nils-herrmann/clean_scirepeval huggingface dataset:
Location Aware Predictive Beamforming for UAV Communications: A Deep Learning Approach
Venue: IEEE Wireless Communications Letters
Year: 2021

The cellular connected unmanned aerial vehicle (UAV) communication becomes a promising technique to realize the beyond fifth generation (5G) wireless networks, due to the high mobility and maneuverability of UAVs which can adapt to heterogeneous requirements of different applications. However, the movement of UAVs impose a unique challenge for accurate beam alignment between the UAV and the ground base station (BS) In this letter, we propose a deep learning based location aware predictive beamforming scheme to track the beam for UAV communications in a dynamic scenario. Specifically, a long short term memory (LSTM) based recurrent neural network (LRNet) is designed for UAV location prediction. Based on the predicted location, a predicted angle between the UAV and the BS can be determined for effective and fast beam alignment in the next time slot, which enables reliable communications between the UAV and the BS. Simulation results demonstrate that the proposed scheme can achieve a satisfactory UAV to BS communication rate, which is close to the upper bound of communication rate obtained by the perfect genie aided alignment scheme.
Tunable resistive pulse sensing (TRPS)
Year: 2020

TRPS is an experimental technique of growing popularity that has been used to measure a range of synthetic and biological colloidal particles, including drug delivery particles, DNA, viruses, and bacteria, among other analytes. Based upon the Coulter method for counting particles, TRPS has the unique capability of measuring a wide range of particles, from ca. 40 nm up to the size of cells, finding numerous applications in nanomedicine and biotechnology. The primary aim of this chapter is to provide a guide that focuses on the use of TRPS technology for particle characterization together with some trouble shooting methods. General TRPS protocols to determine particle size, size distribution, z potential, and concentration are included, and selected comparison studies of TRPS technology with other associated analytical techniques are also presented here.
Simpson's paradox in psychological science: a practical guide
Venue: Front. Psychol.
Year: 2013

The direction of an association at the population level may be reversed within the subgroups comprising that population a striking observation called Simpson's paradox. When facing this pattern, psychologists often view it as anomalous. Here, we argue that Simpson's paradox is more common than conventionally thought, and typically results in incorrect interpretations potentially with harmful consequences. We support this claim by reviewing results from cognitive neuroscience, behavior genetics, clinical psychology, personality psychology, educational psychology, intelligence research, and simulation studies. We show that Simpson's paradox is most likely to occur when inferences are drawn across different levels of explanation (e.g. from populations to subgroups, or subgroups to individuals) We propose a set of statistical markers indicative of the paradox, and offer psychometric solutions for dealing with the paradox when encountered including a toolbox in R for detecting Simpson's paradox. We show that explicit modeling of situations in which the paradox might occur not only prevents incorrect interpretations of data, but also results in a deeper understanding of what data tell us about the world.
Community evolution mining and analysis in social network
Year: 2017

With the development of digital and network technology, various social platforms emerge. These social platforms have greatly facilitated access to information, attracting more and more users. They use these social platforms every day to work, study and communicate, so every moment social platforms are generating massive amounts of data. These data can often be modeled as complex networks, making large scale social network analysis possible. In this paper, the existing evolution classification model of community has been improved based on community evolution relationship over time in dynamic social network, and the Evolution Tree structure is proposed which can show the whole life cycle of the community more clearly. The comparative test result shows that the improved model can excavate the evolution relationship of the community well.
Secrecy Rate Optimizations for a MIMO Secrecy Channel With a Cooperative Jammer
Venue: IEEE Transactions on Vehicular Technology
Year: 2015

In this paper, we study different secrecy rate optimization techniques for a multiple input multiple output (MIMO) secrecy channel, where a multiantenna cooperative jammer is employed to improve secret communication in the presence of a multiantenna eavesdropper. Specifically, we consider two optimization problems, namely, power minimization and secrecy rate maximization. These problems are not jointly convex in terms of the transmit covariance matrices of the legitimate transmitter and the cooperative jammer. To circumvent these nonconvexity issues, we alternatively design the transmit covariance matrix of the legitimate transmitter and the cooperative jammer. For a given transmit covariance matrix at the cooperative jammer, we solve the power minimization and secrecy rate maximization problems based on a Taylor series expansion. Then, we propose two iterative algorithms to solve these approximated problems. In addition, we develop a robust scheme by incorporating channel uncertainties associated with the eavesdropper. By exploiting S Procedure, we show that these robust optimization problems can be formulated into semidefinite programming. Moreover, we consider the secrecy rate maximization problem based on game theory, where the jammer introduces charges for its jamming service based on the amount of the interference caused to the eavesdropper. This secrecy rate maximization problem is formulated into a Stackelberg game where the jammer and the transmitter are the leader and the follower of the game, respectively. For the proposed game, Stackelberg equilibrium is analytically derived. Simulation results have been provided to validate the convergence and performance of the proposed algorithms. In addition, it is shown that the proposed robust scheme outperforms the nonrobust scheme in terms of the achieved secrecy rate and the worst case secrecy rate. Finally, the Stackelberg equilibrium solution has been validated through numerical results.
Binary Classification from Positive Confidence Data
Venue: NeurIPS
Year: 2018

Can we learn a binary classifier from only positive data, without any negative data or unlabeled data? We show that if one can equip positive data with confidence (positive confidence) one can successfully learn a binary classifier, which we name positive confidence (Pconf) classification. Our work is related to one class classification which is aimed at "describing" the positive class by clustering related methods, but one class classification does not have the ability to tune hyper parameters and their aim is not on "discriminating" positive and negative classes. For the Pconf classification problem, we provide a simple empirical risk minimization framework that is model independent and optimization independent. We theoretically establish the consistency and an estimation error bound, and demonstrate the usefulness of the proposed method for training deep neural networks through experiments.
Long time series analysis of urban development based on effective building extraction
Venue: Defense Commercial Sensing
Year: 2020

The effective detection of urban development is the basis of understanding urban sustainability. Although various studies concentrated on long time series analysis on urban development, the resolution of images was too low to focus on a single object. In this paper, we provide a long time series analysis of built up areas at an annual frequency in Beijing, China, from 2000 to 2015, based on the automatic building extraction and high resolution satellite images. We propose a deeplearning based method to extract buildings, and employ an ensemble learning method to improve the localization of boundaries. The time series results of built up areas are analyzed based on two schemes, i.e. change detection over the past fifteen years and evaluation of the whole region in three selected years. Our proposed method achieves an average overall accuracy (OA) of 93% The results reveal that Beijing developed more rapidly during 2001 2008 than other periods in terms of the density and the number of buildings.
Global implementation of WHO's multimodal strategy for improvement of hand hygiene: a quasi experimental study.
Venue: The Lancet. Infectious diseases
Year: 2013

Health care associated infections are a major threat to patient safety worldwide. Transmission is mainly via the hands of health care workers, but compliance with recommendations is usually low and effective improvement strategies are needed. We assessed the effect of WHO's strategy for improvement of hand hygiene in five countries.  We did a quasi experimental study between December, 2006, and December, 2008, at six pilot sites (55 departments in 43 hospitals) in Costa Rica, Italy, Mali, Pakistan, and Saudi Arabia. A step wise approach in four 3 6 month phases was used to implement WHO's strategy and we assessed the hand hygiene compliance of health care workers and their knowledge, by questionnaire, of microbial transmission and hand hygiene principles. We expressed compliance as the proportion of predefined opportunities met by hand hygiene actions (ie, handwashing or hand rubbing) We assessed long term sustainability of core strategy activities in April, 2010.  We noted 21,884 hand hygiene opportunities during 1423 sessions before the intervention and 23,746 opportunities during 1784 sessions after. Overall compliance increased from 51.0% before the intervention (95% CI 45.1 56.9) to 67.2% after (61.8 72.2) Compliance was independently associated with gross national income per head, with a greater effect of the intervention in low income and middle income countries (odds ratio [OR] 4.67, 95% CI 3.16 6.89; p<0.0001) than in high income countries (2.19, 2.03 2.37; p<0.0001) Implementation had a major effect on compliance of health care workers across all sites after adjustment for main confounders (OR 2.15, 1.99 2.32) Health care workers' knowledge improved at all sites with an increase in the average score from 18.7 (95% CI 17.8 19.7) to 24.7 (23.7 25.6) after educational sessions. 2 years after the intervention, all sites reported ongoing hand hygiene activities with sustained or further improvement, including national scale up.  Implementation of WHO's hand hygiene strategy is feasible and sustainable across a range of settings in different countries and leads to significant compliance and knowledge improvement in health care workers, supporting recommendation for use worldwide.
Informationsasymmetri och maloverensstammelse vid implementering av ekonomistyrning En kvalitativ och kvantitativ studie pa Boliden Mineral AB
Year: 2019

Inom ekonomistyrning utgar ekonomer oftast fran att maloverensstammelse existerar och att de anstallda arbetar utifran de uppstallda malen med perfekt information. Men informationsasymmetri finns o
Deciphering interaction fingerprints from protein molecular surfaces
Year: 2019

Predicting interactions between proteins and other biomolecules purely based on structure is an unsolved problem in biology. A high level description of protein structure, the molecular surface, displays patterns of chemical and geometric features that fingerprint a protein's modes of interactions with other biomolecules. We hypothesize that proteins performing similar interactions may share common fingerprints, independent of their evolutionary history. Fingerprints may be difficult to grasp by visual analysis but could be learned from large scale datasets. We present MaSIF, a conceptual framework based on a new geometric deep learning method to capture fingerprints that are important for specific biomolecular interactions. We showcase MaSIF with three prediction challenges: protein pocket ligand prediction, protein protein interaction site prediction, and ultrafast scanning of protein surfaces for prediction of protein protein complexes. We anticipate that our conceptual framework will lead to improvements in our understanding of protein function and design.
PENGARUH PERUBAHAN KEBIJAKAN TERHADAP PENGELOLAAN HUTAN JATI DI AFDEELING NGAWI 1897 1937
Year: 2019

Perubahan kebijakan yang dilakukan oleh negara memiliki dampak langsung terhadap kehidupan seluruh lapisan masyarakat. Perubahan tersebut berdampak langsung pada beberapa sektor baik ekonomi hingga sosial budaya. Salah satu kebijakan yang memiliki dampak besar adalah Boschreglement 1897 terhadap masyarakat desa hutan di Afdeeling Ngawi. Penelitian ini membahas mengenai dampak dari perubahan kebijakan kehutanan bagi kondisi hutan jati dan masyarakat desa hutan yang mendiaminya. Metodologi yang digunakan adalah metode penelitian sejarah. Teori Stompzka mengenai anomic condition menjadi landasan untuk menganalisis topik penelitian ini. Tujuan penelitian ini diharapkan mampu untuk menambah khasanah pemikiran mengenai sejarah lingkungan khususnya sejarah kehutanan di Indonesia. Kebijakan ini memunculkan kategori pencurian baru yakni pemanfaatan sumber daya hutan oleh masyarakat desa hutan tanpa seizin dari pemerintah kolonial Belanda. Perbedaan persepsi mengenai konsep kepemilikan hutan antara masyarakat desa hutan dengan pemerintah memunculkan konflik konflik vertikal. Pasca diberlakukannya kebijakan kehutanan 1897 masyarakat desa hutan memiliki keterbatasan akses terhadap ruang hidupnya. Pembaharuan undang undang ini juga membuka jalan bagi pihak pihak swasta (Tionghoa) untuk melakukan eksploitasi terhadap hutan jati Afdeeling Ngawi. Degradasi hutan secara besar besaran merupakan salah satu akibat dari berpindahnya kepemilikan hutan kepada swasta.
Perceived peer delinquency, proactive criminal thinking, neighborhood disorder, and serious offending: moderated mediation and theoretical integration
Year: 2020

This paper illustrates how theoretical integration in criminology might be achieved, in part, through the use of such research methodologies as mediation and moderation. Analyzing data from the first three waves of the National Youth Survey (N 1725, 53.2% male, mean age 13.87 years) the current study utilized a moderated mediation methodology to test whether neighborhood disorder moderates the peer influence effect. In this study, peer influence was defined as a mediated relationship running from peer delinquency (Peer) to proactive criminal thinking (PCT) to serious offending. The simple mediated relationship was evaluated first and found to be significant. Moderated mediation analysis then revealed that neighborhood disorder moderated the effect of peer delinquency on PCT (a path of the indirect effect) and of PCT on serious offending (b path of the indirect effect) Consistent with predictions, the a path interaction was negative and the b path interaction was positive, although the indirect effect was significant at all levels of neighborhood disorder. These findings indicate that neighborhood disorder may suppress, though not eliminate, the effect of delinquent peers on PCT, while enhancing the effect of PCT on serious offending.
Ableist Microaggressions and the Mental Health of Disabled Adults
Venue: Community Mental Health Journal
Year: 2020

Microaggressions perpetuate inequalities and stereotypes against people from marginalized communities. Research demonstrates that ongoing experiences of identity related microaggressions can negatively impact mental health outcomes, increase somatic symptoms, and increase negative affect. This study explores the relationship between experiences of ableist microaggressions and mental health outcomes among disabled adults by using a quantitative cross sectional survey of 311 U.S. adults who identify as disabled/having a disability, to examine the correlation between ableist microaggressions (using the AMS 65) and mental health (assessed by the MHI 18) Findings indicate that increased experiences ableist microaggressions are negatively correlated with positive mental health outcomes, and that the visibility of disabilities/impairments are correlated with experiencing ableist microaggressions. These findings can inform the work of counselors, therapists, social workers, and other human service professionals when supporting disabled individuals, recognizing that their mental health may be related to these common and often unintentional oppressive interactions.
Content Selection for Real time Sports News Construction from Commentary Texts
Venue: INLG
Year: 2017

We study the task of constructing sports news report automatically from live commentary and focus on content selection. Rather than receiving every piece of text of a sports match before news construction, as in previous related work, we novelly verify the feasibility of a more challenging but more useful setting to generate news report on the fly by treating live text input as a stream. Specifically, we design various scoring functions to address different requirements of the task. The near submodularity of scoring functions makes it possible to adapt efficient greedy algorithms even in stream data settings. Experiments suggest that our proposed framework can already produce comparable results compared with previous work that relies on a supervised learning to rank model with heavy feature engineering.
Approximating Graph Pattern Queries Using Views
Venue: CIKM
Year: 2016

This paper studies approximation of graph pattern queries using views. Given a pattern query Q and a set V of views, we propose to find a pair of queries Qu and Ql, referred to as the upper and lower approximations of Q w.r.t. V, such that (a) for any data graph G, answers to (part of) Q in G are contained in Qu(G) and contain Ql(G) and (b) both Qu and Ql can be answered by using views in V. We consider pattern queries based on both graph simulation and subgraph isomorphism. We study fundamental problems about approximation using views. Given Q and V, (1) we study whether there exist upper and lower approximations of Q w.r.t. V. (2) How to find approximations that are closest to Q w.r.t. V if exist? (3) How to answer upper and lower approximations using views in V? We give characterizations of the problems, study their complexity and approximation hardness, and develop algorithms with provable bounds. Using real life datasets, we verify the effectiveness and efficiency of approximating simulation and subgraph queries using views.
Ozone pollution control strategies examined by Empirical Kinetics Modeling Approach over the Beaumont Port Arthur region in Texas of USA
Year: 2020

Ground level ozone is harmful to both human health and ecological environment, which is formed by reactions of nitrogen oxides (NOx) and volatile organic compounds (VOCs) in the presence of sunlight. With the increasingly rigorous ozone standard in the U.S. it is important to examine ozone pollution control strategies to help air quality management in a concentrated industrial region, such as Beaumont Port Arthur (BPA) areas in Texas of USA. In this study, the method of Empirical Kinetics Modeling Approach (EKMA) associated with the comprehensive air quality modeling with extensions (CAMx) have been employed to demonstrate feasible air quality control strategies to examine the effects of VOCs and NOx abatement on ozone concentration in the BPA area. Case studies included base case simulations as well as those with 25% 50% and 75% reductions of anthropogenic NOx and/or VOCs emissions in the BPA area, which were based on the TCEQ provided meteorological and emission inventories for a high ozone episode. Simulation results indicated that NOx abatement is more effective than VOCs abatement in reducing ozone concentrations for BPA area, which suggestively belongs to the NOx sensitive regime for ozone pollution. The average 8 hr ozone could be reduced 3.3% 7.0% and 11.1% respectively, by 25% 50% and 75% of both NOx and VOCs emission abatement. The effect of pollutant abatement on ozone reduction is observed to be different at eight monitor stations in BPA region. Also, the nonlinear relationship between ozone and its precursors has been observed. This study could be helpful to provide scientific and technological support for the future development of air quality management and ozone control strategies in a concentrated industrial region.
Effects of Pounding and Fluid Structure Interaction on Seismic Response of Long Span Deep Water Bridge with High Hollow Piers
Year: 2019

This article aims to study the effects of pounding and fluid structure interaction on a typical long span deep water bridge with high hollow piers. With potential based fluid elements modeling fluid structure interaction between hollow piers and water, and gap elements simulating pounding at gap locations, three dimensional(3D) finite element models were built for the typical deep water bridge. The longitudinal seismic responses of the bridge under the combination effects of pounding and fluid structure interaction were studied from two cases where the hollow piers contact with outer water only and both outer water and inner water, respectively. For comparison, the individual effects of pounding or fluid structure interaction were also analyzed. The results indicate that the fluid structure interaction could be one of the critical factors which can result in pounding between adjacent segments of deep water bridges, because the fluid structure interaction can amplify the seismic relative displacement between adjacent spans of deep water bridge. The combination effects of pounding and fluid structure interaction are negligible on seismic responses of deep water bridge piers compared with the individual effect of fluid structure interaction; however, they can lead to further increase of deck displacement of approach span, no matter compared with the individual effect of fluid structure interaction or pounding, which increases the possibility of approach span unseating. Whether pounding happens or not, the existence of the inner water in the hollow piers causes aggravated effect on seismic responses of deep water bridge.
Retracted: E learner face identification with local sensitive hashing
Year: 2018

This paper displays a new and productive facial image representation based on local sensitive hashing (LSH) This technique makes it possible to recognize the learners who follow their training in our learning platform; during each session a picture of the student will be taken by the webcam to be compared to that stored in the database. Once recognized, the student must be oriented towards an appropriate profile that takes into account his strengths and weaknesses. The latter are concluded through a predictive study using the J48 as a tool. We also use a light processing module on the client device with a compact code so that we don't need a lot of bandwidth, a lot of network transmission capacity to send the feature over the network, and to be able to index many pictures in a huge database in the cloud.