerals, reprecipitating metal, and upgrading ores.This model is consistent with geologic observations and does not require a huge flux and a single continuous tectonic-hydrothermal event as proposed by previous studies.
MENINGKATKAN PRESTASI BELAJAR MATEMATIKA PADA SISWA KELAS V MELALUI MODEL PEMBELAJARAN KOOPERATIF TIPE THINK PAIR SHARE

This study aims to determine the improvement of students' mathematics learning outcomes through the TPS type cooperative learning model. This type of research is classroom action research. The research subjects consisted of 32 students which were carried out in 2 cycles, namely cycle 1 and cycle 2. Students' mathematics learning outcomes increased through the Think Pair Share Cooperative Learning Model. This can be seen from the learning outcomes of the first cycle which are in the medium, with an average score of 59.22 from the ideal score of 100.00, an increase in the category in the second cycle which is in the high category with an average score of 72.97 of the score. ideally 100.00. Students' motivation to learn Mathematics has increased through the Think Pair Share Cooperative Learning Model. This increase can be seen from the experience of students, attention, and activeness of students in the teaching and learning process in accordance with the results of observations during implementation actions and from the results of student reflections.
Analisis Sentimen Terhadap Implementasi Program Merdeka Belajar Kampus Merdeka Menggunakan Naïve Bayes, K-Nearest Neighboars Dan Decision Tree

The development of technology are getting faster must be accompanied by the ability to adapt to changes from manual to digital, in the field of education. The Industrial internships, independent projects, student exchanges, community service projects, humanitarian initiatives, and other programs are part of the Merdeka Belajar - Kampus Merdeka program, which was launched by the Ministry of Education and Culture. The various of Merdeka Belajar -Kampus Merdeka program got a variety of responses from the public, including positive, negative, and neutral remarks posted on social media. The existence of these comments is able to create a growing sentiment among the general public and academics. Based on these problems, the researchers used twitter comments as a data source to conduct a sentiment analysis on the implementation of their Merdeka Belajar - Kampus Merdeka program. The data from Twitter will be categorized into positive, negative, and neutral classes using the Naïve Bayes method, K-Nearest Neighboars, and Decision Tree. There was a total of 475 data points divided into two groups: training data and testing data. The training data accounts for 80% of the entire data, while the remaining 20% is used for testing, with an accuracy of 99.22% for Naïve Bayes, 96.90% for K-Nearest Neighboars, and 37.21% for Decision.
Pengembangan Teks Eksplanasi sebagai Bahan Ajaran Melalui Pendekatan Genre Expository dengan Media Visual di Kelas XI SMA

This study aimed to develop an expository writing text module with an expository genre approach. The study used the 4D research and development method by Thiagarajan. The stages of this research method arecarried out at the stage of defining, designing, and developing without conducting the dissemination stage. The data consisted of primary and secondary data. The secondary data were taken from articles from relevant previous studies, and books. While the primary data are taken directly from expertsin the formo fan assessment of teaching material products. The study used the documentation techniques. The study used questionnaire to collect data. Then the collected data will be analyzed byusing the data analysis technique of Miles and Huberman. Through the assessmen to material experts, the resulting module received a final score of 3.88 as very validcriteria, and the overall average score of the product design assessment by design experts was 3.67 as very valid criteria. Based on these results, it is concluded that the prototype of the explanatory text writing module with visual media developed is valid and feasible to be tested for the next stage, namely the dissemination stage.
Dimensions of Beliefs Without Strong Supporting Evidence And Reasons for Holding Them

Beliefs without strong supporting evidence (BWSSE) can range from disruptive symptoms of psychosis to religious beliefs or conspiracy theories. The goals of the current study were to identify dimensions of BWSSE categories in the general public and to integrate them with the reasons for holding each dimension. Participants completed a BWSSE questionnaire online, and principal component analysis suggested that the questionnaire captured 6 dimensions of beliefs: Traditional Spiritual, New Age Spiritual, Science, Nonconformist, Supernatural, and Conspiracies. Mixed-model analyses of variance showed that stronger believers in Traditional and New Age spirituality attributed their beliefs more to personal experience, and stronger believers in Conspiracies more to education/personal research. This demonstrates that although spiritual beliefs are strengthened by personal experience, Conspiracy beliefs are strengthened by information gathering. This suggests that conspiracy beliefs may be more amenable to change, through the process of debiasing, if the information can be presented appropriately.
LiNA: Lightweight algorithm for secure internet of things

In the present paper a new idea has been proposed that involve a low-cost encryption/decryption algorithm called (LiNA cipher) that manipulate data with small devices of limited resources. LiNA works under the concept of symmetric block cipher with 64-bit size for data block and with ciphering key of 80-bit for the secret key. The proposal cipher looped with up to 12-rounds to increase data security and the complexity of decryption against the crypto-analysts. The LiNA structure is a product and iterated lightweight cipher with substitution and permutation network design. LiNA cipher implemented and designed by a series of logical and mathematical methods that reduced the gate equivalent (GE) efficiently to match the IoT embedded devices. The experimental results of LiNA cipher after the comparison to the other lightweight block ciphers shows an outstanding execution in the terms of performance and efficiency, especially, with low amount of (GE) that estimated by 1408 GE.
THE EFFECT OF DRILL TECHNIQUE TOWARDS STUDENTS’ VOCABULARY MASTERY IN LEARNING ENGLISH

This research was aimed to answer research question “Is there any effect of Drill Technique towards students’ vocabulary mastery in learning English?” The kind of this research was an experimental research in which divided into two groups were treated with differently which experimental group was by using drill group and second control group was using three phases. The sample of this research were all of first grade students at SMAN 1 Batulayar consisted of 75 students. This proved by figure of means group, the standard deviation and value of t-test was seen that the mean score of experimental group was higher than the mean score of control group (49.7 for the experimental and 4.47 for the control group). Based on statistical analysis using t-test showed that t-table 3.57 &gt; 2.00 t-table at confidence level 0.05 % (95%) and 3.57 &gt; 2.66 t-table at confidence level 0.01% (90%). Finally, it concludes that the use of Drill Technique has positive effect toward students’ vocabulary mastery in learning English at the first year students of SMAN 1 Batulayar in academic year 2021/2022.
An Overview of the Necessary Technologies and Implementation of an AI based Help Desk

A help desk is a platform used to maintain a huge customer base along with maintaining the goodwill of the company among the customers. Identification of the various issues and solutions, ways to fix the issues, customer feedback, along with the problems arising while the IT vendors are trying to develop solutions becomes easier and feasible. Managing all the requests sent to the help desk is a tedious task for the developers and the managers of the help desk due to the heavy flow of incoming queries. Thus, we have proposed a solution which automates this process and minimizes the processing time and resources for incoming requests. The solution uses an Artificial Intelligence (AI) based chatbot, which would be hosted on the company’s website and an email automation system. All the primary customer queries like basic product information would be handled by the chatbot at the company’s website level which will reduce the load on the email system. All the incoming emails would be answered in a systematic, real time manner by the email automation system. We have also built a User Interface (UI) where all the email logs would be visible to the concerned authorities, which provides them a complete authority over the functioning of the system. Thus, this solution provides a consistent way to reduce human costs that incur to the company and aims at targeting maximum customer satisfaction using applications of Artificial Intelligence, Natural Language Understanding (NLU), Natural Language Processing (NLP), Optical Character Recognition (OCR) etc.
T3VIP: Transformation-based $3\mathrm{D}$ Video Prediction

For autonomous skill acquisition, robots have to learn about the physical rules governing the 3D world dynamics from their own past experience to predict and reason about plausible future outcomes. To this end, we propose a transformation-based 3D video prediction (T3VIP) approach that explicitly models the 3D motion by decomposing a scene into its object parts and predicting their corresponding rigid transformations. Our model is fully unsupervised, captures the stochastic nature of the real world, and the observational cues in image and point cloud domains constitute its learning signals. To fully leverage all the 2D and 3D observational signals, we equip our model with automatic hyperparameter optimization (HPO) to interpret the best way of learning from them. To the best of our knowledge, our model is the first generative model that provides an RGB-D video prediction of the future for a static camera. Our extensive evaluation with simulated and real-world datasets demonstrates that our formulation leads to interpretable 3D models that predict future depth videos while achieving on-par performance with 2D models on RGB video prediction. Moreover, we demonstrate that our model outperforms 2D baselines on visuomotor control. Videos, code, dataset, and pre-trained models are available at http://t3vip.cs.uni-freiburg.de.
MFIM: Megapixel Facial Identity Manipulation

Face swapping is a task that changes a facial identity of a given image to that of another person. In this work, we propose a novel face-swapping framework called Megapixel Facial Identity Manipulation (MFIM). The face-swapping model should achieve two goals. First, it should be able to generate a high-quality image. We argue that a model which is proficient in generating a megapixel image can achieve this goal. However, generating a megapixel image is generally difficult without careful model design. Therefore, our model exploits pretrained StyleGAN in the manner of GAN-inversion to effectively generate a megapixel image. Second, it should be able to effectively transform the identity of a given image. Specifically, it should be able to actively transform ID attributes (e.g., face shape and eyes) of a given image into those of another person, while preserving ID-irrelevant attributes (e.g., pose and expression). To achieve this goal, we exploit 3DMM that can capture various facial attributes. Specifically, we explicitly supervise our model to generate a face-swapped image with the desirable attributes using 3DMM. We show that our model achieves state-of-the-art performance through extensive experiments. Furthermore, we propose a new operation called ID mixing, which creates a new identity by semantically mixing the identities of several people. It allows the user to customize the new identity.
PERANCANGAN RADIO FREQUENCY IDENTIFICATION (RFID) PADA TRANSAKSI PEMINJAMAN DAN PENGEMBALIAN BUKU DI PERPUSTAKAAN

Radio frequency identification or better known as RFID is a method of identification of objects that use radio waves. The process of identification by RFID Reader and RFID Transponder (RFID Tag). An RFID tag is attached to an object or an object to be identified. Each RFID tag has a unique identification number data, so no RFID tag has the same ID number. RFID Reader reads the ID number contained in the RFID tag so that the object or object can be identified. Radio frequency identification (RFID) applications have been widely developed. One of the RFID developed here is as a Transaction on Lending and Returning Books in a library with a Web system. The system is made easier for admins to carry out the lending process and the return transaction process because every transaction process that occurs is stored in the database.
UJI MODEL HIDROLIK FISIK (UMH-FISIK) PELIMPAH BENDUNGAN CIBEET DI KABUPATEN BOGOR

Among the vital components of a dam is the spillway structure. Therefore, the building requires testing of physical hydraulic models, one of which is carried out at the Water Hydraulics and Geotechnical Center laboratory. This physical hydraulic model test study aims to analyze the hydraulic behavior of the dam spillway, mainly the discharge curve and flow elevation, average flow velocity, flow direction pattern, and hydrostatic pressure. This study uses a physical hydraulic model (modeling), which is a research method that focuses on 3-dimensional physical modeling and using the initial design from the consultant (series 0) by modeling some of the core parts of the dam such as spillway structures, dam body structures, launch channels, energy dampers, some of the contours of the river upstream, and some of the contours of the river downstream. The research instrument used were: Thompson discharge measuring instrument, level meter as a means of predicting water level elevation, current meter velocity measuring instrument, floating object as a research aid, a piezometer to determine hydrostatic pressure. The results showed that the spillway capacity could drain the PMF return period discharge (QPMF = 2091,75 m3/s) with the available guard height of 1,25 m, meeting the planning criteria of 0,75 m. At the Q2th and Q25th discharges, there is no hydraulic jump in the energy reducer and leads directly to the transition channel. In contrast, at the Q100th and Q1000th discharges, a hydraulic jump occurs in the energy reducer. The flow velocity, downstream of the spillway, especially on the left side of the guide wall, was recorded at a relatively high velocity, allowing turbulence to occur. The flow direction pattern that occurs upstream of the reservoir is reasonably even towards the spillway, and there is no crossflow. There is negative pressure at the piezometer point P5 with a 2-year return discharge of -0,25 N/m2, a 25-year return discharge of -0,25 N/m2, and a 100-year return discharge of -0,15 N/m2, which is still within the safe limits and does not exceed the allowable provisions, namely -1.00 m (for pairs) and -4.00 m (for concrete).
Attendance Information System Utilizing Global Positioning System (GPS) Using Appsheet Application

In the current developing era, there are many ways to detect the presence of a person in an agency or company. Starting from the type of presence using fingerprints, the person's face and location, and the identification card at the institution the person works at. Many attendance lists use fingerprints but have shortcomings in the form of inaccuracies in the fingerprint application. Therefore, we conducted a study, designed and implemented an application to detect a person's presence using location using the Global Positioning System (GPS) method. This study aims to provide accuracy in carrying out a person's attendance list so that there will be no cheating by where someone does attendance according to that person's presence. In this study, in addition to using location as a basis for taking attendance, it is also equipped with the date, time, location, and real-time photos of yourself. The results obtained from this application are in the form of a person's attendance report that is accurate both from time and location as well as someone who does the attendance.
Vehicle Detection and Classification Algorithm Based on Improved Mask R-CNN

Vehicle detection and classification technology is an important part of ITS system. It is often used in traffic flow statistics, ETC non-parking charging system and other scenarios, which solves a series of problems effectively in traffic control. In this paper, we design ResNet-HDC feature extraction network and New-FPN feature fusion network to address coarse-grained vehicle classification and recognition problem. We improve Mask R-CNN algorithm and propose a vehicle detection and classification algorithm based on improved Mask R-CNN to complete accurate recognition and classification of vehicles. To further optimize the training results, vehicle images are preprocessed before the algorithm model training and high-performance Tesla T4-GPU processor is used to enhance image recognition during the training process. After training and testing, the results show that the method enhance the precision of vehicle detection effectively, and the average accuracy is increased by about 10%.
THE DEVELOPMENT OF A CLOUD-BASED UNIVERSITY RESEARCH REPOSITORY SOFTWARE USING A CONFIGURABLE SUBSCRIPTION MODEL

With more research that are added every year of every school calendar, there is no doubt the researches fell in a file or stack of hardbound that resides in the library. Unfortunately, this research should not only settle on the shelves. Making them electronically available as references, or to be cited are the ones it truly deserves. This paper emphasizes the need of a cloud-based research repository to be implemented in every university that can be utilized to serve its purpose. This research repository is based on an online publication and subscription model. Online publication provides reading sources via internet in which is accessible and more convenient to most people. The repository will also adapt the concept of configurability as the users may have their own preferences with regards on how they publish or subscribe a paper. These would give them more options on deciding how they would publish and or avail paper references. Research which are within the repository that will be referenced, cited, or downloaded has corresponding renumeration based on the approval of the University. In this way more researchers will continue to provide more scholarly output to be published and to gain more citing, downloads and eventually more renumerations. The repository has the potential to expand as more researchers will be turned its service and would be beneficial to stakeholders. The respondents on this paper shows the acceptability of the process making more likely to work in any educational institution. Moreover, as time progress, researchers and organizations would avail to use the software in accordance with their needs as well as the preferences of its user with the configurability of the software, thus providing a continuous educational-business process to all stakeholders. And with the current situation of the global pandemic heterogenous access to resources are all being sought.
Pandemic and Language Education: Lessons for Literacy Learning in Elementary School

Distance learning is presently followed via way of means of instructional establishments global to offer college students with ongoing education for the duration of the COVID-19 pandemic. The impact of the pandemic was felt at all levels of society, including in elementary schools especially in the learning activities. This study aims to determine the use of teaching materials used before and during the pandemic, as well as changes in learning activities in elementary school students. Design of the research is descriptive qualitative research. The data were collected through online questioner, documentation and interviews. Participants in the survey were the teachers of elementary school in Indonesia. Using examples of curriculum changes, student surveys, and exemplary student responses, this study provided departmental scholars with the opportunity to reassess their education system online and offline and renew their role as teachers. The findings were analyzed using a structural equation model. This research contributes as an evaluation material in the learning system during a pandemic so that it can improve the quality of learning both offline and online. Keywords: literacy learning, pandemic, elementary school