Reviewerly/exHarmony huggingface dataset:
Real-world-events data sifting through ultra-small labeled datasets and graph fusion

The information on social media is vital, especially for events such as natural disasters or terrorist attacks, that might cause rapid growth of data sharing through social media networks. However, collecting and processing data of an event is a challenging task and essentially requires a great deal of data cleaning and filtering out what is relevant/irrelevant to the event. Data sifting task endeavors to identifying the related content to the depicted event data. We propose a learning strategy to dynamically learn complementary contributions from different data-driven features through a semi-supervised graph-fusion technique. Our proposed method relies upon minimal training labeled data samples — ultra-small data learning. Learning through a small labeled set is also of particular interest to forensic investigators and medical researchers — concerning massive data labeling and minimizing energy-efficient computing to reduce redundancy and repetitions. We assess the effectiveness of the proposed semi-supervised method on five datasets from real-world events. Compared with prior-art (supervised and semi-supervised ones), experimental results show the proposed method achieves the best classification results and most efficient computational footprint.
Reflections on the Construction of “Double-Qualified” Teachers in Higher Vocational Colleges

Vocational education is an important part of the overall education system. The development of higher vocational education is one of the guiding principles of education in China. The development of teachers is an important support for the development of vocational education. Teachers who can teach theoretically and guide students in practical work are known as “double-qualified” teachers. Building a highly qualified and professional double-qualified teaching team is the fundamental task in modernizing vocational education. Firstly, this paper discusses the importance of “double-qualified” teachers by describing the relevant policies of the Ministry of Education in China. Secondly, it reviews the research works of early scholars. Thirdly, it analyzes the main problems of teacher training in higher education institutions. Fourthly, it proposes five suggestions for the development of a “double-qualified” teaching team in higher education institutions. A high level and professional teaching team is an important support for the high-quality development of vocational institutions. School leaders must attach great importance to the construction of a “double-qualified” teaching team and increase the support in terms of policies, institutional protection, and financial investment.
ARIMA MODEL OF OUTLIER DETECTION FOR FORECASTING CONSUMER PRICE INDEX (CPI)

The Consumer Price Index (CPI) is a indicator used by Badan Pusat Statistik (BPS) which describes the average change in the prices paid by urban consumers for a market basket of consumer goods and services in a certain period. The case on Consumer Price Index (CPI) of Probolinggo City, if the Consumer Price Index (CPI) increase then describe inflation occurs and conversely. The Consumer Price Index (CPI) of Probolinggo City increase is not fixed. This study is to forecast the Consumer Price Index (CPI) that the results can be used as one of the considerations in carrying out economic development in the future. Research focused on the data of Consumer Price Index (CPI) of Probolinggo City from January 2014 to April 2022. Methodology implemented in this study is Autoregressive Integrated Moving Average (ARIMA). Result show that ARIMA without an outlier was the best model for predicting Consumer Price Index (CPI) of Probolinggo City for the next 8 months. This model shows the value of MAPE is . The value of forecasting results in each month has decreased and increased not so significantly where in May 2022 the forecasting value was 108,391 then in June 2022 the forecasting value became 108,411 and so on until December 2022 the forecasting results using ARIMA model of 107,845.
Implementation of 8E Learning Cycle Model with Instagram to Overcome Student Misconceptions in Buffer Solution Material

This study aims to determine the effectiveness of applying the 8E learning cycle model with Instagram to overcome student misconceptions in Buffer Solution material. In particular, this study analyzed the differences between the 8E learning cycle model and the online (conventional) expository model with Instagramin overcoming student misconceptions about buffer solution materials. This research method is a quasi-experiment with a non-equivalent control group design. Data collection used a three-tier multiple choice test technique and five experts' validated student response questionnaires. The sampling technique uses purposive sampling. Data analysis techniques use descriptive and inferential analysis of t-tests. The t-test is used to analyze the difference in concept understanding learning outcomes between the experimental and control classes to determine the effectiveness of the 8E learning cycle model. The results showed there were significant differences in concept understanding and misconceptions between experimental class students and control class students (0.00&lt;0.05). Experimental class concept understanding was higher (43.62%) than the control class (28.95%), and experimental class misconception was lower (40.76%) than the control class (47.81%). From these data, it can be concluded that the application of the 8E learning cycle model is more effective than the expository (conventional) online model in overcoming misconceptions in buffer solution materials. The 8E learning cycle model can be an alternative to overcome misconceptions and improve students' understanding of concepts in buffer solution materials.
Factors Influencing Speaking Anxiety of FLSP Freshmen

Anxiety is one of the biggest challenges that has harmed language development. Among the four-language skill, speaking is the most anxiety-provoking skill. This present article aims to identify the factors influencing freshmen’s speaking anxiety in Foreign Language for Specific Purpose (FLSP) class. The researcher conducted a case study with a descriptive qualitative approach. Moreover, 20 FLSP freshmen in the communication science department participated in this study. The data was collected using a close-ended and open-ended questionnaire of the Foreign Language Speaking Anxiety Scale (FLSAS) derived from Horwitz et al. (1986). The result exposed that the primary factor influencing freshmen speaking anxiety is “fear of negative evaluation,” followed by “test anxiety” and “communication apprehension.” This study ends with implications to assist the educator in fostering speaking and providing students with a positive environment to effectively support them in overcoming anxiety feelings.&#x0D;
UTILIZATION OF APPRAISAL SYSTEM FOR COPYWRITING STRATEGY IN FOOD’S ADVERTISEMENT (A SYSTEMIC FUNCTIONAL LINGUISTIC APPROACH)

This paper investigated the appraisal system used in the copywriting of food advertisements. The purpose of this research was to describe the utilization appraisal system in food advertisements. This study is qualitative and descriptive research. The data gathered from emotive words that contain about attitudes (affect, judgment, and appreciation) in the caption and picture of food advertisements. The instagram account of burgerking, pizzahut, and richeese factory as the data source. The result is the implementation of affect, appreciation, and judgment for copywriting strategy of the advertisement.
Embedded Raspberry Pi Vehicle Detection and Classification using Single Shot Detector and Dilated Multi-Column Convolutional Neural Network

Detection and classification of vehicle types is one of the most important applications in field of road safety. In this paper, we propose a deep learning process to detect and classify vehicles by using Single shot Detector (SSD) for detection and Di-lated Multi-Column Convolutional Neural Network (DMCCNN) for classification. Rather than using a fixed-scale convolutional layer, the second model we use is capable to extract features from various scales of an image employing different dilated filters to improve the performance classification, especially for similar-looking vehicles like Suv and Sedan. An embedded Raspberry Pi vehicle detection and classification system is developed using a built-in Pi camera. The results are comparable with desktop-based results in the literature yielding an accuracy of 95.93 % on BIT dataset.
Aplikasi Informasi Kegiatan Webinar Berbasis WEB

Webinars are inseparable activities from the world of education in higher education. However, there are still many webinars that hold conventionally starting from the announcement of the event, registration of participants, to the process of implementing the event. So that it feels less effective. Therefore, this application was created to make it easier to provide information to all students about the latest webinar in the University so that publications can be effective and efficient, this design can help solve problems that occur when webinars are held, such as attendance, information about presenters and others. The research method used in designing this web-based application is a field study, namely by direct observation, interviews with related parties, and also by conducting documentation to obtain the required information. In addition, the author also conducted various discussions as well as from various media containing the information needed, analyzing needs, and designing. The second stage is to build the system using the Waterfall type SDLC (System Development Life Cycle) method. The Waterfall Model provides a sequential or sequential software lifecycle approach starting from analysis, design, coding, testing, and maintenance.
On the (mis)calculation of forensic science error rates

Proceedings of the National Academy of Sciences (PNAS), a peer reviewed journal of the National Academy of Sciences (NAS) - an authoritative source of high-impact, original research that broadly spans the biological, physical, and social sciences.
KUALITAS LAYANAN PORTAL OPEN DATA BANDA ACEH (ODBA) DALAM KETERBUKAAN INFORMASI PUBLIK DI DINAS KOMUNIKASI INFORMATIKA DAN STATISTIK KOTA BANDA ACEH

One of the goals of the reform program in Indonesia is the realization of good governance. The Indonesian Open Government Movement (OGI) is a form of movement between the government and the community to realize good governance, namely through principles based on public information. One of the OGI programs to achieve this is through the open data project portal, one of which is the Banda Aceh Open Data Portal (ODBA). This study aims to find out how the quality of ODBA Portal services in public information at the Department of Communication, Informatics and Statistics (Diskominfontik) of Banda Aceh City and the strategy of Banda Aceh Diskominfotik to improve the quality of ODBA Portal services. The research method used is descriptive qualitative. Informants in this study were determined by purposive sampling technique. Data were collected by interview, observation, documentation, and triangulation techniques. Data analysis techniques used are data reduction, data presentation, and drawing conclusions. The theory used is based on three dimensions of the quality of a portal site proposed by Rocha (2012: 374-382), namely content quality, service quality, and technical quality. The results showed that the service quality of the ODBA Portal was quite good. However, there are several things that need to be improved on the ODBA Portal, such as the availability of features for proposing datasets, features for feedback, special personnel to handle open data portal maintenance, and others. To make the ODBA Portal have a better quality, the Department of Communication, Informatics and Statistics of Banda Aceh City needs to provide expert programmers, especially in the field of maintenance and add the main features that must exist in an open data portal. The City of Banda Aceh Diskominfotik has also implemented several strategies to improve the quality of the ODBA Portal service.&#x0D; Keywords: ODBA Portal, Open Data, Open Data Portal, Public Information Disclosure, Quality of Website Portal
Reading Habits and Integration of Technology in Understanding English Texts: A Case Study of EFL Students

AbstractThis study aims at exploring how studentsâ€™ interest in reading books using technology and exploring how technology affects studentsâ€™ reading habit. Type of design used in this study is quantitative and using questionnaire as the main instrument. In general, it can be said that the level of student interest in reading is still relatively low. Most students think that they were not the kind of students who spend a lot of time reading about English. The technology that develops in the context of learning and reading comprehension shows students' interest in integrating their reading interests using mobile phone and laptops.Keywords: Interest in reading, reading habits, technology
Trends and Suggestions on RPA Application in Korean Industry Using News Article Crawling

In the 4th industrial revolution, companies are making efforts to replace human resources with automated machines by reflecting social phenomena such as digitalization, 52-h work week, and minimum wage increase.&#x0D; Robotic process automation (RPA), which has emerged rapidly owing to people working from home and non-face-to-face interaction during the COVID-19 pandemic, is being applied to various fields such as in the manufacturing and service industries. In this study, Korean RPA market trends are analyzed. This study proposes the future application of RPA through news articles crawled from Naver, related studies, and reports.
Contextual Teaching and Learning Using Local Content Material on Students’ Reading Comprehension at a Junior High School in Indonesia

One of the important skills in learning English is reading. There should be an effective strategy to teach this skill. This research is combining the form of contextual teaching and learning with local content material. By combining these two terms, there must be an increasing result from the students mastering reading skills. This research aims to examine the impact of contextual teaching and learning using the local content material on students’ reading comprehension at a junior high school in Indonesia. The population of its research is eighth-grade students, and two classes were selected as samples experimental class (treatment) and controlled class. This experimental study used reading tests as instruments to get the data. The test was formatted into multiple-choice items, consisting of pre-test and post-test. The researchers used the pre-test, treatment, and post-test techniques to collect the data. But in the control class, no treatment was applied to mastering reading skills. There was a significant effect in the treatment class than in the control class. It was proven by the effect size’s score of medium effect showed .5 deviation. It indicated that the treatment of using contextual teaching and learning with local content was successful.
ANALISIS STRUKUR KALIMAT TEKS BERITA “DINKES DKI :PASIEN GANGGUAN GINJAL AKUT BANYAK YANG MENINGGAL KARENA TERLAMBAT TERDIAGONIS” PADA KOMPAS.COM TERBITAN 22 OKTOBER 2022, 21:30 WIB

The purpose of this study is (1) to describe the errors in terms of syntax, which are found in online media Kompas.com; (2) to provide correction of language errors in terms of syntax, which are contained in Kompas.com online media. This research is a descriptive qualitative research. The data collection technique used is the listening technique to obtain data by listening to the use of language and note-taking techniques to record words or sentences for analysis. The results of the analysis regarding the analysis of language errors can be concluded that there are forms of language errors in the field of syntax. One of them is the researcher determines the structure of sentences in news texts based on functions, categories, and roles.
ANALISIS KESALAHAN BERBAHASA INDONESIA DALAM KARANGAN TEKS EKSPOSISI SISWA SEKOLAH MENENGAH ATAS KELAS X

The purpose of this research is : (1) to describes the error of Indonesian language in exposition text by the students at class X, (2) causes of error, and (3) the effort which is done by the teacher and student to solve the error. This research is a qualitative descriptive research with a sample student text SMAIT Ummul Quro Bogor kelas X IPA 1 dan X IPA 3. The sampling technique used was purposive sampling. Data collection techniques used were in-depth interviews and document analysis. Data analysis technique used is the interactive analytical model that includes four components, namely data collection, data reduction, data presentation, and verification. The conclusions of this study are as follows. Firstly, the linguistic elements of language errors that often occur in the student text is divided into four errors : spelling error, diction, sentence, and paragraph. Secondly, language errors that often occur in a student text exposition caused by several factors, among others: is inadequate of language mastery, lack of examples by the teachers, the influence of foreign language, lack of writing peactice, and lack of writing time. Thirdly, the efforts have been made to minimize errors include: improving students' language mastery, having more practices in writing, implementing appropriate correction technique, and implementing a process approach to teaching writing.
Analisis Kesalahan Berbahasa dalam Berita Online “Makna Di Balik Keris Tidak Melulu Soal Hal Mistis” Kompas.com

Language has an important role in presenting sources of information and knowledge. One of the media used as a source of information is print media such as newspapers or newspapers. Newspapers are now not only in the form of print on paper, but many newspapers have created their own blogs or pages so that news can be read online. News has a characteristic, namely using straightforward language and writing systematics that are guided by the General Guidelines for Indonesian Spelling.
AN INVESTIGATION ON THE INSTRUCTIONAL PRACTICES FOLLOWED BY TEACHERS ON CHILDREN WITH READING DIFFICULTIES IN PRIMARY CLASSES

Reading is the most important skill in an individuals' life, which enriches the skills and abilities to develop and plays a crucial role in academic achievements. This study was to investigate the instructional practices of school settings on identification and reading instructions on children with reading difficulties (CRD) in primary classes. A survey research method was carried out in Zonal Education in Puttalam district, 70 primary teachers and 20 principals participated in this study, an open-ended questionnaire, formal interview, and classroom observations were carried out for data collection. Descriptive Statistical methods were used to analyze the quantitative data with the SPSS Ver. 20 software and content analysis method were used to analyze the qualitative data. The results show that the identification of children with reading difficulties was carried out by 71.4% of schools by reading exams or observations. However, there is no valid instrument nor criteria used to identify the children with reading difficulties. The class size is significantly related to the number of students with reading difficulties. 94% of the teachers facilitate the reading and teach the students to read for 1-2 periods per week at the beginning of the year and later they carry out usual classroom teaching as usual. Moreover, these study findings conclude the identification and instructional practices of CRD are low in the Puttalam district, and principals of study do not know what is going on in the classroom, no school-level plans are executed for the literacy or reading developments.
Artificial Intelligence for Indication of Invasive Assessment of Calcifications in Mammography Screening

Purpose Lesion-related evaluation of the diagnostic performance of an individual artificial intelligence (AI) system to assess mamographically detected and histologically proven calcifications. Materials and Methods This retrospective study included 634 women of one screening unit (July 2012 – June 2018) who completed the invasive assessment of calcifications. For each leasion, the AI-system calculated a score between 0 and 98. Lesions scored &gt; 0 were classified as AI-positive. The performance of the system was evaluated based on its positive predictive value of invasive assessment (PPV3), the false-negative rate and the true-negative rate. Results The PPV3 increased across the categories (readers: 4a: 21.2 %, 4b: 57.7 %, 5: 100 %, overall 30.3 %; AI: 4a: 20.8 %, 4b: 57.8 %, 5: 100 %, overall: 30.7 %). The AI system yielded a false-negative rate of 7.2 % (95 %-CI: 4.3 %: 11.4 %) and a true-negative rate of 9.1 % (95 %-CI: 6.6 %; 11.9 %). These rates were highest in category 4a, 12.5 % and 10.4 % retrospectively. The lowest median AI score was observed for benign lesions (61, interquartile range (IQR): 45–74). Invasive cancers yielded the highest median AI score (81, IQR: 64–86). Median AI scores for ductal carcinoma in situ were: 74 (IQR: 63–84) for low grade, 70 (IQR: 52–79) for intermediate grade and 74 (IQR: 66–83) for high grade. Conclusion At the lowest threshold, the AI system yielded calcification-related PPV3 values that increased across categories, similar as seen in human evaluation. The strongest loss in AI-based breast cancer detection was observed for invasively assessed calcifications with the lowest suspicion of malignancy, yet with a comparable decrease in the false-positive rate. An AI-score based stratification of malignant lesions could not be determined. Key Points: Citation Format
Evaluating Data Migrations with Respect to Interoperability in Hybrid Cloud

Cloud computing is the most popular environment in industry which is gaining popularity due to its enormous powerhouse facilities like scalability, virtualization, ubiquitous computing, on demand access to pool of resources on a pay per basis. It provides a broad access to shared resources which are rapidly provisioned with minimal management efforts. Hybrid cloud is the most chosen cloud model in the recent years with its powerful combination of private and public clouds. While working with hybrid cloud model, the data has to be migrated between the private and public clouds as and when needed. This paper studies the performance of hybrid cloud, while the data is migrated between the clouds. This paper deals with consolidation and data distribution technologies implemented for effective data migration technologies in hybrid cloud. CloudSim simulator has been used to study the performance issues of different data migration techniques while implementing interoperability.
Computational Pragmatics

In agent-based data-driven DBS, propositions do not denote truth values. Instead they are content built (i) from the classical semantic kinds concept, indexical, and name, connected (ii) by the classical semantic relations of subject/predicate, object\predicate, adnominal|noun, adverbial|verb, and conjunct−conjunct, (iii) coded by address, (iv) at the elementary, phrasal, and clausal level of grammatical complexity, Computational pragmatics1 relies on the on-board orientation system, which is part of the agent’s interface component and monitors moment by moment as a sequence of STARs.