Reviewerly/exHarmony huggingface dataset:
Pembingkaian Media Online Mengenai Berita Pemilihan Ketua Umum PSSI

Absctract—This research is motivated by the world of Indonesian football which is in the spotlight of many parties for various reasons, one of which is the problem that occurs at PSSI. The Indonesian Football Association (PSSI) as a federation, on Saturday, November 4, 2019, the new General Chairman was officially elected. The online media Tirto.id and Mediaindonesia.com are online-based mass media that quite often disseminate information about the election of a new PSSI General Chair. A media cannot be separated from the construction and determination of attitude in presenting reality, one of which is regarding the election of the PSSI General Chair. This study uses qualitative methods with the Zhongdang Pan and Gerald M. Kosicki framing analysis. This framing analysis looks at how the media frames news facts by exploring four elements of text, namely syntax, script, thematic, script, thematic, and rhetorical. The results showed that, syntactically, Tirto.id and Mediaindonesia.com both compiled a news scheme through headlines and news leads based on background information and source quotes. In a script, Tirto.id presents news more widely, while Mediaindonesia.com presents news that emphasizes only the general chairman election event. Thematically, Tirto.id and Mediaindonesia.com try to prioritize the objectivity of their news. The difference is that Tirto.id is more in-depth and wants to explain the polemic and related issues behind the election of the general chairman compared to Mediaindonesia.com. Rhetorically, Tirto.id and Mediaindonesia.com both emphasize facts on words and sentences in their stories. The difference is that Tirto.id is more numerous and on target so that the news is more interesting and tends to be proactive in its reading. Meanwhile, Mediaindonesia.com is less so that it feels more formal in the news articles. Keywords: News, Framing Analysis, Pan & Kosick i
Consolidated Financial Statements Audit Hour Disclosure and Audit Quality

2014년 개정된 외부감사에 대한 법률에 따라 감사인은 감사보고서와 연결감사보고서에 감사실시내역을 공시하여야 한다. 이와 관련, 별도재무제표 감사보고서 발행 이후 추가로 감사시간을 투입하여 연결감사보고서를 발행한 경우 감사인은 연결감사시간을 추가로 반영하여 공시할 수 있다. 이에 본 연구는 연결재무제표를 발행한 기업을 대상으로 감사보고서와 연결감사보고서 상공시된 외부감사실시내용을 비교, 분석하여 감사인이 연결재무제표 감사시간을 구분하여 공시한 기업을 조사한다. 그리고 연결재무제표 감사에 투입한 감사시간을 별도로 공시한 기업에 대한 감사품질을 분석한다. 구체적으로, 2014-2016 기간, 연결재무제표를 작성하여 공시한 기업 대상 3,196개 기업-연도 표본을 통해 분석한다. 감사품질은 성과조정 재량적발생액의 절대값을 이용한다. 분석 결과, 감사인이 연결감사시간을 별도로 공시한 기업의 감사인의 연결감사 투입시간과 감사품질은 양의 관련성이 나타나 감사노력 증가에 따른 감사품질 제고 결과를 확인하였다. 본 연구는 선행연구에서 인지되지 않았던 감사보고서와 연결감사보고서 상 공시된 감사시간이 차별적으로 나타날 수 있다는 연구결과를 제시함으로써 관련 후속 연구에 유용한 정보를 제공한다. 또한, 감사인의 연결감사업무에 대한 추가적인 노력이 감사품질에 영향을 미친다는 실증 결과를 확인하여 혼재되었던 선행연구의 결과를 해석하는데 도움이 될 수 있다는 공헌점을 지닌다.In accordance with the Act on External Audits, revised in 2014, auditors are required to disclose the audit hours in audit reports and consolidated audit reports. In this regard, the auditor may disclose the consolidated audit hour by additionally reflecting their efforts. However, there is a problem that prior studies do not consider this at all. Therefore, this study examines the companies that the auditor has classified and disclosed the audit hour of the consolidated financial statements. In addition, this paper analyzes the audit quality for companies that separately disclose the audit hour in auditing the consolidated financial statements. Specifically, the analysis period is 2014-2016, and sample is 3,196 company-year samples targeted. Absolute value of performance adjusted discretionary accruals is used for proxy of audit quality. As a result of the analysis, consolidated audit hour is positively associated with audit quality. This study provides useful information for related follow-up studies by presenting research results that the audit hour discriminately disclosed in audit reports and consolidated audit report. In addition, it has a contributing point that it can be helpful to interpret the mixed evidence for association between audit effort and audit quality by suggesting empirical results that the additional efforts of the auditor s consolidated audit work affect the audit quality.
Modeling monthly insulation data

This paper discusses the probability distribution functions (PDF) of monthly insolation for four locations in Libya based on analysis of 30 years of historical weather data calculated by National Renewable Energy Laboratory (NREL), in order to get appropriate probability distribution that best fits the data for a given month of the year. The frequency distributions used for solar irradiation data include Weibull, Normal, Lognormal and Gamma. The observed radiation at four locations in Libya on a monthly basis are analyzed to evaluate the suitability of the probability distribution functions based on the mean square errors. The analysis showed all the probability functions are appropriate for all the locations where weather conditions are relatively steady throughout the year. From the analysis it is concluded that Normal and Weibull distributions gives the best fit for observed solar radiation.
Novel GPU Enabled Deep Learning Architecture for LIDAR based auto labelling for Autonomous Vehicles

As Autonomous vehicles (AV) are closer to becoming reality, it becomes mandatory to be able to characterise the performance of the sensors used in AV before it gets into production deployment. This validation process requires large amounts of ground truth data to be established with precise information about the real world position and pose of the objects around the vehicle. LIDAR is a preferred sensor for ground truthing due to its ability to estimate the depth of the objects precisely. In order to reduce the manual efforts in ground truthing,.In this paper, we propose a novel deep learning network for automated object detection and pose estimation on LIDAR point cloud data, for automated ground truthing. The algorithm is based on a multi-layer deep 3D convolutional neural network with a custom loss function and activation layers. Typically, the volume of point cloud input data itself is huge plus the computational complexity makes training and inferencing highly time intensive. The architecture of the deep learning network is considered in such a way, that the activation functions for the particular layers are designed based on the sensitivity of the feature, which is being extracted from that layer .This helped in saving time of computation with our compromising the accuracy of feature extraction. Loss function was designed so that it utilizes regression to achieve efficient localization of objects. Though the architecture of the network helped improving, the speed of training and inferencing, further improvement was required for efficient training turnaround time and real time inferencing, which was achieved with efficient utilisation of NVDIA GPUs, which was the hardware, used to deploy the automated labelling algorithms The above approaches ensured real time execution of the inferencing engine on Velodyne HDL 64 and 128 LIDAR, which was essential for real time labelling and ground truthing
Library: ANTH Remote Instruction Resources: Getting Started

This guide contains various instruction modules that teachers can use for remote library instruction
PEMBELAJARAN MENULIS TEKS DRAMA PADA SMP KELAS VIII MENGGUNAKAN MODEL EXAMPLE NON EXAMPLE MEDIA KOMIK BERBASIS TEKNOLOGI INFORMASI

This study aims to determine the scenario and implementation of learning to write drama text for VIII grade junior high school students using the Example Non Example Model of IT-based comic media, to determine the responses of teachers and VIII grade junior high school students to learning writing drama text using The Example Non Example Model of IT-based comic media and to find out what difficulties were experienced by VIII grade junior high school students in completing the tasks of writing drama texts. This study uses a qualitative description method. The implementation of learning is in accordance with the learning scenario, but the application of the steps of the non-example model is carried out sequentially. Of the 23 students, there were 19 students who scored above the KKM standard ≥ 71 with a percentage of 82.6% categorized as Very High. Teacher and student questionnaire sheets obtain maximum data, namely the learning of drama texts using the Example Non Example Model of IT-based comic media can provide innovative methods for students, attract student interest, and student motivation to learn. The media used for categorized students succeed in writing drama texts. Student difficulties can be seen from the average knowledge and skills. The lowest average knowledge value is 65 ≤ 100 about language rules, while the lowest average skill value is 67 ≤ 100 about structure
Normalized conformalprediction for time series data

Every forecast is valid only if proper prediction intervals are stated. Currently models focus mainly on point forecast and neglect the area of prediction intervals. The estimation of the error of ...
Research Guides: Quarantine Corner: Government Resources on COVID-19

While classes are online and socializing is limited, here are some things to break the boredom. Links shared by the FDLP for Patrons/Public
Intelligent Robot Design for Five-in-a-Row Game

In this research, an intelligent robot arm is designed to play a five-in-a-row automated game with a user. Hardware and software are developed for a system that integrates artificial intelligence technology with computer vision; a six-axis robot arm is used to achieve the goal of automated game played between human and robot. Results are demonstrated for the system using maximum weighting value and layer tree search and reinforcement learning algorithms. The system also provides protection of user safety during the game when a hand is in the vision range. The results show the system can perform successfully in the game.
≪동문선(東文選)≫의 편찬(編纂) 체제(體制)와 문체(文體) 분류(分類) 및 ≪문선(文選)≫으로부터의 수용(受容)

Dong Mun Seon (東文選) not only contains a large number of Korean ancient literature that is difficult to find in Koryo(高麗) Dynasty and its previous period of poetry and prose works, but also helps to study the literary styles and genres and their development trends and characteristics in ancient Korea. Dong Mun Seon is a collection of selected poetry and prose works according to the style of articles. It divides the ancient poetry and prose works of Korea into 48 styles. Its genre classification and arrangement method are mainly influenced by the collection of articles in Chinese history represented by Wen Xuan (文選). The genre classification and arrangement method of Dong Mun Seon is generally similar to that of Chinese anthologies, which undoubtedly comes from the affirmation and acceptance of the compilation style of these Chinese anthologies by the editors of Dong Mun Seon. Dong Mun Seon classifies all kinds of selected poetry and prose, and collects works in a certain order. Such classification and collection is beneficial to the actual arrangement of a large number of poetry and prose works, and can fully reflect the editors'' deep understanding of genre classification. Generally speaking, the genre classification of Dong Mun Seon is influenced by the collection of traditional Chinese articles and its genre theory, and has its own unique classification characteristics. His anthology accepted the traditional compilation method of “set up the genre according to the text(因文而立體)” represented by the anthology of Wen Xuan, and the genre classification of ancient Korean poetry and prose was generally based on the actual creation of domestic writers. At the same time, there is also a situation of “recording the text according to the style(因體而錄文)” in the selection of Dong Mun Seon.
Privacy Preserving on Searchable Encrypted Data in Cloud

Cloud computing is the latest paradigm which offers different cloud services by rearranging of resources and provides them on the bases of user’s demand. Users are using cheaper data storage and computation offered in the cloud environment, and they are also facing many problems about reliability, privacy-preserving, and optimized searching of their outsourced data. Proposed scheme “Privacy-preserving keyword search” allows users to encrypt their stored data while preserving some search capabilities and also seek few efforts to consider the reliability of the searchable encrypted data outsourced to the clouds. Client-side encryption and server-side searching of encrypted data without decryption in server-side enable more efficient and eliminate privacy issues between client and server.
Understanding Target Suitability in Cyberspace: An International Comparison of Cyber Victimization Processes

Economic forms of cybercrime affect millions of people around the world. Preparatory crimes such as spam, scam and malware are increasingly enacted by cybercriminals. However, literature has shown that some people are more vulnerable than others to these types of attacks and this may be a circumstance that varies cross-nationally. Using a comparative research design, behaviors that are associated with a higher probabUity of victimization by economic preparatory crimes are identified. The results obtained ffom two samples, one Spanish and one Australian, show that despite similar victimization prevalence, the correlates of routine activities vary substantially. While 6 of the 11 behaviors analyzed were similar, other substantial differences were found. The greatest risk for Spanish participants is online shopping, while for Australians it is downloading files. Differences were also found for use of antivirus, pirated software, contacting strangers and taking part in video conferences. Based on the current research, it is concluded that cyber victimization should locus on identifying nuances in the daily activities performed by online users, rather than on broader constructs such as interaction or visibility. Further, preventive strategies must take into account differences in routine behaviors across different geographical areas.
Design of 2D fringe pattern for tele-centric Fourier transform profilometry

A one-shot fringe projection scheme with a 2D fringe pattern for tele-centric Fourier transform profilometry is presented. Even though the size of the inspected object is so small that the surface is not fully projected by one fringe, unwrapping can be performed without ambiguity.
SOFTWARE EFFORT ESTIMATION USING NEURO-FUZZY APPROACH BASED ON LEVEN-MARQUARDT ALGORITHM

Software effort estimation is the method of estimating the effort and expense required to build computer. Efficient software development is focused on an accurate estimate of effort. When an effective and appropriate approach is not used for estimation, it may lead to a failure of the project. There are a number of methods available for estimating the effort. This paper discusses the Leven-Marquardt algorithm used to train neural networks. The suggested methodology used the combination of neural networks and fuzzy logic as a neuro-fuzzy approach to the calculation of machine effort.
Smart chatbots as virtual assistants in the Library

The aim of the editorial is to constitute the first step of a project on smart CRM, Chatbot and Artificial Intelligence systems for informational and didactic orientation in scientific libraries. Availability and characteristics of software for interacting with users of information services is examined. In particular, Chatbots connected to AiaS services (Artificial Intelligence as a Service) could manage the interaction between human beings and smart software through the Internet. So that way will be possible to take into account the users actual needs, according to different binding conditions. This user interface would be able to collect and define an information profile of the applicant. Data is so available to improve the front end organization and of the linked document bibliographic repository as well. Overcoming the current metaphor based on browsing through a paper document with fingers, would surely be advantageous, starting a new (always analog) way of interacting with machines just talking with them. Particularly in order to gather Net docuverse information, notable characteristics of IBM, Apple and Amazon experimental front ends are briefly discussed. Significantly, a particular use of these smart interfaces is for didactic orientation, being able to take into account the curricular specificity of the learner and the characteristics of the training system. The advantages for research and teaching of these Smart Systems are considerable, integrating perfectly with the IT tools currently available, without requiring financial investments beyond the reach of Public research Institutes
Personal Contexts Of Social Educators Professional Training

The article is devoted to the analysis of subjective foundations of social educators training. The authors aim to identify the relationship between personal meanings of individual life of students and their professional orientation. As criteria for the personal context of vocational education, the authors propose to consider orientation of students to their own social experience; life attitudes of students; personal meaning of knowledge. The study was conducted using a survey in which 288 3–5-year students from 14 Russian universities took part. It showed that the students’ lifestyles for constructive interaction with others in general coincide with the competencies that they should master in the learning process. In the learning process, students “refract” the acquired knowledge through a personal context; this allows them to understand better the essence of social pedagogy as a theory and practice of solving social problems of the family and the child. The empirical research data allowed the authors to conclude that, in general, the personal context plays a significant role in the student's understanding of himself/herself as a future specialist. The following methods of updating personally significant professional knowledge and competencies are disclosed in the article: an increase in active teaching methods, including case studies, discussions, problem solving; teamwork when passing pedagogical practices; regular reflection of educational activities, including focus groups; development of collective and individual start-ups as final qualification works.
Adversarial Open Set Domain Adaptation Based on Mutual Information

Domain adaptation aims to transfer knowledge from a domain with adequate labeled samples to a domain with scarce labeled samples. Prior research has introduced various open set domain adaptation settings in the literature to extend the applications of domain adaptation methods in real-world scenarios. This paper focuses on the type of open set domain adaptation setting where the target domain has both private ('unknown classes') label space and the shared ('known classes') label space. However, the source domain only has the 'known classes' label space. Prevalent distribution-matching domain adaptation methods are inadequate in such a setting that demands adaptation from a smaller source domain to a larger and diverse target domain with more classes. For addressing this specific open set domain adaptation setting, prior research introduces a domain adversarial model that uses a fixed threshold for distinguishing known from unknown target samples and lacks at handling negative transfers. We extend their adversarial model and propose a novel adversarial domain adaptation model with multiple auxiliary classifiers. The proposed multi-classifier structure introduces a weighting module that evaluates distinctive domain characteristics for assigning the target samples with weights which are more representative to whether they are likely to belong to the known and unknown classes to encourage positive transfers during adversarial training and simultaneously reduces the domain gap between the shared classes of the source and target domains. A thorough experimental investigation shows that our proposed method outperforms existing domain adaptation methods on a number of domain adaptation datasets.
Kombinasi Algoritma Brute Force dan Stemming pada Sistem Pencarian Mashdar

In this study Brute Force and Stemming algorithms are combined in the mashdar word search system. The purpose of this study is to facilitate the user in finding the basic words of a word along with its changes based on the review of basic words to mashdar. The data used in this study were obtained from 50 books of Tashrif by Sheikh Hasan bin Ahmad. The results of the study by combining brute force and stemming algorithms in mashdar search with a test sample of 15 words obtained an accuracy value of 78.9%, 86.6% precission, 84.6% recall and 66.6% specificity.
Development of a phase shifting interferometer using recycled components

We present the development of a single shot interferometric system based on polarization and diffractive elements recovered from spare computers. The use of salvaged lenses, beam splitter cubes and linear polarizers lower the cost of our system in comparison with those already reported. Our system is also capable of dynamic phase measurements with an accuracy comparable to similar implementations with high end manufactured optics. We report here our results obtained from four simultaneous interference patterns. The presented interferometer can be easily implemented for various applications in single shot polarizing phase shifting interferometry.
Hybrid swarm intelligence for feature selection on IoT-based infrastructure

Swarm intelligence techniques are deployed to estimate the fitness on the search spaces and estimates the optimisation. Since the evolution of the genetic algorithm (GA) and particle swarm optimisation (PSO) optimisation problems and complex real-world problems were solved. There is a need to enhance the performance of optimisation and exploration of the search spaces. In moth-flame optimisation algorithm, the fittest moth-flame combinations with the best positions of the moth-flames after many iterations provided the optimal solutions. There is a concern for local-minima for moth-flame optimisation and the convergence rate is more, so it may skip the global optimal search. The combination of the simulated annealing (SA) and the moth-flame optimisation (MFO) provides a solution to local minima, increases the diversity of the population and increases the exploration, reduces the convergence rate to increase the performance of MFO to reach the global optima and increases the performance of MFO.
The nexus between financial development and human development: the case of developing countries / Bilgehan Tekin

The purpose of this study is to examine the relationship between financial development and human development from the health and welfare dimensions of developing countries. This study aims to determine whether the financial developments of the countries have an effect on the basic human development of the individuals and whether human development indicators have an impact on financial development. In this study, the relationship between financial development and human development were revealed by using data obtained from developing countries. The financial development levels of countries was measured using the financial development index. The index is calculated by using M3 / GDP, private sector loans / GDP and loans to banks from private sector / GDP ratios. The human development index is calculated by considering various health indicators and GNP per capita. The data includes annual data for the period 1970- 2016. Pedroni and Kao cointegration analysis and Dumitrescu and Hurlin panel causality analysis were performed in the study. The results show that there is long-term cointegration relationship and two-way causality between financial and human development in developing countiries.