Reviewerly/exHarmony huggingface dataset:
Analisis penerimaan pemustaka terhadap electronic theses &amp; dissertations di Perpustakaan Universitas Gadjah Mada

Introduction. Electronic theses &amp; dissertations is one important service at Universitas Gadjah Mada (UGM) Library is to simplify the end-user reading service. However,it is still not understood whether the users are satisfied with the new service. An analysis is needed to examine the user acceptance of electronic theses &amp; dissertations implemented by UGM Library.Data Collection Method. This paper used an acceptance analysis with a qualitative approach by interviewing three UGM students.Analysis Data. The paper applied Stuart Hall's theory of encoding-decoding.Results and Discussions. The results showed that the informants were categorises into two positions. One informant was in a dominant hegemonic position and the others were in negotiated positions. The background of the study program, the level of education and experiences, might influence the differences in the acceptance and interpretation of electronic theses &amp; dissertations.Conclusions. There are various perspectives of how users examine to the electronic theses &amp; dissertations at UGM Library.
THE EFFECT OF LEARNING MODELS AND INDONESIAN LANGUAGE PROFICIENCY, ON THE ABILITY TO WRITE PROCEDURAL TEXTS

The purpose of this study was to determine the effect of learning models and Indonesian language proficiency, on the ability to write procedure texts in Seluma Vocational High School students. The method used in this study is the experimental method. The data in this study were collected using test techniques, namely the writing test and the objective ability test for writing text procedures. The results showed that there was an influence between the interaction of learning models and Indonesian language proficiency on the ability to write procedure texts in class XI Vocational High School students in Seluma. The conclusion in this study is that the learning model and Indonesian language proficiency significantly influence the ability to write procedure texts of class XI students at Seluma State Vocational School.
Three music facility makeovers in Arizona

Considerable prior experience at higher education music campuses in Flagstaff, Chandler and Mesa, Arizona led to our engagement in substantial repurposing and renovation of their rehearsal, recording, practice, and performance facilities. Specific challenges due to existing mechanical system noise, poor sound isolation, and overall room-acoustics issues are discussed as well as their solutions and measured data upon completion.
The Development of Vocabulary Learning Media By Using "Mini Walking Dictionary" Refers to the Project-Based Learning to the Students of Vocational High School

The ability of a person to speak English as a mean of communication both oral and written is influenced by mastering the vocabulary. Unfortunately, the vocabulary lessons are considered as old learning and it's abandoned by English teachers today. “Mini Walking Dictionary” offers the solution. This dictionary is developed from students' project-based learning and enhanced through 4 stages: the define phase, the design phase, the development phase and the disseminate phase. Thus it will create a valid and practical vocabulary media for students. Mini Walking Dictionary has been arranged based on the students' condition and characteristic aspects that all of them have been analyzed in detail. Therefore, Mini Walking Dictionary is very appropriately used to help the English teachers as a first step in overcoming the problems of students who have difficulty in learning English both oral and written. Keywords: Learning media, the development of learning media, Mini Walking Dictionary, Vocabulary learning, project-based learning.
Copyright of artificial intelligence autonomous production: some reflections around the concepts of mind and intelligence

The research problem of the present article consists of two questions: can an Artificial Intelligence (IA) be considered an author? Who owns the copyrighted material produced by IA? The first topic gives a brief deductive and theoretical approach to the ontology of mind and artificial intelligence. Subsequently, the compatibility between these guidelines for the legal concept of author contained in some Copyright Laws. In the end, it is proposed the ontological impossibility of an AI holds intellectual property rights, even if derived from autonomous acts, attributing them to its programmer/creator.
Lightweight prediction based big/little design for efficient neural network inference

The accuracy improvement of neural networks may be only a few percentage points while the computation effort explodes, as previous less computation-intensive designs can already produce correct results for a large portion of inputs. We employ a lightweight prediction based Big/Little design to process those "easy" inputs with a little DNN and those "difficult" inputs with a big DNN.
Training of Multi-layered Neural Network for Data Enlargement Processing Using an Activity Function

In this paper, we present a study on activity functions for an MLNN (multi-layered neural network) and propose a suitable activity function for data enlargement processing.We have carefully studied the training performance of Sigmoid, ReLu, Leaky-ReLu and L & exp.activity functions for few inputs to multiple output training patterns.Our MLNNs model has L hidden layers with two or three inputs to four or six outputs data variations by BP (backpropagation) NN (neural network) training.We focused on the multi teacher training signals to investigate and evaluate the training performance in MLNNs to select the best and good activity function for data enlargement and hence could be applicable for image and signal processing (synaptic divergence) along with the proposed methods with convolution networks.We specifically used four activity functions from which we found out that L & exp.activity function can suite DENN (data enlargement neural network) training since it could give the highest percentage training abilities compared to the other activity functions of Sigmoid, ReLu and Leaky-ReLu during simulation and training of data in the network.And finally, we recommend L & exp.function to be good for MLNNs and may be applicable for signal processing of data and information enlargement because of its performance training characteristics with multiple teacher training patterns using original generated data and hence can be tried with CNN (convolution neural networks) of image processing.
LibGuides: ENC1102 Powley OER: History

Resources for Dr. Tammy Powley's English Composition II open educational resource course at Indian River State College.
초등 사회과 지역 수준 교육과정과 지역 교과서의 발달 : 대구시를 사례로

This study is to trace development of regional curricula and textbooks, based on the 4th grade social studies regional textbooks in the city of Daegu. The curricular regionalization in the social studies has been emphasized since the syllabus era, but its genuine starting point was the 6th National ...
Impact of TLS 1.3 to Operational Network Security Practices

Network-based security solutions are used by enterprises, the publicsector, internet-service providers, and cloud-service providers toboth complement and enhance host-based security solutions. As TLS is awidely deployed protocol to secure communication, these network- basedsecurity solutions must necessarily interact with it. This documentdescribes this interaction for current operational security practicesand notes the impact of TLS 1.3 on them.
Headlight Range Estimation for Autonomous Driving using Deep Neural Networks.

When driving at night, a good illumination of the road ahead is crucial. With autonomous driving at close temporal proximity, this not only concerns human drivers but also autonomous systems capable of controlling the car. To achieve fully autonomous driving, a variety of sensors are integrated into the vehicles. Cameras act as one of the major sensors. However, due to their passivity, cameras cannot see well in the dark. To mitigate this shortcoming, modern cars are equipped with powerful headlights that provide proper illumination of the road ahead while avoiding the dazzling of other traffic participants. To use the headlights' full potential and to also provide advanced light functionality like glare-free high beam, they need to be properly adjusted. After the initial calibration during production, this setting is prone to undesirable degradation, primarily due to mechanical reasons. We present a completely new application of computer vision and machine learning to automatically detect wrongly adjusted headlights by estimating their pitch angle from the images of a vehicle-attached camera for advanced driving assistance systems (ADAS). We show that we can achieve high performance in terms of accuracy and robustness by training a deep neural network in an end-to-end fashion. To demonstrate the benefits of our proposed approach, an additional handcrafted baseline method is implemented.
Learning interpretable Gene Regulatory Networks via merging Bayesian networks

Nuestro trabajo empieza con la necesidad de reconstruir una red de regulacion genetica para el genoma humano usando datos del cerebro. Para conseguirlo, estudiamos el problema biologico de como aprender una red de regulacion genetica y revisamos la literatura para ver cuales son los metodos mas populares para resolver este problema, junto con sus ventajas y limitaciones. Al final, decidimos que el metodo que mejor se ajusta a nuestras necesidades son las redes bayesianas, sobre todo por su interpretabilidad. En este trabajo presentamos un nuevo algoritmo, FGESMerge, capaz de aprender la estructura de una red de regulacion genetica mediante la union de varias redes bayesianas aprendidas localmente alrededor de cada uno de los genes, utilizando una variante del Fast Greedy Equivalence Search (FGES). El metodo es competitivo con el estado del arte en su capacidad de recuperar la estructura original y ademas es mucho mas rapido y escala a decenas de miles de variables. Tambien presentamos una solucion al problema de inferencia para redes bayesianas con miles de variables. FGES-Merge y la herramienta de inferencia estan disponibles publicamente en Neurosuites y pueden ser utilizadas por la comunidad de biologia para guiar su investigacion hacia las interacciones entre genes que nuestro modelo predice.---ABSTRACT---Our work was motivated by the need of learning a genome-wide regulatory network for the human brain from the Allen Human Brain Atlas dataset. To achieve this, we studied the biological problem and we reviewed the literature for different methods for learning gene regulatory networks, noting their advantages and limitations. We decided to use Bayesian networks because of their interpretability and so we present a new method for learning the structure of gene regulatory networks via merging of locally learned Bayesian networks, based on the Fast Greedy Equivalent Search algorithm. The method is competitive with the state of the art in recall of the true structure while also being much faster and scaling up to the tens of thousands of variables. We also solved the problem of inference for large numbers of variables in Bayesian networks. Both the structure learning algorithm and the inference tool are available publicly at Neurosuites and can be used to guide biological research by testing new gene interactions that are predicted with high confidence by the model.
Application of Quality in Use Model to Assess The User Experience of Open Source Digital Forensics Tools

Open source digital forensics tools are playing an important role for forensics investigations. So, there is a need to assess these tools to ensure they meet users' needs. The existing literature does not satisfy the requirements of assessing their quality-in-use. This paper assesses three most used digital forensics tools, namely autopsy, DFF, and DART using five quality-in use characteristics, namely, effectiveness, productivity, efficiency, error safety, and cognitive load. The results demonstrated that Autopsy, DFF, and DART performances are similar in terms of efficiency and productivity. DDF outperformed the other two in effectiveness. Autopsy was the best in terms of error safety, and DART had the highest cognitive load. The relevant community may consider these findings in selecting solutions to perform its duties. The future researches can involve more studies to encompass additional aspects of software quality, to compare open and closed source digital forensics programs and to enhance testing efforts
Synthetic Analysis of Hidrograf Units using the Method of HSS Nakayasu, Snyder And Limantara (Study in DAS Way Sulan)

DAS Way Sulan located in East Lampung Regency of Lampung Province. DAS Way Sulan this was the area of review in the research of the preparation of this thesis. Flood-prone areas in the planning area includes the  rea of the estuary's Way Home, flood plains and alluvial plain especially along the Way Sulan. Factors cause flooding include the high rainfall, the closure of land upstream capacity and reduced flow of the rivers especially in areas of lower reduced due to sedimentation and topographic area. Flood hazards/safeguards for potential flooding in River Way Sulan can do planning safeguards against a flood with a building plan that aims to reduce the damage that occurs due to the flood levels most minimum. Building planning in the field of water resources can be done well if rainfall data at each station the rain can be known and calculated using the debitnya method of the HSS
중국인 학습자를 위한 문화교육으로서 한 중 소설 비교읽기* -4.19와 문화대혁명을 중심으로-

The article purpose is Reading Chinese translation text as a Korean integrated education for Chinese students . Although number of foreign students...
TIPPING POINTS PILOT STUDY: WEARABLE DEVICES AND ALGORITHMS

Abstract Little is known about the use and acceptability of fitness watches (e.g. Fitbit) by diverse older adults, or how data from affordable (&amp;lt;$40) devices could be triangulated with self-report data to predict adverse health outcomes. We investigated interest and acceptability of fitness watch technology among Mexican American older adults via a week-long trial. Participants were asked to consistently wear the watches and complete daily diaries of activity, questionnaires, and a semi-structured interview. The watch data was triangulated with data from the daily diaries and questionnaires to validate its usefulness in developing algorithms that could detect important physiological transitions that lead to tipping points. Interview data was qualitatively analyzed and coded for barriers and facilitators of watch use and acceptability. Preliminary results suggest that participants are eager and willing to wear a fitness device. Participants reported interest in monitoring their health and using the device to track and improve physical activity.
Shall and Will in the Corpus of History English Texts

This paper deals with the meanings of the verbal forms shall and will in the late Modern English period, as evinced in the Corpus of History English Texts .Earlier literature on modal verbs in historical periods includes Fachinetti (1997) and Gotti (2003).We study these modals using corpus tools in order to identify the senses of these two verbs in context and to group findings according to meaning.Our notion of modality mainly follows from Palmer (1986; 2001 ), Hoye (2008) ) and van der Auwera and Plungian (1998).Conclusions show that these verbal forms had indeed modal meanings, even if their periphrastic use to indicate future was evident.
ICT-Media Exposure and HIV/AIDS Awareness Among Adolescent Almajiri Pupils in the North-East of Nigeria: A Knowledge, Attitude and Practice Conceptual Review

We thank Prof. Muhammad Yahuza Bello, Vice-Chancellor, Bayero University Kano (BUK), Nigeria and Umaru A. Pate, Dean, School of Postgraduate Studies, BUK for their kind intellectual support. Abstract The importance of information and communication technology-related media awareness in health communication cannot be overemphasized. Perhaps the importance of ICT in health communication may not be well grasped without the prior understanding of the central position information and communication occupy within the health communication matrix. Over the last three and a half decades, HIV/AIDS pandemic has been one of the topical public health issues in Sub-Sharan Africa, especially in Nigeria. The application of ICT in combatting the scourge in the country needs no further emphasis especially because Nigeria is the most populous nation in Africa and the second nation with the highest population of HIV infected people in the world. Adolescence, literacy, media awareness and other social issues have been identified as significant factors aiding the spread of the scourge. Despite the progresses made in research in this area, issues regarding ICT-related HIV/AIDS media awareness among almajiri pupils in the country, particularly in the North-East region where the population of almajiris is the highest, has received little research attention. This paper proposes a conceptual framework designed on a mixed method approach for adoption in exploring the HIV/AIDS ICT-media awareness based on the knowledge, attitude and practice (KAP) analysis. The paper is expected to provide a strong conceptual underpinning toward an empirical investigation of this problem, with the aim of assessing the relevance of ICT in combatting the scourge among one of the most vulnerable groups in the society. Keywords: Adolescents, Almajiri pupils, KAP, Media awareness, HIV/AIDS, ICT and health communication, North-East of Nigeria DOI : 10.7176/NMMC/85-03 Publication date: November 30 th 2019
Case Study on User-Specific Online Comparison and Program Development and Operation Based on the Core Capabilities of University

대학의 구조개혁 및 국가지원 사업에서 사회적 흐름의 변화와 대학교육의 사회적 적합성을 향상시키는 지표로 핵심역량 기반 교육과정이 중요시 되고 있다. 이에 수요자 중심 역량기반 온라인 비교과 프로그램을 개발 및 운영한 사례를 통해 시사점을 제공하는데 목적이 있다. 본 연구는 온라인 비교과 프로그램을 구성하기 위해 재학생 사전 수요조사, 콘텐츠 개발 및 프로그램 운영, 사후 만족도 조사, 개선안 도출 및 환류평가의 프로세스로 진행되었다. 실시 결과, 글로컬역량 관련 요구도가 가장 높았으며, 해당 강좌를 온라인콘텐츠로 개발하고 학습관리시스템에 탑재하여 학생들에게 제공하였다. 수강학생 설문조사 결과, 연습중심의 콘텐츠는 시스템적 지원에 대한 요구가 많았으며, 내용중심의 콘텐츠는 강사와 내용전달방식에 따라 만족도가 다르게 나타났다. 또한 사전사후 핵심역량의 차이를 분석한 결과 해당역량에 유의미한 변화가 있었다. 본 연구는 향후 온라인 비교과프로그램 개발 연구 시 콘텐츠의 내용과 방식, 시간 등의 주요 변인연구에 시사점을 제시하였다.Core competency-based curriculum is gaining importance as an indicator of changing social trends and for improving the social suitability of university education in the structural reform of universities and state support projects. Thus, this study aimed to develop customerpersonalized competency-based online extracurricular content, and thus provide implications for future curriculum research. To this end, a student pre-demand survey, content development and program operation, a post-satisfaction survey, elicitation of student satisfaction, and reflective evaluation were carried out in order to organize an online program. The courses were developed as online content and were provided to students through the learning management system. Results showed that the demand for glocal competency was most. The survey results revealed that practice-oriented content required considerable technical support, and content-oriented content elicited different satisfaction levels depending on the instructor and the method of content delivery. In addition, an analysis of the core competencies after the program showed significant changes in those competencies. This study provides implications for future online extracurricular development research, such as for content, “method of delivery and time taken to learn.
The Effectiveness of Group Investigation Strategy in Teaching Reading Comprehension. (A Quasi Experiment at First Grade Senior High School of Kramatwatu).

Fitria Febriyanti. 152301903. 2019. The Effectiveness of Group Investigation Strategy in Teaching Reading Comprehension. (A Quasi Experiment at First Grade Senior High School of Kramatwatu).This research investigates the effectiveness of group investigation in teaching reading comprehension on descriptive text lesson. This research is aimed at knowing the application of group investigation strategy in teaching reading comprehension at first grade senior high school of SMAN 1 Kramatwatu; and at knowing the influence of group investigation strategy on student’s reading comprehension at first grade senior high school of SMAN 1 Kramatwatu. The method used for this research is experimental with two classes, called experiment and control class using pre-test and post-test technique. This research involves 60 students as sample among first class of SMAN 1 Kramatwatu year 2019 as population. This result of this research shows that score of t-test t0:tt = 5,31 > 2,00, in degree of significance 5% and t0:tt = 5,31 > 2,66 in degree of significance 1% so that Hα (alternative hypothesis) of the result is accepted and Ho (null hypothesis) is rejected. It means that using group investigation strategy has significant influence in teaching reading comprehension.Keywords: Experimental, Group Investigation, Reading Compreh
Improving localization-based approaches for breast cancer screening exam classification

We trained and evaluated a localization-based deep CNN for breast cancer screening exam classification on over 200,000 exams (over 1,000,000 images). Our model achieves an AUC of 0.919 in predicting malignancy in patients undergoing breast cancer screening, reducing the error rate of the baseline (Wu et al., 2019a) by 23%. In addition, the models generates bounding boxes for benign and malignant findings, providing interpretable predictions.
SemIDEA: Towards a Semantic IoT Data Analytic Framework for Facilitating Environmental Protection

Internet of Things (IoT) is an emerging paradigm that involves both industry and academic communities. In term of smart cities, IoT plays an essential role in the technological development applied to society to improve life quality. In several application fields such as environmental monitoring, using the concept of the sensors network to produce data is also considered as the Internet of Things platform for data producing. In the race of designing IoT as a part of the Future Internet architecture, Information and Communication Technology (ICT) industry and academic communities have realized the crucial problem in IoT is the interoperability of the information and sersvices [1]. In order to enable the interoperability among systems and data services in sensors networks, in this paper we propose an IoT data analytic framework that deals with the heterogeneous sensors data sources and play as a data management tool in the context of environmental monitoring. This proposed framework also helps reuse data, share knowledge and provide environmental rules among the data services with Semantic Web technologies across IoT platforms. We describe a semantic data model, rules, and a reasoning platform taking SPARQL queries as rules to enable high-level data abstraction and knowledge extraction. Our approach is realized by Semantic Web technologies as the core with reusable components for supporting different types of services through Web of Things.
LibGuides: ENC1102 Powley OER: Biography

Resources for Dr. Tammy Powley's English Composition II open educational resource course at Indian River State College.