Natural User Interface for Education in Virtual Environments

Education and self-improvement are key features of human behavior. However, learning in the physical world is not always desirable or achievable. That is how simulators came to be. There are domains where purely virtual simulators can be created in contrast to physical ones. In this research we present a novel environment for learning, using a natural user interface. We, humans, are not designed to operate and manipulate objects via keyboard, mouse or a controller. The natural way of interaction and communication is achieved through our actuators (hands and feet) and our sensors (hearing, vision, touch, smell and taste). That is the reason why it makes more sense to use sensors that can track our skeletal movements, are able to estimate our pose, and interpret our gestures. After acquiring and processing the desired – natural input, a system can analyze and translate those gestures into movement signals

Participative Placemaking in Serbia: The Use of the Limitless GIS Application in Increasing the Sustainability of Universal Urban Design

The 20th century brought about major social challenges related to civil and human rights, triggering changes in urban environments and gradually adjusting the spatial and functional performances of cities to the needs of all users. In this article, the concept of Universal Urban Design (i.e., “Design for All”) is regarded as a sustainable placemaking process which enables the higher accessibility and usability of cities for all people, regardless of their age or (dis)abilities. The pilot project “Creating Accessible Pedestrian Corridors by the Limitless GIS Application” conduced in Serbia from 2017 to 2019 by the Faculty of Architecture at the University of Belgrade and the Non-Governmental Organization (NGO) Limitless proposes an innovative approach to urban design. Based on information and communication technology (ICT) adaptation, it is focused on the alternative concept-design of buildings, provision of ICT-based infrastructure, socioeconomic integration of all users, and ultimately on overall urban sustainability. The main outcome of the project was the development of a Geographic Information System (GIS) android application and an e-platform for adaptive placemaking. The project also provides a set of accessibility criteria based on Universal Urban Design, criteria that enable the mapping of locations based on the type of use, a set of recommendations for identified problems, as well as a brief analysis of the latest technological solutions for overcoming detected physical barriers. The Limitless GIS android application differs from the existing ones since it primarily identifies two target groups: (1) people with disabilities who could upload necessary data by established criteria; and (2) employees in the public sector (city authorities and municipalities) in charge of planning alternative routes and setting priorities and investment costs based on the identified problems. Pilot results of the project have revealed that in the current Serbian practice, there is still a lack of planned, consistent and continuous movement routes in urban areas. Terrain configuration represents a serious limitation for people with disabilities, while lifting platforms are recognized as a better solution than ramps (both for paraplegics and quadriplegics), due to their higher efficiency and minimized spatial requirements. Therefore, the android application and e-platform presented in this article contribute to the detection of actual problems at the local level as well as to the overall improvement of planning/design practice in Serbian citie

A neural network based model for mass non-residential real estate price evaluation of Lisbon, Portugal

Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementAn accurate estimation of the real estate value became very important to make correct purchase and sale transaction, calculate taxes, mortgages for loans. Mass appraisal systems that use modern methodology based on artificial intelligence significantly help to deal with these issues. Objectives of this article are: using artificial neural networks (AANs) build mass appraisal model to evaluate market price of non-residential real estate of Lisbon, Portugal; evaluate performance of AANs and compare it with results generated by other models based on different methodologies and prove AANs superiority in issues connected with real estate apprising

Street recovery in the age of COVID-19: Simultaneous design for mobility, customer traffic and physical distancing

This paper explores the relationship between urban traffic, retail location and disease control during the COVID-19 pandemic crisis and tries to find a way to simultaneously address these issues for the purpose of street recovery. Drawing on the concept of the 15 min city, the study also aims at seeking COVID-19 exit paths and next-normal operating models to support long-term business prosperity using a case study of Royal Street, East Perth in Western Australia. Nearly half of the shops became vacant or closed at the end of 2020 along the east section of Royal Street, demonstrating the fragility of small business in a car-oriented street milieu that is inadequately supported by proper physical, digital and social infrastructure. A key finding from the analysis is the formulation of the concept of the Minute City. This describes a truly proximity-centred and socially driven hyper-local city, where residents and retailers work together on the local street as a walkable public open space (other than movement space), and benefit from ameliorated traffic flow, improved business location and a safer, connected community

Context-dependent environmental sound monitoring using SOM coupled with LEGION

Environmental sound measurement networks are increasingly applied for monitoring noise pollution in an urban context. Intelligent measurement nodes offer the opportunity to perform advanced analysis of environmental sound, but trade-offs between cost and functionality still have to be made. When using a tiered architecture, local nodes with limited computing capabilities can be used to detect sound events of potential interest, which are then further analyzed by more powerful nodes. This paper presents a human-mimicking model for detecting rare and conspicuous sound events. Features encoding spectro-temporal irregularities are extracted from the sound, and a Self-Organizing Map (SOM) is used to identify co-occurring features, which most likely belong to a single sound object. Extensive training allows this map to be tuned to the typical sounds that are heard at the microphone location. A Locally Excitatory Globally Inhibitory Oscillator Network (LEGION) is used to group units of the SOM in order to construct distinct sound objects

D3P : Data-driven demand prediction for fast expanding electric vehicle sharing systems

The future of urban mobility is expected to be shared and electric. It is not only a more sustainable paradigm that can reduce emissions, but can also bring societal benefits by offering a more affordable on-demand mobility option to the general public. Many car sharing service providers as well as automobile manufacturers are entering the competition by expanding both their EV fleets and renting/returning station networks, aiming to seize a share of the market and to bring car sharing to the zero emissions level. During their fast expansion, one determinant for success is the ability of predicting the demand of stations as the entire system is growing continuously. There are several challenges in this demand prediction problem: First, unlike most of the existing work which predicts demand only for static systems or at few stages of expansion, in the real world we often need to predict the demand as or even before stations are being deployed or closed, to provide information and decision support. Second, for the new stations to be deployed, there is no historical data available to help the prediction of their demand. Finally, the impact of deploying/closing stations on the other stations in the system can be complex. To address these challenges, we formulate the demand prediction problem in the context of fast expanding electric vehicle sharing systems, and propose a data-driven demand prediction approach which aims to model the expansion dynamics directly from the data. We use a local temporal encoding process to handle the historical data for each existing station, and a dynamic spatial encoding process to take correlations between stations into account with Graph Convolutional Neural Networks (GCN). The encoded features are fed to a multi-scale predictor, which forecasts both the long-term expected demand of the stations and their instant demand in the near future. We evaluate the proposed approach with real-world data collected from a major EV sharing platform for one year. Experimental results demonstrate that our approach significantly outperforms the state of the art, showing up to three-fold performance gain in predicting demand for the expanding EV sharing systems

시각적 의도가 지배적인 공간을 위한 커뮤니케이션 디자인에 관한 연구

학위논문 (박사) -- 서울대학교 대학원 : 미술대학 디자인학부 디자인전공, 2021. 2. 김경선.This dissertation seeks to explore the possibilities of visual communication design within the field of spatial design. Spatial Graphics is defined as a means of communication in which the nature and intention of the space is effectively communicated through visual expression. The aim of this thesis, on the one hand, is to articulate practices and strategies of visual communication as legitimate spatial design, while at the same time expanding the understanding of space with dominant visual intent so that new interactions and forms of communication can be revealed. Countless graphic designers have utilized visual language as a means of organizing and designing space, resulting in interdisciplinary collaborations between architects, interior designers, and other artists. Thus, one can observe traces of aesthetic and cultural influences on the work of contemporary graphic designers, reflecting a development toward greater independence. In this context, design as a concept is no longer confined to static, closed forms, but is largely integrated with dynamic environments in which life is lived and experienced. This dissertation should be understood as a contribution to understanding how graphic design as a discipline can extend its potential to encompass spatial design. The latter is an area that has been relatively less examined within the graphic design field. Expanding the potential of graphic design, this dissertation seeks to explore the possibilities of reading the field as an articulation of a multi-sensory experience by paying particular attention to graphic designs contextual diversity in a variety of disciplinary contexts. The dissertation thus focuses on a central trend in the graphic design field: the ways in which the practice of graphic design as a communicative discourse constitutes crucial and aesthetic interventions into public space. These interventions illustrate, among other things, how central properties within graphic design methodologies and approaches can recite and intensify spatial strategies and potentials in the environmental framework inhabited by people. To this end, an important dimension for the conduction of this research was the professional background knowledge and diverse work experiences of the researcher as a seasoned practitioner within the field of graphic design. The specific methods of conducting research for this paper are as follows: First, the concepts, historical meaning, and components of space are examined and analyzed. Secondly, the method of spatial graphics is described through case analysis and spatial characteristics. The main purpose of this dissertation is to explore the possibilities of constructing a significant model that stages, frames, and enables the coordinates for future research on the relationship between graphic design and space consciousness, and more specifically a model that draws the coordinates of a new spatial interpretation and visualization within the field of graphic design.본 논문은 공간 디자인 영역에 내재하는 비주얼 커뮤니케이션 디자인의 가능성을 탐구한다. 공간 그래픽이란 시각적 표현을 통해 공간의 성격과 의도를 효과적으로 전달하는 의사소통 수단을 일컫는다. 본 연구의 목적은 공간 디자인으로서 비주얼 커뮤니케이션 디자인의 타당성을 표명하고, 나아가 시각적 의도가 지배적인 공간에 대한 이해를 확장함으로써 새로운 상호작용과 의사소통 형식을 발견하는 데 있다. 디자인은 우리가 삶을 경험하는 방식, 그러므로 물리적 공간을 경험하는 방식에 큰 영향을 미친다. 대다수의 그래픽 디자이너들은 공간을 구성하고 설계하는 수단으로 시각적 언어를 활용하여 건축가, 실내 디자이너, 그 밖의 다양한 예술가들과 함께 학제적 협업을 이루어 왔다. 이러한 동시대 그래픽 디자이너들의 작업은 더욱 발전된 독립성을 반영함으로써 미학적, 문화적 영향을 미쳤다. 이러한 맥락에서, 디자인이라는 개념은 고정되고 폐쇄된 형식으로 국한될 수 없으며, 오히려 우리가 살아가고 경험하는 역동적인 환경과 융합되어 있다고 할 수 있다. 이에 본 논문은 그래픽 디자인 연구에서 상대적으로 간과되어 온 공간 디자인으로서 그것의 확장 가능성을 규명하기 위해, 하나의 학문으로서 그래픽 디자인이 어떻게 공간 디자인 분야에 영향을 미치는지 다양한 사례를 통해 살펴본다. 특히 본고가 주목하는 지점은 다학제적 관점을 수용함으로써 생산되는 그래픽 디자인의 다양한 맥락이며, 이는 그래픽 디자인을 다감각적 경험의 표현으로 이해하는 데 필수적이다. 따라서, 본 연구는 오늘날 그래픽 디자인 분야에서 나타나는 중심적인 경향에 초점을 맞춰, 그래픽 디자인 실천이 담론적 기능을 수행함으로써 공공 공간에 비판적이고 미적으로 개입하는 방식을 탐구한다. 이러한 개입은 무엇보다도 그래픽 디자인의 방법론 및 접근 방식에 내재된 고유한 특성에 의한 것으로, 그래픽 디자인은 그 자체로 우리가 생활하는 환경 체제 내부의 공간적 전략과 잠재성을 상연하고 또 강화하는 방식을 명시하기 때문이다. 연구자가 그래픽 디자이너로 활동하면서 쌓은 전문적인 시각과 실무 경험은 이러한 연구를 수행하는 데 중요한 배경이 된다. 본 논문의 구체적인 연구 방법론은 다음과 같다. 먼저, 공간의 개념과 그것의 역사적 의미 및 구성요소를 검토하고, 이를 그래픽 디자인 연구의 관점에서 살펴본다. 둘째, 동시대 그래픽 디자인의 다양한 사례들에 대한 분석을 통해 공간 그래픽의 기법과 그것의 공간적 특성에 대해서 설명한다. 이러한 과정을 통해, 본 논문이 궁극적으로 목표하는 바는 그래픽 디자인과 공간 인식 사이의 관계를 상호작용의 맥락에서 파악하고, 이를 새로운 공간 해석 및 시각화를 가능하게 하는 환경 구성의 원리로 논하는 것이다. 나아가 후속 연구를 위한 기틀을 마련하고자 이를 상연하고, 생산하고 또한 작동시키는 주요한 모델의 구축 가능성을 탐구한다.1. Research Background 1 1.1. Introduction 1 1.2. Terminology 4 1.3. Structure Of Thesis 12 2. Research Context 14 2.1. Formation Of Graphic Space 14 2.2. Graphic Design As Spatial Practice 20 2.3. Typography In Space 28 2.4. Color And Light In Space 33 2.5. Object And Display In Space 36 2.6. Study In Place Branding 41 2.7. Study In Art and Design 46 3. Research Methods 52 3.1. Case Studies 52 3.2. Precedent Research Project 60 4. Visual Exploration 66 4.1. Theme Of Nature 69 4.2. Exhibition Identity 72 4.3. 3d Model 74 4.4. Visual Vocabulary 78 5. Exhibition 81 5.1. Exhibition at Art Hae Gallery 81 5.2. Exhibition at SNU Museum Of Art 91 6. Conclusion 105 Bibliography/References 107Docto

Cooperative Scene-Event Modelling for Acoustic Scene Classification

Acoustic scene classification (ASC) can be helpful for creating context awareness for intelligent robots. Humans naturally use the relations between acoustic scenes (AS) and audio events (AE) to understand and recognize their surrounding environments. However, in most previous works, ASC and audio event classification (AEC) are treated as independent tasks, with a focus primarily on audio features shared between scenes and events, but not their implicit relations. To address this limitation, we propose a cooperative scene-event modelling (cSEM) framework to automatically model the intricate scene-event relation by an adaptive coupling matrix to improve ASC. Compared with other scene-event modelling frameworks, the proposed cSEM offers the following advantages. First, it reduces the confusion between similar scenes by aligning the information of coarse-grained AS and fine-grained AE in the latent space, and reducing the redundant information between the AS and AE embeddings. Second, it exploits the relation information between AS and AE to improve ASC, which is shown to be beneficial, even if the information of AE is derived from unverified pseudo-labels. Third, it uses a regression-based loss function for cooperative modelling of scene-event relations, which is shown to be more effective than classification-based loss functions. Instantiated from four models based on either Transformer or convolutional neural networks, cSEM is evaluated on real-life and synthetic datasets. Experiments show that cSEM-based models work well in real-life scene-event analysis, offering competitive results on ASC as compared with other multi-feature or multi-model ensemble methods. The ASC accuracy achieved on the TUT2018, TAU2019, and JSSED datasets is 81.0%, 88.9% and 97.2%, respectively