Reviewerly/exHarmony huggingface dataset:
Penerapan Kain Tenun Baduy Dengan Teknik Zero Waste Substraction Cutting Kedalam Busana Demi-Couture

Abstract Fashion production is the second-largest producer of waste in the world after waste oil. Therefore, a movement called Zero Waste is needed to minimize the waste produced. There are several Zero Waste pattern techniques, and one of them is Subtraction Cutting. Thus, Subtraction Cutting has the potential to be used in the design of women's clothing. The final form of the Zero Waste pattern will be used as an inspiration for the design line to make Demi-Couture clothing with the addition of Baduy Weaving cloth as a fashion material. The final result of this study was in the form of Demi-Couture for 4 looks collection using the Zero Waste Subtraction Cutting technique as a technique and Baduy Weaving Suat Songket as the main material. Keywords: Demi-Couture, Tenun Baduy, Zero Waste
12th IEEE/ACM International UCC/BDCAT'19 CloudAM'19 Workshop Chairs' Welcome Message &amp; Organization

Welcome to the 8th International Workshop on Cloud and Edge Computing, and Applications Management - CloudAM2019, which will be held in conjunction with the 12th IEEE/ACM Utility and Cloud Computing Conference (UCC) in Auckland, New Zealand, from 2-5 December 2019. CloudAM is a successful series of workshops that bring together practitioners and researchers on current research advances on cloud computing, virtualization technologies and real applications. As it is anticipated that this interest will keep expanding with the emergence of edge computing infrastructures, this 8th edition of CloudAM will also cover the topics of edge and fog computing. Cloud and edge infrastructures can work together to fulfill requirements from a variety of applications, composing the so-called Cloud Continuum to the edge. Furthermore, clouds must provide appropriate levels of performance to large groups of diverse users, and those clouds are accessed through virtualized wide area networks, where edge/fog devices can act as a first layer of computing capacity closer to the user. Management systems are essential for that and thereby for the future success of the fog-cloud hierarchy. New systems, methods, and approaches for cloud and edge computing, virtualization, and applications management are to be discussed at this workshop. In this edition of CloudAM, we received six submissions and we could only accept three of them. On the other hand, another the CloudAM program also includes nine high-quality papers that were submitted to the UCC main track and directed for presentation in the workshop. All papers were reviewed and evaluated based on relevance, quality, and novelty. Overall, a number of 12 contributions, covering a broad number of topics, will be presented and discussed during a one-day workshop.
Online signature verification using hybrid wavelet transform

Online signature verification is a prominent behavioral biometric trait. It offers many dynamic features along with static two dimensional signature image. In this paper, the Hybrid Wavelet Transform (HWT) was generated using Kronecker product of two orthogonal transform such as DCT, DHT, Haar, Hadamard and Kekre. HWT has the ability to analyze the signal at global as well as local level like wavelet transform. HWT-1 and -2 was applied on the first 128 samples of the pressure parameter and first 16 samples of the output were used as feature vector for signature verification. This feature vector is given to Left to Right HMM classifier to identify the genuine and forged signature. For HWT-1, DCT HAAR offers best FAR and FRR. . For HWT-2, KEKRE 128 offers best FAR and FRR. HWT-1 offers better performance than HWT- 2 in terms of FAR and FRR. As the number of states increase, the performance of the system improves. For HWT - 1, KEKRE 128 offers best performance at 275 symbols whereas for HWT - 2, best performance is at 475 symbols by KEKRE 128.
Extended Answer and Uncertainty Aware Neural Question Generation

In this paper, we study automatic question generation, the task of creating questions from corresponding text passages where some certain spans of the text can serve as the answers. We propose an Extended Answer-aware Network (EAN) which is trained with Word-based Coverage Mechanism (WCM) and decodes with Uncertainty-aware Beam Search (UBS). The EAN represents the target answer by its surrounding sentence with an encoder, and incorporates the information of the extended answer into paragraph representation with gated paragraph-to-answer attention to tackle the problem of the inadequate representation of the target answer. To reduce undesirable repetition, the WCM penalizes repeatedly attending to the same words at different time-steps in the training stage. The UBS aims to seek a better balance between the model confidence in copying words from an input text paragraph and the confidence in generating words from a vocabulary. We conduct experiments on the SQuAD dataset, and the results show our approach achieves significant performance improvement.
Kualitas Media Pembelajaran Interaktif Calon Guru Biologi FKIP UMS Materi Sistem Organ Manusia Produk Komputasi Pembelajaran Biologi Tahun Akademik 2018/2019

This study aims to determine the quality of instructional media for prospective biology teachers of FKIP UMS on human organ system material for computational biology learning products in the academic year 2018/2019. Research including qualitative research. Data collection techniques using observation and documentation. Observations were performed with an observation sheet with a rating scale to assess the quality of the media in terms of interface or appearance and learning material. Data analysis was performed descriptively based on the results of the calculation of the percentage rating scale from the observations. The results obtained an average percentage of MPI Human Organ Systems is 77.9%. The percentages of each media were MPI Motion System 71.8%, MPI Digestive System 80.9%, and MPI Respiratory System 80.9%. Some evaluations in terms of appearance and learning materials of the MPI Human Organ System are about the accuracy of layout settings, consistency of the shape and location of navigation buttons, ease of navigation, suitability of button functions, relevance of material selection and presentation of questions.
Visual Representation of Musical Rhythm in Relation to MusicTechnology Interfaces - an Overview

The present paper presents an overview of the ways we make sense of rhythm through visual means in music in terms of visual representation and notation, relating this to the user interfaces of musi ...
A Fine-Grained Sentiment Dataset for Norwegian

We introduce NoReC_fine, a dataset for fine-grained sentiment analysis in Norwegian, annotated with respect to polar expressions, targets and holders of opinion. The underlying texts are taken from a corpus of professionally authored reviews from multiple news-sources and across a wide variety of domains, including literature, games, music, products, movies and more. We here present a detailed description of this annotation effort. We provide an overview of the developed annotation guidelines, illustrated with examples, and present an analysis of inter-annotator agreement. We also report the first experimental results on the dataset, intended as a preliminary benchmark for further experiments.
Constraints on Quantum Entanglement in Symmetric Physical Systems

Author(s): Meill, Alexander | Advisor(s): Meyer, David A | Abstract: Quantum entanglement rapidly becomes unwieldy to calculate as the number of particlesand the dimension of the spaces associated to those particles increase. One meaningful approachwhich simplifies that analysis is the restriction to subsets of states which obey some physicallyrelevant symmetry. In this thesis, entanglement properties of totally permutation-symmetric,translationally invariant, and party-site symmetric states are examined, as well as those of smallbond-dimensional matrix product states.
Creating a Motivate and Innovative Educational Environment for Intensive Knowledge Accumulation by Future Teachers of Natural Sciences on the formation of High School Students’ Safe Behavior

The paper is about one of the pedagogical conditions for the preparation of future teachers of natural sciences for the organization of safe life activities of high school students - the creation of a motivational and innovative educational environment for the intensive accumulation of knowledge by future teachers of natural sciences for the formation of safe behavior of high school students.
Semantic of the form in rock-music: art-pedagogical aspect (on example of hardand-heavy)

Purpose of Article - description of the semantic features of the hard-and-heavy musical composition in artistic and pedagogical aspects - the following tasks are specifically applied: individual perspectives of the study of semantics in rock music; need an organization theme), describe the structure and semantic model of hard and heavy compositions. Methodology relies on an integrated approach with the use of system-structural, functional and comparative methods, which allows to explore the characteristics of musical composition's semantics in hardand-heavy at the intonational-thematic, genre, compositional levels. Scientific novelty consists in describing the models of the structural and semantic organization of hard-and-heavy compositions on the basis of a study of the processes of shaping, thematic and structural organization. Hard-and-heavy uses various types of forms - from simple to complex, mirror-symmetric, open, alternative, which are based on one of the three types of thematic organization: monoriff, polyriff, spiral. Structural models of hard-and-heavy musical forms emerge based on the interaction of genre features of vocal and instrumental music. Each structural model corresponds to a generalized semantic model with a specific range of values. The guiding lines for semantic interpretation are representations of typical forms. The semantic model of a typical hardand-heavy composition has several particular models that play the role of a meaningful scenario, define the functional and dynamic profile of the piece, and create the semantic field of this form. Semantic analysis of the rock-piece`s form, as a component of the operational level of artistic and pedagogical analysis, provides an awareness of the joint action of the means of musical expression in their interconnection and conditionality of content. It reveals the structural features of a piece of music, facilitating the process of perception and providing active influence of musical images on the listeners
A Hybrid Morpheme-Word Representation for Machine Translation of Morphologically Rich Languages

We propose a language-independent approach for improving statistical machine translation for morphologically rich languages using a hybrid morpheme-word representation where the basic unit of translation is the morpheme, but word boundaries are respected at all stages of the translation process. Our model extends the classic phrase-based model by means of (1) word boundary-aware morpheme-level phrase extraction, (2) minimum error-rate training for a morpheme-level translation model using word-level BLEU, and (3) joint scoring with morpheme- and word-level language models. Further improvements are achieved by combining our model with the classic one. The evaluation on English to Finnish using Europarl (714K sentence pairs; 15.5M English words) shows statistically significant improvements over the classic model based on BLEU and human judgments.
SEMI-SUPERVISED SPECTRAL-TEXTURE IMAGE CLASSIFICATION ALGORITHM

When classifying satellite images, training sample often turns out to be unrepresentative. This leads to low segmentation quality. In such conditions, it is advisable to use semi-supervised classification methods, which simultaneously utilize both training sample and unclassified data. At the same time, high resolution satellite images are characterized by high interclass heterogeneity of spectral characteristics, which demands to take spatial information into account. We propose a new semi-supervised classification algorithm for multispectral images, that utilizes both spectral and texture features. The use of the semi-supervised concept allows improving the classification quality when the amount of training sample is small. The results of experiments on model and satellite images confirming the effectiveness of the proposed algorithm are given.
Shorter QA-NIZK and SPS with Tighter Security.

Quasi-adaptive non-interactive zero-knowledge proof (QA-NIZK) systems and structure-preserving signature (SPS) schemes are two powerful tools for constructing practical pairing-based cryptographic schemes. Their efficiency directly affects the efficiency of the derived advanced protocols.
Security-Related Cynicism: A Double-Edged Sword?

Employees are exposed to a great number of security requirements such as information security policies (ISPs) or technical controls. Motivated by prior research indicating that such requirements can also have adverse effects, we introduce the concept of security-related cynicism. Based on organizational literature on employee cynicism, we conceptualize security-related cynicism as a negative attitude with cognitive, affective, and behavioral components directed towards key targets of an organization's information security ecosystem, i.e. the people responsible for information security, the employed security technologies, and ISPs in use. We present our initial development of security-related cynicism and integrate it in a model including psychological contract violation and in- and extra-role security behaviors (ISP compliance and voice). In doing so, we propose that cynical employees, though unwilling to follow ISPs unquestioningly, could also be the devil's advocate and challenge ineffective ISPs by raising their voice, making security-related cynicism a double-edged sword for organizations.
D3MC: A Reinforcement Learning Based Data-Driven Dyna Model Compression

Artificial intelligence (AI)-driven medical devices have created a new excitement in healthcare sector. While deeper and wider neural networks are designed for complex healthcare applications, model compression can be an effective way to deploy networks on medical devices that often have hardware and speed constraints. Most state-of-the-art model compression techniques require a resource centric manual process that explores a large model architecture space to find a trade-off solution between model size and accuracy. Recently, reinforcement learning (RL) approaches are proposed to automate such a hand-crafted process. However, most RL model compression algorithms are model-free that require longer time with no assumptions of the model. On the contrary, model-based (MB) approaches are data driven; have faster convergence but are sensitive to the bias in the model. In this paper, we develop data-driven dyna model compression (D3MC) algorithm that integrates model-based and model-free RL approaches. We evaluate our algorithm on a variety of imaging data from dermoscopy to X-ray on different popular and public model architectures. Compared to model-free RL approaches, our approach achieves faster convergence; exhibits better generalization across different data sets; and preserves comparable model performance.
User strategies for mobile device-based interactions to prevent shoulder surfing

Shoulder surfing, also known as visual hacking, is the activity of obtaining information from or about others by observing visual content of displays that actually should be kept secret, such as PINs, passwords, or private text messages. Approaches that address shoulder surfing on mobile devices mainly focus on ways to recognize observers or to complicate visual presentations for them from the system's perspective. However, users also have developed their own strategies to keep their input secret. With this work, we contribute an investigation of strategies to prevent shoulder surfing from the users' perspective. We performed a user study and observed 32 participants while interacting with smartphones using different kinds of eyes-free device-based interaction techniques. We identified several strategies that users had to prevent shoulder surfing. These strategies help us to develop effective ways to design useful interactions that overcome shoulder surfing issues.
BI-RADS Breast Tumor Classification Through Image Mining

In this article, a computer aided diagnostic system for BI-RADS classification of breast cancer is proposed. The approach involves image processing capabilities to extract features from tumors in mammography and image mining to classify them as BI-RADS 2, BI-RADS 3, BI-RADS 4C or BI-RADS 5. Images from the BCDR repository were used for the experiments. The results showed the efficacy of the proposed method, which classified tumors with considerable accuracy in four BI-RADS categories.
Effect of Fun Learning Enrichment Program (FLEP) on At-Risk Students’ Motivation and Aspiration to Learn

The purpose of this study is to examine effects of the Fun Learning Enrichment Program (FLEP) on motivation and aspiration to learn among population of low-achieving students. The study used quasi experimental design with pre-post control group. A total of 596 students participated in the study for three consecutive years. The students were given a module consisted of 120 fun learning enrichment activities in mathematics and science that promotes self-motivation and aspiration to learn. Results show significant increase in motivation and aspiration to learn among the students after attending the FLEP program. In conclusion, low-achieving students can develop motivation and aspiration to learn when given environment that promotes positive learning experience.
Enhancing Out-Of-Domain Utterance Detection with Data Augmentation Based on Word Embeddings

For most intelligent assistant systems, it is essential to have a mechanism that detects out-of-domain (OOD) utterances automatically to handle noisy input properly. One typical approach would be introducing a separate class that contains OOD utterance examples combined with in-domain text samples into the classifier. However, since OOD utterances are usually unseen to the training datasets, the detection performance largely depends on the quality of the attached OOD text data with restricted sizes of samples due to computing limits. In this paper, we study how augmented OOD data based on sampling impact OOD utterance detection with a small sample size. We hypothesize that OOD utterance samples chosen randomly can increase the coverage of unknown OOD utterance space and enhance detection accuracy if they are more dispersed. Experiments show that given the same dataset with the same OOD sample size, the OOD utterance detection performance improves when OOD samples are more spread-out.
On using 2D sequence-to-sequence models for speech recognition

Attention-based sequence-to-sequence models have shown promising results in automatic speech recognition. Using these architectures, one-dimensional input and output sequences are related by an attention approach, thereby replacing more explicit alignment processes, like in classical HMM-based modeling. In contrast, here we apply a novel two-dimensional long short-term memory (2DLSTM) architecture to directly model the input/output relation between audio/feature vector sequences and word sequences. The proposed model is an alternative model such that instead of using any type of attention components, we apply a 2DLSTM layer to assimilate the context from both input observations and output transcriptions. The experimental evaluation on the Switchboard 300h automatic speech recognition task shows word error rates for the 2DLSTM model that are competitive to end-to-end attention-based model.
Translational Health Informatics from Risk Prediction Modeling to Risk Assessment Service

This tutorial will focus on the issues when utilizing new scientific discoveries in healthcare, especially in the era of Artificial Intelligence, moving from bench to bedside, on to communities and finally to the population. Instructors will firstly give an overview of translational health informatics from risk prediction modeling to risk assessment service, and introduce the pipeline of risk prediction modelling with hands-on, then deep dive to key steps along the translational journey, for addressing real-life problems such as risk model adaption and localization, dealing with unobservable features when applying risk models, and bridging the gap from a risk score to intervention plan.
Web Based Tools: Emerging Paradigms in the Field of Academic Research

Progress of every profession, academic discipline, and society at large rides on the back of research and development. Research generates new information and knowledge. It is a standardized process of identifying the problem, collecting data or evidence, tabulating data and its analysis, drawing inference and establishing new facts in the form of information. Therefore, research is a long process and a lot of time is required to complete research work. The information and communication technology, especially the internet and the www, descended from the cyberspace help researchers a lot in this regards. There are a lot of web-based programmes, tools, sites, and open source initiatives that help researchers to make the process more efficient and organized and thus save the time of the researchers too. The research domain of library and information science has witnessed a rapid increase in the use of web-based tools in recent years. This paper addresses some web-based tools, websites, open-source initiatives that would help academic community especially research scholars immensely to customize search engines, to search relevant documents of his/her subject interest, to organize and manage citations, to assemble topic related articles and other documents in one place, to get access to open access & other e-resources and many more.
Omnidirectional Mobile Robot Structure Design

With the development of automation, Unmanned Vehicle will play a more and more important role in the future industrial production field, and omnidirectional wheeled robots will be widely used in mobile platforms. The omnidirectional AGV trolley has the unique characteristics that the ordinary wheeled mobile robot is irreplaceable, and has great significance and effect for exploring the free walking of the moving mechanism. This paper mainly describes the layout and principle of the omnidirectional moving mechanism based on the Mecanum wheel.