nils-herrmann/clean_scirepeval huggingface dataset:
Can you get emotional support through a screen? A look into digital and in person emotional support and emotion regulation
Venue: Inquiry@Queen's Undergraduate Research Conference Proceedings
Year: 2019

Social support is positively related to overall well being and relationship quality with others, and specifically, may help with successful emotion regulation (Himle, Jayaratne, Thyness, 2008; Liang, Ho, Li, Turban, 2014; Strine, Chapman, Balluz, Mokdad, 2008; Thoits, 2011) With the rapid increase in the use of information and communication technologies (ICT) much social support is now sought and received digitally rather than in person, which involves different methods of interacting with others. The current study examines the indirect effects of seeking and receiving social support both digitally and in person on the relationship between emotion intensity and emotion regulation success. Two hundred participants were recruited from the Queen's University psychology participant pool. Participants were prompted through a smart phone experience sampling app three times a day for two weeks to answer questions about their emotions and social support. We predict that emotion intensity will be related to lower emotion regulation success but more seeking and receiving social support. We also predict that seeking and receiving social support will be related to each other and that they will both be related to higher emotion regulation success. Additionally, it is expected that seeking and receiving emotional support in person and digitally will be part of two indirect pathways from emotion intensity and emotion regulation success. The current study will provide information on whether digital emotional support has equivalent beneficial effects on emotion regulation as in person emotional support, which could inform targets for future emotion regulation interventions.
RfD Net: Point Scene Understanding by Semantic Instance Reconstruction
Venue: CVPR
Year: 2021

Semantic scene understanding from point clouds is particularly challenging as the points reflect only a sparse set of the underlying 3D geometry. Previous works often convert point cloud into regular grids (e.g. voxels or bird eye view images) and resort to grid based convolutions for scene understanding. In this work, we introduce RfD Net that jointly detects and reconstructs dense object surfaces directly from raw point clouds. Instead of representing scenes with regular grids, our method leverages the sparsity of point cloud data and focuses on predicting shapes that are recognized with high objectness. With this design, we decouple the instance reconstruction into global object localization and local shape prediction. It not only eases the difficulty of learning 2 D manifold surfaces from sparse 3D space, the point clouds in each object proposal convey shape details that support implicit function learning to reconstruct any high resolution surfaces. Our experiments indicate that instance detection and reconstruction present complementary effects, where the shape prediction head shows consistent effects on improving object detection with modern 3D proposal network backbones. The qualitative and quantitative evaluations further demonstrate that our approach consistently outperforms the state of the arts and improves over 11 of mesh IoU in object reconstruction.
Evaluation Model for the Implementation of Information Technology Service Management using Fuzzy ITIL
Year: 2019

Information technology (IT) service management is an essential part for development of a company's IT. This case study discusses how to convalesce IT services using the information technology infrastructure library (ITIL) framework and measure service level management (SLM) using Fuzzy ITIL (FITIL) approach. This paper aims to obtain an appropriate model for the measurement of IT service management by using fuzzy approach. Besides that, this paper aims to be able to provide an improving recommendations and IT governance based on current value (as is) and expected value (to be) The research method functioned is by measuring maturity level using best practice of ITIL v3 to condition before and after of improving process based on a questionnaire that has been performed. After obtaining the value of the maturity level for each cycle within ITIL, then the value will be created as an input for FITIL. The manufacture of FITIL is done in 4 stages, namely fuzzification, knowledge base, inference, and defuzzification. The results of the conditions before and after of the improving process have been successful in increasing the level of maturity in each ITIL cycle. The case study indicates an improvement in the increased level of maturity in SLM with FITIL approach.
Observation of nonlinear dynamics in an optical levitation system
Venue: Communications Physics
Year: 2020

Optical levitation of mechanical oscillators has been suggested as a promising way to decouple the environmental noise and increase the mechanical quality factor. Here, we investigate the dynamics of a free standing mirror acting as the top reflector of a vertical optical cavity, designed as a testbed for a tripod cavity optical levitation setup. To reach the regime of levitation for a milligram scale mirror, the optical intensity of the intracavity optical field approaches 3 MW cm 2. We identify three distinct optomechanical effects: excitation of acoustic vibrations, expansion due to photothermal absorption, and partial lift off of the mirror due to radiation pressure force. These effects are intercoupled via the intracavity optical field and induce complex system dynamics inclusive of high order sideband generation, optical bistability, parametric amplification, and the optical spring effect. We modify the response of the mirror with active feedback control to improve the overall stability of the system.
Surgical approaches for open reduction and internal fixation of intra articular distal humerus fractures in adults: A systematic review and meta analysis.
Venue: Injury
Year: 2018

A number of surgical approaches have been described for open reduction and internal fixation (ORIF) of intra articular distal humerus (IDH) fractures in adults. However, there is no consensus as to which approach is better in terms of functional outcomes and complications. The purpose of this study was to determine whether the functional outcomes and types and rates of complications are influenced by the choice of surgical approach for ORIF of IDH fractures (AO/OTA types 13 B C)  A systematic review of literature was performed using the PubMed, EMBASE and Cochrane Database of Systematic Reviews databases. Studies, both prospective and retrospective and comparative or non comparative, dealing with surgical approaches for ORIF of IDH fractures in adult patients were included. Conference abstracts, studies looking primarily at the results of internal fixation rather than the surgical approach, those including extra articular distal humeral fractures, pediatric distal humeral fractures <18 years of age) delayed unions, non unions, malunions, cadaveric studies, pathological fractures and studies with <10 patients were excluded. Studies that looked at surgical modalities other than internal fixation (for e.g. total elbow arthroplasty) for intra articular distal humerus fractures or those that did not report a validated functional outcome scoring system were also excluded.  studies were included in the qualitative analysis, of which 5 were comparative studies and 6 were non comparative. Quantitative analysis was performed on two sets of two studies, each set comparing the Bryan and Morrey or the triceps split approach to the olecranon osteotomy approach, and revealed no significant differences in the Mayo Elbow Performance Score, range of motion and rates of complications. The overall methodological quality of the studies included in the review was low.  High quality evidence on surgical approaches for ORIF of IDH fractures in adults is lacking. Evidence from low quality studies indicates that there is no difference in the functional outcomes or complication rates when comparing the Bryan and Morrey or triceps split to the olecranon osteotomy approach. Future research in the form of high quality randomized controlled trials is needed to determine which approach is superior in terms of functional outcomes and complications.
Effect of Nurse Home Visits vs. Usual Care on Reducing Intimate Partner Violence in Young High Risk Pregnant Women: A Randomized Controlled Trial
Venue: PloS one
Year: 2013

Expectant mothers and mothers of young children are especially vulnerable to intimate partner violence (IPV) The nurse family partnership (NFP) is a home visitation program in the United States effective for the prevention of adverse child health outcomes. Evidence regarding the effect of nurse home visiting on IPV is inconsistent. This study aims to study the effect of VoorZorg, the Dutch NFP, on IPV.  A random sample of 460 eligible disadvantaged women <26 years, with no previous live births, was randomized. Women in the control group (C; n=223) received usual care; women in the intervention group (I; n=237) received usual care plus nurse home visits periodically during pregnancy and until the child's second birthday.  At 32 weeks of pregnancy, women in the intervention group self reported significantly less IPV victimization than women in the control group in: level 2 psychological aggression (C: 56% vs. I: 39% physical assault level 1 (C: 58% vs. I: 40% and level 2  2 psychological aggression (C: 60% vs. I: 46% level 1 physical assault (C: 65% vs. I: 52% and level 1 injury (C: 27% vs. I: 17% At 24 months after birth, IPV victimization was significantly lower in the intervention group for level 1 physical assault (C: 44% vs. I: 26% and IPV perpetration was significantly lower for level 1 sexual assault (C: 18% vs. I: 3% Multilevel analyses showed a significant improvement in IPV victimization and perpetration among women in the intervention group at 24 months after birth. , compared with the usual care, is effective in reducing IPV during pregnancy and in the two years after birth among young high risk women.
Determining the edge of potential field data using Normalized enhanced analytical signal of different orders
Year: 2019

Detecting the edge plays a substantial role in explaining the data of the potential field. One of the most common methods for detecting the edge is the use of analytical signal. The interference of the anomalies adjacent sources ensues the limiting of the use of analytic signal in detecting the border of the masses. In order to overcome this problem, have been used the enhanced analytical signals, but this method cannot display the edges of anomalies with strong and weak domains simultaneously. In the present study, has been used the enhanced analytical signal of different orders that the filters, introduced by Yao et al. (2015) have been investigated. For this purpose, the new edge detector filter has been introduced as Normalization Analytic Signal (NAS) Then the Normalized Second Order Enhanced Analytic Signal (NSAS) and Modified Normalized Third Order Enhanced Analytic Signal (MNTAS) have been introduced respectively. Also, the diagrams have been drawn using Oasis Montaj 6.4.2 software. Moreover, this method has been applied to artificial data from various synthetic models to assess the accuracy and efficiency of the mentioned filters. The modified of the Tilt angle of the Total Horizontal Gradient (TAHG) filters have been used for comparing and evaluating the proposed method with others. In order to verify, having applied the introduced filters to synthetic data, these filters have been used to interpret ground magnetic data which has been collected in Maki in the region of Kashmar.
Interactive distributed cloud based web server systems for the smart healthcare industry
Venue: ArXiv
Year: 2020

The work aims to investigate the possible contemporary interactive cloud based solutions in the fields of the applied medicine for the smart Healthcare as the data visualization open source free system distributed under the MIT license. A comparative study of a number of the well known implementations of the Ray Casting algorithms was studied. A new method of numerical calculus is proposed for calculating the volume the method of spheres, as well as a proposal for paralleling the algorithm on graphic accelerators in a linearly homogeneous computing environment using the block decomposition methods. For the artifacts control algorithm of the cubic interpolation was used. The cloud server architecture was proposed.
Open Ended Long Form Video Question Answering via Hierarchical Convolutional Self Attention Networks
Venue: IJCAI
Year: 2019

Open ended video question answering aims to automatically generate the natural language answer from referenced video contents according to the given question. Currently, most existing approaches focus on short form video question answering with multi modal recurrent encoder decoder networks. Although these works have achieved promising performance, they may still be ineffectively applied to long form video question answering due to the lack of long range dependency modeling and the suffering from the heavy computational cost. To tackle these problems, we propose a fast hierarchical convolutional self attention encoder decoder network. Concretely, we first develop a hierarchical convolutional self attention encoder to efficiently model long form video contents, which builds the hierarchical structure for video sequences and captures question aware long range dependencies from video context. We then devise a multi scale attentive decoder to incorporate multi layer video representations for answer generation, which avoids the information missing of the top encoder layer. The extensive experiments show the effectiveness and efficiency of our method.
Two Lattice Based Differential Fault Attacks Against ECDSA with wNAF Algorithm
Venue: ICISC
Year: 2015

Elliptic curve cryptosystem (ECC) is widely used in cryptographic device. Despite its solid mathematical security, ECC is still vulnerable to many kinds of physical attacks. In this paper, we present two new lattice based differential fault attacks (DFA) against the famous ECC signature algorithm standard ECDSA with wNAF algorithm of scalar multiplication. Compared with the fault attack proposed in Crypto'2000, our first attack adopts a different way to deduce parts of the nonce k. The former recovered parts of k mainly by guessing technique, while our attack combines the guessing technique and solving equation with one unknown. So our attack is applicable for the weaker attack scenes allowing more random faulty bits. In our second proposed attack, instead of injecting faults during calculating kG, we focus on injecting faults during calculating wNAF transformation of k before calculating kG. If the targets during wNAF transformation of k are skipped by fault injection, we can build some DFA models to retrieve parts of k. In both of the two attacks, the attacker can mount lattice attack to recover the private key in ECDSA with the derived parts of k. Finally, we verify the feasibility of our proposed attacks by experiments.
The use of technical analysis by fund managers: International evidence
Year: 2010

The use of technical analysis by financial market professionals is not well understood. This paper thus analyzes survey evidence from 692 fund managers in five countries, the vast majority of whom rely on technical analysis. At a forecasting horizon of weeks, technical analysis is the most important form of analysis and up to this horizon it is thus more important than fundamental analysis. Technicians are as experienced, as educated, as successful in their career and largely just as overconfident in decision making as others. However, technical analysis is somewhat more popular in smaller asset management firms. What we find most significant is the relation of technical analysis with the view that prices are heavily determined by psychological influences. Consequently, technicians apply trend following behavior.
Synthesis of an emerging morpholine typed Gemini surfactant and its application in reverse flotation carnallite ore for production of potash fertilizer at low temperature
Year: 2020

Carnallite is a kind of high quality source of raw material for the production of potash fertilizer (KCl) in industry. However, how to produce potash fertilizer sustainably at low temperature has always been a problem. In this work, we synthesized an emerging morpholine typed Gemini surfactant, butanediyl a, o bis (morpholino dodeculammonium bromide) (BM) which can be used to collect NaCl in reverse flotation carnallite ores in a low temperature environment. We compared its ability to collect NaCl and carnallite with the monomeric surfactant 4 laurylmorpholine (LM) at low temperatures. The flotation test results indicated that BM has a stronger collecting ability for NaCl than that of conventional LM collector. At room temperature (25 degC) BM exhibits a forceful collecting function to NaCl and preeminent selectivity for carnallite. The recovery of NaCl ran up to 98.0% when the concentration of BM was 1 x 10 5 mol/L. Under the same condition, the flotation recovery using LM was only 39.0% The recoveries of carnallite of the two were not more than 3.5% When the environment temperature descended, the effect of BM for NaCl exhibited a stronger stable trend. The recovery with BM as a collector raised notably from 68.0% to 96.5% with temperature ranging from 0 degC to 15 degC. However, in the same scope of dosage and temperature, the recovery with LM collector only raised from 3.5% to 31.5% At 0 degC, LM lost the vast majority of its collector performance, while BM still showed high performance.
Hierarchical Gating Networks for Sequential Recommendation
Venue: KDD
Year: 2019

The chronological order of user item interactions is a key feature in many recommender systems, where the items that users will interact may largely depend on those items that users just accessed recently. However, with the tremendous increase of users and items, sequential recommender systems still face several challenging problems: (1) the hardness of modeling the long term user interests from sparse implicit feedback; (2) the difficulty of capturing the short term user interests given several items the user just accessed. To cope with these challenges, we propose a hierarchical gating network (HGN) integrated with the Bayesian Personalized Ranking (BPR) to capture both the long term and short term user interests. Our HGN consists of a feature gating module, an instance gating module, and an item item product module. In particular, our feature gating and instance gating modules select what item features can be passed to the downstream layers from the feature and instance levels, respectively. Our item item product module explicitly captures the item relations between the items that users accessed in the past and those items users will access in the future. We extensively evaluate our model with several state of the art methods and different validation metrics on five real world datasets. The experimental results demonstrate the effectiveness of our model on Top N sequential recommendation.
Entrapment allegations in right wing terrorism cases: A mixed methods analysis
Year: 2018

Entrapment allegations have been widespread in post 9/11 US terrorism prosecutions, but existing research focuses almost exclusively on neojihadi and left wing prosecutions. It is thus unclear whether entrapment is also prevalent in right wing terrorism cases. This article employs a mixed method approach to analyze entrapment claims in right wing terrorism cases. Quantitative analyses of a database of post 9/11 terrorism prosecutions show that right wing cases have significantly fewer entrapment indicators than neojihadi and left wing terrorism cases, and are far less likely to have particularly high entrapment scores. Detailed qualitative analyses of five right wing terrorism investigations reveal that four cases feature potentially strong entrapment claims. However, a comparative analysis finds that these claims are significantly weaker than those in many neojihadi and left wing cases. We theorize that micro meso and macro level mechanisms enabled the occasional emergence, but far lower prevalence and strength, of viable entrapment claims in right wing terrorism investigations.
Analyzing China's OFDI using a novel multivariate grey prediction model with Fourier series
Venue: Int. J. Intell. Comput. Cybern.
Year: 2019

With the development of economy, China's OFDI constantly increase in recent year. Meanwhile, OFDI has spillover effect on economic development and technological development of home country. Thus, accurate OFDI prediction is a prerequisite for the effective development of international investment strategies. The purpose of this paper is to predict China's OFDI accurately using a novel multivariable grey prediction model with Fourier series.  This paper applied a multivariable grey prediction model, GM(1,N) to forecast China's OFDI. In order to improve the prediction accuracy and without changing local characteristics of grey model prediction, this paper proposed a novel grey prediction model to improve the performance of the traditional GM(1,N) model by combining with residual modification model using GM(1,1) model and Fourier series.  The coefficients indicate that the export and GDP have positive influence on China's OFDI, and, according to the prediction result, China's OFDI shows a growing trend in next five years.  This paper proposed an effective multivariable grey prediction model that combined the traditional GM(1,N) model with a residual modification model in order to predict China's OFDI. Accurate forecasting of OFDI provides reference for the Chinese Government to implement international investment strategies.
Real time Accurate Surface Reconstruction Pipeline for Vision Guided Planetary Exploration Using Unmanned Ground and Aerial Vehicles
Year: 2012

This report discusses work completed over the summer at the Jet Propulsion Laboratory (JPL) California Institute of Technology. A system is presented to guide ground or aerial unmanned robots using computer vision. The system performs accurate camera calibration, camera pose refinement and surface extraction from images collected by a camera mounted on the vehicle. The application motivating the research is planetary exploration and the vehicles are typically rovers or unmanned aerial vehicles. The information extracted from imagery is used primarily for navigation, as robot location is the same as the camera location and the surfaces represent the terrain that rovers traverse. The processed information must be very accurate and acquired very fast in order to be useful in practice. The main challenge being addressed by this project is to achieve high estimation accuracy and high computation speed simultaneously, a difficult task due to many technical reasons.