Reviewerly/exHarmony huggingface dataset:
An Analysis of Cultural Contents in English Textbook Used by the Eighth Grade Students of Junior High School 03 Bangkinang

The title of this thesis is “An Analysis of Cultural contents in English Textbook used by the Eighth Grade Students of Junior High School 03 Bangkinang”. This research was conducted based on some problems related to the cultural contents dissemination in the English Textbook. Absolutely, the objective of national education in Indonesia is set based on the cultural value and ideology of the nation. Thus, English textbook evaluation need to be conducted in order to know the appropriateness of the contents in the textbook. This research consisted of two formulations of the problem: how are the cultural contents disseminated in the English textbook entitled ‘English in Focus for Grade VIII (SMP/MTs), and what are the cultural contents disseminated in the English textbook. The objectives of this research are to know about how the cultural contents are disseminated in the English textbook and what are the cultural contents disseminated in the English textbook. The data of the research were collected from reading passages and also pictures in the English Textbook which was published by National Education Department. This research is a descriptive qualitative but the element of quantitative in the form of how the data are counted in a percentage has also been used. In order to know what cultural contents are disseminated in the English Textbook, the cultural contents were categorized into the source or local culture, the target culture, and the international culture (Cortazzi &amp; Jin, 1999). Moreover, in order to know how the cultural contents were disseminated in the English Textbook, the cultural contents were categorized into four senses; the aesthetic sense, the sociological sense, the semantic sense, and the pragmatic sense (Adaskou, Britten &amp; Fahsi, 1990).The research found that local or source culture was predominant in the textbook. The cultural contents of (43.75%) referred to the local culture, (40.62%) referred to the international culture, and (21.87%) referred to the target culture. Additionally, in order to know how the cultural contents are disseminated in textbook, the research found that generally the cultural contents were disseminated by the aesthetic sense (46.15%), the sociological sense (30.76%), and the pragmatic sense (23.07%), while the semantic sense was not found. Based on the findings, it could be concluded that the contents of English textbook in focus for grade VIII has already successfully achieved the national education goal. National characters or national culture should be input in education field.
Measuring Fine-Grained Domain Relevance of Terms: A Hierarchical Core-Fringe Approach

We propose to measure fine-grained domain relevancethe degree that a term is relevant to a broad (e.g., computer science) or narrow (e.g., deep learning) domain.Such measurement is crucial for many downstream tasks in natural language processing.To handle longtail terms, we build a core-anchored semantic graph, which uses core terms with rich description information to bridge the vast remaining fringe terms semantically.To support a finegrained domain without relying on a matching corpus for supervision, we develop hierarchical core-fringe learning, which learns core and fringe terms jointly in a semi-supervised manner contextualized in the hierarchy of the domain.To reduce expensive human efforts, we employ automatic annotation and hierarchical positive-unlabeled learning.Our approach applies to big or small domains, covers head or tail terms, and requires little human effort.Extensive experiments demonstrate that our methods outperform strong baselines and even surpass professional human performance. 1
Sistem Informasi Pendaftaran Mahasiswa Baru Menggunakan Framework Codeigniter dan Application Programming Interface

One of the most important things in the work process is the presentation of information that is fast and accurate. Data is processed in a short time, it will increase work efficiency, one of which is by using the system to process and display data into information. Information systems are needed considering technology is growing and now people are required to use more technology to reduce activities outside the home. Problems that often arise are the tight location of registration and the length of service for one registrant due to filling out registration forms and screening examinations for new students. In addition, the large accumulation of registration and trial files also takes a long time so that announcements of new student graduations cannot be made. The goal is to build a new student admission information system for all faculties at the Indonesian Methodist University, reduce applicants who come to the registration location, reduce the use of paper registration forms, help submit and fill in student data, conduct online screening exams, provide information on new student registration, schedule and payment of tuition fees. The result of this initialization is building a new student registration information system using the Codeigniter Framework and Application Programming Interface (API).&#x0D; &#x0D; Index Terms—Application Programming Interface (API); Codeigniter framework; information systems; online registration
Consistency and Finite Sample Behavior of Binary Class Probability Estimation

We investigate to which extent one can recover class probabilities within the empirical risk minimization (ERM) paradigm. We extend existing results and emphasize the tight relations between empirical risk minimization and class probability estimation. Following previous literature on excess risk bounds and proper scoring rules, we derive a class probability estimator based on empirical risk minimization. We then derive conditions under which this estimator will converge with high probability to the true class probabilities with respect to the L1-norm. One of our core contributions is a novel way to derive finite sample L1-convergence rates of this estimator for different surrogate loss functions. We also study in detail which commonly used loss functions are suitable for this estimation problem and briefly address the setting of model-misspecification.
Teachers’ Level of Adaptability and Performance: Their Response to the Rapidly Transforming Academic World

This research investigated the level of adaptability and performance of junior and senior high school teachers in Guimba, Nueva Ecija as their response to the rapidly transforming academic world.It utilized descriptive-correlational research and researchers-made instrument.The researchers discovered that the responders are on average 37 years old.They were usually master's degree holders who were single.The majority of them focused on Science and Mathematics as their areas of specialization.The bulk of them dealt with one to five distinct disciplines depending on the number of courses they taught.They have six to seven teaching loads at any given time.In terms of their other related work, the majority of them have two other associated works.Teachers have very satisfactory teaching performance and a high level of adaptability in completing other related jobs and adapting to a fast-changing academic environment.Lastly, teachers with a high level of adaptation also have a high level of teaching performance.
Classification of Sad Emotions and Depression Through Images Using Convolutional Neural Network (CNN)

The human face has various functions, especially in expressing something. The expression shown has a unique shape so that it can recognize the atmosphere of the feeling that is being felt. The appearance of a feeling is usually caused by emotion. Research on the classification of emotions has been carried out using various methods. For this study, a Convolutional Neural Network (CNN) method was used which serves as a classifier for sad and depressive emotions. The CNN method has the advantage of preprocessing convolution so that it can extract a hidden feature in an image. The dataset used in this study came from the Facial expression dataset image folders (fer2013) where the dataset used for classification was taken with a ratio of 60% training and 40% validation with the results of the trained model of 60% total loss and 68% test accuracy.
Image feature synthesis & matching in a CBIR system for improving retrieval performance using block contour method

In this research paper, the image feature synthesis & matching in CBIR system for improving retrieval performance using block contour method is presented along with the simulation results carried out in the Matlab environment. The results show the efficacy of the methodology that is being developed. In the following paragraphs, the background work relating to the development of the high computational algorithm development is presented. The brief in-depth step by step approach for achieving this goal is depicted in the future paragraphs. The contributory work developed in this paper discusses about the RGB histogram & block contour concepts which were used to extract the different features of the images and to carry out the performance of the retrieval systems. The simulation results show the efficiency of the methodology that is being developed here.
Perangkat Lunak 3D Modelling Properti sebagai Media Pemasaran menggunakan Augmented Reality Berbasis Android pada Perumahan Graha Cipta Hertasning

This study aims to produce an application that can display a 3D house model in an Augmented Reality environment so that it can help buyers to physically see the house they are going to buy as well as to help property company marketing to manage the house by displaying information on house specifications. The result of the research is an application that can display 3D house images and 3D house plans when highlighting the marker in the direction of the highlighted brochure marker object. The method used in making AR applications is Superimposition Based Augmented Reality .The System Testing Method uses a direct test method based on the Black Box technique by testing the functionality of the application, buttons and the suitability of the application results. Keyword : Augmented Reality, House, Marketing
THE IJINKAN (THE FORMER ENGINEERS’ RESIDENCE OF KAGOSHIMA COTTON MILL) ITS FLOORPLAN AND THE LIVES OF FOREIGN ENGINEERS

The Ijinkan (the former engineers’ residence of Kagoshima Cotton Mill) is one of western-style buildings in Bakumatsu Japan. In its floorplan, room-sizes and components including doors, windows and verandahs were designed in the same manner. With reference to the archaeological surveys, it is revealed that the main building, two attached building and stable were laid almost symmetrically in the rectangular plot of land. Considering the lives of foreign engineers employed in the Satsuma, the Ijinkan was probably designed as a boarding house, which was different to other existing western-style buildings in Bakumatsu Japan.
Mākslīgais intelekts un nākotnes regulējuma dilemma

Digital innovations such as artificial intelligence systems, although limited in their current operational capacity, can be considered to be part of our daily life. Various ways in which these systems are implemented into day-to-day aspects directly affect not only the further development of the industrial sector but the society as a whole. The purpose of this article is to provide a brief insight into the current situation and the various initiatives of the European Union institutions in relation to the methodology for the application of civil liability in the case of damage caused by artificial intelligence systems, as well as to assess the content of future regulatory framework that has been published by the European Parliament, with whom it is intended to establish a common methodology throughout the European Union for the application of civil liability regime, if the damage is caused by artificial intelligence systems.
Aplikasi Algoritma Dijkstra dalam Penyelesaian Berbagai Masalah

Dijkstra is a greedy algorithm that gives a choice of several available shortest routes and then provides a solution. The application of Dijkstra's Algorithm in everyday life is very diverse. This study collects research results regarding the application of Dijkstra's Algorithm to solve everyday problems such as the shortest path problem, this mini-review paper can explain the study of Dijkstra's Algorithm for various things, including solving bi-objective shortest routes, multi-objective routes, emergency evacuation, Dijkstra's graph, the connection between LBS features, best route distribution, and fuzzy solution.
PERBANDINGAN ALGORITMA DIJKSTRA DAN ALGORITMA ANT COLONY DALAM PENENTUAN JALUR TRANSPORTASI UMUM

The purpose of this research is to compare the working principle and characteristics between Dijkstra algorithm and Ant Colony Optimization in determining the shortest path Dijkstra algorithm requires weight to determine the shortest path, without the weight of Dijkstra, algorithm cannot run , while Ant Colony Optimization algorithm does not require weight at run because on the working principle of this algorithm will produce the output or weight when the ant finishes the journey . Therefore, this algorithm consume more RAM and takes a long time of execution when run than Dijkstra algorithm. The Dijkstra algorithm got the fastest result 0.0045 seconds while on algorithm Ant Colony Optimization 0.0126 sec, for RAM usage result obtained by Dijsktra algorithm stable 387.14 kb different from ACO obtained results vary with the smallest result is 712.42 kb The equation of both of these algorithms are the output path and the resulting distance are the same so that it can be implemented for the determination of public transportation routes. The application of this research will be applied to Transjogja which is one of the public transportations in Yogyakarta.
Big Data Science Over the Past Web

Web archives preserve unique and historically valuable information. They hold a record of past events and memories published by all kinds of people, such as journalists, politicians and ordinary people who have shared their testimony and opinion on multiple subjects. As a result, researchers such as historians and sociologists have used web archives as a source of information to understand the recent past since the early days of the World Wide Web. The typical way to extract knowledge from a web archive is by using its search functionalities to find and analyse historical content. This can be a slow and superficial process when analysing complex topics, due to the huge amount of data that web archives have been preserving over time. Big data science tools can cope with this order of magnitude, enabling researchers to automatically extract meaningful knowledge from the archived data. This knowledge helps not only to explain the past but also to predict the future through the computational modelling of events and behaviours. Currently, there is an immense landscape of big data tools, machine learning frameworks and deep learning algorithms that significantly increase the scalability and performance of several computational tasks, especially over text, image and audio. Web archives have been taking advantage of this panoply of technologies to provide their users with more powerful tools to explore and exploit historical data. This chapter presents several examples of these tools and gives an overview of their application to support longitudinal studies over web archive collections.
PENDAMPINGAN PENERAPAN MANAJEMEN PEMBELAJARAN BERBASIS MULTIPLE INTELLIGENCES DI SMA KECAMATAN WAY JEPARA KABUPATEN LAMPUNG TIMUR

This study aims to describe, reveal, and find the dominant factors of multiple intelligence-based learning management in improving learning achievement in the field of life skills. The focus of this research is on planning, organizing, implementing, evaluating, and learning outcomes. This study uses a qualitative design with a naturalistic approach and based on constructivism, which views reality as having multiple dimensions, data were collected through interviews, observation, documentation, and triangulation. The results of this study conclude that multiple intelligence-based learning management is very effective for fulfilling students' life skills, that each student can develop their respective types of intelligence in various ways, intelligence is not only limited to IQ, but there are other intelligences including linguistic intelligence, Mathematical logic, spatial, kinesthetic, musical, interpersonal, intrapersonal, and naturalistic. Learning management based on multiple intelligences begins with MIR (multiple intelligences research for each new student as the basis for preparing lesson plans. The learning implementation is preceded by apperception containing alpha zones in the form of special greetings, fun stories, ice breaking, or singing. The core activities consist of exploration, elaboration, and singing). confirmation, apperception exploration in the form of warmer, pre-teach, and scene setting, elaboration containing learning strategies and methods, while confirmation in the form of teacher and student questions and answers to determine lesson acceptance, Evaluation by means of authentic assessment which includes three domains of knowledge (cognitive) consisting of tests daily, UTS, UAS, annual test, attitude (affective) assessment of teachers, self, friends, and anecdotal records, assessment of skills (psychomotor) in the form of performance (performance), work (product), and making projects (project). The obstacle to learning management based on Multiple Intelligences is changing the paradigm a teacher, making lesson plans, choosing varied learning strategies, and conducting authentic student assessments.
Doubly-Affine Extractors, and Their Applications.

In this work we challenge the common misconception that information-theoretic (IT) privacy is too impractical to be used in the real-world: we propose to build simple and reusable IT-encryption solutions whose only efficiency penalty (compared to computationally-secure schemes) comes from a large secret key size, which is often a rather minor inconvenience, as storage is cheap. In particular, our solutions are stateless and locally computable at the optimal rate, meaning that honest parties do not maintain state and read only (optimally) small portions of their large keys with every use. Moreover, we also propose a novel architecture for outsourcing the storage of these long keys to a network of semi-trusted servers, trading the need to store large secrets with the assumption that it is hard to simultaneously compromise too many publicly accessible ad-hoc servers. Our architecture supports everlasting privacy and post-application security of the derived one-time keys, resolving two major limitations of a related model for outsourcing key storage, called bounded storage model.Both of these results come from nearly optimal constructions of so called doubly-affine extractors: locally-computable, seeded extractors Ext(X,S) which are linear functions of X (for any fixed seed S), and protect against bounded affine leakage on X. This holds unconditionally, even if (a) affine leakage may adaptively depend on the extracted key R = Ext(X,S); and (b) the seed S is only computationally secure. Neither of these properties are possible with general-leakage extractors.
Las humanidades ante el reto de la COVID-19

The Covid-19 pandemic has shocked the ways of organizing the nations and has put enormous pressure on the knowledge systems. In these circumstances, the humanities offer a perspective that allows us to understand this event in its real complexity and, likewise, alert us to the potential risks faced by societies built around democratic and humanistic values.
A Comparative Assessment of Text-independent Automatic Speaker Identification Methods Using Limited Data

Automatic Speaker Identification (ASI) is one of the active fields of research in signal processing.Various machine learning algorithms have been used for this purpose.With the recent developments in hardware technologies and data accumulation, Deep Learning (DL) methods have become the new state-of-the-art approach in several classification and identification tasks.In this paper, we evaluate the performance of traditional methods such as Gaussian Mixture Model-Universal Background Model (GMM-UBM) and DL-based techniques such as Factorized Time-Delay Neural Network (FTDNN) and Convolutional Neural Networks (CNN) for text-independent closed-set automatic speaker identification on two datasets with different conditions.LibriSpeech is one of the experimental datasets, which consists of clean audio signals from audiobooks, collected from a large number of speakers.The other dataset was collected and prepared by us, which has rather limited speech data with low signal-to-noise-ratio from real-life conversations of customers with the agents in a call center.The duration of the speech signals in the query phase is an important factor affecting the performances of ASI methods.In this work, a CNN architecture is proposed for automatic speaker identification from short speech segments.The architecture design aims at capturing the temporal nature of speech signal in an optimum convolutional neural network with low number of parameters compared to the well-known CNN architectures.We show that the proposed CNN-based algorithm performs better on the large and clean dataset, whereas on the other dataset with limited amount of data, traditional method outperforms all DL approaches.The achieved top-1 accuracy by the proposed model is 99.5% on 1-second voice instances from LibriSpeech dataset.
Pemanfaatan Aplikasi Paint Di TK Aisyiyah Bustanul Athfal Ar-Ridho Medan Amplas

The purpose of this community service activity is to provide skills for the use of computer-based learning media, especially the use of the Paint application in Kindergarten Aisyiyah Bustanul Athfal Ar-Ridho Medan Amplas.Learning media are all things that teachers use to make it easier to deliver learning materials. The learning media studied are paint-based computer learning media applications that are used to stimulate children's cognitive abilities, especially in the aspects of learning and problem solving, logical thinking, and symbolic thinking. Keywords: Utilization, Paint Application,
Automated Gadget to Descry Fiat Currency Bills with Gross Balance Updater

Tallying and assessing bills notes with precision and the high rate is a formidable crisis for banks, shops, and even customers. Formerly the appearance of cash counting devices, people used to measure money manually. This protocol was not only dreary and time-consuming but also causes many errors during evaluation. This mini-project intends to see whether appliance vision strategies can be used to comprehend and measure Indian currency bills accurately and at an increased rate. Although there are money distinction algorithms catalogued in the literature, the proposed applications operate offline with stagnant images of the bills/paper notes. In this proposed mini-project, a color sensor-based procedure for the categorization of striding paper notes/bills is examined.