Reviewerly/exHarmony huggingface dataset:
KLASIFIKASI MULTILABEL PADA ABSTRAK TUGAS AKHIR MENGGUNAKAN VECTOR SPACE MODEL DAN K-NEAREST NEIGHBORS

The final project is one of the requirements of graduation students. Students who want to do the final project need to see the final project result on the same topic that has been done before. With a large number of end-task documents, it certainly takes a great effort to find the final project document on the same topic. The final grouping can be automated using the document classification method. The methods that can be used to classify documents are K-Nearest Neighbors as classifier and Vector Space Model to measure the distance between documents From the initial observation, the multilabel classification in the final abstract using Vector Sapce Model and K-Nearest Neighbors has not been evaluated. Because some previous studies have led to the testing of single labels and only lead to one method, as the method is tested. Classification of abstract document final task consists of 2 stages of making distance table using vector space model and multilabel classification using KNN. This method has not been able to predict the label accurately because the exact exact ratio of its optimum value is only 0.57 when m = 4 and k = 8. This method is good enough in predicting the label even though not precisely. Can be seen from the accuracy value of its optimum which is 0.74 when m = 4 and k = 9. The exact match ratio and accuracy value of this method has the optimum value at m = k / 3.
EDPRL: A Language for Specifying Data Privacy Requirements of Enterprises

Use of customer data, including personally identifiable information, by enterprises for business purposes raise privacy concerns. Rising incidents of privacy breaches show that there is an urgent need for designing and implementing proper privacy controls. The most important pre-requisite for this is the correct identification of data privacy requirements in a timely manner. Existence of large number of enterprise assets (that store and process customer data), and continuous changes in requirements, render such identification extremely difficult. Moreover, ad-hoc methods often lead to erroneous identification of requirements. It is important to devise a methodology for the structured representation of data privacy requirements that considers the intricate relationships between enterprise assets that handle those data. This would also enable the implementation of automated processes for privacy controls. This paper presents a structured language called Enterprise Data Privacy Requirement Language (EDPRL) for specifying privacy requirements of an enterprise.
Exploring Context Information for Accurate and Fast Object Detection

Current top-performing object detectors depend on deep CNN backbones, such as ResNet-101 and InceptionNet, benefiting from their powerful feature representations but suffering from high computational costs. Conversely, some lightweight model based detectors can run at real time speed, while their performance is inferior to those equipped with powerful backbone network. In this paper, we propose an effective yet efficient one-stage detector. The proposed detector inherits the architecture of SSD and introduces two novel modules, Feature Enhancement Module (FEM) and Feature Fusion Module (FFM). The FEM could strengthen features by increasing the size of receptive field and introducing more context, while The FFM could enhance the shallow part of the detector by fusing two adjacent feature maps. To evaluate their effectiveness, experiments are conducted on two major benchmarks. Experimental results demonstrate that the proposed detector performs much better than the original SSD, without losing real-time processing speed.
Measurement method for axisymmetric 3D stress-tensor fields using background-oriented schlieren

Stress fields affect various characteristics of materials. However, measurement methods for three-dimensional stress fields tend to be complicated because stress tensors generally consist of six independent components. We therefore propose a simple method for measuring axisymmetric three-dimensional stress fields by measuring deflection angles of light rays using the background-oriented schlieren technique. Assuming axial symmetry of the stress field, we use the Lagrangian optics to derive a relationship between two-dimensional deflection angle and three-dimensional stress. Using independent ray polarizations, the method can reconstruct the respective refractive indices from the deflection angle. Equilibrium equations for the stress tensor can be written under the assumption of axial symmetry. By applying appropriate approximations, we formulate normal and shear stress-tensor components, which enables reconstruction of these components from refractive indices. Stress-tensor components can be experimentally generated by applying a load to a glass plate surface on the basis of the Hertz contact theory. The proposed method reconstructs the stress-tensor components from a refractive index field that is induced by the stress in the glass. The reconstructed axial-stress tensor σzz and shear-stress tensor τrz well agree with numeric calculations using structural analysis software. Other stress-tensor components, however, slightly deviate from those of the numeric calculations.
Person ReID: Optimization of Domain Adaption Though Clothing Style Transfer Between Datasets

It is manifested that when training and testing models on different datasets, the performance of trained models will severely dropped due to the differences in style of the datasets. In person ReID task, the clothing style is a crucial factor existing in different datasets, which has not been considered in the current research. We proposed a novel approach of Optimization of Domain Adaption Though Clothing Style Transfer (ODA-CST), which includes clothing mask extraction and clothing style transfer. Firstly, we generate the clothing mask by jointly locally extracting clothing and globally detecting the person. Meanwhile, we also organize a clothing mask dataset to improve the model. Our ODA-CST can effectively generate photos with the clothing style transferred, which is the first method that tries to solve the clothing style gap in person ReID task to the best knowledge. The importance of clothing style transfer and the effectiveness of our method are verified by the experiment.
Learning Resources: Online Safety & Security: Feel Safe, Be Safe

In this section we will look at Online Security, Online Safety, Radicalisation and Extremism
A Feature-based Method for Shipboard Video Stabilization

The aim of this article is to present a digital shipboard video stabilization method to stabilize the unstable video due to the unwanted camera shakes and jitters caused by the motion and vibration of ships. The proposed video stabilization algorithm consists of motion estimation, filtering and compensation. The idea of motion estimation is detecting corner points using adaptive Harris algorithm, then the corner points are tracked by optical flow algorithm to determine the camera motion. In addition, the Fourier series curve fitting is designed to cope with the randomness of unwanted camera motion. After motion filtering, the image sequence is moved to compensate the unwanted camera motion according to the motion filtering results. To evaluate the performance, the video stabilization algorithm is evaluated using the video chips captured on an experimental ship. The results show that the variance of frame motion in X and Y axes has been reduced 85% and 95% respectively. The main limitations are the assumption that there is no scale variance between frames, and the camera motion is described by rigid motion model. Our video stabilization algorithm detects the corner points using adaptive threshold which is based on the image information, the desired corner points are selected and the noise are reduced at the same time. In addition, the motion filter is based on the Fourier series curve fitting method which makes the global motion smoother and restores the ego motion of camera.
Learning A Recurrent Neural Network for State Estimation using Filtered Sensory Data.

State estimation is one of the essential tasks for autonomous systems, which is required in multiple applications, such as localization, object tracking, mapping, and many more. Various solution paradigms have been proposed by the scientific community to solve this well established problem. Some of the commonly used techniques are based on Bayesian inference, specifically the particle filter as it has the advantage of modeling arbitrary distributions without the unimodal assumption limitation. The particle filter has proven to be successful in many applications, however, a large set of particles is required in order to have robust estimates against noisy measurements and erroneous data association, which impedes the runtime performance of the filter. This study shows that a learning framework that trains a recurrent neural network with labeled data generated from the probabilistic estimation of a particle filter is capable of exploiting the expressive power of neural networks in order to capture the behavior of the filter and handle the noisy sensory information. The trained model is capable of performing the estimation with lower runtime complexity, making it applicable to numerous autonomous systems. This approach also proves to be helpful in situations when the ground truth data can not be accessed. We train and evaluate our strategy using raw GPS sensor measurements from the Oxford RobotCar dataset. The results show that the performance of the recurrent network closely matches that of the particle filter without exhaustive tuning and that the network is able to generalize effectively on test datasets as well.
Perceived Visual Enjoyment Factor in Artistic Playability : In Case Study Real Time Strategy (RTS) Game

Each game has their own unique feature, which attracts gamers by constantly playing the game daily. The game appeal also regards the interface attributes, Game mechanics, and interfaces as a factor towards excitement in playing the game. Nevertheless, there is limited discussion pertaining to perceived visual enjoyment factor in artistic playability, especially among youth based on the Real Time Strategy (RTS) game to support the statement. For this purpose, Defence of the Ancients 2 (DOTA 2) were used as a case study as inspired game play. The game according to gamers is essential for each level to deliver challenges that encourage the gamers themselves as motivational goal. In contrary in winning factor, there are also aspects of UX indicates substantially important as the game experience, that is: anatomy of function, and menus, plays important role in achieving goals, especially for the gamers. Therefore, this paper discusses the components of successful game.Method:The sample was tested using System Usability Scale (SUS) for interviews and questionnaire. Despite of a small sampling, SUS is trusted with its accuracy and reliability, also has established an industry standard, with numerous previous references. Based on findings, the online questionnaire distribution (N=10)Results:The result indicates that the players were satisfied with the mechanics of the game, comparatively, the player felt enthusiastic with the competitive challenge to finish the game, and to achieve their objectives. The findings in the paper also established that the visual was not the driven factor for the user’s engagement in continuously playing the game, but desire to complete the challenge in order to gain satisfaction upon completion. The significant finding in this article, that DOTA 2 game largely by definition depends on CTPM (Critical Thoughts Per-Minutes) and communication within the team because critical thinking is highly required in other to perceive the enjoyment; but the intensity, breadth, and acceleration also significantly
Cheltenham Borough Council is taking part in #OurDay

From parks to planning, recycling to licensing, the hundreds of vital services the council provides will be brought to life when officers from Cheltenham Borough Council take part in a social media marathon on Tuesday 19 November.
SISTEM CERDAS PEMANTAU HEWAN TERNAK PADA ALAM BEBAS BERBASIS INTERNET OF THINGS (IOT)

One of the common problems experienced by animal farmers is heat stress or cold stress caused by changes in the environment. This resulted in a decrease in the productivity of livestock, cattle. Early monitoring needs to be done to avoid problems through monitoring tools for temperature, heart rate, and internet-based location of things (IoT). The monitor receives the value through the paired sensor and is sent to the web server. Users or breeders get information about the condition of farm animals and observe changes in value through graphs through the android application. The system built is able to receive values in a short interval time (10 seconds) so that the value obtained is the most recent value. Based on observations on the graph, the user can identify drastic changes, both decreases or increases, in the temperature and heart rate of the animal's condition and take precautions as early as possible.
Architectural Style Classification Based on DNN Model

Deep neural networks (DNN) have been widely used for image classification. One major hurdle of deep learning approaches is that large sets of labeled data are necessary, which can be prohibitively costly to obtain, particularly in architectural style classification. Data augmentation can alleviate this labeling effort. In this paper, we use data augmentation to increase the number of architectural style datasets. To extract building elements, the inputs are preprocessed by Deformable Part Model (DPM) first, and then the preprocessed images are sent to the data augmentation to increase the number of images. Next, we design a deep neural network based on GoogLeNet. The proposed network aims to learn robust feature embeddings to improve architectural style classification performance. Finally, architectural style can be classified by the robust feature embeddings. Experimental results show that our approach achieves promising performance and is superior to previous methods.
Run-time adaptation of modalities of interaction and context of use in web mobile apps

Several approaches have emerged to support the development of mobile web applications (apps).Front-end frameworks (FeF) have emerged to support developers in the construction of responsive mobile web apps.However, these frameworks do not provide resources to handle easily variables of the context of use and to deal with different modalities of interaction.Considering this gap, we proposed the HyMobWeb, an approach that assists developers in working with these aspects.By grasping the popularity of the FeFs, HyMobWeb proposes a flexible and reusable approach based on FeF structure.It works with a hybrid approach that treats the adaptation in two phases.The static one, performed in the development time, allows developers to implement the resources of adaptation.The dynamic one performs the adaptation during the run-time.In this article, we present the HyMobWeb dynamic adaptation approach.As end-users are the receivers of the dynamic adaptation our evaluation was carried out in the perspective of this audience.The results showed that the adaptations regarding the context of use were the ones that presented more impact on the user experience.We concluded that the HyMobWeb dynamic adaptation provides ways to enhance user interaction in mobile web apps when compared with RWD resources.
The power of the crowd and open data – learnings from the OZ Minerals Explorer open innovation challenge

SummaryWe report on the results and lessons learned from Australia’s largest minerals exploration crowdsourcing challenge - the OZ Minerals Explorer Challenge. We discuss some of the challenges in running an international competition with a large amount of technical data at scale, and the methods used to engage innovators from outside the traditional geoscience community. We discuss specific examples of innovative approaches which have been submitted. We also examine the ways in which open innovation and crowdsourcing can provide a novel approach to rapidly evaluating tenement prospectivity and to unlock value from companies’ data assets.
Effects of Interaction through Different Types of Mobile Chatting on Speaking and Writing Performance

The purpose of this study is to investigate the effects of interaction between two mobile chatting conditions, voice-chatting and text-chatting, on speaking and writing performance. Forty-four students taking two College English classes participated in the present study. They were divided into two different experimental groups: voice-chatting and text-chatting groups. Both groups took pre-tests for speaking and writing tasks from TOEIC. During the semester, they carried out the same speaking activities on various topics via voice-chatting or text-chatting. Participants paired up and communicated in two different modes with given tasks such as describing a picture, responding to questions, and expressing an opinion. Post-tests were administered at the end of the semester. The major findings of the study were as follows: First, significant differences were found in terms of speaking and writing performance in both groups. Participants in the voice-chatting group, however, did not significantly show improvement in their performance in the writing task, expressing an opinion. Second, different types of chatting on mobile devices did not have any influence on students’ speaking or writing performance after practicing different tasks. Lastly, mobile chatting provided a stimulating environment to actively participate in class and also increased time for students to practice speaking and writing. It can be concluded that employing mobile chatting is effective in improving learners speaking and writing performance and it motivates students to be interested in learning. Pedagogical implications and future studies will be discussed.
Penerapan Multimedia TAVAGIS Berbasis Prezi dalam Pembelajaran Kurikulum 2013 bagi Guru Sekolah Dasar di Kabupaten Kuningan

APPLICATION OF PREZI-BASED TAVAGIS MULTIMEDIA IN LEARNING CURRICULUM 2013 FOR ELEMENTARY SCHOOL TEACHERS IN KUNINGAN REGENCY. The curriculum currently being implemented in elementary schools in Indonesia is the 2013 curriculum. One of the problems faced regarding the implementation of the 2013 curriculum is the lack of mastery of information and technology (IT) by teachers, due to learning habit patterns that still do not consider IT's role in improving quality learning. Though teachers are required to master IT in this technological era. This community service activity is intended for fourth grade teachers in elementary schools in Kuningan District, Kuningan Regency. The purpose of this training is to improve the skills of teachers in the IT field, in making and implementing Prezi-based TAVAGIS Multimedia in 2013 elementary school curriculum learning. The method of implementing this activity consists of several stages, namely: 1) Planning which includes partner surveys, training licenses, preparation of training modules, training preparation and coordination, and program socialization, 2) Implementation of PKM activities which include training on Prezi-based TAVAGIS multimedia development and use assistance multimedia that has been made, 3) Evaluation and follow-up. Based on the results of observations and quisioner, training in making and assisting the implementation of Prezi-based TAVAGIS multimedia runs smoothly and some obstacles that arise can be resolved so that this activity can improve the knowledge and skills of making Prezi-based TAVAGIS multimedia, thus helping teachers to create interactive, interesting, and fun learning.
The Technical Committee on Musical Acoustics: Integral part of the interdisciplinary nature of acoustics

The Technical Committee on Musical Acoustics (TCMU) of the Acoustical Society of America (ASA) is concerned with the application of science and technology to the field of music. Traditionally, the areas of interest for those doing musical acoustics have included: the physics of musical sound production, questions of music perception and cognition, and the analysis and synthesis of musical sounds and composition. It is clear that many of the technical committees of the ASA are highly interdisciplinary and TCMU is no exception. The TCMU organizes special sessions often featuring a family of musical instruments, a style of music, or a technique of musical performance. Additionally, sessions have featured innovative techniques for studying acoustics which have broad application across the other technical committees. TCMU also regularly hosts musical performances at ASA meetings and visits to local music venues or musical instrument factories in order to connect researchers to practitioners. The TCMU encourages all members of the ASA to engage with us in the pursuit of understanding the production, radiation, perception, and cognition of musical sounds.
twtxt feels a little like launching simple ...

#twtxt feels a little like launching simple digital bottle notes into the vast oceans of the Internet
A Content-Aware Approach for Analysing Eye Movement Patterns in Virtual Reality

Observing eye movement is a direct way to analyse human’s attention. Eye movement patterns in normal environment have been widely investigated. In virtual reality (VR) environment, previous studies of eye movement patterns are mainly based on content-unrelated influential factors. Considering this issue, in this paper, a novel content-related factor is studied. One crucial kind of region of interest (ROI), namely vision-penetrable entrance, is chosen to analyse eye movement pattern differences. The results suggest that users show more interest in vision-penetrable entrances than in other regions. Furthermore, this kind of difference is identified as higher average density of fixation. As far as we know, this paper is the first attempt to study specific types of ROI in virtual reality environments. The method utilised in this paper can be applied in other ROI analysis.
Mejora del Rendimiento Académico Mediante la Aplicación de Metodologías de Trabajo en Equipo y Sistemas de Respuesta Inmediata en la Universidad China

The educational opening of China through academic agreements with different institutions of higher education from the rest of the world, also means the possibility of applying well-known tools and methodologies in contexts in which its application was not carried out until now.In this sense, the present work seeks to apply different methodologies and tools for the management of teamwork and faceto-face response systems.For this, a quasi-experimental study is carried out in the Mechanical School of Xiangtang University for three years.This study shows the academic performance of students in two subjects, one as a control group and another as an experimental group.The control group follows the traditional teaching process at the Chinese University and in the experimental group a Spanish exchange teacher adapts tools to the Chinese context to encourage teamwork and increase the participation of students in class.The results obtained show an increase in student participation and academic performance in the subject where the different techniques and tools were applied.
When I set up a local network ...

When I set up a local network (so far building one in New Haven and Ghana) each group gets a shared hosting account, a domain,
Library Guides: Research4Life Training: HINARI Workshop 2017

This training is supported by the Elsevier Foundation 2014 New Scholars and Innovative Libraries in Developing Countries program