nils-herrmann/clean_scirepeval huggingface dataset:
Public Opinion Detection in an Online Lending Forum: Sentiment Analysis and Data Visualization
Venue: 2020 IEEE 5th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA)
Year: 2020

Public opinion entails emotions, wishes, attitudes and ideas among individuals and various social groups in a certain historical stage and social space. This research aims to employ natural language processing (NLP) sentiment analysis and data mining technologies to build a public opinion analysis system to serve enterprises' need of online public opinion detection. By using the data set from an online pear to pear (P2P) lending forum with 4148 reviews, we analyzed the data with data visualization techniques.
Reliability Analysis of High Rise Building Considering Wind Load Uncertainty
Year: 2018

In engineering structures, the safety problems are always depending on the respond of structures to different types of load. The safety assessment of a high rise building is highly depending on the analysis of environmental load. Many codes and practices have proposed many requirements for engineers in the design works. These include safety factors, limitations on damage, maximum deflections and so on. When violations in these requirements occur, the structure is believed to be dangerous. But once the problem becomes complicated such as multiple unknown loads in one building, it requires reliability analysis in the design. It must take care of all the assumptions and uncertainties in the structural design. In probabilistic assessment, any input variable is considered as an uncertainty. However, the traditional way to deal with these problems may have problems when uncertainties are large. Many probabilistic safety measures need to be reconsidered in engineering work. This paper, we will provide reliability analysis on a high rise building with consideration of wind load. All the most commonly applied reliability methods are been utilized in this analysis and compared base on the performance. The statistical influences including correlation and distribution type are also discussed in the same reliability problem.
Empirical Bayes Transductive Meta Learning with Synthetic Gradients
Venue: ICLR
Year: 2020

We propose a meta learning approach that learns from multiple tasks in a transductive setting, by leveraging unlabeled information in the query set to learn a more powerful meta model. To develop our framework we revisit the empirical Bayes formulation for multi task learning. The evidence lower bound of the marginal log likelihood of empirical Bayes decomposes as a sum of local KL divergences between the variational posterior and the true posterior of each task. We derive a novel amortized variational inference that couples all the variational posteriors into a meta model, which consists of a synthetic gradient network and an initialization network. The combination of local KL divergences and synthetic gradient network allows for backpropagating information from unlabeled data, thereby enabling transduction. Our results on the Mini ImageNet and CIFAR FS benchmarks for episodic few shot classification significantly outperform previous state of the art methods.
A bi objective maximal covering location problem: a service network design application
Venue: 2020 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)
Year: 2020

This paper proposes a bi objective maximal covering location problem (MCLP) that involves customer preferences and balances between covered demand and the number of uncovered customers. The first objective maximizes the weighted sum of the covered demand, in which the weights are based on customer preferences, while the second objective is to minimize the number of uncovered customers. This newly proposed bi objective model can be applied to the design of service networks, such as post offices, health centers, delivery services, etc. Three multi objective evolutionary algorithms (MOEAs) are adapted to the considered bi objective MCLP and applied on the set of modified real life MCLP test instances that include large number of customer nodes and potential facility locations. The obtained experimental results show that all three MOEAs are suitable for solving the bi objective MCLP, as they successfully provide solutions on the considered test instances of challenging dimensions.
24/7 Place Recognition by View Synthesis
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence
Year: 2015

We address the problem of large scale visual place recognition for situations where the scene undergoes a major change in appearance, for example, due to illumination (day/night) change of seasons, aging, or structural modifications over time such as buildings being built or destroyed. Such situations represent a major challenge for current large scale place recognition methods. This work has the following three principal contributions. First, we demonstrate that matching across large changes in the scene appearance becomes much easier when both the query image and the database image depict the scene from approximately the same viewpoint. Second, based on this observation, we develop a new place recognition approach that combines (i) an efficient synthesis of novel views with (ii) a compact indexable image representation. Third, we introduce a new challenging dataset of 1,125 camera phone query images of Tokyo that contain major changes in illumination (day, sunset, night) as well as structural changes in the scene. We demonstrate that the proposed approach significantly outperforms other large scale place recognition techniques on this challenging data.
FBK HLT: An Effective System for Paraphrase Identification and Semantic Similarity in Twitter
Venue: *SEMEVAL
Year: 2015

This paper reports the description and performance of our system, FBK HLT, participating in the SemEval 2015, Task #1 "Paraphrase and Semantic Similarity in Twitter" for both subtasks. We submitted two runs with different classifiers in combining typical features (lexical similarity, string similarity, word n grams, etc) with machine translation metrics and edit distance features. We outperform the baseline system and achieve a very competitive result to the best system on the first subtask. Eventually, we are ranked 4 th out of 18 teams participating in subtask "Paraphrase Identification"
Empirical Bayes Analysis of RNA seq Data for Detection of Gene Expression Heterosis
Venue: Journal of agricultural, biological, and environmental statistics
Year: 2015

An important type of heterosis, known as hybrid vigor, refers to the enhancements in the phenotype of hybrid progeny relative to their inbred parents. Although hybrid vigor is extensively utilized in agriculture, its molecular basis is still largely unknown. In an effort to understand phenotypic heterosis at the molecular level, researchers are measuring transcript abundance levels of thousands of genes in parental inbred lines and their hybrid offspring using RNA sequencing (RNA seq) technology. The resulting data allow researchers to search for evidence of gene expression heterosis as one potential molecular mechanism underlying heterosis of agriculturally important traits. The null hypotheses of greatest interest in testing for gene expression heterosis are composite null hypotheses that are difficult to test with standard statistical approaches for RNA seq analysis. To address these shortcomings, we develop a hierarchical negative binomial model and draw inferences using a computationally tractable empirical Bayes approach to inference. We demonstrate improvements over alternative methods via a simulation study based on a maize experiment and then analyze that maize experiment with our newly proposed methodology.
Scope and extent of healthcare associated Middle East respiratory syndrome coronavirus transmission during two contemporaneous outbreaks in Riyadh, Saudi Arabia, 2017
Venue: Infection Control Hospital Epidemiology
Year: 2019

To investigate a Middle East respiratory syndrome coronavirus (MERS CoV) outbreak event involving multiple healthcare facilities in Riyadh, Saudi Arabia; to characterize transmission; and to explore infection control implications.   Cases presented in 4 healthcare facilities in Riyadh, Saudi Arabia: a tertiary care hospital, a specialty pulmonary hospital, an outpatient clinic, and an outpatient dialysis unit.  Contact tracing and testing were performed following reports of cases at 2 hospitals. Laboratory results were confirmed by real time reverse transcription polymerase chain reaction (rRT PCR) and/or genome sequencing. We assessed exposures and determined seropositivity among available healthcare personnel (HCP) cases and HCP contacts of cases.  In total, 48 cases were identified, involving patients, HCP, and family members across 2 hospitals, an outpatient clinic, and a dialysis clinic. At each hospital, transmission was linked to a unique index case. Moreover, 4 cases were associated with superspreading events (any interaction where a case patient transmitted to =5 subsequent case patients) All 4 of these patients were severely ill, were initially not recognized as MERS CoV cases, and subsequently died. Genomic sequences clustered separately, suggesting 2 distinct outbreaks. Overall, 4 (24% of 17 HCP cases and 3 (3% of 114 HCP contacts of cases were seropositive.  We describe 2 distinct healthcare associated outbreaks, each initiated by a unique index case and characterized by multiple superspreading events. Delays in recognition and in subsequent implementation of control measures contributed to secondary transmission. Prompt contact tracing, repeated testing, HCP furloughing, and implementation of recommended transmission based precautions for suspected cases ultimately halted transmission.
Integrated, Continuous Emulsion Creamer.
Venue: Analytical chemistry
Year: 2017

Automated and reproducible sample handling is a key requirement for high throughput compound screening and currently demands heavy reliance on expensive robotics in screening centers. Integrated droplet microfluidic screening processors are poised to replace robotic automation by miniaturizing biochemical reactions to the droplet scale. These processors must generate, incubate, and sort droplets for continuous droplet screening, passively handling millions of droplets with complete uniformity, especially during the key step of sample incubation. Here, we disclose an integrated microfluidic emulsion creamer that packs "creams" assay droplets by draining away excess oil through microfabricated drain channels. The drained oil coflows with creamed emulsion and then reintroduces the oil to disperse the droplets at the circuit terminus for analysis. Creamed emulsion assay incubation time dispersion was 1.7% 3 fold less than other reported incubators. The integrated, continuous emulsion creamer (ICEcreamer) was used to miniaturize and optimize measurements of various enzymatic activities (phosphodiesterase, kinase, bacterial translation) under multiple and single turnover conditions. Combining the ICEcreamer with current integrated microfluidic DNA encoded library bead processors eliminates potentially cumbersome instrumentation engineering challenges and is compatible with assays of diverse target class activities commonly investigated in drug discovery.
Fuzzing: on the exponential cost of vulnerability discovery
Venue: ESEC/SIGSOFT FSE
Year: 2020

We present counterintuitive results for the scalability of fuzzing. Given the same non deterministic fuzzer, finding the same bugs linearly faster requires linearly more machines. For instance, with twice the machines, we can find all known bugs in half the time. Yet, finding linearly more bugs in the same time requires exponentially more machines. For instance, for every new bug we want to find in 24 hours, we might need twice more machines. Similarly for coverage. With exponentially more machines, we can cover the same code exponentially faster, but uncovered code only linearly faster. In other words, re discovering the same vulnerabilities is cheap but finding new vulnerabilities is expensive. This holds even under the simplifying assumption of no parallelization overhead. We derive these observations from over four CPU years worth of fuzzing campaigns involving almost three hundred open source programs, two state of the art greybox fuzzers, four measures of code coverage, and two measures of vulnerability discovery. We provide a probabilistic analysis and conduct simulation experiments to explain this phenomenon.
AEKF Based 3 D Localization of Road Surface Images with Sparse Low Accuracy GPS Data
Venue: 2018 IEEE 88th Vehicular Technology Conference (VTC Fall)
Year: 2018

This paper presents a technique for localizing road surface images acquired by a downward facing monocular camera on a vehicle with sparse low accuracy Global Positioning System (GPS) readings. Images are collected by reading vehicle speed through on board diagnostics (OBD) such that distance between two neighboring images is constant. The images are then stitched to create the road surface of arbitrary length. Lastly, the three dimensional (3 D) road surface is created and globally corrected by using the GPS and the elevation map as well as the Adaptive Extended Kalman Filter (AEKF) The advantage of this technique is the possible deployment of a sparse low accuracy GPS due to the use of the adaptive version of Extended Kalman Filter (EKF) The proposed technique was used for localization of local roads and highways of 6.9 km total length in Blacksburg, VA. The results of the localization show the reconstructed 3 D differ from the satellite imagery data only by 7.97%
Intimate Partner Victimization Among College Students With and Without Disabilities
Venue: Journal of interpersonal violence
Year: 2016

Prior research indicates that both college students and individuals with disabilities are at an increased risk of experiencing intimate partner victimization (IPV) However, little is known about IPV risk and its relationship to emotional well being among the intersection of these two populations. Utilizing a sample of approximately 20,000 college students from the American College Health Association's (ACHA) National College Health Assessment II (NCHA II) this study focuses on this overlooked intersection by examining IPV among college students with disabilities. Multivariate binary logistic regression models were used to estimate the relationship among disability, IPV, and emotional well being. College students with disabilities were approximately twice as likely to experience IPV than their counterparts without disabilities. Students with mental disabilities and multiple disability types were found to have the greatest likelihood of experiencing IPV. Victims with disabilities were more likely than victims without disabilities to report experiencing depression symptoms, self harm behavior, and stress. Recommendations for reducing and preventing IPV among a college student population are discussed.
How to Create Competitive Organization: Leveraging Strategic Capabilities in Russia
Venue: Modeling Economic Growth in Contemporary Russia
Year: 2019

What core strategic capabilities should multinational and domestic firms possess to create competitive organization in Russia? In this chapter, we try to answer this question with our pilot case study of six firms operating in the Russian high tech, low tech, and services markets four global companies and two Russian firms. Our research shows that customer orientation is the crucial strategic capability, highlighted by all of the firms involved in the research. For multinational and high tech players, this is followed by research and development, mentioned by two thirds of the respondents. Moreover, the four multinational companies leverage their strategic capabilities of cross cultural management and general sales capabilities as keys for their success in Russia. Russian firms emphasize importance of entrepreneurship, understanding local customer needs, and an engaged team as strategic capabilities that particularly differentiate them from the multinational players in the Russian market.
Learning bi utterance for multi turn response selection in retrieval based chatbots
Venue: International Journal of Advanced Robotic Systems
Year: 2019

Multi turn response selection is essential to retrieval based chatbots. The task requires multi turn response selection model to match a response candidate with a conversation context. Existing methods may lose relationship features in the context. In this article, we propose an improved method that extends the learning granularity of the multi turn response selection model to enhance the model's ability to learn relationship features of utterances in the context, which is a key to understand a conversation context for multi turn response selection in retrieval based chatbots. The experimental results show that our proposed method significantly improves sequential matching network for multi turn response selection in retrieval based chatbots.
Lightweight Low Cost UAV Radar Terrain Mapping
Venue: 2019 13th European Conference on Antennas and Propagation (EuCAP)
Year: 2019

Aerial 3D scene mapping can be done using vision based methods where many 2D images are combined to create 3D maps. However, these methods have certain disadvantages, especially in scenarios where there is limited or inconsistent lighting, few image features, or fast motion. The low cost and wide availability of automotive 77 GHz allow it to be used in conjunction with unmanned aerial vehicles to achieve terrain mapping with Synthetic Aperture Radar (SAR) techniques. We investigate the feasibility of using such a radar to complement or replace maps generated from vision based methods. This technique is tested outdoors on a drone flight with real targets.
Workplace Bullying, Emotional Abuse and Harrassment in Fire Departments
Year: 2019

Firefighters are heroes who save lives and protect property. They are highly revered in societies all around the world and perform under the most stressful of conditions. Drawing on literature from the United States (USA) this chapter J. C. Griffith D. L. Roberts Embry Riddle Aeronautical University, Worldwide Campus, Daytona Beach, FL, USA e mail: griff2ec@erau.edu; rober596@erau.edu Springer Nature Singapore Pte Ltd. 2018 P. D'Cruz et al. (eds. Special topics and particular occupations, professions and sectors, Handbooks of Workplace Bullying, Emotional Abuse and Harassment 4, https:/doi.org/10.1007/978 981 10 5154 8_15 1 1 reviews the culture, demographics and changing mission of the fire service as a backdrop to workplace harassment and bullying issues. The fire service has unique organizational dynamics that can lead to harassment and bullying and, at the same time, are the critical reasons for working to eliminate intentional and unintentional unfair treatment of women and minorities. Recent literature and studies show that the battle to eradicate harassment and bullying is far from over. More women than men perceived differential treatment based on gender, race and sexual orientation. Moreover, more women than men have reported ill fitting equipment issues in multiple studies. Recommended solutions include ensuring harassment and bullying are not tolerated by verifying all know that a policy exists and how to follow it. Fire stations should be designed to ensure women have separate sleeping quarters and showers, which afford privacy. Fire station leadership should also ensure firefighting equipment issued to its members fit (to include female sized equipment and turnout gear) so that firefighters have confidence that the equipment will protect them while they save others. The International Association of Fire Chiefs (IAFC) has taken steps to identify areas of bullying and discrimination and is working diligently to enforce and develop effective strategies to mitigate these issues. Future research should include continued studies of the US fire service as well as studies of non US fire services. Additional research should also focus on the effects of bullying, sexual harassment and discrimination on bystanders and volunteer firefighters.
Efficient Cooperative HARQ for Multi Source Multi Relay Wireless Networks
Venue: 2018 14th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
Year: 2018

In this paper, we compare the performance of three different cooperative Hybrid Automatic Repeat reQuest (HARQ) protocols for slow fading half duplex orthogonal multiple access multiple relay channel. Channel State Information (CSI) is available at the receiving side of each link only. Time Division Multiplexing is assumed, where each orthogonal transmission occurs during a time slot. Sources transmit in turns in consecutive time slots during the first transmission phase. During the second phase, the destination schedules in each time slot one node (source or relay) to transmit redundancies based on its correctly decoded source messages (its decoding set) with the goal to maximize the average spectral efficiency. Bidirectional limited control channels are available from sources and relays towards the destination to implement the necessary control signaling of the HARQ protocols. Among the three proposed HARQ, two follow the Incremental Redundancy (IR) approach. One consists in sending incremental redundancies on all the messages from the scheduled node decoding set (Multi User encoding) while the other one helps a single source (Single User encoding) chosen randomly. The third one is of the Chase Combining (CC) type, where the selected node repeats the transmission (including modulation and coding scheme) of one source chosen randomly from its decoding set. Monte Carlo simulations confirm that the IR type of HARQ with Multi User encoding offers the best performance, followed by IR type of HARQ with Single User encoding and CC type of HARQ. We conclude that IR type of HARQ with Single User encoding offers the best trade off between performance and complexity for a small number of sources in our setting.
Application of PID type Generalized Predictive Control Algorithm in Lateral Semi active Suspension System for High speed Train
Year: 2010

Aiming at the controller problems of the lateral suspension systems of railway vehicles,the 17 degrees lateral model of the whole vehicle were given in the paper.The generalized Predictive Control(GPC) strategy was applied to the semi active suspension systems.The traditional spectrum analysis was used to analyze the relationships among lateral,rolling and yaw vibrations that affected the lateral ride quality of the vehicle.The result shows that the lateral suspension vibration of the vehicle system is greatly reduced,and the dynamical performance and ride comfort of the vehicle system are considerably improved by using the PID GPC Algorithm.