Reviewerly/exHarmony huggingface dataset:
Awareness and Utilization of Web 2.0 Technology of Young Teachers in Catholic Schools

The development of the World Wide Web in the 1990s has brought about various technological advancements in Information and Communication Technology (ICT), which provides fast-growing web solutions (Gough, 2010). One of these web innovations is the emergence and growth of Web 2.0 technology. Web 2.0 Technology with different web sites allows users to create, generate, and share information online. However, its application has been tagged as a critical disruptive technology in education with electronic learning or e-learning. The emergence of Web 2.0 technology is the start of the more complicated innovation in the teaching-learning process. It is the second generation of the World Wide Web. Hence, the paper describes the level of awareness and extent of utilization of Web 2.0 technology of young teachers in Catholic Schools in Antique during the school year 2019-2020 in terms of sex and ICT training. Likewise, it explores the relationship existing between the teachers' demographics and their awareness and extent of utilization. Also, it determines the correlation among awareness and utilization of Web 2.0 technology of young teachers.
ANDROID-BASED EVENT INFORMATION APPLICATION IN THE CITY OF MAKASSAR USING LOCATION BASED SERVICE TECHNOLOGY

Android Based Event Information App in Makassar City using Location Based Sevice technology is an application that provides information about event information, especially in the city of Makassar by utilizing the Android platform. This research is based on the background because there are still many people who do not know the information about events that are ongoing or will be held in the city of Makassar. That is due to the lack of information obtained and the lack of a forum to convey information about the spread of events easily. The purpose of this research is to build an event information application to help the public receive event information quickly and easily, to help people find the route to the event they want with the help of Location-Based Service technology with use of the android platform to convey event information so that it can be accessed whenever and wherever they want. This research produces an Android-based Event Information Application that helping people get event information with 70% testing results and making it easier for people to find routes to the event location according to their wishes by using technology Location-Based Service with a percentage of 60% strongly agrees.
Future Vision of Interactive and Intelligent TV Systems using Edge AI

Recently the Brazilian DTV system standards have been upgraded, called TV 2.5, in order to provide a better integration between broadcast and broadband services. The next Brazilian DTV system evolution, called TV 3.0, will address more deeply this convergence of TV systems not only at low-level network layers but also at the application layer. One of the new features to be addressed by this future application layer is the use of Artificial Intelligence technologies. Recently, there have been practical applications using Artificial Intelligence (AI) deployed to improve TV production efficiency and correlated cost reduction. The success in operationalize and evaluate these applications is a strong indication of the interest and relevance of AI in TV. This paper presents TeleMÃ­dia Labâ€™s future vision on interactive and intelligent TV Systems, with particular focus on edge AI. Edge AI means use in-device capabilities to run AI applications instead of running them in cloud.
Distinguishing Between Foreground and Background Events in News

Determining whether an event in a news article is a foreground or background event would be useful in many natural language processing tasks, for example, temporal relation extraction, summarization, or storyline generation.We introduce the task of distinguishing between foreground and background events in news articles as well as identifying the general temporal position of background events relative to the foreground period (past, present, future, and their combinations).We achieve good performance (0.73 F 1 for background vs. foreground and temporal position, and 0.79 F 1 for background vs. foreground only) on a dataset of news articles by leveraging discourse information in a featurized model.We release our implementation and annotated data for other researchers 1 .
Blind SQL Injection Attacks Optimization

This paper presents new and evolved methods to perform Blind SQL Injection attacks. These are much faster than the current publicly available tools and techniques due to optimization and redesign ideas that hack databases in more efficient methods, using cleverer injection payloads; this is the result of years of private research. Implementing these methods within carefully crafted code has resulted in the development of the fastest tools in the world to extract information from a database through Blind SQL Injection vulnerabilities. These tools are around 1600% faster than the currently most popular tools. The nature of such attack vectors will be explained in this paper, including all of their intrinsic details.
Implementation of C-Map Application to Improve Students’ Understanding of Work and Energy Matter

The aims of the study were analyzing students' understanding and skills to make concept mapping in work energy matter through C-Map application software.True experimental method with randomized control group pre-test and post-test design was utilized in the research method.The research involved 72 public high school students from second semester, 10 th grade in Indonesia, composed of 36 students in an experiment group (EG) and 36 students in control group (CG).Data were collected by giving a test of work and energy to evaluate students' understanding through C-Map application during Spring Semester 2019.A specific rubric from the previous researchers was used to evaluate students' skills in developing concept map.Analysis of data used independent t-test and normalized gain (Ngain).The independent test revealed the implementation of C-Map application affected in improving students' understanding of work and energy.Students' understanding of these concepts performed that EG higher than CG.It was supported by the obtained of normalized gain (N-gain).The N-gain of EG and CG was 0.39 and 0.26, respectively.Students' skill to make concept mapping in the topic of work and energy through C-Map application achieved 81.36 of 100 with a very good category.C-Map application guide students to arrange the hierarchical structure concept of work and energy, construct concept from focus question and see how the concept related with another concept.
Word Retrieval based on FREAK Descriptor to Identify the Image of the English Letter that Corresponds to the First Letter of the Word

For the reason of colossal technological developments, the requirement of image information methods became a significant issue. The aim of this research was to retrieve the word based on Fast Retina Key-points (FREAK) descriptor .The suggested system consists of four stages. In the first stage, the images of English letters are loaded. Points are detected via SUSAN in the second stage. FREAK used in the third stage and then a database was created containing 26 English letters. The image to be tested was entered and the points are extracted in the fourth stage and then Manhattan distance was used to calculate the distance between the value of the test image descriptors and all the values of the descriptors in a database. The experimental results show that the precision and the recall values were high for retrieval of the words when using SUSAN because it extracts a large number of interest points compared to the Harris method. For example, for the letter H was 104 with SUSAN while it was 42 for Harris, therefore; the precision for retrieval of the word Hour was 89% and recall was 93% when using SUSAN while precision was 77% and recall was 80% when using Harris.
Adaptation As Controllable Process For Decision Making Improvement

This study explores adaptation as a factor of decision quality improvement.It stems from the assertion that the quality of a decision shall be determined by the ensuing reduction of uncertainty rather than by the decision implementation outcome.The paper builds upon the tenets of transformational theory, game theory, cognitive science as well as the ideas of a quantitative description of how information resources contribute to the output of products.We investigate causal relationships associated with the cognitive trap of equating the quality of the decision with its implementation outcome.The phenomenon of adaptation is proposed to be considered as a controllable process of uncertainty reduction.We advance the thesis that transformation of quantity of knowledge into quality that occurs in an adaptive system drives the uncertainty reduction thus increasing the decision-making quality.The conjecture is tested that, at each point in time, the adaptation speed is inversely proportional to the laboriousness of training.The results obtained with two training simulators are analyzed, and the patterns of the adaptation process revealed for two types of thinking: the reflexive mind and reasoning mind.Also, we identify the features of decision making as observed in the course of controlled adaptation and determine the efficiency limits of adaptation as such controllable process.
A Co-Attentive Cross-Lingual Neural Model for Dialogue Breakdown Detection

Ensuring smooth communication is essential in a chat-oriented dialogue system, so that a user can obtain meaningful responses through interactions with the system.Most prior work on dialogue research does not focus on preventing dialogue breakdown.One of the major challenges is that a dialogue system may generate an undesired utterance leading to a dialogue breakdown, which degrades the overall interaction quality.Hence, it is crucial for a machine to detect dialogue breakdowns in an ongoing conversation.In this paper, we propose a novel dialogue breakdown detection model that jointly incorporates a pretrained cross-lingual language model and a co-attention network.Our proposed model leverages effective word embeddings trained on one hundred different languages to generate contextualized representations.Co-attention aims to capture the interaction between the latest utterance and the conversation history, and thereby determines whether the latest utterance causes a dialogue breakdown.Experimental results show that our proposed model outperforms all previous approaches on all evaluation metrics in both the Japanese and English tracks in Dialogue Breakdown Detection Challenge 4 (DBDC4 at IWSDS2019).
Subgraph-Indexed Sequential Subdivision for Continuous Subgraph Matching on Dynamic Knowledge Graph

Continuous subgraph matching problem on dynamic graph has become a popular research topic in the field of graph analysis, which has a wide range of applications including information retrieval and community detection. Specifically, given a query graph <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>q</mi> </math> , an initial graph <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <msub> <mrow> <mi>G</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msub> </math> , and a graph update stream <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3"> <mo>△</mo> <msub> <mrow> <mi>G</mi> </mrow> <mrow> <mi>i</mi> </mrow> </msub> </math> , the problem of continuous subgraph matching is to sequentially conduct all possible isomorphic subgraphs covering <math xmlns="http://www.w3.org/1998/Math/MathML" id="M4"> <mo>△</mo> <msub> <mrow> <mi>G</mi> </mrow> <mrow> <mi>i</mi> </mrow> </msub> </math> of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M5"> <mi>q</mi> </math> on <math xmlns="http://www.w3.org/1998/Math/MathML" id="M6"> <msub> <mrow> <mi>G</mi> </mrow> <mrow> <mi>i</mi> </mrow> </msub> </math> (= <math xmlns="http://www.w3.org/1998/Math/MathML" id="M7"> <msub> <mrow> <mi>G</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msub> <mtext> </mtext> <mo>⊕</mo> <mtext> </mtext> <mo>△</mo> <msub> <mrow> <mi>G</mi> </mrow> <mrow> <mi>i</mi> </mrow> </msub> </math> ). Since knowledge graph is a directed labeled multigraph having multiple edges between a pair of vertices, it brings new challenges for the problem focusing on dynamic knowledge graph. One challenge is that the multigraph characteristic of knowledge graph intensifies the complexity of candidate calculation, which is the combination of complex topological and attributed structures. Another challenge is that the isomorphic subgraphs covering a given region are conducted on a huge search space of seed candidates, which causes a lot of time consumption for searching the unpromising candidates. To address these challenges, a method of subgraph-indexed sequential subdivision is proposed to accelerating the continuous subgraph matching on dynamic knowledge graph. Firstly, a flow graph index is proposed to arrange the search space of seed candidates in topological knowledge graph and an adjacent index is designed to accelerate the identification of candidate activation states in attributed knowledge graph. Secondly, the sequential subdivision of flow graph index and the transition state model are employed to incrementally conduct subgraph matching and maintain the regional influence of changed candidates, respectively. Finally, extensive empirical studies on real and synthetic graphs demonstrate that our techniques outperform the state-of-the-art algorithms.
NLP@JUST at SemEval-2020 Task 4: Ensemble Technique for BERT and Roberta to Evaluate Commonsense Validation

This paper presents the work of the NLP@JUST team at SemEval-2020 Task 4 competition that related to commonsense validation and explanation (ComVE) task.The team participates in sub-taskA (Validation) which related to validation that checks if the text is against common sense or not.Several models have trained (i.e.Bert, XLNet, and Roberta), however, the main models used are the RoBERTa-large and BERT Whole word masking.As well as, we utilized the results from both models to generate final prediction by using the average Ensemble technique, that used to improve the overall performance.The evaluation result shows that the implemented model achieved an accuracy of 93.9% obtained and published at the post-evaluation result on the leaderboard.
Kiai Sebagai Patron dan Sponsor Praktik Multiliterasi di Pesantren Pada Era Media Digital

AbstractLiteracy is no longer single entity; there are several aspects of literacies, especially in the era of information technology and digital media today, so it is called multiliteracies. This article presents the results of research on multiliteracies practice products in the form of Islamic boarding school (pesantren) website. Applying the theoretical framework of the new literacy study approach, this research focuses on the context, patron, or sponsorship of multiliteracy practices, and santri responses through it. Data were collected through textual analysis, interviews, and observations at the Nuris Pesantren in Jember. The results showed that patrons of the pesantren multiliteracies practice that produced website were the kiai and the sons of the kiai. Literacy patrons or sponsors always color the content and cultivation of any web or multiliteracies product. Kiai pesantren holds positions as patron and sponsor of pesantren-based multiliteracy practices in the age of digital media technology. The kiai’s vision and thought have an influence on the practice and products of pesantren multiliteracies. The kiai serves as a model (patron) of literacy as well as a sponsor (supporting element) of multiliteracy practices. The kiai remains a “filter” of values for the santri and the community in the digital era. AbstrakLiterasi kini tidak lagi satu, tetapi beberapa aspek, terlebih di era teknologi informasi dan media digital, sehingga disebut dengan multiliterasi. Tulisan ini menyajikan hasil penelitian tentang produk praktik multiliterasi yang berupa website pondok pesantren. Dengan menerapkan kerangka teoritik pendekatan kajian literasi baru, penelitian ini memfokuskan bahasan pada konteks, patron, atau sponsor yang membentuk produk praktik multiliterasi, serta respon santri terhadap praktik tersebut. Data dikumpulkan dengan telaah dan analisis tekstual, wawancara, dan observasi di Pondok Pesantren Nuris Jember. Hasil penelitian menunjukkan bahwa patron atau sponsor praktik multiliterasi pesantren yang menghasilkan produk website adalah kiai dan putra-putra kiai. Patron atau sponsor literasi senantiasa mewarnai konten dan penggarapan website atau produk multiliterasi apapun. Kiai pesantren memegang posisi sebagai patron dan sponsor praktik multiliterasi berbasis pesantren di zaman teknologi media digital. Visi kiai dan pemikirannya memberikan pengaruh pada praktik dan produk literasi/multiliterasi pesantren. Kiai menjadi teladan (patron) literasi sekaligus juga menjadi sponsor (unsur yang mendukung) praktik multiliterasi. Namun, kiai tetap menjadi “penyaring” nilai bagi santri dan masyarakat di tengah revolusi teknologi digital.
Evaluating Cross-Lingual Transfer Learning Approaches in Multilingual Conversational Agent Models

With the recent explosion in popularity of voice assistant devices, there is a growing interest in making them available to user populations in additional countries and languages. However, to provide the highest accuracy and best performance for specific user populations, most existing voice assistant models are developed individually for each region or language, which requires linear investment of effort. In this paper, we propose a general multilingual model framework for Natural Language Understanding (NLU) models, which can help bootstrap new language models faster and reduce the amount of effort required to develop each language separately. We explore how different deep learning architectures affect multilingual NLU model performance. Our experimental results show that these multilingual models can reach same or better performance compared to monolingual models across language-specific test data while require less effort in creating features and model maintenance.
NEED ANALYSIS OF ESP FOR NON-ENGLISH STUDY PROGRAM

In non-English study programs, English learning material is arranged based on the specificities of the English learners themselves, commonly known as English for Specific Purpose (ESP). By using a qualitative approach and descriptive method, this study aims to map the students’ English language skills, determine the objectives of learning English, and the concept of ESP material needed by students in the non-English Study Program at UMSU. Sources of data in this study were 80 (eighty) respondents (students) from non-English study programs who had already completed their general English course. Data analysis was performed by using qualitative descriptive methods in terms of numbers and percentages. The results show that the students’ needs vary from one student to another depending on their respective fields of knowledge. The students’ average ability starts from the low until intermediate level, and speaking and listening skills cover those needed by the learners of the respective study program. Their learning objectives are divided into two criteria, short-term goals related to current needs such as academic/educational needs and long-term goals related to their world of work after completing education. The concept of ESP English learning needed depends on the varying needs of each existing non-English study program. Thus, the ESP concept that is designed must be adapted to these needs.
Cloud infrastructure for HPC investment analysis

With the consolidation of cloud computing technology, there is a growing interest in exploring it to support High Performance Computing (HPC). However, migrating such applications to public or private cloud environments brings some challenges, in particular, the cost in financing the migration process. In this paper, a literature review is presented with selected papers about analyzing cloud infrastructure investments. In particular, the selected papers analyse how investments impact applications. For discussion of related works, conditions for running HPC applications in the cloud are characterized.
A New Similarity Measure of Picture Fuzzy Sets and Application in the Fault Diagnosis of Steam Turbine

Picture fuzzy set is an extension of fuzzy sets and intuitionistic sets.It is demonstrated have a wide application in the fact and theoretical.In this paper, we propose some novel similarity measures between picture fuzzy sets.The novel similarity measure is constructed by combining negative functions of each degree membership of picture fuzzy set.This similarity is shown that is better other similarity measures of picture fuzzy sets in some cases.Next, we apply them in several pattern recognition problems.Finally, we apply them to find the fault diagnosis of the steam turbine.
EVALUASI KESESUAIAN LAHAN TANAMAN JAGUNG (Zea mays L.) PADA LAHAN KERING DI KECAMATAN WAGIR KABUPATEN MALANG

Malang Regency has a large area of dry land and currently being developed as a center for food crops, especially corn. Corn production in Malang Regency has not provided high productivity, one of which is in Wagir Regency. This study aims to determine the actual land suitability class, determine the characteristics of the land that affects the productivity of corn, determine the actual productivity class of corn, and develop new land suitability criteria using the boundary line method. This research was conducted in May - September 2019 in Wagir District, Malang, using a physiographic survey method based on the Land Mapping Unit. Soil samples were taken at a depth of 0-120 cm (minipit and drilling) at each observation points (42 points) and analyzed in the laboratory (texture, pH, CEC, C-Organic, BS, N-total, P2O5, Potassium, Ca, Mg, and Na). The determination of land suitability class is carried out using the SPKL (Sistem penilaian kesesuaian lahan) application and the modification of the criteria is carried out using the boundary line method. The results of the land suitability evaluation according to the criteria of Ritung et al. (2011) in Wagir District, Malang Regency, included in class S3 and N, with limiting factors in rainfall, Base Saturation, pH, C-Organic, N-total, P2O5, Potassium, slope and erosion hazard. Stepwise analysis result showed that slope and air temperature determined corn productivity in research area. Boundary lines analysis gave results that modified suitability classified as S3 and N which is the same category as actual suitability classes.