Augmented Reality

Augmented Reality (AR) is a natural development from virtual reality (VR), which was developed several decades earlier. AR complements VR in many ways. Due to the advantages of the user being able to see both the real and virtual objects simultaneously, AR is far more intuitive, but it's not completely detached from human factors and other restrictions. AR doesn't consume as much time and effort in the applications because it's not required to construct the entire virtual scene and the environment. In this book, several new and emerging application areas of AR are presented and divided into three sections. The first section contains applications in outdoor and mobile AR, such as construction, restoration, security and surveillance. The second section deals with AR in medical, biological, and human bodies. The third and final section contains a number of new and useful applications in daily living and learning

Real-time Measurement and Control of Urban Stormwater Systems

Urban watersheds are being stressed beyond their capacity as storms are becoming more frequent and intense. Flash flooding is the leading cause of natural disaster deaths in the United States. Simultaneously, population pressures are changing landscapes and impairing water quality by altering the composition of urban stormwater runoff. Presently, the only solution to combat these challenges relies on the construction of larger infrastructure, which is cost prohibitive for most cities and communities. Advances in technology and autonomous systems promise to usher in a new generation of “smart” stormwater systems, which will use city-scale sensing and control to instantly “redesign” themselves in response to changing inputs. By dynamically controlling pumps, valves and gates throughout the entire city this paradigm promises to push the performance of existing assets without requiring the construction of new infrastructure. This will allow for entire urban watersheds to be dynamically controlled to meet a variety of desired outcomes. Despite technological advances and an established fundamental knowledge of water systems, it is presently entirely unclear how “smart” stormwater systems can actually be built. This dissertation conducts a review of existing “static” solutions and provides an assessment of a number of limited, but highly promising, real-world control studies. An analysis of sensor network scalability is then carried out, focusing on how large water sensor networks can be enabled by leveraging wireless connectivity and web-services. A study of urban water quality follows, which shows how real-time data improve our watershed-scale understanding of pollutant loads during storm events. In turn, through an unprecedented real-world study, it is illustrated how this improved understanding can be used to control flows across a watershed. A feedback control-based approach is then introduced to enable the control of urban watersheds. Through extensive simulation, this framework is applied to identify which control assets have the highest potential to improve watershed performance and to determine how many sites must be retrofitted to achieve desired outcomes. Finally, an analysis of input uncertainty is carried out, which quantifies the importance of weather forecasts in improving control performance across the scale of urban headwater catchments. The dissertation closes by laying out future directions in the emerging field of “smart” stormwater research.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/140797/1/bpwong_1.pd

Data and the city – accessibility and openness. a cybersalon paper on open data

This paper showcases examples of bottom–up open data and smart city applications and identifies lessons for future such efforts. Examples include Changify, a neighbourhood-based platform for residents, businesses, and companies; Open Sensors, which provides APIs to help businesses, startups, and individuals develop applications for the Internet of Things; and Cybersalon’s Hackney Treasures. a location-based mobile app that uses Wikipedia entries geolocated in Hackney borough to map notable local residents. Other experiments with sensors and open data by Cybersalon members include Ilze Black and Nanda Khaorapapong's The Breather, a "breathing" balloon that uses high-end, sophisticated sensors to make air quality visible; and James Moulding's AirPublic, which measures pollution levels. Based on Cybersalon's experience to date, getting data to the people is difficult, circuitous, and slow, requiring an intricate process of leadership, public relations, and perseverance. Although there are myriad tools and initiatives, there is no one solution for the actual transfer of that data

Embedded web server for the AVR Butterfly enabling immediate access to wireless sensor node readings

The "AVR Butterfly" (BF) is not just a microcontroller, but rather an autonomous embedded system kit including several sensors. Our main objective was first to provide Internet connectivity to the BF and then to evaluate its further capabilities as a sensor network node. To this end, we equipped the BF with a TCP/IP stack and a Zigbee transceiver. As a case study, we constructed a node and a gateway based on the BF and formed a simple wireless sensor network (WSN). In order to enable remote users to access, on demand, sensor node readings through their web browsers, an HTML Server application was developed for the BF-gateway. We demonstrate that despite the scarcity of the available resources, if we enhance the BF with a popular Ethernet chip and the optimal TCP/IP stack for 8-bit microcontrollers, we can obtain a powerful, yet simple and inexpensive, monitoring device with Internet connectivity capabilities. © Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering 2010

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed

Европейский и национальный контексты в научных исследованиях

В настоящем электронном сборнике «Европейский и национальный контексты в научных исследованиях. Технология» представлены работы молодых ученых по геодезии и картографии, химической технологии и машиностроению, информационным технологиям, строительству и радиотехнике. Предназначены для работников образования, науки и производства. Будут полезны студентам, магистрантам и аспирантам университетов.=In this Electronic collected materials “National and European dimension in research. Technology” works in the fields of geodesy, chemical technology, mechanical engineering, information technology, civil engineering, and radio-engineering are presented. It is intended for trainers, researchers and professionals. It can be useful for university graduate and post-graduate students