Reviewerly/exHarmony huggingface dataset:
Visualization of Data on Earthquake Prone Areas from the Analysis of Earthquake Data Vibrations

The earthquake is a natural disaster that often occurs in Indonesia recorded 50 times in 2019 which is the largest contributor to losses both houses, public facilities, and the second casualties after the tsunami. The cause of the many losses from earthquakes is the detection and notification, as well as earthquake monitoring is still relatively slow, by using earthquake vibration data we can analyze earthquake-prone areas from indicators of magnitude, frequency, depth, as well as the risk of loss if affected by a disaster especially the earthquake in this study required a data house design to do ETL (Extract, Transform, Load) using Pentaho data integration which transforms data into OLAP then vibration data is analyzed using Fuzzy Topsis method to determine earthquake-prone areas then data is displayed using Desktop Tableau provide information to the regional service to find out earthquake-prone areas and the risk of losses to be monitored, overcome and early notice to the public.
Klasifikasi Kinerja Pengajaran Dosen Menggunakan Metode ANFIS Sebagai Upaya Peningkatan Sistem Penjaminan Mutu Internal (SPMI)

A college is a place for education providers that aim to produce quality human resources and be able to face increasingly fierce work competition. Lecturers become one of the important elements in producing competent human resources. The task of the lecturer is to carry out the Tri Dharma of Higher Education which includes teaching, research and community service. The purpose of this study was to obtain a teaching performance classification of lecturers using the Adaptive Neuro-Fuzzy Inference System (ANFIS) method as an effort to improve the internal quality assurance system. Where in this learning process planning, implementation, evaluation, control and improvement have been carried out as a form of implementation of the Internal Quality Assurance System (SPMI). The data used in this study are data from the questionnaire sheets of lecturers' reaction sheets from students to the teaching of lecturers who support courses. The data used is data for 1 academic year, namely data for the 2017/2018 academic year. The results of this study are that ANFIS is suitable for classifying lecturers' performance because the accuracy obtained is 0.5.
Querying XML Data using Description Logics

Recently, ontology-based data access is more and more employed in the context of data integration. That is, to the usual data layer of an information system we superimpose a conceptual layer to be exposed to the client. In this paper, we discuss a way to query XML data over conceptual layer using Description Logics. Given a XML data file, we first map the XML DTD to a corresponding relational schema preserving the original semantics of the XML DTD, and at the meantime, we store the XML data into the relational database. After that, we create an ontology described in Description Logics with respect to the relational schema. When a Description Logic query is posted to the ontology TBox, we map it to SQL query with respect to the relational database. In this way, we can query XML data using Description Logics. The main contribution of this thesis can be seen as the following two parts: 1. We proposed a mapping from XML DTD to relational schema with constraints preserving the original XML DTD semantics. 2. We described a framework of querying XML data using Description Logics, more precisely, the DL-LiteA logic.
High assurance on cyber-physical interactive systems

This work was financed by National Funds through the Portuguese fundingagency, FCT - Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) within project: UID/EEA/50014/2019
Algorithm Based on Stockwell Transform for Processing of Communication Signal to Detect Superimposed Harmonics and Transient Disturbances

An algorithm based on Stockwell Transform focused on processing of communication signals to detect harmonics and transient disturbances superimposed on the signals is presented in this paper. These disturbances are being superimposed on the signals in the communication channel or at the transmitter or the receiver stations. Investigated transient disturbances include impulsive transient and oscillatory transients. Communication signals incorporating harmonics or transient disturbance are decomposed with the help of Stockwell Transform and S-matrix is derived. A summation of absolute values curve, median curve and maximum absolute values plot are proposed to detect disturbances. These curves are obtained from S-matrix. On comparing these plots of signal having harmonics or transient disturbances with respective curves of pure sinusoidal communication signal, superimposed harmonics or transient disturbance have been detected successfully. Effectiveness of the proposed approach is established using the MATLAB software.
The Effectiveness of Hypno-EFT in Reducing Public Speaking Anxiety in Vocational high school X Jakarta Students

Students majoring in office administration are more afraid of public speaking than examinations. Students feel insecure add to their anxiety to do public speaking. This study aims to empirically examine the effectiveness of Hypno-EFT in reducing public speaking anxiety in vocational high school X Jakarta students. The sample in this study was adolescents in class 10-1 majoring in office administration, vocational high school X Jakarta, with a total of 30 study participants. The research method used was a quasi-experimental one group pretest posttest design. The data analysis technique used in this study was paired sample t-test. Based on the analysis, it is known that there are differences before and after hypno-EFT which shows Hypno-EFT is effective in reducing public speaking anxiety in vocational high school X Jakarta students with a significance value of 0,000 (p
Creating Computer Games

Writing computer games is a great way to make programming enjoyable, but it does have its disadvantages. The main disadvantage is that to make a working game you need to write a lot of code which takes a lot of time. A full working game is usually too much for a beginner programming book. Fear not, as this book uses worked examples and takes advantage of the simplicity of Python and Pygame Zero to make it as painless as possible. In this book you will create a few different games to illustrate different programming techniques.
Figshare integration with ORCID

Presented at the ORCID Research Visibility Workshop, Merensky Library, University of Pretoria, Pretoria, South Africa, 14 August 2019
LibGuides: JoVE: Science Education

This guide provides information about JoVE and the features available through Gumberg Library's subscription.
Self-Assttentive Associative Memory

Heretofore, neural networks with external memory are restricted to single memory with lossy representations of memory interactions. A rich representation of relationships between memory pieces urges a high-order and segregated relational memory. In this paper, we propose to separate the storage of individual experiences (item memory) and their occurring relationships (relational memory). The idea is implemented through a novel Self-attentive Associative Memory (SAM) operator. Found upon outer product, SAM forms a set of associative memories that represent the hypothetical high-order relationships between arbitrary pairs of memory elements, through which a relational memory is constructed from an item memory. The two memories are wired into a single sequential model capable of both memorization and relational reasoning. We achieve competitive results with our proposed two-memory model in a diversity of machine learning tasks, from challenging synthetic problems to practical testbeds such as geometry, graph, reinforcement learning, and question answering.
Prediction Priority of Defective Modules for Testing Resource Allocation

Software development is a complex process, and extensive software systems developed by integrating the smaller modules that are tested independently during the testing phase. The testing phase is tedious and provided with limited time and resources to produce the software on time. To distribute the proportionate allocation of software testing resources for cost reduction using software defect prediction has drawn notable attention. Although there have been lots of studies on using software product metrics to identify defect-prone modules, the priority of defective modules for testing resource allocation is still unexplored. It is not easy to assess the appropriate amount of workforce for the exact software module testing concerning its number of faults present. There is much work done in the prediction of the fault-proneness of the software systems, which predicts either a module is faulty or not. However, it is the priority that needs to be identified in terms of low, medium, and high, which will decide the resources and the order in which the defect should resolve. The most-faulty module matters more for a developer and needs immediate attention. Therefore, in this study, the prioritization of faulty modules in low, medium, and high categories for software defect dataset is performed. A new infrastructure, software defect prediction model, based on categorized data is developed, and extensive study with benchmark machine learning algorithms is designed and conducted for different software fault datasets. The main impact of this work is to allow the appropriate allocation of testing resources to the prioritized modules.
Research Guides: Executive DBA courses: Citation Management

A guide specifically for the doctoral candidates in the Executive DBA program. Also useful for other courses with traditionally academic research assignments.
Watermarking Image Scheme Based on Image Content and Corners Decomposition Method

In this paper, we suggest a new watermarking scheme. The purpose of this technique is based on image content description and specifically the corner points. In our proposed scheme, Harris detector is used for get some corner points, which are united with a rectangle decomposition method in order to get a set of insertion blocks and to bind the watermark with the image content. The proposed scheme is divided into two phases: The embedding scheme, where we embed the watermark into the original image (one bit of message in each rectangle insertion block) to get the watermarked image. The extracting scheme is the reverse phase that aims to extract the embedded message from the watermarked image. The experimental results demonstrate that the proposed scheme preserves the image visual quality (PSNR up than 53 dB) and with less algorithm complexity (0.3 s as average) and we arrive to detect 100% of message embedded (messages between 9 to 20 bits) in various images.
Bilinear Graph Neural Network with Node Interactions

Graph Neural Network (GNN) is a powerful model to learn representations and make predictions on graph data. Existing efforts on GNN have largely defined the graph convolution as a weighted sum of the features of the connected nodes to form the representation of the target node. Nevertheless, the operation of weighted sum assumes the neighbor nodes are independent of each other, and ignores the possible interactions between them. When such interactions exist, such as the co-occurrence of two neighbor nodes is a strong signal of the target node's characteristics, existing GNN models may fail to capture the signal. In this work, we argue the importance of modeling the interactions between neighbor nodes in GNN. We propose a new graph convolution operator, which augments the weighted sum with pairwise interactions of the representations of neighbor nodes. We term this framework as Bilinear Graph Neural Network (BGNN), which improves GNN representation ability with bilinear interactions between neighbor nodes. In particular, we specify two BGNN models named BGCN and BGAT, based on the well-known GCN and GAT, respectively. Empirical results on three public benchmarks of semi-supervised node classification verify the effectiveness of BGNN -- BGCN (BGAT) outperforms GCN (GAT) by 1.6% (1.5%) in classification accuracy.Codes are available at: this https URL.
Ray W. Howard Library: Stable Links: eReference

This guide will cover proxy prefixes and the use of building URLs that will work for both on campus and off campus users within the Shoreline Community College information systems. The information here reflects the changes being made to our certificates Reference books like encyclopedias and dictionaries need to be linked with proxies through our EZProxy for off campus use. We have Oxford resources like the Oxford English Dictionary and the Encyclopedia of Human Rights.
PENGARUH MODEL PEMBELAJARAN EXAMPLE NON EXAMPLE (ENE) TERHADAP KEMAMPUAN MENULIS DESKRIPSI PADA SISWA KELAS IV SEKOLAH DASAR

This study aims to determine the effect of Example Non-Example (ENE) learning model in improving students' writing description skills. Example Non-Example (ENE) learning model is a type of learning that utilizes images in conveying learning material. Students are required to analyze the picture shown by the educator then pour it into the written description. This research method is a kind of quantitative research types quasy Experiment Design. The population in this study were all grade IV students of SD Muhammadiyah 1 Bandar Lampung. The sample in this study was class IV C as an experimental class, and class IV A as a control class. The sampling technique is to use the Simple Random Sampling technique. Data analysis techniques using the normality test, homogeneity test, and hypothesis testing (t-test). Based on the results of this study there is the influence of the Example Non Example (ENE) learning model and the conventional learning model on the writing skills of the students' description. That is, there is the influence and the difference between the experimental class and control class.
An Analysis of Students’ Narrative Text Translation from English to Indonesian at the Tenth Grade Students of SMA N 3 Kota Jambi Academic Year 2018/2019

This research was done to analyze the translation methods used by the tenth of social grade students at SMA N 3 Kota Jambi Academic Year 2018/2019.  The method of this research was descriptive qualitative. The sample of this research was the tenth of social grade students at SMA N 3 Kota Jambi. Then to get the sample of this research, the researcher used random sampling technique. The instrument of this research was a translation test. In translation analysis processes, the researcher used theory of translation method based on Newmark Theory. The findings of this research showed that there are only four methods used by the students in translating the text. They are Word-For-Word Translation, Literal Translation, Free Translation, and Communicative Translation. It can be seen from the table that the most dominant method used by the 26 students was literal translation method. The second dominant was word-for-word translation method. Meanwhile, the third and fourth translation method applied by the students was free translation and communicative translation. Then, there are four methods which did not applied by the students in translating the story. They were faithful translation, semantic translation, adaptation translation, and idiomatic translation method. Here, the students used more than one method to translate the narrative text. Based on the data, literal translation method is the most dominant method used by the students. It happens because the students just translate the words by its literal meaning and they tried to achieve the nearest equivalence meaning in the target language. Keywords : Analysis, Translation Methods, Narrative Text.
Engaging learning with Augmented Reality for primary school science education

Augmented Reality (AR) is one of the visualization technologies that gradually gaining considerable attention in every field, especially in education area. AR have been applying in education field to create a unique learning experience. In early age of education, primary school students have trouble grasping and understanding the abstract science concept. By bringing the AR into the classroom, AR can serve as an effective tool to gain understanding since AR offer rich media learning. Therefore, the purpose of this project is to design and develop a Science AR application for primary school students. Besides displaying each process upon presentation of its corresponding marker, students can visualize the concept of science in process of learning. Three existing application of AR in the field of education has been review to produce a better version of application. ADDIE model has been chosen in development of this application. There were five phases involved in the model to make sure that the designing and developing of the application has achieves the proposed objective. The application was evaluated by the teacher and primary school students to investigate its effectiveness and user perception toward the application. The result showed that students give positive feedback and they agree this application can improved their understanding in science subject.
The bright side of dark tourism in Baguio City: understanding its impact to the stakeholders.

Dark Tourism in Baguio City has been gaining a lot of attention from those who seek the grim and haunted. Tourists are fond of the ghost stories and the paranormal activities that have been told about certain sites while locals are engaged to dreaded stimulation experiences without knowing the shadowed past behind it. The purpose of this study is to gather data on how dark tourism sites, as a 'pull' factor to tourists, have impacted Baguio City as a whole; including the municipality, the people under its governance, and it's out-turn to the lives of the residents. Researchers have yet to investigate how to deal with the growing number of tourists visiting the locality, and apprehend the variables stated in this research. The design used for this study is descriptive, quantitative research. Non-probability, convenience sampling was used since this is the rational choice for cases where identifying all members of a population is impossible (De Vos, 1998). Questionnaires were distributed to residents aged twenty (20) years old and above. The respondents were ninety (90) residents who are staying nearby dark tourism sites, having their perceptions about the impacts of dark tourism in the area. Based on the findings, residents perceived the benefits of dark tourism in Baguio city as highly beneficial. It also concludes that Baguio city residents experience positive outcomes from tourism.
Research on Private Cloud System Architecture and User Data Security Based on Simulation

In view of the false related problems in the construction of data security risk assessment index system, it is difficult to converge to the optimal solution of state space by traditional methods, which leads to poor evaluation performance. In this paper, the author sets up a data security risk assessment index system under the background of private cloud. Under the constraint of learning samples of stochastic functional, the author solves the optimal solution of data security risk assessment index system under the background of private cloud. At the same time, the position vector fitness updating method is used to optimize the training of data security risk assessment. The results show that, under the background of private cloud, the use of data security risk assessment index system can effectively solve the virtual goodness and false correlation existing in the collection data, thus avoiding the influence on the more explicit variables. It can also effectively reduce the errors caused by observation data, thus reducing computation cost, and ultimately making data security risk assessment more precise.
Twitter Storytelling Generator Using Latent Dirichlet Allocation and Hidden Markov Model POS-TAG (Part-of-Speech Tagging)

Twitter active users in Indonesia reached 50 million users from a total worldwide of 284 million in 2015. In January 2019, active users on Twitter increased by 52% compared to 2018 where active users were only 27%.A large number of users causes the number of tweet documents increases. Tweet documents that contain information such as user activity, news, story can be processed into valuable information for journalists. All of the information collected then arranged based on related tweets into a storytelling that will become news/article. The whole process is still done manually by collecting one by one for each tweet and most of the tweet documents are collected from the trending topic. Actually, that should be done automatically by collecting tweets that have the same topic. Therefore, this research proposes a method of Twitter storytelling generator that combines Latent Dirichlet Allocation (LDA) and Hidden Markov Model POS-TAG (Part-of-Speech Tagging), so it can generate twitter storytelling based on the certain topic. We implemented two scenarios of the experiment. The first experimental calculating the value of perplexity on LDA and HMM POS-TAG, yielding the lowest perplexity value of 6.31 with alpha 0.001, beta 0.001, and the number of topics 4. While the second experimental calculating the value of ROUGE-1, ROUGE-2, BLEU-1, and BLEU-2 on the results of Twitter storytelling generator, yielding the best ROUGE-1 value is 0.470 with the beta cap value of 0.1 and the best ROUGE-2 value is 0.149 with the beta cap value of 0.001. Meanwhile, the best BLEU-1 value is 0.617 on the topic 1 and the best BLEU-2 value is 0.432 on the topic 3. Twitter storytelling generator using the proposed method has good performance when HMM POS-TAG can tagging the tweet documents correctly.
A Study on the Concept and Case Studies of Readingtainment

본 연구는 리딩테인먼트의 개념과 리딩테인먼트의 사례를 다루고 있다. 우선, 리딩테인먼트의 개념을 설명하고 있다. 일본에서부터 불어온 리딩테인먼트는 최근 한국에서 더욱 발전하는 양상을 보이고 있다. 더불어 리딩테인먼트의 사례, 특히 온라인에서 활용되고 있는 리딩테인먼트에 대한 논의까지 개념을 확장한다. 그리고 최근 왕성하게 콘텐츠를 생산하고 있는 북튜버와 북트레일러, 북스타그램, 디지털 라키비움 등의 사례를 명료하고 간략하게 제시한다. 그리고 리딩테인먼트를 통해 독서와 출판의 활력을 찾고 위기를 기회로 전환할 수 있는 분기점을 찾으면서 결론을 맺고 있다.This study deals with the concept of Readingtainment and the case of Readingtainment. First, the concept of Readingtainment is explained. The Readingtainment, which has been introduced from Japan, has recently shown signs of further development in Korea. In addition, the concept extends to the case of Readingtainment, especially the discussion of Readingtainment being used online. And we present clear and brief examples of booktuber, booktrailer, bookstagram and digital lacibium, which have been actively producing content recently. And we conclude by finding a turning point through Readingtainment where we can find the vitality of reading and publishing and turn the crisis into an opportunity.