snu-aidas/HVMap-dataset huggingface dataset:
Enhanced Modelling and Performance in Braided Pneumatic Muscle Actuators

Pneumatic technology has been successfully applied for over two millennia. Even today, pneumatic cylinder based technology forms the keystone of many manufacturing processes where there is a need for simple, high-speed, low-cost, reliable motion. But when the system requires accurate control of position, velocity or acceleration profiles, these actuators form a far from satisfactory solution. Braided pneumatic muscle actuators (pMAs) form an interesting development of the pneumatic principle offering even higher power/weight performance, operation in a wide range of environments and accurate control of position, motion and force. This technology provides an interesting and potentially very successful alternative actuation source for robots as well as other applications. However, there are difficulties with this approach due to the following. (i) Modeling errors. Models of the force response are still nonoptimal and for good results these models are highly complex, which makes accurate design difficult. (ii) Low bandwidth—the bandwidth of the actuator—link assemblies are often considered to be too low for practical success in many applications, particularly robotics. In this paper we address these limitations and show how the performance in each area can be enhanced with overall improvements in the response and utility of the braided pMAs. KEY WORDS—actuators, braided pneumatic muscle actuators, McKibben muscles
High Dimensional Semiparametric Gaussian Copula Graphical Models

We propose a semiparametric approach called the nonparanormal SKEPTIC for efficiently and robustly estimating high-dimensional undirected graphical models. To achieve modeling flexibility, we consider the nonparanormal graphical models proposed by Liu, Lafferty and Wasserman [J. Mach. Learn. Res. 10 (2009) 2295–2328]. To achieve estimation robustness, we exploit nonparametric rank-based correlation coefficient estimators, including Spearman’s rho and Kendall’s tau. We prove that the nonparanormal SKEPTIC achieves the optimal parametric rates of convergence for both graph recovery and parameter estimation. This result suggests that the nonparanormal graphical models can be used as a safe replacement of the popular Gaussian graphical models, even when the data are truly Gaussian. Besides theoretical analysis, we also conduct thorough numerical simulations to compare the graph recovery performance of different estimators under both ideal and noisy settings. The proposed methods are then applied on a large-scale genomic data set to illustrate their empirical usefulness. The R package huge implementing the proposed methods is available on the Comprehensive R Archive Network: http://cran.r-project.org/.
A qualitative study on factors that influence women’s choice of delivery in health facilities in Addis Ababa, Ethiopia

BACKGROUND
Facility based delivery for mothers is one of the proven interventions to reduce maternal and neonatal morbidity and mortality. This study identified women's reasons for seeking to give birth in a health facility and captured their perceptions of the quality of care they received during their most recent birth, in a population with high utilization of facility based deliveries.


METHODS
This qualitative study was conducted in eight health centers in Addis Ababa. Women bringing their index child for first vaccinations were invited to participate in an in-depth interview about their last delivery. Sixteen in-depth interviews were conducted. Interviews were conducted by trained researchers using a semi-structured interview guide. The data were transcribed verbatim in Amharic and translated into English. A thematic analysis was conducted to answer specific study questions.


RESULTS
All research participants expressed a preference for facility based delivery because of their awareness of obstetric complications, and related perceptions that facility-birth is safer for the mother and child. Dimensions of quality of care and the cost of services were identified as influencing decisions about whether to seek care in the public or private sector. Media campaigns, information from social networks and women's experiences with healthcare providers and facilities influenced care-seeking decisions.


CONCLUSIONS
The universal preference for facility-based birth by women in this study indicates that, in Addis Ababa, facility based delivery has become a preferred norm. Sources of information for decision-making and the dimensions of quality prioritized by women should be taken into account to develop interventions to promote facility-based births in other settings.
Diffusion-on-Manifold Aggregation of Local Features for Shape-based 3D Model Retrieval

Aggregating a set of local features has become one of the most common approaches for representing a multi-media data such as 2D image and 3D model. The success of Bag-of-Features (BF) aggregation [2] prompted several extensions to BF, that are, VLAD [12], Fisher Vector (FV) coding [22] and Super Vector (SV) coding [34]. They all learn small number of codewords, or representative local features, by clustering a set of large number of local features. The set of local features extracted from a media data (e.g., an image) is encoded by considering distribution of features around the codewords; BF uses frequency, VLAD and FV uses displacement vector, and SV uses a combination of both. In doing so, these encoding algorithms assume linearity of feature space about a codeword. Consequently, even if the set of features form a non-linear manifold, its non-linearity would be ignored, potentially degrading quality of aggregated features. In this paper, we propose a novel feature aggregation algorithm called Diffusion-on-Manifold (DM) that tries to take into account, via diffusion distance, structure of non-linear manifold formed by the set of local features. In view of 3D shape retrieval, we also propose a local 3D shape feature defined for oriented point set. Experiments using shape-based 3D model retrieval scenario show that the DM aggregation results in better retrieval accuracy than the existing aggregation algorithms we've compared against, that are, VLAD, FV, and SV, etc..
Comparison between SPM and IPM motor drives for EV application

Electric Vehicles make use of permanent magnet synchronous traction motors for their high torque density and efficiency. A comparison between interior permanent magnet (IPM) and surface mounted permanent magnet (SPM) motors is carried out, in terms of performance at given inverter ratings. A simplified analytical approach is proposed and its results are confirmed by actual motor design, validated through FEA. The main result of the proposed analysis is to put in evidence the different behavior of IPM and SPM motors in terms of overload capability: as expected, the overload current results in a power overload of the IPM motor, while in the SPM motor the maximum power is upper limited irrespectively of the current overload.
Explaining consumer satisfaction of services: The role of innovativeness and emotion in an electronic mediated environment

a r t i c l e i n f o The services section has started to dominate economic activity in many industrialized economies since the last decade. The growth of services in Electronic Mediated Environment (EME) has changed the manner in which firms and consumers interact. Drawing on such theoretical foundations as trust, risk perceptions, trying, emotion, and satisfaction, this study proposes an integrative research model to investigate the relationships among these constructs in the EME context. We collected data from 415 consumers and found that consumer innovativeness and emotion are significant antecedents of trust, risk perception of service, perceived benefits, and service quality. These important factors will influence consumer satisfaction in EME. This empirical investigation breaks a new ground for future studies to understand and gauge the influence of innovativeness and emotion in emerging IT artifacts such as EME services. The service sector has become quantitatively the most essential sector in the world economy over the last decade. It now leads economic activities in a wide variety of industrialized economies. According to CIA World Factbook [14], the service industry accounted for 76.8% and 73.1% of the U.S. and European Union gross domestic product in 2011, respectively. Concurrently, there are more service companies on the list of Future 500 companies than before. Given the precipitously growing rate of the service section, technologically empowered advancements of information technology (IT) and the ever developing Internet are constantly galvanizing today's organizations to more effectively and efficiently coordinate with their constituents via the value-added electronic services (e-services) conduit. Furthermore, the mushrooming growth of e-commerce reflects the increasingly paramount role of IT in e-services while IT spurs the influx of e-service economy across the Internet. It is apparent that Information Systems (IS) plays a crucial role in EME because contemporary organizations have to leverage IT to improve business performance and assist the communication and service delivery amid various value-chain constituents. Consumers play a focal role in the paradigmatic change from the exchange of goods towards a service-centered model of exchange as found in both IS and marketing literature [73]. In this study, the conceptual definition of services in EME is based on Dai and Salam [19] and thereafter refers to the " services being facilitated by IT where the consumer interacts with a proper user interface including web site, mobile phone, social media, virtual world environment, tablets, etc., so as to gain a consumption …
An extension of the GQM+Strategies approach with formal causal reasoning

Context: Successful organizations need to manage and synchronize their strategic objectives with daily operations and activities. In general, achieving that requires a continuous process of organizational alignment. GQM + Strategies is an approach that helps software organizations with documenting and aligning organizational goals and strategies, and developing measurement programs. Objective: In this paper, the GQM + Strategies approach is further evolved and extended to include capabilities to evaluate the relationships of organizational goals and strategies through causal analysis. Method: We used an analytical paradigm to develop a formal causal model over the GQM + Strategies structure. In addition, an empirical pre-experimental study was designed to test practitioners’ abilities to provide necessary input for the formal causal model. Results: A developed formal causal model over the GQM + Strategies structure allows the use of causal reasoning for the purpose of analyzing dependencies among chosen sets of goals. We illustrate this by showing how to analyze the impact of risky goals on other goals in the grid. The results of the empirical study showed that the practitioners had no difficulties providing their predictions, i.e. inputs into the causal model. Conclusion: The proposed solution extends the existing GQM + Strategies knowledge base by further elaborating and clarifying the process of creating grids by introducing causality theory. The use of causality theory allows experts to quantify their knowledge and beliefs regarding the effectiveness of organizational strategies. As a part of future work, formal causal models and causal reasoning can be implemented as a supporting software tool for the GQM + Strategies approach. © 2017 Elsevier B.V. All rights reserved.
Eye images increase generosity , but not for long : the limited effect of a false cue

⁎ Corresponding author. E-mail address: asparks@uoguelph.ca (A. Sparks). 1090-5138/$ – see front matter © 2013 Elsevier Inc. Al http://dx.doi.org/10.1016/j.evolhumbehav.2013.05.001 Article history: Initial receipt 5 November 2012 Final revision received 3 May 2013
OpenStreetMap: User-Generated Street Maps

The OpenStreetMap project is a knowledge collective that provides user-generated street maps. OSM follows the peer production model that created Wikipedia; its aim is to create a set of map data that's free to use, editable, and licensed under new copyright schemes. A considerable number of contributors edit the world map collaboratively using the OSM technical infrastructure, and a core group, estimated at approximately 40 volunteers, dedicate their time to creating and improving OSM's infrastructure, including maintaining the server, writing the core software that handles the transactions with the server, and creating cartographical outputs. There's also a growing community of software developers who develop software tools to make OSM data available for further use across different application domains, software platforms, and hardware devices. The OSM project's hub is the main OSM Web site.
Hypertrophy of labia minora: experience with 163 reductions.

OBJECTIVE
Our purpose was to describe the surgical procedure, its results, and its complications and to determine whether patients are satisfied with surgical reduction of labia minora in cases of hypertrophy.


STUDY DESIGN
The records of 163 patients who underwent reduction of the labia minora during a 9-year period were reviewed. The ages of the patients ranged from 12 to 67 years (median, 26). Motives for requesting surgery were aesthetic concerns in 87% of the cases, discomfort in clothing in 64%, discomfort with exercise in 26%, and entry dyspareunia in 43%. Anatomic results were assessed 1 month postoperatively. Patient satisfaction was assessed by means of a mailed questionnaire.


RESULTS
No surgery-related significant complications were noticed. Anatomic results were satisfactory for 151 patients (93%). Ninety-eight completed questionnaires were returned. Eighty-one patients (83%) found that the results after surgery were satisfactory. Eighty-seven (89%) were satisfied with the aesthetic result, and 91 (93%) approved the functional outcome. Four patients (4%) would not undergo the same procedure again.


CONCLUSION
Labia minora reduction is a simple surgical procedure associated with a high degree of patient satisfaction.
DESC: enabling secure data exchange based on smart contracts

Dear editor, As data are one of the most important factors of today’s intelligent systems but are relatively scarce, people try exchanging data with other organizations or public marketplaces. However, data exchange is now lack of a secure execution mechanism to automatically and fairly protect the rights which are seriously concerned by data owners. For instance, data owners cannot limit the identity of a data transferee who is banned to take the data by any way. Moreover, data transferees are also afraid that their applications for exchange may be unfairly treated. For instance, data owners could dynamically change data price when multiple transferees submit their applications at the same time. A data marketplace can take over the role of a trusted third party during data exchange, but single point failure is always a serious problem in a large-scale distributed system. Furthermore, these marketplaces usually use contracts based on natural languages which may be maliciously misinterpreted and cannot be automatically executed. Numerous researches have been presented to provide digital rights management (DRM) [1]. For instance, Zhu et al. [2] presented a privacypreserving video subscription scheme with the limitation of expire date. However, rights of data owners are more complex than rights of digital content owners. Decentralized and trustworthy enforcement for access control policies is a long-term issue. Han et al. [3] proposed an optimized mechanism which is a trusted and decentralized access control framework for the client/server architecture. These studies still need third party authorities which are used to execute or supervise the rights control, leading to a few trust and security issues. Existing studies [4] on attribute-based access control have been applied to many fields, such as e-commerce and Internet of Things. This article introduces attribute-based access control and proposes a secure framework for data exchange based on smart contracts (DESC) to enable automatic and fair access control. Featuring with decentralized, fair, transparent, immutable and traceable advantages, blockchain 2.0 [5] provides a generalized framework for implementing decentralized compute resources named smart contracts which define rights and policies in mathematical and programming forms. Once the predefined smart contract is triggered by a transaction, it can automatically execute the specific contractual clauses. To find out which data rights are seriously concerned by data owners, we investigate the DRM mechanisms and several data exchange platforms: GBDEX, national engineering lab for big data distribution and exchange technologies. Then,
A vision-based method for weeds identification through the Bayesian decision theory

One of the objectives of precision agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. This paper outlines an automatic computer vision-based approach for the detection and differential spraying of weeds in corn crops. The method is designed for post-emergence herbicide applications where weeds and corn plants display similar spectral signatures and the weeds appear irregularly distributed within the crop’s field. The proposed strategy involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based measuring relationships between crop and weeds. The decision making determines the cells to be sprayed based on the computation of a posterior probability under a Bayesian framework. The a priori probability in this framework is computed taking into account the dynamic of the physical system (tractor) where the method is embedded. The main contributions of this paper are: (1) the combination of the image segmentation and decision making processes and (2) the decision making itself which exploits a previous knowledge which is mapped as the a priori probability. The performance of the method is illustrated by comparative analysis against some existing strategies. 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
HD Maps: Fine-Grained Road Segmentation by Parsing Ground and Aerial Images

In this paper we present an approach to enhance existing maps with fine grained segmentation categories such as parking spots and sidewalk, as well as the number and location of road lanes. Towards this goal, we propose an efficient approach that is able to estimate these fine grained categories by doing joint inference over both, monocular aerial imagery, as well as ground images taken from a stereo camera pair mounted on top of a car. Important to this is reasoning about the alignment between the two types of imagery, as even when the measurements are taken with sophisticated GPS+IMU systems, this alignment is not sufficiently accurate. We demonstrate the effectiveness of our approach on a new dataset which enhances KITTI [8] with aerial images taken with a camera mounted on an airplane and flying around the city of Karlsruhe, Germany.
Distance Transforms of Sampled Functions

We describe linear-time algorithms for solving a class of problems that involve transforming a cost function on a grid using spatial information. These problems can be viewed as a generalization of classical distance transforms of binary images, where the binary image is replaced by an arbitrary function on a grid. Alternatively they can be viewed in terms of the minimum convolution of two functions, which is an important operation in grayscale morphology. A consequence of our techniques is a simple and fast method for computing the Euclidean distance transform of a binary image. Our algorithms are also applicable to Viterbi decoding, belief propagation, and optimal control. ACM Classification: F.2.1, I.4 AMS Classification: 68T45, 68W40
DENSER Cities: A System for Dense Efficient Reconstructions of Cities

This paper is about the efficient generation of dense, colored models of city-scale environments from range data and in particular, stereo cameras. Better maps make for better understanding; better understanding leads to better robots, but this comes at a cost. The computational and memory requirements of large dense models can be prohibitive. We provide the theory and the system needed to create cityscale dense reconstructions. To do so, we apply a regularizer over a compressed 3D data structure while dealing with the complex boundary conditions this induces during the data-fusion stage. We show that only with these considerations can we swiftly create neat, large, “well behaved” reconstructions. We evaluate our system using the KITTI dataset and provide statistics for the metric errors in all surfaces created compared to those measured with 3D laser. Our regularizer reduces the median error by 40% in 3.4 km of dense reconstructions with a median accuracy of 6 cm. For subjective analysis, we provide a qualitative review of 6.1 km of our dense reconstructions in an attached video. These are the largest dense reconstructions from a single passive camera we are aware of in the literature. Video: https://youtu.be/FRmF7mH86EQ
Fusion of IMU and Vision for Absolute Scale Estimation in Monocular SLAM

The fusion of inertial and visual data is widely used to improve an object’s pose estimation. However, this type of fusion is rarely used to estimate further unknowns in the visual framework. In this paper we present and compare two different approaches to estimate the unknown scale parameter in a monocular SLAM framework. Directly linked to the scale is the estimation of the object’s absolute velocity and position in 3D. The first approach is a spline fitting task adapted from Jung and Taylor and the second is an extended Kalman filter. Both methods have been simulated offline on arbitrary camera paths to analyze their behavior and the quality of the resulting scale estimation. We then embedded an online multi rate extended Kalman filter in the Parallel Tracking and Mapping (PTAM) algorithm of Klein and Murray together with an inertial sensor. In this inertial / monocular SLAM framework, we show a real time, robust and fast converging scale estimation. Our approach does not depend on known patterns in the vision part nor a complex temporal synchronization between the visual and inertial sensor. The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n. 231855 (sFly). Gabriel Nützi is currently a Master student at the ETH Zurich. Stephan Weiss is currently PhD student at the ETH Zurich. Davide Scaramuzza is currently senior researcher and team leader at the ETH Zurich. Roland Siegwart is full professor at the ETH Zurich and head of the Autonomous Systems Lab. G. Nützi · S. Weiss · D. Scaramuzza · R. Siegwart ETH Autonomous Systems Laboratory, 8092, Zurich, Switzerland, www.asl.ethz.ch E-mail: nuetzi@student.ethz.ch, stephan.weiss@mavt.ethz.ch, davide.scaramuzza@ieee.org, rsiegwart@ethz.ch 2
Emotion detection in suicide notes

0957-4174/$ see front matter 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.eswa.2013.05.050 ⇑ Corresponding author at: LT3 Language and Translation Technology Team, University College Ghent, Groot-Brittanniëlaan 45, 9000 Ghent, Belgium. Tel.: +32 9 224 97 53. E-mail addresses: bart.desmet@hogent.be (B. Desmet), veronique.hoste@ hogent.be (V. Hoste). Bart Desmet a,b,⇑, Véronique Hoste a,c