User Position Research Articles

Placement Retargeting of Virtual Avatars to Dissimilar Indoor Environments.

Rapidly developing technologies are realizing a 3D telepresence, in which geographically separated users can interact with each other through their virtual avatars. In this article, we present novel methods to determine the avatar's position in an indoor space to preserve the semantics of the user's position in a dissimilar indoor space with different space configurations and furniture layouts. To this end, we first perform a user survey on the preferred avatar placements for various indoor configurations and user placements, and identify a set of related attributes, including interpersonal relation, visual attention, pose, and spatial characteristics, and quantify these attributes with a set of features. By using the obtained dataset and identified features, we train a neural network that predicts the similarity between two placements. Next, we develop an avatar placement method that preserves the semantics of the placement of the remote user in a different space as much as possible. We show the effectiveness of our methods by implementing a prototype AR-based telepresence system and user evaluations.

Location-Privacy-Preserving Technique for 5G mmWave Devices

In fifth generation (5G) cellular networks, a single base station equipped with multiple antennas can determine the user position within centimeters, by processing the wireless millimeter-wave channel estimate. A fake base station serving a victim user can also obtain the user location. In order to protect the user privacy, we propose a technique to prevent localization. We design a user transmit beamformer, so that the angles of departure of each channel path are hidden to the base station, thus preventing localization. We also optimize the allocated power, in order to maximize the achievable rate. The proposed solution is compared with both the capacity-achieving beamforming (without location privacy) and the zero-forcing beamforming, which still provides location privacy, at the cost of a lower rate.

Modelo de teste perceptual das nasais do talian como recurso para a compreensão do português brasileiro de áreas colonizadas por descendentes de italianos

O objetivo deste artigo é apresentar um modelo de teste perceptual de identificação das vogais nasais do talian como recurso para a compreensão do posicionamento dos usuários sobre os falares presentes em localidades colonizadas por descendentes de italianos. Com o uso do software TP, dez informantes foram submetidos aos testes de percepção, avaliando estímulos com características do talian ou não marcados. Os resultados mostraram uma avaliação negativa aos estímulos com características do talian, pronúncia estigmatizada na localidade, enquanto que as formas não marcadas receberam boas avaliações.

Computational Complexity Closed-Form Upper Bounds Derivation for Fingerprint-Based Point-of-Interest Recognition Algorithms

Place recognition and user positioning methods are becoming trending topics among the research community thanks to the need of providing cutting-edge solutions to enable innovative and efficient Location-Based Services (LBS) and applications. However, the mobile framework suffers from typical constraints on energy and computational capabilities due to the inherent characteristics of wireless mobile devices. For this reason, in order to be suitable for deploying in such framework, a place recognition algorithm should be thrifty in terms of resource consumption. In this paper we consider six different WiFi-based outdoor positioning approaches and we analytically derive an upper-bound for their computational burden in terms of number of FLoating-point OPerations (FLOPs).

An SBAS Integrity Model to Overbound Residuals of Higher-Order Ionospheric Effects in the Ionosphere-Free Linear Combination

The next generation of satellite-based augmentation systems (SBAS) will support aviation receivers that take advantage of the ionosphere-free dual-frequency combination. By combining signals of the L1 and L5 bands, about 99% of the ionospheric refraction effects on the GNSS (Global Navigation Satellite Systems) signals can be removed in the user receivers without additional SBAS corrections. Nevertheless, even if most of the negative impacts on GNSS signals are removed by the ionospheric-free combination, some residuals remain and have to be taken into account by overbounding models in the integrity computation conducted by safety-of-live (SoL) receivers in airplanes. Such models have to overbound residuals as well, which result from the most rare extreme ionospheric events, e.g., such as the famous “Halloween Storm”, and should thus include the tails of the error distribution. Their application shall lead to safe error bounds on the user position and allow the computation of protection levels for the horizontal and vertical position errors. Here, we propose and justify such an overbounding model for residual ionospheric delays that remain after the application of the ionospheric-free linear combination. The model takes into account second- and third-order ionospheric refraction effects, excess path due to ray bending, and increased ionospheric total electron content (TEC) along the signal path due to ray bending.

Android-based GO-COURSE Application with Location Based Services Method

Advances in technology in the field of Android-based applications are expected to bring changes in the world of education intended for English language education. At present the method of searching institute courses that are present in a variety of applications offered, but the existing applications are not yet complete on this matter related to the applications offered do not meet the specific needs of the course institution search applications that are provided in the English village pare. LBS and algotima dijkstra can be used in the analysis and design of android-based applications, it is required an application to search for locations such as applications needed by user in addition to places of study can also find a place to spend the night while studying, where traveling provides the facilities that have been provided. The results of the Go-Course application can conclude that it must meet the needs of users to carry out the process of finding a chair, boarding house, boarding house and travel package from a smartphone by providing a fairly accurate position. By applying the Djikstra algorithm to the Go-Course Application, you can set the shortest route to the boarding house and boarding house with the user's position and current distance in the form of a map. All functions in the Go-Cource application for finding seats, boarding, boarding and tour packages can run correctly through Blackbox Testing and in accordance with manufacturing recommendations.Keywords: LBS, Dijkstra, Android, GPS, Go-Course.

Affective computing study of attention recognition for the 3D guide system

The eye-tracking has been widely used in multiple discipline studies in recent years. However, most of the studies focused on the analysis for static images or text but less for highly interactive operation application. In addition, the affective computing rose and development in recent years have changed completely the design of thinking pattern for the human–computer interaction. Therefore, this study hopes to integrate the affective computing into the 3D guide system which was developed for the real campus through the eye-tracking technology. The analysing user's gaze position and recognising attention emotion are according to the interest region which is stetted into the environment, and shows the feedback content corresponds to the area and the emotion. Through the most intuitive gaze analysis, the operation burden can be reduced and the user's interactive experience can be improved to achieve intuitive and user-friendly experience. The results can also apply for medical therapy on human attention training.

Doppler-aided positioning in GNSS receivers - A performance analysis

The main objective of Global Navigation Satellite Systems (GNSS) is to precisely locate a receiver based on the reception of radio-frequency waveforms broadcasted by a set of satellites. Given delayed and Doppler shifted replicas of the known transmitted signals, the most widespread approach consists in a two-step algorithm. First, the delays and Doppler shifts from each satellite are estimated independently, and subsequently the user position and velocity are computed as the solution to a Weighted Least Squares (WLS) problem. This second step conventionally uses only delay measurements to determine the user position, although Doppler is also informative. The goal of this paper is to provide simple and meaningful expressions of the positioning precision. These expressions are analysed with respect to the standard WLS algorithms, exploiting the Doppler information or not. We can then evaluate the performance improvement brought by a joint frequency and delay positioning procedure. Numerical simulations assess that using Doppler information is indeed effective when considering long observation times, and particularly useful in challenging scenarios such as urban canyons (constrained satellite visibility) or near indoor situations (weak signal conditions which need long integration times), thus providing new insights for the design of robust and high-sensitivity receivers.

Visible Light-Based User Position, Orientation and Channel Estimation Using Self-Adaptive Location-Domain Grid Sampling

In this paper, visible light-based positioning (VLP) is studied. VLP is greatly challenging because (i) it is essentially a non-convex optimization problem since the visible-light received signal strength (RSS) is nonlinear with the user equipment (UE) position; and (ii) in addition to the UE location, the visible light RSS also depends on the UE orientation and small-scale channel gains, which are unknown in practice. This complicates the VLP problem due to the enlarged searching space. To address these challenges, we propose a location-domain grid sampling scheme. Specifically, the location-domain grid sampling can potentially partition the location space into small cells, and hence the non-convexity challenge of RSS-based VLP is mitigated. In addition, using the location-domain grid sampling, we transform VLP into a sparse recovery problem. A novel group sparse learning (GSL) algorithm with self-adaptive location-domain grids is proposed to achieve an efficient RSS-based VLP solution, via exploring the inherent sparse structure. The convergence of our GSL algorithm is established. Thanks to the adaptivity of dynamic location-domain grids, the required number of location-domain grids can be significantly reduced, compared with conventional fixed-grid-based GSL solutions. Moreover, the proposed GSL-based VLP method jointly learns the UE location, orientation and channel gain, thus achieving a robust RSS-based VLP solution against parameter uncertainties. Finally, our simulation result verifies the large performance gain of the proposed RSS-based VLP solution over state-of-the-art VLP baselines, thanks to our self-adaptive grid sampling and problem-specific group sparse learning.

A Computation Effective Range-Based 3D Mapping Aided GNSS with NLOS Correction Method

Global navigation satellite system (GNSS) positioning in dense urban areas remains a challenge due to the signal reflection by buildings, namely multipath and non-line-of-sight (NLOS) reception. These effects degrade the performance of low-cost GNSS receivers such as in those smartphones. An effective three-dimensional (3D) mapping aided GNSS positioning method is proposed to correct the NLOS error. Instead of applying ray-tracing simulation, the signal reflection points are detected based on a skyplot with the surrounding building boundaries. The measurements of the direct and reflected signals can thus be simulated and further used to determine the user's position based on the measurement likelihood between real measurements. Verified with real experiments, the proposed algorithm is able to reduce the computational load greatly while maintaining a positioning accuracy within 10 metres of error in dense urban environments, compared with the conventional method of ray-tracing based NLOS corrected positioning.

Examining Social Capital, Social Support, and Language Use in an Online Depression Forum: Social Network and Content Analysis.

BackgroundThe use of peer-to-peer online support groups and communities has grown into a social phenomenon. Many people use online support groups and communities to seek and provide social support. It is essential to examine how users’ participation behaviors may contribute to different outcomes.ObjectiveThis study aimed to (1) use the structural positions of online depression forum users in their reply network to predict received support and (2) examine their language use reflecting their health conditions.MethodsA total of 2061 users and their 62,274 replies posted on a depression forum from July 2004 to July 2014 were extracted using a web crawler written in Python. The content of the forum users’ posts and replies and their reply patterns were examined. A social network analysis method was used to build the reply networks of users. The computerized text analysis method was used to measure features of the forum users’ language styles.ResultsForum users’ bridging social capital (operationalized as network betweenness) was positively associated with the level of communication accommodation in their received replies (P=.04). Forum users’ bonding social capital (operationalized as network constraint) was negatively associated with the level of communication accommodation in their received replies (P<.001). The forum users’ change in their use of self-referent words and words expressing negative emotions were examined as linguistic proxies for their health conditions and mental states. The results revealed a general negative association between the number of received replies and the degree of decrease in the use of words expressing negative emotion (P=.007).ConclusionsThe structural positions of online depression forum users in the reply network are associated with different participation outcomes in the users. Thus, receiving replies can be beneficial to online depression forum users.

Efficient Combinations of NOMA With Distributed Antenna Systems Based on Channel Measurements for Mitigating Jamming Attacks

This article aims at proposing new efficient combinations of distributed antenna systems with nonorthogonal multiple access for combating the influence of harmful jamming on a downlink transmission system. A large set of practical channel measurements was performed in an indoor work environment in order to encompass a wide panoply of user positions, antennas, and jammer configurations. Then, three strategies were studied for the selection of subbands, antennas, and transmit powers so as to alleviate the influence of jamming. First, a configuration where the paired users are served by a unique antenna was considered. Then, two other configurations were studied, where paired users are served by two different antennas. It was shown that, in these two strategies, under specific channel and power conditions, it is possible to allow both paired users to perform successive interference cancellation (SIC) to remove interuser interference. The dual-SIC strategy, when applied with joint antenna transmission, presents a good robustness to jamming and yields important throughput gains, compared to the classical single-SIC scenario and single-antenna dual-SIC transmission.

PENGEMBANGAN DESAIN GANTUNGAN PAKAIAN INKLUSIF UNTUK MEMUDAHKAN AKTIVITAS MENJEMUR PAKAIAN

&#x0D; &#x0D; &#x0D; Title: Development of Inclusive Hanger Design to Facilitate Clothes Drying Activities&#x0D; Laundry activities, including drying are still recommended to be done by the elderly independently. However, the decline in the physical condition of the elderly, including a decrease in the balance of body position, cannot be avoided. In the observation at the GKJ Gondokusuman nursing home, the drying place is uses a rope on the roof or pole that is quite high from the reach of the elderly hand. When drying clothes, the elderly must stretch their arms and tiptoe because of the differences in height of the clothesline. This condition can increase the risk of accidents for the elderly who lose balance. This study aims to develop a product to dry the laundry and reduce the distance between the users with a high clothesline. This product development was using design research and product design. The research method was based in ergonomics knowledge through an inclusive design approach. The techniques used were behavioral observation, assessment of body activities, like Nordic Body Map (NBM) and Rapid Entire Body Assignment (REBA). The results of the NBM stated that the elderly experienced pain in the right side of the body, while the results of the REBA assessment showed a score of 10. This condition showed that the elderly posture while drying still had a high risk of injury. As the results of these studies, the product is designed with a function to hang laundry that make user's body position more balanced because there is no need to stretch arms and tiptoe too high. Users also easily put clothes on the hanger because there is a grip feature for both hands.&#x0D; &#x0D; &#x0D;

Iterative Prototyping of Urban CoBuilder: Tracking Methods and User Interface of an Outdoor Mobile Augmented Reality Tool for Co-Designing

This research presents results from a study developing a smartphone app, Urban CoBuilder, in which citizens can collaboratively create designs for urban environments using augmented reality technology and game mechanics. Eight prototypes were developed to refine selected design criteria, including tracking strategies, design elements, user experience and the interface with game mechanics. The prototypes were developed through an iterative design process with assessments and incremental improvements. The tracking was especially challenging and using multiple bitonal markers combined with the smartphone’s gyroscope sensor to average the user position was identified as the most suitable strategy. Still, portability and stability linked to tracking need to be improved. Design elements, here building blocks with urban functions textures, were realistic enough to be recognizable and easy to understand for the users. Future studies will focus on usability tests with larger user groups.

The Performance Analysis of INS/GNSS/V-SLAM Integration Scheme Using Smartphone Sensors for Land Vehicle Navigation Applications in GNSS-Challenging Environments

Modern smartphones contain embedded global navigation satellite systems (GNSSs), inertial measurement units (IMUs), cameras, and other sensors which are capable of providing user position, velocity, and attitude. However, it is difficult to utilize the actual navigation performance capabilities of smartphones due to the low-cost and disparate sensors, software technologies adopted by manufacturers, and the significant influence of environmental conditions. In this study, we proposed a scheme that integrated sensor data from smartphone IMUs, GNSS chipsets, and cameras using an extended Kalman filter (EKF) to enhance the navigation performance. The visual data from the camera was preprocessed using oriented FAST (Features from accelerated segment test) and rotated BRIEF (Binary robust independent elementary features)-simultaneous localization and mapping (ORB-SLAM), rescaled by applying GNSS measurements, and converted to velocity data before being utilized to update the integration filter. In order to verify the performance of the integrated system, field test data was collected in a downtown area of Tainan City, Taiwan. Experimental results indicated that visual data contributed significantly to improving the accuracy of the navigation performance, demonstrating improvements of 43.0% and 51.3% in position and velocity, respectively. It was verified that the proposed integrated system, which used data from smartphone sensors, was efficient in terms of increasing navigation accuracy in GNSS-challenging environments.

Real-Time PPP-RTK Performance Analysis Using Ionospheric Corrections from Multi-Scale Network Configurations

The long convergence time required to achieve high-precision position solutions with integer ambiguity resolution-enabled precise point positioning (PPP-RTK) is driven by the presence of ionospheric delays. When precise real-time ionospheric information is available and properly applied, it can strengthen the underlying model and substantially reduce the time required to achieve centimeter-level accuracy. In this study, we present and analyze the real-time PPP-RTK user performance using ionospheric corrections from multi-scale regional networks during a day with medium ionospheric disturbance. It is the goal of this contribution to measure the impact the network dimension has on the ambiguity-resolved user position through the predicted ionospheric corrections. The user-specific undifferenced ionospheric corrections are computed at the network side, along with the satellite phase biases needed for single-receiver ambiguity resolution, using the best linear unbiased predictor. Such corrections necessitate the parameterization of an estimable user receiver code bias, on which emphasis is given in this study. To this end, we process GPS dual-frequency data from four four-station evenly distributed CORS networks in the United States with varying station spacings in order to evaluate if and to what extent the ionospheric corrections from multi-scale networks can improve the user convergence times. Based on a large number of samples, our experimental results showed that sub-10 cm horizontal accuracy can be achieved almost instantaneously in the ionosphere-weighted partially-ambiguity-fixed kinematic PPP-RTK solutions based on corrections from a network with 68 km spacing. Most of the solutions (90%) were shown to require less than 6.0 min, compared to the ionosphere-float PPP solutions that needed 68.5 min. In case of sparser networks with 115, 174 and 237 km spacing, 50% of the horizontal positioning errors are shown to become less than one decimeter after 1.5, 4.0 and 7.0 min, respectively, while 90% of them require 10.5, 16.5 and 20.0 min. We also numerically demonstrated that the user’s convergence times bear a linear relationship with the network density and get shorter as the density increases, for both full and partial ambiguity resolution.

Global Autonomous Positioning in GNSS-Challenged Environments: A Bioinspired Strategy by Polarization Pattern

How to determine the absolute position of users, such as underwater autonomous vehicles, ships or other long-range vehicles, is a fascinating and challenging issue, especially in global navigation satellite system -denied environments. In this article, a bioinspired global autonomous positioning system based on polarized skylight is proposed. By comparing with the related literatures, the system is able to global positioning based on the degree of polarization pattern (DoP) pattern. To be more specific, in an attempt to use the DoP pattern for the geolocalization purposes, a bioinspired polarization compass is designed and in addition, an overall maximum DoP (MDoP) determination algorithm is presented. Moreover, on the basis of the MDoP value, the sun elevation angle can be ultimately measured by using the DoP pattern. The sun elevation angle difference algorithm is used to deduce the absolute position of users. Finally, the bioinspired global autonomous positioning system is developed and validated through experiments. The test results show that the location errors are in range of few kilometers, of which the latitude accuracy is 0.113° (1σ), and the longitude accuracy is 0.082° (1σ).

Research on Crowdsourcing network indoor localization based on Co-Forest and Bayesian Compressed Sensing

Indoor Localization Technology (ILT) based on Wi-Fi network has been rapidly developed with high localization accuracy and low hardware requirements. Collecting the Received Signal Strength (RSS) samples to construct the fingerprint database, however, is time consuming and labor intensive, hindering the application of the technology. An Indoor Localization Method is proposed based on Co-Forest and Bayesian Compressed Sensing (ILM-CFBCS), utilizing the crowdsourcing network technology to collect RSS data and the min-max method to preprocess the data so as to establish the indoor fingerprint database. The user's position is determined according to the decision result of the random forest classifier trained by the Co-Forest algorithm combining with majority principle. Finally, a constructing method of offline fingerprint database is put forward by combining the similarity between Bayesian compressed sensing theory and reference point fingerprint to realize the fingerprint database update. The experimental results show that the proposed method can achieve good localization performance by using a small amount of data with labeled positions.

Learning VAA: A new method for matching users to parties in voting advice applications

ABSTRACT Voting Advice Applications (VAAs) aim to increase voters’ political competence by providing them with the closest political party according to their preferences. To do this, VAAs usually compare and aggregate the positions of users and political parties on a set of policy issues by defining a conceptual space and some distance metric on it. In this paper, we argue that the main method for performing the comparison adapts to users’ preferences unsatisfactorily because 1) they use unjustified a priori decisions for weighting policy issues and 2) they employ the same issue-voting space on all policy issues. Some exceptional cases address these issues by providing a community-based recommendation, but often come with lack of interpretability. To fill these gaps, we propose an adaptive algorithm that learns the configuration of the conceptual space from users’ answers. We employ a hybrid VAA that uses expert coding for the party positions and users’ data to adjust the calculation of the distance between users and parties. This new matching method, the Learning VAA, innovates by adjusting the saliency and issue-voting space for every policy issue. We argue and empirically demonstrate that our model fits better the users’ preferences while providing a higher degree of interpretability.

Identification of User Roles in Enterprise Social Networks: Method Development and Application

The importance of gaining insights into informal organizational structures for management purposes is acknowledged by both research and practice. However, “traditional” approaches to analyzing informal organizational social networks involve significant manual effort and do not scale for larger datasets. Enterprise Social Networks (ESN) have emerged as important tools for informal employee interactions, such as for problem-solving and information sharing. While the analysis of ESN back end data might provide insights into the informal fabric of organizations, and in particular employees’ roles in such networks, there is a lack of systematic approaches for carrying out ESN analytics, such as for user role identification. Following a design science research process, a process-based method to identify user roles from ESN data was developed and evaluated. The method’s efficacy is demonstrated through an in-depth application in a case study of Australian professional services firm Deloitte. In doing so the paper shows how ESN data can be utilized to derive metrics that characterize participation behavior, message content, and structural network positions of ESN users.