Reviewerly/exHarmony huggingface dataset:
A Visual Programming Environment for Describing Complex Big Data Functions

The rapid advancement of technology and the increasing reliance on computer systems have elevated the significance of programming skills in various domains. Traditional programming techniques, primarily text-based languages, have been the backbone of software development for decades. However, these techniques often require a steep learning curve, limiting their accessibility to individuals without technical backgrounds. To address this issue, Visual Programming Environments (VPEs) have emerged as a powerful alternative, offering intuitive interfaces, consisting of graphical components such as buttons, icons or moving elements. The simple visual layout of these building blocks makes programming more accessible to non-technical users, and enables them to understand, design, and explain complex big data pipelines. While VPE's offer significant benefits, they are not without their limitations. Firstly, these environments may impose constraints on the flexibility and expressiveness of programming constructs, limiting advanced programming techniques that require fine-grained control over complex algorithms. Additionally, the graphical nature of VPE's may result in less efficient coding practices, as users might prioritize visual aesthetics over performance optimization. It is also of great importance that these services can be containerized, in order to be easily deployed and scaled, when talking about big data scenario's requirements. In this study, a VPE named Pipeline Modeler is implemented, capable of translating visual graph representations into operations, which can be then executed in big data scenarios, such as analytics pipelines and flow management on finance datasets. With the use of node blocks, one can create a graph to declare a complex mathematical flow or a pipeline of linked operations that need to be executed on a given set of data. After proper evaluation and experimentation, it is identified that this service is ideal for multiple big data and microservices scenarios, considering pipeline management cases, and that is why the Pipeline Modeler can be a great solution in the pursuit of inclusive and efficient software development and data management.
The Major Challenge in Improving Image Dark Channel Defogging Algorithm

With the rapid development of computer vision and image processing technology, scene image processing under particular weather conditions has become an important research direction, especially in foggy conditions of the image, which is easily affected by haze, resulting in unclear picture quality and image information loss. The defogging algorithm came into being to solve this kind of image problem. This paper analyzes the advantages and disadvantages of dark channels and histogram algorithms. Given the time and space complexity and incomplete fog removal of the dark channel and histogram algorithm, a combined improved algorithm is proposed, a fast fog removal algorithm combining dark channel and histogram enhancement. The analysis of experimental results shows that the fast-defogging algorithm combined with dark channel and histogram enhancement proposed in this paper can restore better visual effects and preserve edge details. Especially in the distant image area, image details are easier to obtain, and the time and space complexity of the algorithm is reduced.
Sistem Informasi Penyewaan Alat Berat Berbasis Web Pada Cv. Trindo Jaya Pasifik Jambi

CV.Trindo Jaya Pasifik Jambi is one of the companies located in the Jambi area where the heavy equipment rental system still uses books, agendas. So that there are problems, namely it is difficult to increase the number of orders in heavy equipment rental significantly, the slow dissemination of information for rental and how to rent heavy equipment in detail, and the availability and price of heavy equipment to be rented and the occurrence of obstacles in processing heavy equipment rental data in recording data. customer, The purpose of this research is to design a web-based heavy equipment rental system at CV.Trindo Jaya Pasifik Jambi. The method used in system design is the prototyping method. While the system modeling tools used by the author are Use Case Diagrams, Activity Diagrams, Class Diagrams. The prototype of this rental information system is expected to make it easier for CV.Trindo Jaya Pasifik Jambi to carry out the process of renting heavy equipment and facilitate the dissemination of the required information.
CONCEPTS, THEORETICAL APPROACHES AND MODELS OF HIGHER EDUCATION AND SCIENCE INNOVATICS

The article is devoted to the consideration of concepts, theoretical approaches, and models of higher education and science innovatics. The main sections that can include the theory and practical implementation of higher education and science innovatics are shown.
PENGGUNAAN WEBSITE APPSHEET SEBAGAI TEMU BALIK ARSIP INAKTIF FOTO DI DINAS PERPUSTAKAAN DAN KEARSIPAN KABUPATEN PONOROGO

&lt;p&gt;&lt;em&gt;Information is an important part of communication between individuals and groups. Information is closely related to archive search. Archive searching is an important part of archive editing because searching allows researchers to find important information in archives. Based on the results of an archive search survey at one of the archival institutions, namely the Ponorogo Regency Library and Archives Service, archive searches are still limited through Microsoft Excel and there are no other innovations. Seeing current technological developments, researchers offer solutions for searching archives through the AppSheet website at the Ponorogo Regency Library and Archives Service. The purpose of this study, among others, is to find out how to use the AppSheet website, use the AppSheet website in related agencies, as well as the advantages and disadvantages of the AppSheet website. The research method in this study is a qualitative method through interviews and observation. The informants in this study were 4 archivists in related agencies. The results of the study show that how to use the AppSheet website consists of 22 steps. How to use the AppSheet website in related agencies include: 1) The features provided are quite easy to use. 2) Retrieval components that are fulfilled include: users, queries, documents, and matching. 3) The description is complete. 4) The retrieval step is quite easy. 5) Available metadata include: processing unit, file number, file number, description of archive information, time period, and amount. 6) Obstacles in the operation of the AppSheet website as a retrieval of inactive photo archives so far not all users can access and cannot be operated offline. 7) The solution for operating the AppSheet website as a retrieval of inactive photo archives is that later users who really need access to these inactive photo archives will be allowed to view them to get information to support their final thesis or assignment. In addition, active photos need to be placed on a flash disk to back up data. 8) There is no comparison with other applications. 9) Criticism and suggestions follow technology and regulatory developments in politics and law and features are added. Disadvantages of the AppSheet website include: users must understand technology and need to share links so that other users can access them. The advantages: increasing efficiency, effectiveness, presentation of information, when it is static it can be accessed by the public.&lt;/em&gt;&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: Inactive Photo Archive Retrieval, AppSheet Website, Ponorogo District Library and Archives Service.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;
STRATEGI PEMELIHARAAN ARSIP DINAMIS INAKTIF MELALUI ALIH MEDIA

&lt;p&gt;&lt;em&gt;The Ponorogo Regency Library and Archives Service is a central organization in the field of Libraries and Archives throughout Ponorogo Regency. Along with the development of information technology, the Ponorogo Regency Library and Archives Office has carried out inactive dynamic archive media transfer activities. This study aims to determine the procedure for implementing media transfer in the Ponorogo Regency Library and Archives Office. This research method is a qualitative method with a field study research method through observation and interviews. The results showed that the procedure for transferring inactive dynamic archive media starts from preparing tools for the media transfer process, preparing inactive archives that will be carried out media transfer activities, scanning inactive archives, storing media transfer archives on computer / CD folders as a storage medium for digital inactive archives, returning archives to their original place.&lt;/em&gt;&lt;/p&gt;
Joyful Learning as a Worthwhile Instructional Activity for English Beginner Students in the Post Covid 19 Pandemic Era

During the Covid-19 pandemic, there were many ways that schools used to keep learning going, and one of the learning approaches that are meaningful and fun in the child's world is joyful Learning. SDIT Al-Furqan located in Enrekang regency, South Sulawesi, Indonesia, also felt the impact of the Covid-19 pandemic. The most visible effect is that their enthusiasm for Learning has decreased because they have been "sent home" for a long time. The researchers concluded that using children's songs will be easy to gain success in their listening goal and make the students more interested in learning English. For this reason, English for beginners in the new normal era through joyful Learning can be used as a choice to restore the learning mood of students. Joyful Learning assumed as a worthwhile learning activity in English. The researcher applied a pre-experimental class design with one group pretest and posttest design. The population of this research was fifth-grade students of SDIT AL-Furqan, Indonesia. The data analysis showed that the joyful learning method positively impacts the students. It was proved by the students' mean score in pretest was better than in posttest. Moreover, the students also give their positive perceptions of implementing joyful Learning. Briefly, joyful learning activities positively affect beginner elementary school students' English achievement.
The Difficulties in Indonesian-English Translation on the Sixth Semester of the English Education Study Program of Muhammadiyah Kotabumi University: A Case Study

Translation is a skill in the process of replacing a message or written statement from one language with a message and statement of the same in another language, where the message and statement conveyed from the source language must be the same as the target language. In fact there are several aspects of difficulties that make students’ difficulties in translation. Those aspects are lexical, grammatical, and stylistic difficulties. The objectives of this research are (1) to describe the difficulties in translating Indonesian-English on the sixth semester students of English education study program of Muhammadiyah Kotabumi University, and (2) to find out the difficulties dominate in translating Indonesian-English on the sixth semester students of English education study program of Muhammadiyah Kotabumi University. The method will be used is qualitative case study method. The researchers will use sampling techniques to get the information and data which is needed by the researchers. Purposive sampling is a sampling technique with certain considerations. In this case the researchers take 6 students who got low score of translating Indonesian-English as subject of the research. The research data is obtained from documents which this case are the results of students’ Indonesian-English translation. The researchers will use the data analysis model of Miles and Huberman. Activities in this data analysis will use data reduction, data presentation, and drawing conclusions/verification. From the data analysis shows that
Analysis of Students’ Motivation and Ability in Writing Essay

This research aimed to find out the students’ motivation and ability in writing essay. Investigation and analysis related to motivation and ability of students in writing will be used as consideration in determining the learning method or model applied in writing class. This research used descriptive qualitative research. The data sources or respondents in this research were students of English Education Study Program at Tadulako University who joined the Writing in Professional Context course. The instruments used were writing proficiency test, questionnaire, and interview. The results of data analysis showed that the students’ motivation in writing essay is very strong. In addition, the students’ ability to write essay, especially in terms of five aspects, namely content, organization, vocabulary, language use, and mechanics is quite good.
Indonesian EFL Students’ Autonomus Learning Implementation in Online Learning

Although studies on online learning have been widely discussed, most of the studies still focus on the students’ experiences adjusting to online learning. However, few studies have analyzed students’ experiences in online learning regarding autonomous learning implementation. This study aimed at identifying Indonesian EFL students' autonomous learning implementation in online learning. A questionnaire adapted from Khotimah et al. (2019) and Hidayati and Husna (2020) was used as a single instrument to obtain data from EFL students from 22 universities around Indonesia. This study sample was selected using a random sampling technique, and the data was analyzed using a simple percentage statistics formula. The results showed how students learned English online in four areas: listening, reading, speaking, and writing. They also showed how the students felt about online learning on their own. These experiences relate to students’ experiences selecting learning materials and learning activity preferences. These preferences are divided into learning English for academic purposes and learning English for pleasure. However, regarding students’ efforts to foster their autonomous online learning, the students had implemented three categories of autonomous learning, namely the initiating process, monitoring process, and evaluating process in their learning process. Hence, the research results are expected to provide new insights for the readers about implementing online learning, which can support the students to be more autonomous learners.
Perbandingan Tingkat Akurasi Prediksi Peningkatan Kasus Positif Covid-19 antara Metode Neural Network Backpropagation dan Long Short Term Memory (LSTM)

The COVID-19 (Coronavirus) pandemic is likely to be one of the most serious globalproblems in the past year. Countries do not have similar experiences with the spreadof the virus and its effects from various fields. Estimating the number of previous casesof COVID-19 can help make decisions in the form of actions and plans to prevent thevirus. This study aims to provide a forecasting model that predicts confirmed COVID-19 cases in the city of Semarang. This study applies a machine learning algorithm,namely the Recurrent Neural Network (RNN) to predict COVID-19 cases in the city ofSemarang. The process of fine-tuning each model is described in this study andnumerical comparisons between the two models are concluded using differentevaluation measures; mean sequence error (MSE).
SYTEMATIC LITERAURE REVIEW : PENERAPAN METODE ALGORITMA C4,5 UNTUK KLASIFIKASI

Abstract---Data mining is extracting data in processing information with the aim of finding important patterns in piles of data. With data mining we can classify, predict, and make a decision. Classification is a way of grouping a data according to the characteristics of a data to be classified. In the process, the classification is divided into two, namely manually and with the help of technology. Manual classification is a classification carried out by humans without the help of technology, while classification with the help of technology has several algorithms, including C4.5, Naive Bayes, Fuzzy, and K-Nearest Neighbor. 5 for classification, a systematic approach is used in the form of a systematic literature review (SLR). SLR is defined as a process in which the identification, assessment, and interpretation of all available research evidence is carried out with the aim of answering a number of research questions
Exploiting Category Information in Sequential Recommendation

In recent years, sequential recommender systems have been widely applied for service recommendations. However, most existing solutions do not take full advantage of one key factor that usually influences user behaviors: the category of services. It is necessary yet challenging to capture users’ category preferences. Firstly, the complex inherent relationships that exist among categories are vital but difficult to mine and encode. Secondly, since interest preferences and category preferences are closely related, their dynamic evolution has to be studied simultaneously. To tackle the above challenges, we propose a novel Reciprocal Dual-Channel Network (RDCN) to capture users’ comprehensive dynamic characteristics toward more accurate recommendations. For the former challenge, we devise a novel strategy to obtain the co-occurrence information of services and categories and jointly pre-train their embeddings. For the latter challenge, we design a Co-Guided Attention module and a Co-Guided GRU module to extract interest preferences and category preferences, respectively. Experimental results on three public datasets have demonstrated the necessity of exploiting the category information and the effectiveness of the proposed RDCN model.
Code-Based PSO-SVM Algorithm for Network Security Posture Warning of Power System

The current power system online early warning technology achieves dynamic security assessment of the power system by analyzing the offline data of the power grid, which leads to low early warning accuracy due to the broad formulation of early warning indicators. In this regard, the power system network security posture early warning technology based on PSO-SVM algorithm is proposed. The PSO-SVM algorithm is optimized by adding nonlinear decreasing inertia weights to process the broad frequency vectors of the power system and reduce the broad frequency oscillation amplitude. A comprehensive early warning index based on the energy weight factor is established to achieve accurate early warning of the network security posture of the power system. In the experiment, the early warning accuracy of the proposed early warning technique is verified. The analysis of the experimental results shows that the early warning of power system network security posture constructed by using the proposed method has high early warning accuracy.
Improvements in Language Modeling, Voice Activity Detection, and Lexicon in OpenASR21 Low Resource Languages

OpenASR21 evaluation was on 15 low resource languages and 3 case sensitive languages. During the evaluation, participants got significant reduction in word error rates (WER) with text downloaded from the internet for only the case sensitive languages, since the development and evaluation audio contained broadcast news. For the 15 low resource languages, participants showed only small gains for some of the languages. The reason is that the development and test set contain dialog between two people, which is very different from the primarily news texts and web pages available over the internet. Here, we show that training text translated from other OpenASR21 languages reduces the WER for many languages. During the evaluation, one team added words to the lexicon using a 3-gram phone language model, but they do not show what WER reduction they achieve. We show that adding new words in the lexicon from public text is beneficial for languages where the out-of-vocabulary rate is high, and outline conditions for reducing the WER. Adding an attention layer to the TDNN (time delay neural net) based voice activity detector reduced the WER for 17 out of the 18 languages. With all the improvements combined, we are getting lower word error rate for the development set for three languages (Farsi, Kazakh and Tamil) than the site that achieved the best error rate for all the languages during the evaluation period.
Code-Mixed Text-to-Speech Synthesis Under Low-Resource Constraints

Text-to-speech (TTS) systems are an important component in voice-based e-commerce applications. These applications include end-to-end voice assistant and customer experience (CX) voice bot. Code-mixed TTS is also relevant in these applications since the product names are commonly described in English while the surrounding text is in a regional language. In this work, we describe our approaches for production quality code-mixed Hindi-English TTS systems built for e-commerce applications. We propose a data-oriented approach by utilizing monolingual data sets in individual languages. We leverage a transliteration model to convert the Roman text into a common Devanagari script and then combine both datasets for training. We show that such single script bi-lingual training without any code-mixing works well for pure code-mixed test sets. We further present an exhaustive evaluation of single-speaker adaptation and multi-speaker training with Tacotron2 + Waveglow setup to show that the former approach works better. These approaches are also coupled with transfer learning and decoder-only fine-tuning to improve performance. We compare these approaches with the Google TTS and report a positive CMOS score of 0.02 with the proposed transfer learning approach. We also perform low-resource voice adaptation experiments to show that a new voice can be onboarded with just 3 hrs of data. This highlights the importance of our pre-trained models in resource-constrained settings. This subjective evaluation is performed on a large number of out-of-domain pure code-mixed sentences to demonstrate the high quality of the systems.
Konkani Phonetic Transcription System 1.0

A phonetic transcription system provides pronunciation of words, mostly in International Phonetic Alphabet (IPA) format. Phonetic transcription is the visual representation of phones in the form of characters and symbols represented in the IPA format. This paper describes the development of an automatic phonetic transcription system for an under-resourced Indian language, Konkani. In this paper, we have proposed an automatic phonetic word transcription generation system based on a set of deterministic linguistic rules mainly derived from the available work on Konkani literature. Some general rules, like Schwa deletion, are also considered in the design process. Parallel 101 sentences with 397 unique words have been used to test the accuracy of the system. Our system shows a Word Error Rate (WER) of 60, whereas existing system had a WER of 92.5.
Adversarially Trained Hierarchical Attention Network for Domain-Invariant Spoken Language Identification

State-of-the-art spoken language identification (LID) systems are sensitive to domain-mismatch between training and testing samples, due to which, they often perform unsatisfactorily in unseen target domain conditions. In order to improve the performance in domain-mismatched conditions, the LID system should be encouraged to learn domain-invariant representation of the speech. In this paper, we propose an adversarially trained hierarchical attention network for achieving this. Specifically, the proposed method first uses a transformer-encoder which uses attention mechanism at three different-levels to learn better representations at segment-level, suprasegmental-level and utterance-level. Such hierarchical attention mechanism allows the network to encode LID-specific contents of the speech in a better way. The network is then encouraged to learn domain-invariant representation of the speech using adversarial multi-task learning (AMTL). Results obtained on unseen target domain conditions demonstrate the superiority of proposed approach over state-of-the-art baselines.