Reviewerly/exHarmony huggingface dataset:
SSeg-LSTM: Semantic Scene Segmentation for Trajectory Prediction.

In this paper, we propose the use of semantic segmentation to incorporate scene information for better understanding of human motion in crowded environments. Our proposed SSeg-LSTM method leverages SegNet, which is a semantic segmentation encoder-decoder architecture, to extract semantically meaningful scene features. We then train the Social Scene LSTM (SS-LSTM) model with the contextual information regarding dynamics, social neighborhood, and scene semantics to predict future trajectory points of pedestrians. Experimental evaluation on public datasets show better performance for SSeg-LSTM than SS-LSTM which highlights the utility of semantic encoding for trajectory prediction.
In-Place Ink Text Editor

Indirect writing interface is currently widely used for handwriting text entry with a pen, however, it may cause additional eye and hand movement. Gu and Lee suggested a revival of the concept of direct writing and they showed the potential of the direct writing interface in editing text. In this demo, we demonstrate an In-Place Ink text editor prototype which is a notepad-like simple text editor with direct writing feature.
Earthquake Damage Estimation by Sparse Modeling Using Geospatial Big Data

The recent diversification and accumulation of data from GPS equipped mobile phones, building sensors, and other resources in Japan has caused a large increase in the number of earthquake disaster scenarios that can be identified. Disaster prevention planning requires us to contemplate which scenario should be focused on and the required response to various scenarios. As a means to solve this problem, the damage distribution of building collapse and fire from GPS data can be used to estimate future damage based on people flow and various hypocenter models of earthquakes. We propose a method that uses sparse modeling to extract scenarios that are important for disaster estimation and prevention. As a result, this paper makes it possible to quickly grasp the scenario distribution, which was previously impossible to do, and to extract the significant scenarios.
Firebolt: A System for Automated Low-Level Cinematic Narrative Realization

Creation of machine generated cinematics currently requires a significant amount of human author time or manually coding domain operators such that they may be realized by a rendering system. We present FireBolt, an automated cinematic realization system based on a declarative knowledge representation that supports both human and machine authoring of cinematics with reduced authorship and engineering task loads.
Pengelolaan Pembelajaran Bahasa Inggris Di Kelas X SMK Negeri 1 Surakarta, Kota Surakarta

This research aims to ; 1) Describe the preparation of learning English in SMK 1 Surakarta. 2) Describe the implementation of learning English in SMK 1 Surakarta city. 3) Describe the evaluation of the implementation of learning English in SMK 1 Surakarta. This research method uses qualitative methods with ethnographic research designs. This research was conducted in state Vocational high school 1 Surakarta, as one of the pilot schools for implementing the 2013 curriculum. The data used in this study consisted of primary data and secondary data. Data analysis techniques used in this study are interactive model analyzes. While the data collection method uses: in-depth interviews, observation and documentation. The results of the study show that: 1) English teachers in SMK 1 Surakarta have prepared curriculum planning 2013 before the new school year begins although some are incomplete. 2) The implementation of English learning in SMK Negeri 1 Surakarta is good such as: a) All teachers have implemented learning in accordance with RPP. b) the objectives in the lesson plan are in accordance with the theme, the material in the syllabus and the student’s handbook. c) Not only based on the handbook but the teacher also enriches material from other sources. d) Approaches, models and strategies and learning methods used vary according to the objectives of the 2013 curriculum learning material that is student-centered, fun, creative and innovative with a scientific approach. e) Teachers use the available infrastructure and learning tools, also use other learning facilities, both found in the home or school environment. 3) The teacher has conducted an assessment in accordance with the 2013 curriculum guidelines, assessment in terms of attitudes, knowledge and skills, the principal also conducts evaluation activities by way of administrative supervision and classroom supervision.
QoS-based Web Service Recommendation using Popular-dependent Collaborative Filtering

Since, most of the organizations present their services electronically, the number of functionally-equivalent web services is increasing as well as the number of users that employ those web services. Consequently, plenty of information is generated by the users and the web services that lead to the users be in trouble in finding their appropriate web services. Therefore, it is required to provide a recommendation method for predicting the quality of web services (QoS) and recommending web services. Most of the existing collaborative filtering approaches don’t operate efficiently in recommending web services due to ignoring some effective factors such as dependency among users/web services, the popularity of users/web services, and the location of web services/users. In this paper, a web service recommendation method called Popular-Dependent Collaborative Filtering (PDCF) is proposed. The proposed method handles QoS differences experienced by the users as well as the dependency among users on a specific web service using the user/web service dependency factor. Additionally, the user/web service popularity factor is considered in the PDCF that significantly enhances its effectiveness. We also proposed a location-aware method called LPDCF which considers the location of web services into the recommendation process of the PDCF. A set of experiments is conducted to evaluate the performance of the PDCF and investigating the impression of the matrix factorization model on the efficiency of the PDCF with two real-world datasets. The results indicate that the PDCF outperforms other competing methods in most cases.
Efficient Instance and Semantic Segmentation for Automated Driving.

Environment perception for automated vehicles is achieved by fusing the outputs of different sensors such as cameras, LIDARs and RADARs. Images provide a semantic understanding of the environment at object level using instance segmentation, but also at background level using semantic segmentation. We propose a fully convolutional residual network based on Mask R-CNN to achieve both semantic and instance level recognition. We aim at developing an efficient network that could run in real-time for automated driving applications without compromising accuracy. Moreover, we compare and experiment with two different backbone architectures, a classification type of network and a faster segmentation type of network based on dilated convolutions. Experiments demonstrate top results on the publicly available Cityscapes dataset.
Motion Planning for Collision Mitigation via FEM-Based Crash Severity Maps.

This paper presents a novel collision mitigation method for traffic scenarios in which accidents are inevitable. When a predicted accident is imminent, the suggested software agent changes the trajectory of the ego vehicle to optimize the predicted crash configuration. The target function results from the degree of crash severity, based on the deformation of the safety cage in the occupant area. We have performed numerous crash simulations with detailed FEM models to determine the crash severity for possible crash configurations. Since inevitable crash scenarios are inherently time-critical, the focus is on fast optimization. The proposed heuristic search algorithm computes a collision trajectory from a given initial state by searching for the maneuver leading to the lowest crash severity in the reachable crash configuration set. We rely on a previously developed approach to trajectory modeling that guarantees a minimum execution time for trajectory generation and collision detection and respects the limits of vehicle dynamics. Simulations prove the applicability of the proposed algorithm.
Satisfação da equipe de enfermagem com a imagem corporal

Objetiva-se identifi car a satisfação dos profi ssionais da equipe de enfermagem com a imagem corporal, e avaliarse as características pessoais, profi ssionais e a necessidade do uso de adornos durante a jornada de trabalhointerferem na satisfação com a imagem corporal. Estudo transversal quantitativo realizado com enfermeiros,técnicos e auxiliares de enfermagem por meio da Escala de Avaliação da Satisfação com a Imagem Corporal. Aamostra foi de 182 profi ssionais, sendo 92,3% (n=168) mulheres, a idade média foi 32,74 anos (±8,3). O escoremédio total foi de 83,8 (±14,1). Houve diferenças estatisticamente signifi cativas na comparação dos escores nasubescala “Preocupação com o Peso” com as variáveis sexo (p=0,03) e estado civil (p=0,02). Concluí-se que a equipede enfermagem referiu estar, em geral, moderadamente satisfeita com a imagem corporal. A preocupação com opeso foi maior nos indivíduos solteiros e do sexo masculino.Palavras-chave: Imagem Corporal; Autoimagem; Cuidados de Enfermagem; Enfermagem.&#x0D; AbsTRAcTThe aim is to identify the satisfaction of the nursing staff professionals with their body image and to assesswhether the personal, professional characteristics and need to use adornments during working hours interferewith satisfaction with body image. A cross-sectional quantitative study carried out with nurses, technicians andnursing assistants using the Body Image Satisfaction Scale. The study was composed of 182 professionals, 92.3%(n=168) female, with an average age of 32.74 years (±8.3). The average total score was 83.8 (±14.1). There werestatistically signifi cant differences when comparing the scores on the subscale “Worry with Weight” with thegender (p=0.03) and marital status (p=0.02). It concludes that nursing staff reported being moderately satisfi edwith their body image in general. The worry with weight was higher between the singles and males.Keywords: Body Image; Self Concept; Nursing Care; Nursing.
The role of between- versus within-speaker acoustic variability in vocal identity perception

Our recent studies [JASA 145(Pt. 2), 1930, (2019); this conference] show that acoustic spaces characterizing within- and between-speaker variability in voice quality have similar structures, with a few features (acoustic variability and formant dispersion) important for all speakers combined with idiosyncratic features characterizing individual talkers. These findings suggest that voice discrimination should be based on shared features, while “telling voices together” should depend on knowledge of each individual’s vocal idiosyncrasies. To test this hypothesis, we selected a set of voices that varied systematically in acoustic closeness to each other and to the center of the group acoustic space, based on values of shared features. Listeners were presented with multiple samples of each voice and were asked to sort the voices into piles according to perceived speaker identity. Based on prototype models of voice perception, we hypothesized that errors in telling voices apart would be strongly predictable from distances in the group acoustic space, but that errors in telling voices together would not be significantly associated with these distances. Separate analyses will attempt to shed light on the features and strategies involved in this second kind of judgment. [Work supported by NIH/NSF.]
JOGOS SONOROS NA FALA INFANTIL E MUDANÇAS NA INTERPRETAÇÃO DO OUTRO

portuguesResumo: Focalizamos, neste artigo, os jogos sonoros infantis, isto e, as aproximacoes/associacoes entre segmentos sonoros semelhantes, que dominam a fala da crianca em um momento inicial de seu percurso linguistico. A partir do confronto com uma diversidade de formas pelas quais a crianca joga com os sons dos significantes de sua lingua materna, suspeitamos que haveria tambem uma variacao na interpretacao do outro, na dependencia do contexto dialogico, o que configuraria a chamada flexibilidade pragmatica da interpretacao em aquisicao de linguagem. Nessa perspectiva, a analise de tres episodios de dialogo entre uma crianca e sua mae deu indicacoes de que diferencas entre jogos sonoros infantis estariam relacionadas a diferencas entre as interpretacoes da mae para esses jogos. EnglishAbstract: In this article, we focus on children's sound games, i.e., the approximations/associations among similar sound segments, which dominate child’s speech at an early point in their linguistic course. By comparing the various ways children play with the sounds of signifiers of their mother tongue, we have supposed that there would also be a variation in the interpretation of the other, depending on the dialogic context, which would configure the so-called pragmatic flexibility of interpretation in language acquisition. From this perspective, the analysis of three episodes of dialogue between a child and her mother indicates that the differences in children’s sound-plays would be related to differences in mother's interpretations for these games.
READING STRATEGIES IN ISLAMIC BOARDING SCHOOL: A SMALL SCALE SURVEY

Reading strategies issues appear in EFL context, not only in formal education but also in informal education, for example in Islamic boarding school. The aims of this study is to identify the use of reading strategies by the students of Islamic boarding school. This study included 71 students at Islamic boarding school from higher education with the different studies in their university as respondents. The researcher used quantitative research with Survey of Reading Strategies (SORS) based on Mokhtari and Sheorey’s (2002) questionnaire. The questionnaire was divided into three categories: Global strategies, Problem-solving strategies, and Support strategies. There are 30 items used point Likert scale from level 1-5 as the main instrument in data retrieval. To analyze the data, the researcher using SPSS and Microsoft Excel. The result showed that the most reading strategies used by the students is problem-solving strategies with mean score = 3,952 followed reading strategies with mean score = 3,663 and the lowest one is support strategies with mean 3,633. The score of each domain indicate in high level of use. It means almost of students believe and use reading strategies while reading academic materials.
INTERJECTIONS IN THE INDONESIAN COMIC SERIES NEXT G AND THE DUTCH COMIC SERIES Kik

Interjections are the words frequently found in both Indonesian and Dutch comic books. This study focuses on the types of interjection that have meaning and express feelings in a comic series published in Indonesia, Next G. This study aims to describe the types of interjection that express feelings in the comic series Next G in terms of the number and the syllable pattern and explains other characteristics of the use of interjection in the comic series. The method used in this study is descriptive qualitative using literature review as its data collection technique obtained from the comparison of the analysis and the interjection (Haeseryn, 1997) in the Dutch comic book Kik. The result of the study shows that the interjections that express feelings in the comic Next G and the comic Kik are similarly dominated by fear and the highest number of syllable consists of one to two syllables The functions of the interjection in both comic series are similar, to add excitement and to express strong emotions to the story. The use of interjections that comes from foreign languages can be found more in the Indonesian comic series Next G compared to the Dutch comic series Kik.
Performance Analysis of Various Meta-Heuristic Based Load Balancing in Cloud Computing

Today one of the new and emerging technologies is Cloud Computing, which denotes to operating, organizing, and retrieving the services over the internet. It is the pre-requisite of IT services on the Internet. In this, Load balancing is the issue region of Cloud Computing, which has a noteworthy effect for characterizing the resource accessibility. In this, Meta-heuristic techniques are applied on Load Balancing in Cloud Computing and their results are shown.
Moving Objects Counting Dashboard Web Application Design

The ability to detect and count people using digital image processing techniques has a lot of applications. Retail stores need to understand foot traffic to organise their goods, understand peak times or prevent theft. Business or government agencies could use the counter to design or manage buildings and other public places. A system of object detection algorithm runs on CCTV footages needs a good platform to display the result that easy to access and interactive. This paper will explain the design of dashboard web application used to display the number of objects in a CCTV video and in our implementation the objects are people in a building and vehicles on the traffic intersections. The main focus of this paper is the novel software architecture that is consisted of four different programs that are communicating with each other. Those programs are publisher, object detection, video combiner, and dashboard program. Object detection system is using YOLOv3, an algorithm using deep learning and convolutional neural networks (CNN) that can detect objects fast and real-time. The terminology means that the web application can detect the number of objects in a live CCTV video with few seconds of delay. The computer specification that is used in the test to achieve real-time result is Intel Xeon E3 CPU, NVIDIA GTX1060 GPU, and 8 GB of RAM. OpenCV, an open source library for computer vision and machine learning is also used. The dashboard design is using Dash by Plotly, an open source Python based framework to create web application.
To infinity and beyond: The life story of brass instrument shock waves

One of the most spectacular features of the sound of trumpets, trombones, and french horns is the way in which the spectral content evolves during a crescendo. The gentle rounded timbre which these instrument create when played very quietly becomes increasingly bright as the loudness increases, and at the fortissimo level the sound develops a snarling brilliance described as “brassy.” In 1980, Jim Beauchamp suggested that nonlinear sound propagation might play a role in this spectral enrichment, and in 1996, experiments by Mico Hirschberg, Joel Gilbert and colleagues confirmed that the cumulative effect of nonlinear distortion in a trombone could lead to shock wave formation. This paper reviews the experimental studies which have subsequently been undertaken to understand better the circumstances which lead to the theoretically infinite pressure gradient of a shock wave, and the way in which the wavefront evolves as it travels on to the bell and into the open space beyond.
Linkage between Results of Unified State Exam in Mathematics and Education Outcomes in Calculus and Analytical Geometry in the First Half-Year Term

Linkage between the rating points in the first half-year term in Calculus and Analytical Geometry, and the points of USE (Unified State Exam), of first-year students of engineering specialization is studied. The training sample includes the data of 365 students (284 male and 81 female students). Statistical analysis of gender samples has established that the points obtained by female students in Analytical Geometry were significantly (at level 5%) higher than the points obtained by male students; the points in Calculus in both gender samples had no significant difference. A significant positive correlation of all variables has been revealed; hereby, in the female student sample, the correlation is stronger. The authors have constructed regression models purposing to predict the students’ resulting term rating points in Calculus and Analytical Geometry in both gender samples by virtue of their USE points and ratings in both subjects before the exams. The adjusted coefficient of determination for the final rating in Calculus is about 0.85, as well as for the resulting rating in Analytical Geometry in the female student sample. In the male student sample, the coefficient of determination is 0.78. The mentioned differences make it preferable to use separate models for prediction of education outcomes for male and female students. The suggested regression model has been verified on a test sample of 161 students taught in the same specialization in the previous year. For the test sample, the regression model has shown good results.
Distributed optoelectronic system of environmental monitoring in a real-time mode

The system for monitoring environmental indicators and the state of the environment was developed. It solves the problem of incorrect environmental monitoring using monitoring devices based on Arduino platforms.
Multioracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets

In software engineering, the imprecise requirements of a user are transformed to a formal requirements specification during the requirements elicitation process. This process is usually guided by requirements engineers interviewing the user. We want to partially automate this first step of the software engineering process in order to enable users to specify a desired software system on their own. With our approach, users are only asked to provide exemplary behavioral descriptions. The problem of synthesizing a requirements specification from examples can partially be reduced to the problem of grammatical inference, to which we apply an active coevolutionary learning approach. However, this approach would usually require many feedback queries to be sent to the user. In this work, we extend and generalize our active learning approach to receive knowledge from multiple oracles, also known as proactive learning. The ``user oracle'' represents input received from the user and the “knowledge oracle” represents available, formalized domain knowledge. We call our two-oracle approach the “first apply knowledge then query” (FAKT/Q) algorithm. We compare FAKT/Q to the active learning approach and provide an extensive benchmark evaluation. As result we find that the number of required user queries is reduced and the inference process is sped up significantly. Finally, with so-called On-The-Fly Markets, we present a motivation and an application of our approach where such knowledge is available.
Selection-based Question Answering of an MOOC.

e-Yantra Robotics Competition (eYRC) is a unique Robotics Competition hosted by IIT Bombay that is actually an Embedded Systems and Robotics MOOC. Registrations have been growing exponentially in each year from 4500 in 2012 to over 34000 in 2019. In this 5-month long competition students learn complex skills under severe time pressure and have access to a discussion forum to post doubts about the learning material. Responding to questions in real-time is a challenge for project staff. Here, we illustrate the advantage of Deep Learning for real-time question answering in the eYRC discussion forum. We illustrate the advantage of Transformer based contextual embedding mechanisms such as Bidirectional Encoder Representation From Transformer (BERT) over word embedding mechanisms such as Word2Vec. We propose a weighted similarity metric as a measure of matching and find it more reliable than Content-Content or Title-Title similarities alone. The automation of replying to questions has brought the turn around response time(TART) down from a minimum of 21 mins to a minimum of 0.3 secs.