Reviewerly/exHarmony huggingface dataset:
ENHANCING STUDENTS’ VOCABULARY MASTERY THROUGH ANIMATED VIDEOS OF THE EIGHT GRADE STUDENTS AT SMP NEGERI 2 PARANGINAN IN ACADEMIC YEAR 2018/2019

This research is a Classroom Action Research with the objective of the study find out whether the application of animated movies significantly enhance the students’ vocabulary mastery. The research was conducted at the Eight Grade Students  of SMP N. 2 Paranginan in Academic  Year 2018/2019. The population of the research was 82, and the sample was 32 students. The sample was taken by applying cluster random sampling technique. The research was only done on one cycle for based on the students’ level of vocabulary mastery and paired t-test analysis, based on the students’ pre-test,  it was found that the students’ score is between poor and fail, in which there are four students who got 40 – 55 (poor), and thirty two students got 1.695518742, and the P value is 8.37038E-23. Based on this, the researcher concluded that the null hypothesis was rejected, and the alternative hypothesis was accepted, or there is a significant enhancement of students’ vocabulary mastery by taught by animated videos.
Implementing the Financial Performance Standards and its Significance in the attached Departments in Jordanian public sector

The investigation meant to decide the effect of the utilization of financial standards on the internal auditor's performance risk management standard, institutional control standard, and reporting standard in the public financial management sector in Jordan. To accomplish the investigation destinations; The analyst planned a survey disseminated to all officers, directors of internal control, internal and outer auditors, and heads of offices inside the examination populace addressed by the Ministry of Finance and its (5) units. (125) polls were disseminated to the example individuals, of which (109) legitimate surveys for the reasons for factual examination were recovered, with a reaction pace of (87.2%) of the circulated surveys. For the reasons for checking the investigation theories, unmistakable measurable strategies were utilized, notwithstanding straightforward and different direct relapse examination utilizing SPSS programming, to break down the attributes of the example and test the examination speculations.
An Efficient Functionality Learning Image Compression by Ift Technique

Image compression is the course towards apportioning an image into different size as adaptable for the customer to proceed , recollecting a definitive goal to change the depiction of a photo into something that is more fundamental and less referencing to survey. Value learning has been done in the zone of image compression. Since, most of the compression cycle just depends upon quality images. In Image compression, the quality of image is more important than other fields.This paper follows the regular Image picture division as a depiction issue and joins handiness getting the hang of recollecting as extreme goal to help the client from picking where to give sharp information. Explicitly part, our proposed structure overviews a surrendered division by building a "dubiousness field" over the image area thinking about cut-off, normal, flawlessness and entry terms. The client can continue managing the rule of the information on the solicitation plane, in this manner current giving extra preparing information where the classifier has the base conviction. Our strategy portrayals against capricious plane confirmation demonstrating a normal DSC [Dice similarity coefficient] change of 19% in the hidden five plane proposals (pack questions).
Google Docs Data Curation Primer

This work was created as part of the “Specialized Data Curation” Workshop #3 held at Washington University in St. Louis, MO on November 5-6, 2019.
Design Optimization of Heat Exchanger by Old and New Generations Metaheuristic Optimization Algorithms: Insights and Comparisons

This study compares the performance of 3 old generation algorithms namely Genetic Algorithm, Particle Swarm Optimization, and Differential Evolution with two new generation algorithms namely Firefly Algorithm and Symbiotic Organism Search in the optimization of the heat exchanger. The optimization procedure involves the selection of the major geometric parameters such as tube diameters, tube length, baffle spacing, a number of tube passes, tube layout, head type, baffle cut, etc., as per TEMA standard and minimization of total annual cost is considered as the design target. The methodology takes into account the geometric and operational constraints typically recommended by design codes. Three different case studies are presented to demonstrate the comparative effectiveness and accuracy of the proposed five algorithms. From the results of all the three case studies, it is concluded that DE performed the best in terms of capturing the lowest value of total cost and minimum execution time. The new generation algorithm, SOS performed the second-best as it captures the lowest values of total cost every time, honors the constraints every time in reasonably low execution time. The final optimized heat exchanger complies with the TEMA standard, having the lowest cost, and obeys all geometry, velocity, and service constraints.
PREDIKSI INFLOW DAN OUTFLOW UANG KARTAL DI PROVINSI BALI DENGAN METODE NEURO-FUZZY

In this paper, we present a novel approach to data-driven neuro-fuzzy modeling, which aims to create accurate monthly inflow and outflow forecast of money (M0) in Bali Province. The data is monthly time series included some religious ceremony identification variables and a monthly dummy variable from January 2011 to March 2019. Well known, Bali Province has unique cultures, the only one province which Hinduism majority religion in Indonesia, and listed as top tourism destination in the world. The neuro-fuzzy models were created using ANFIS architecture and sliding window time series analysis, then simulated using walk forward validation, interpreted using MAPE, and NRMSE. Based on the simulation of the last 24 months, the model of inflow obtained MAPE 23.33% (worth considering) and NRMSE 18.68% (accurate). Meanwhile, the model of outflow obtained MAPE 19.24% (accurate) and NRMSE 8.71% (very accurate). These models and their pieces of information could assist the central bank in Bali Province to prepare cash for money (M0) outflow and managed technic for counting money (M0) inflow.
THE ANALYSIS OF WRITING ERROR IN FACEBOOK ACCOUNT: JUAL BELI DAERAH RANGKASBITUNG- LEBAK BANTEN GROUP PERIOD OCTOBER- DECEMBER 2020

In some social media they will advertise their product with an interesting picture or even with the text advertise. We can easily find the mix languages between Indonesian and English as the text description for some product. The aim of this study is to analyze writing error in Facebook: Jual Beli Daerah Rangkasbitung-Lebak Banten Group period October-December 2020. This research was conducted using descriptive qualitative research. The result shows that written errors were found in the writing of a post in the group, but this did not really affect the error in conveying the meaning of the word. The result after we analyze Facebook group that called Jual Beli Daerah Rangkasbitung-Lebak Banten Group period October-December 2020, they have some mistakes or errors on their post. The mistakes can happen because they didn’t know how to pronounce that, and just write them based how they pronounce and didn’t know or try to know the correct spelling in English language. Keywords : Writing Error, Code Mixing, Linguistic, Social Media
Activity Recognition From Smartphone Data Using WSVM-HMM Classification

A lot of real-life mobile sensing applications are becoming available nowadays. The traditional approach for activity recognition employs machine learning algorithms to learn from collected data from smartphpne and induce a model. The model generation is usually performed offline on a server system and later deployed to the phone for activity recognition. In this paper, we propose a new hybrid classification model to perform automatic recognition of activities using built-in embedded sensors present in smartphones. The proposed method uses a trick to classify the ongoing activity by combining Weighted Support Vector Machines (WSVM) model and Hidden Markov Model (HMM) model. The sensory inputs to the classifier are reduced with the Linear Discriminant Analysis (LDA). We demonstrate how to train the hybrid approach in this setting, introduce an adaptive regularization parameter for WSVM approach, and illustrate how our proposed method outperforms the state-of-the-art on a large benchmark dataset.
LibGuides: Literature of World Cultures: Further Questions?

This LibGuide provides tips on researching World Literature, writing papers, and choosing some books to read just for fun.
Motion and Interaction Tracking Tool for Virtual Reality Environments

Evaluating user behavior in virtual reality environments is a challenging task, requiring leading with spatial user freedom and with non-conventional visualization and interaction devices. By gathering and analyzing user movements and interactions, researchers and even game designers can notice important behavioral patterns and correlations. This paper aims to present an automatic motion and interaction tracking tool for virtual reality environments that allows researchers and game developers to move from the pure observational paradigm, such as video recording and questionnaires, to one that considers quantitative data. After gathering users’ data, the tool automatically generates charts to assist the analysis process and also allows the replaying of all user behavior executed in the application. A case study case is shown in which a user navigates and interacts in a virtual reality city performing instrumental activities of daily living (IADL). Using the tool presented here, we conclude that tracking user behavior automatically in a virtual reality environment is possible. To facilitate the software development process, we have developed a Unity Asset, allowing developers to use the tool easily by importing our asset into their projects.
Implementasi Sistem Informasi KRS Online dengan Metode Software Development Life Cycle Model Waterfall

Efarina University is one of the universities in North Sumatra that still uses KRS manually. Using Course Selection manually will cause the data not well organized. It will increase the risk of damage and loss of data for active students and alumni, especially now that we have entered the era of the industrial revolution 4.0. Therefore, an integrated information system is needed to manage and manage student Course Selection data properly. For that, a method is needed to implement all the processes for creating the application. The method used is the Software Development Life Cycle (SDLC) Waterfall model with five (5) fundamental stages, 1) requirements analysis, 2) system design using UML (Unified Modeling Language), 3) implementation of the planned system, 4) evaluation with blackbox testing to ensure the system runs well, and lastly 5) repair (maintenance). With this method, the application runs in line with the previous plan and thus and reduces data loss for course selection. It is also easier for lecturers and students to fill out and implement student course selection administration.
Best Wireless Photo Printers

Nothing quite beats the simplicity that wireless technology offers and this time it is being employed in a photo printer to offer you a clutter-free, ...
Bee Resto: Food Ordering Apps for Individual Restaurant

The increasing number of restaurants has made the industry became more competitive. All restaurants keep improving the quality of their operation especially providing good customer service. The most common service offered by restaurants is ordering the food using the traditional method. The traditional method can be considered if the restaurant does not have a large number of customers. But if there are a lot of customers in the restaurant, it will pose various problems for the restaurant staff. In today’s market, using advances Technologies have many benefits to improve service quality like in terms of time savings and ease of restaurant and customer affairs. Therefore, this study was conducted to develop a food ordering application for an individual restaurant which is Kayu Kitchen Restaurant. This application was developed using a platform known as Mit App Inventor. The research method used in this study is waterfall Development based Methodology with the following phase: planning phase, analysis phases, design phase, and development and implementation phase. The result of this research is an ordering food application based on Android for Kayu Kitchen Restaurant and all core functions were developed successfully. The apps help restaurant management increases efficiency and reduce human error and provide convenience for both employees and customers. It can be concluded that this application is an attractive solution for the restaurant industry. For future work, order history can be added as the feature to show customer’s order history and also to be developed on other platforms such as an iPhone OS.
A Study of Meaning Construction of XY Series Neologisms

This study examines the word formation of XY series neologisms, where y is fixed and x is replaced by other words. Cho (2019) suggests that H-type word formation should be accepted as one of word formation processes considering the differences of meaning between the parent word and its series. Ahn and Cho (2019) discuss the similarities of the XY series neologisms with the H-type word formation in the case that the parent word serves as a basis for series production, whether the word formation of the parent word belongs to blending or compounding. This study focuses on the meaning construction of series neologisms, such as the –gate series, within a cognitive framework. To this end, Booij’s (2013) analysis of morphological constructions is explored. Once the segmented part, that is, the remnant, becomes part of constructions or schemas, the meaning of the segmented part, a semantic preserver inherited from the parent word, is inherited into the series neologisms. As in Construction Grammar, meaning is attributed directly to schematic constructions.
The Relationship Between Information and Communication Technology (ICT), International Migration and Economic Growth in Turkey

The paper examines the information and communication technology-international migration-economic growth nexus for Turkish economy using annual time series data covering the period of (1998-2019). Toda-Yamamoto Causality Test (TY) was used in the application of econometric method The results obtained indicated that there is a unidirectional causality from international migration to economic growth in the long run for Turkey. This is inline with the empirical evidences that external immigrant movements can promote economic growth in receiving country. Although the form of migration to Turkey is unclear in terms of skilled or unqualified labor force, international migrants, even including daytripper workers from neighbour countries, boost the economic activities especially in agriculture, construction and service sectors in Turkey. The paper also concluded that there is a one-way causal relationship between ICT and economic growth. The ICT usage can make a substantial contribution to economic growth of Turkey so Turkish government should improve the infrastructure of Internet and mobile phone with a conscious policy initiative. Besides, lastly, it is observed that there is not a causal relationship between migration and ICT at 5 % for Turkey. It’s found that there is a unidirectional causality from migration to ICT at 10 %.
A Brief Note from the New <i>BSSA</i> Editor-in-Chief

Research Article| September 14, 2021 A Brief Note from the New BSSA Editor‐in‐Chief P. Martin Mai P. Martin Mai 1King Abdullah University of Science and Technology, Thuwal, Saudi Arabia Search for other works by this author on: GSW Google Scholar Bulletin of the Seismological Society of America (2022) 112 (1): 1–2. https://doi.org/10.1785/0120210220 Article history first online: 14 Sep 2021 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Tools Icon Tools Get Permissions Search Site Citation P. Martin Mai; A Brief Note from the New BSSA Editor‐in‐Chief. Bulletin of the Seismological Society of America 2021;; 112 (1): 1–2. doi: https://doi.org/10.1785/0120210220 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentBy SocietyBulletin of the Seismological Society of America Search Advanced Search Just a few weeks ago, I officially started a new chapter in my scientific life. On 1 July 2021, my transition into the role as Editor‐in‐Chief (EIC) for the Bulletin of the Seismological Society of America (BSSA) began, working side by side and learning from Thomas Pratt, who has led BSSA since 2016. To be frank, in early 2021 I did not imagine that my academic path may lead this way … and now, I am taking off onto a new trail of experiences and challenges. So, what happened? Rewind.BSSA was launched in 1911. Since then, BSSA... You do not currently have access to this article.
METODE 划线分析法 [HUÀXIÀN FĒNXĪ FĂ] UNTUK MENINGKATKANKUALITAS PEMBELAJARAN ANALISIS POLA KALIMAT MATAKULIAHSINTAKSIS BAHASA MANDARIN

To improve the quality of online learning during the pandemic, students need an efficient and easy-to-understand method. The 划线分析法 [huaxian fēnxī fa] method is a method of analyzing sentence patterns using lines that represent each element of a word ina sentence. The 划线分析法 [huaxian fēnxī fa] method is useful for training students' analytical skills while increasing attractiveness because it uses different line patterns and colors to analyze a sentence. The purpose of this study was to find out how to apply the 划线分析法 [huaxian fēnxī fa] method in optimizing the learning of Mandarin sentence analysis in Mandarin syntax courses. The data is collected using zoom recordings and observation records. The results showed the quality of the learning process in the analysis of complex sentences of Mandarin syntax improved. Through the application of these methods, from the observations made, students who previously had difficulty analyzing sentences gained a deep understanding in analyzing sentences.Kata Kunci: metode pembelajaran, analisis kalimat, sintaksis mandarin
A coleção de livros textos e o currículo acadêmico: relacionamento quantitativo

The importance of the knowledge of the basic bibliography concerned to graduation course is emphazised. lt establishes a "ratio" that results of the relation between the enrolled students number and the book copies number existent in library. This "ratio" determines neessities under guantitative view-point and shows priorities in the acquisition process.
Komunikasi Antarbudaya dalam Kancah Global: Kompetensi Komunikasi Antarbudaya Pelajar Indonesia di Amerika

In the era of globalization, competition and competition between countries is unavoidable. Every individual is competing to prepare themselves in global competition. Studying abroad is one of the chosen ways to equip oneself. However, in cultural activities there will be intercultural conflicts, culture shock, as evidenced by various cases, such as cases of resignation due to not being able to adapt to the new culture. Intercultural conflicts are also seen in the enthusiasm of Indonesian students to America which has decreased by 3.4%. This study aims to describe the intercultural communication of Indonesian students in America with a qualitative research method, which refers to the interpretive paradigm and phenomenological approach and uses in-depth interviews as a data collection technique. The theories used as a reference are the theory of Intercultural Communication Competence and Anxiety & Uncertainty Management. The results of the study revealed that the competence of the students who were characterized by motivation, knowledge and skills did not only talk about results and realization, but also about the process, from nothing to something and a little to more. It was called dynamic capabilities, where students are able to continue to move, accept and adapt to circumstances. All three were shown from before starting to starting college in America. Motivation was also not enough to carry out cross-cultural activities, but motivation to continue to communicate with other students and differences and new habits. And it doesn't stop at knowledge, the most important competency was the application of knowledge through and daily implementation with other people.
F3SNet: A Four-Step Strategy for QIM Steganalysis of Compressed Speech Based on Hierarchical Attention Network

Traditional machine learning-based steganalysis methods on compressed speech have achieved great success in the field of communication security. However, previous studies lacked mathematical modeling of the correlation between codewords, and there is still room for improvement in steganalysis for small-sized and low embedding rate samples. To deal with the challenge, we use Bayesian networks to measure different types of correlations between codewords in linear prediction code and present F3SNet—a four-step strategy: embedding, encoding, attention, and classification for quantization index modulation steganalysis of compressed speech based on the hierarchical attention network. Among them, embedding converts codewords into high-density numerical vectors, encoding uses the memory characteristics of LSTM to retain more information by distributing it among all its vectors, and attention further determines which vectors have a greater impact on the final classification result. To evaluate the performance of F3SNet, we make a comprehensive comparison of F3SNet with existing steganography methods. Experimental results show that F3SNet surpasses the state-of-the-art methods, particularly for small-sized and low embedding rate samples.
CHARM: An Improved Method for Chinese Precoding and Character-Level Embedding

The numerical transformation of text is a key step in natural language processing tasks, among which the word embedding model is the most representative. However, the word embedding model is insufficient in representing unregistered and low-frequency words, and the character-level embedding model makes up for it. Most Chinese character-level models focus on the independent use of Chinese character features such as strokes, radicals, and pinyin, or the shallow correlations between some features, while the inherent correlations among different features such as pronunciation, glyph, stroke order, and word frequency are not fully utilized. Through the statistical analyses of various features of Chinese characters, this paper proposes a precoding method based on Character Helix Alternative Representation Model (CHARM), which can realize the reversible mapping of Chinese characters or words to English-like sequences, and the advantage of this method is verified in the text classification test based on TextCNN. Experimental results on three test sets show that the model performs well, and can be a replacement character-level corpus for the original Chinese text.