Miracle-dz/UniFAR-FTUs huggingface dataset:
Resolving Other-Anaphora

Reference resolution is a major component of any natural language system. In the past 30 years significant progress has been made in coreference resolution. However, there is more anaphora in texts than coreference. I present a computational treatment of other-anaphora, i.e., referential noun phrases (NPs) with non-pronominal heads modified by “other” or “another”: [. ] the move is designed to more accurately reflect the value of products and to put steel on more equal footing with other commodities. Such NPs are anaphoric (i.e., they cannot be interpreted in isolation), with an antecedent that may occur in the previous discourse or the speaker’s and hearer’s mutual knowledge. For instance, in the example above, the NP “other commodities” refers to a set of commodities excluding steel, and it can be paraphrased as “commodities other than steel”. Resolving such cases requires first identifying the correct antecedent(s) of the other-anaphors. This task is the major focus of this dissertation. Specifically, the dissertation achieves two goals. First, it describes a procedure by which antecedents of other-anaphors can be found, including constraints and preferences which narrow down the search. Second, it presents several symbolic, machine learning and hybrid resolution algorithms designed specifically for other-anaphora. All the algorithms have been implemented and tested on a corpus of examples from the Wall Street Journal. The major results of this research are the following: 1. Grammatical salience plays a lesser role in resolving other-anaphors than in resolving pronominal anaphora. Algorithms that solely rely on grammatical features achieved worse results than algorithms that used semantic features as well. 2. Semantic knowledge (such as “steel is a commodity”) is crucial in resolving other-anaphors. Algorithms that operate solely on semantic features outperformed those that operate on grammatical knowledge. 3. The quality and relevance of the semantic knowledge base is important to success. WordNet proved insufficient as a source of semantic information for resolving other-anaphora. Algorithms that use the Web as a knowledge base achieved
Transfer of driving behaviors across different racing games

Transfer learning might be a promising approach to boost the learning of non-player characters' behaviors by exploiting some existing knowledge available from a different game. In this paper, we investigate how to transfer driving behaviors from The Open Racing Car Simulator (TORCS) to VDrift, which are two well known open-source racing games featuring rather different physics engines and game dynamics. We focus on a neuroevolution learning framework based on NEAT and compare three different methods of transfer learning: (i) transfer of the learned behaviors; (ii) transfer of the learning process; (iii) transfer of both the behaviors and the process. Our experimental analysis suggests that all the proposed methods of transfer learning might be effectively applied to boost the learning of driving behaviors in VDrift by exploiting the knowledge previously learned in TORCS. In particular, transferring both learned behaviors and learning process appears to be the best trade-off between the final performance and the computational cost.
Deep Tensor Encodings

Learning an encoding of feature vectors in terms of an over-complete dictionary or a information geometric (Fisher vectors) construct is wide-spread in statistical signal processing and computer vision. In content based information retrieval using deep-learning classiers, such encodings are learnt on the aened last layer, without adherence to the multi-linear structure of the underlying feature tensor. We illustrate a variety of feature encodings incl. sparse dictionary coding and Fisher vectors along with proposing that a structured tensor factorization scheme enables us to perform retrieval that can be at par, in terms of average precision, with Fisher vector encoded image signatures. In short, we illustrate how structural constraints increase retrieval delity.
Towards Guidelines for Preventing Critical Requirements Engineering Problems

[Context] Problems in Requirements Engineering (RE) can lead to serious consequences during the software development lifecycle. [Goal] The goal of this paper is to propose empirically-based guidelines that can be used by different types of organisations according to their size (small, medium or large) and process model (agile or plan-driven) to help them in preventing such problems. [Method] We analysed data from a survey on RE problems answered by 228 organisations in 10 different countries. [Results] We identified the most critical RE problems, their causes and mitigation actions, organizing this information by clusters of size and process model. Finally, we analysed the causes and mitigation actions of the critical problems of each cluster to get further insights into how to prevent them. [Conclusions] Based on our results, we suggest preliminary guidelines for preventing critical RE problems in response to context characteristics of the companies.
Aerial Mast vs Aerial Bridge Autonomous UAV Relay: A Simulation-Based Comparison

This paper provides a simulation-based comparison between two strategies for an autonomous mobile aerial node communication relay between two mobile ground nodes with non-line-of-sight (NLOS). For both strategies, the airborne relay is considered as a signal repeater between the two ground mobile vehicles. The first strategy (aerial bridge) implies that an unmanned aerial vehicle (UAV) is trying to keep an optimal position between the two ground nodes while in the aerial mast strategy; the UAV is always placed directly above one of the ground vehicles. The comparison is based on Winner II propagation model applied to a 2.4 GHz waveform. Simulation results demonstrate in each case the variation of transmitted signal strength due to ground vehicles and UAV movement. Trajectories were generated randomly for both ground nodes on a street map of an urban area in order to achieve a statistical analysis of both strategies and discuss their advantages in terms of signal transmission and UAV navigation control.
Drawing : A New Way To Search ( Computer Vision )

Computers having the ability to understand our quick line drawings will allow for broader forms of expression and communication. In our project, we aim to use machine learning techniques to efficiently recognize labels of handdrawn images. After implementing and analyzing classical and deep learning models, we found that a simplified Convolutional Neural Network was best for this task.
Deep Learning for Depth Learning CS 229 Course Project , 2013 Fall

Extracting 3D depth information from images is a classic problem of computer vision. Traditionally image depth could be extracted by techniques such as stereo camera or images from multiple views. In this project, we are trying to recognize the depth information by using a single still image from single camera, which has great potential applications in vision and recognition. To learn the complex relationship between single RGB image with its depth information, we chose to use Deep learning algorithms, to learn the multiple level features and corresponding different levels of abstraction. The main goal of the project is to train a deep network that is able to extract local and non-local features and predict a depth-map given a still image. In addition, implementation of other learning algorithm (kernel based, dictionary learning) was also conducted for comparison.
Testing plasmid stability of Escherichia coli using the Continuously Operated Shaken BIOreactor System

Plasmids are common vectors to genetically manipulate Escherichia coli or other microorganisms. They are easy to use and considerable experience has accumulated on their application in heterologous protein production. However, plasmids can be lost during cell growth, if no selection pressure like, e.g., antibiotics is used, hampering the production of the desired protein and endangering the economic success of a biotechnological production process. Thus, in this study the Continuously Operated Shaken BIOreactor System (COSBIOS) is applied as a tool for fast parallel testing of strain stability and operation conditions and to evaluate measures to counter such plasmid loss. In specific, by applying various ampicillin concentrations, the lowest effective ampicillin dosage is investigated to secure plasmid stability while lowering adverse ecological effects. A significant difference was found in the growth rates of plasmid‐bearing and plasmid‐free cells. The undesired plasmid‐free cells grew 30% faster than the desired plasmid‐bearing cells. During the testing of plasmid stability without antibiotics, the population fraction of plasmid‐bearing cells rapidly decreased in continuous culture to zero within the first 48 h. An initial single dosage of ampicillin did not prevent plasmid loss. By contrast, a continuous application of a low dosage of 10 µg/mL ampicillin in the feed medium maintained plasmid stability in the culture. Consequently, the COSBIOS is an apt reactor system for measuring plasmid stability and evaluating methods to enhance this stability. Hence, decreased production of heterologous protein can be prevented. © 2016 American Institute of Chemical Engineers Biotechnol. Prog. , 32:1418–1425, 2016
Ergodic Control of Multi-Class M/M/N+M Queues in the Halfin-Whitt Regime

We study a dynamic scheduling problem for a multi-class queueing network with a large pool of statistically identical servers. The arrival processes are Poisson, and service times and patience times are assumed to be exponentially distributed and class dependent. The optimization criterion is the expected long time average (ergodic) of a general (nonlinear) running cost function of the queue lengths. We consider this control problem in the Halfin-Whitt (QED) regime, that is, the number of servers $n$ and the total offered load $\mathbf{r}$ scale like $n\approx\mathbf{r}+\hat{\rho}\sqrt{\mathbf{r}}$ for some constant $\hat{\rho}$. This problem was proposed in [Ann. Appl. Probab. 14 (2004) 1084-1134, Section 5.2]. The optimal solution of this control problem can be approximated by that of the corresponding ergodic diffusion control problem in the limit. We introduce a broad class of ergodic control problems for controlled diffusions, which includes a large class of queueing models in the diffusion approximation, and establish a complete characterization of optimality via the study of the associated HJB equation. We also prove the asymptotic convergence of the values for the multi-class queueing control problem to the value of the associated ergodic diffusion control problem. The proof relies on an approximation method by spatial truncation for the ergodic control of diffusion processes, where the Markov policies follow a fixed priority policy outside a fixed compact set.
Geometric influences II: Correlation inequalities and noise sensitivity

In a recent paper, we presented a new definition of influences in product spaces of continuous distributions, and showed that analogues of the most fundamental results on discrete influences, such as the KKL theorem, hold for the new definition in Gaussian space. In this paper we prove Gaussian analogues of two of the central applications of influences: Talagrand's lower bound on the correlation of increasing subsets of the discrete cube, and the Benjamini-Kalai-Schramm (BKS) noise sensitivity theorem. We then use the Gaussian results to obtain analogues of Talagrand's bound for all discrete probability spaces and to reestablish analogues of the BKS theorem for biased two-point product spaces.
Did I Really Say That? - Combining Machine Learning and Dependency Relations to Extract Statements from German News Articles

We present a system to extract statements of public ﬁgures from unstructured German news articles. We ﬁrst motivate and deﬁne statements as a temporally-aware extension of quotations and present the three categories of statements: (1) direct, (2) indirect, and (3) mixed-style statements. We use a combination of machine learning and heuristics based on dependency parses to tackle all three types of statements. The quality of our extraction approach is compared to related work in quotation attribution showing that rules based on syntactic structures increase the extraction quality compared to lexical patterns. In addition, we apply the system on a corpus of German news articles and show that it is able to extract statements with high precision (82.4%).
Driving likes, comments, and shares on social networking sites: how post characteristics affect brand interactions in apparel retailing

Based on 415 posts from 6 apparel retail brands, this study analyzes the liking, commenting and sharing behavior on one social networking site. These brand post interactions are explained by post vividness, interactivity, and content. We also consider the post timing and check for post length and fan number. This study extends the literature in three ways: by addressing post content types, including hashtags as an interactive measure, and studying the domain of apparel retailing in which both brands and consumers are highly engaged and exhibit a high likelihood of social interaction. Vividness characteristics and content types have positive and negative effects on the number of post interactions. Interactivity characteristics, apart from links to a website, as well as the period of time a post is positioned at the top of a brand page, positively affect social interactions. However, post publications on weekdays or weekends have no effect on user social interactions and increasing post length negatively affects the liking, commenting, and sharing behavior.
Homography-based Tracking for Central Catadioptric Cameras

This paper presents a parametric approach for tracking piecewise planar scenes with central catadioptric cameras (including perspective cameras). We extend the standard notion of homography to this wider range of devices through the unified projection model on the sphere. We avoid unwarping the image to a perspective view and take into account the non-uniform pixel resolution specific to non-perspective central catadioptric sensors. The homography is parametrised by the Lie algebra of the special linear group SL(3) to ensure that only eight free parameters are estimated. With this model, we use an efficient second-order minimisation technique leading to a fast tracking algorithm with a complexity similar to a first-order approach. The developed algorithm was tested on the estimation of the displacement of a mobile robot in a real application and proved to be very precise
Soft UV Nanoimprint Lithography and Its Applications

Large-area nanopatterning technology has demonstrated high potential which can signifi‐ cantly enhance the performance of many devices and products, such as LEDs, solar cells, hard disk drives, laser diodes, display, etc [1]. For example, nano-patterned sapphire substrates (NPSS) and photonic crystals (PhC) have been considered as the most effective approaches to improve the light output efficiency (internal quantum efficiency and external quantum efficiency) of LEDs and beam shaping [2,3]. The solar cells with sub-micro anti-reflective coating exhibited higher photocurrent and higher power conversion efficiency compared to those without nanostructures [4]. Moreover, the ability to produce large-area microand nanostructures on non-planar surfaces is of importance for many applications such as optics, optoelectronics, nanophotonics, imaging technology, NEMS, and microfluidics [5]. However, creating large-area nanostructures on curved or non-planar surfaces are extremely difficult using existing patterning approaches. Furthermore, a variety of existing nanopatterning technologies such as electron beam lithography (ELB), optical lithography, interference lithography (IL), etc., cannot cope with all the practical demands of industrial applications with respect to high resolution, high throughput, low cost, large area, and patterning on nonflat and curved surface. Therefore, new high volume nanomanufacturing technology strongly needs to be exploited and developed so as to meet the tremendous requires of rapid growing markets.
Re : Benzene and the Dose-Related Incidence of Hematologic Neoplasms in China

subgroups and necessary in others is discussed in our article(1) and its accompanying editorial(2). We find Dr. Atkins’s table showing percent reductions by subgroups potentially misleading because it does not reflect uncertainty in the estimated rates. In addition, it is redundant with the information that we presented in Fig. 4(1),which shows percent reductions by covariate levels and associated confidence intervals. In the past, strong conclusions drawn from subgroup data have caused considerable confusion among breast cancer clinicians and researchers. An excellent example is the persistent belief, based on early studies and hypotheses concerning endogenous hormone levels, that tamoxifen is not efficacious in younger women(3). Subsequently, findings from individual trials, e.g., NSABP B-14, and results of the Early Breast Cancer Trialists’ Collaborative Group overview strongly supported its use in young women with estrogen receptor (ER)positive tumors(4,5). In regard to variation in mortality by age and the ‘‘preliminary nature of these results,’’ the survival comparisons are mature to the degree that, by design, the number of total events was sufficient to allow for pairwise comparisons between the tamoxifen group and chemotherapy groups with statistical power greater than 80%. As Dr. Atkins indicates, survival comparisons within age subgroups are less reliable. Because there was no statistical evidence of an interaction between treatment and age group, we concluded that a benefit exists in both age groups, although the data are suggestive of a greater benefit for younger patients with respect to the other end points, i.e., disease-free survival and distant disease-free survival. Dr. Atkins suggests that the combined use of chemotherapy and tamoxifen is potentially detrimental to premenopausal patients. Our data provide no evidence of significantly increased mortality due to chemotherapy in younger women; moreover, as Dr. Atkins has stated, the result of the report by the Early Breast Cancer Trialists’ Collaborative Group (an increase of 6% with standard deviation of 23%) was highly variable(5). The earlier NSABP study to which Dr. Atkins alludes addressed the question of adding tamoxifen to chemotherapy in ER-negative and ER-positive patients and is not directly relevant to the question at hand (6). Finally, with regard to Dr. Atkins’s statement about the B-20 trial confirming ‘‘what we already know,’’ we wish to reiterate that our study is the first prospective, randomized comparison of the addition of chemotherapy to tamoxifen alone in lymph node-negative, ERpositive patients. This treatment approach could not justifiably be adopted without the conduct of such a trial, precisely for the reasons that apparently motivated Dr. Atkins’s letter, i.e., the potential benefits and costs that patients and their physicians must weigh before deciding to choose this treatment regimen.
An improved authenticated key agreement protocol with perfect forward secrecy for wireless mobile communication

To provide secure communication for mobile devices, an authenticated key agreement protocol is an important primitive for establishing session keys. However, most existing authenticated key agreement protocols are not designed for wireless mobile communication for which bandwidth and device storage capacity are limited. Also, as mobile devices are more vulnerable to attack, providing forward secrecy becomes an essential element in the protocol. Based on Seo and Sweeney's simple authenticated key agreement algorithm (SAKA), we develop an improved authenticated key agreement protocol that eliminates the disadvantages of SAKA and provides identity authentication, key validation, and perfect forward secrecy. Also, our protocol can foil man-in-the-middle attacks. We also show how our proposed protocol can be included in the current 3GPP2 specifications for OTASP to improve A-key (authentication key) distribution, which is the master key in IS-95 and cdma2000 mobile networks. The proposed protocol requires significantly less bandwidth, and less computational and storage overhead, while having higher security compared to 3GPP2 specifications. The proposed protocol can also be applied to other wireless communication scenarios.
Modular deficits in Alzheimer-type dementia

Bringing models and methods of cognitive neuropsychology to bear on the study of dementing disorders, these contributions present sound evidence that diseases of the Alzheimer type compromise brain function in a highly selective manner, affecting some aspects of cognition while sparing others. Included are original case studies that explore in detail the nature of the linguistic, semantic, and visuoperceptual disorders in patients with degenerative dementias. The book pursues a number of themes with important ramifications for the study of higher mental functions. By exploring the neurocognitive modules that are the targets of degenerative processes, it shows that Alzheimer's disease is not one disease but a complex of disease states, that clinical diversity is an essential feature of Alzheimer's disease and Alzheimer-type dementia, that this diversity reflects to a large extent the differential involvement of particular neural systems that support cognition, and that when suitable methods and models are applied, studies of Alzheimer-type dementia can expand our understanding of basic brain-behavior relations.Myrna F. Schwartz is Director of the Neuropsychology Research Laboratory at Moss Rehabilitation Hospital in Philadelphia.Contributors: M. Moscovitch and C. Umilta, M. F. Schwartz, J. A. Stark, A. R. Damasio, G. W. Van Hoesen, B. T. Hyman, J. B. Chawluk, M. Grossman, J. A. Calcano-Perez, A. Alavi, H. I. Hurtig, M. Reivich, A. Martin, J. Baron, M. Moscovitch, H. Chertkow, D. Bub, E. M. Saffran, E. J. Fitzpatrick-DeSalme, H. B. Coslett.
Novel mechanism of brain soluble epoxide hydrolase‐mediated blood pressure regulation in the spontaneously hypertensive rat

The role of soluble epoxide hydrolase (sEH) in the central control of blood pressure (BP) has not been elucidated in spite of peripheral sEH overexpression being linked to hypertension. Thus, our objective was to investigate the involvement of brain sEH in BP control. sEH expression in the hypothalamus and brain stem, two cardioregulatory brain areas, was increased in the spontaneously hypertensive rat (SHR) compared to the Wistar Kyoto (WKY) rat. Inhibition of the enzyme by intracerebroventricular (icv) delivery of AUDA further increased both BP and heart rate (HR) by 32 ± 6 mmHg and 54 ± 10 bpm, respectively, (P<0.05) in the SHR. Analysis of waveform telemetry data revealed a decrease in spontaneous baroreceptor reflex gain following sEH inhibition, indicating the sustained increase in BP may be due to a decrease in baroreceptor reflex function. The hypertensive effect of sEH inhibition is likely a result of an increase in epoxyeicosatrienoic acid (EET)‐mediated generation of ROS. This view is supported by the following: 1) Inhibition of EET formation attenuates AUDA‐induced increase in BP; 2) delivery of an EET agonist increases BP and HR in the WKY rat, and 3) inhibition of NAD(P)H oxidase by gp91ds‐tat prevents AUDA‐induced increases in BP and HR. Finally, electrophysiological studies demonstrate that AUDA increased neuronal firing rate exclusively in the SHR, an effect completely abolished by gp91ds‐tat. These observations suggest that EETs and sEH inhibition are involved in increasing BP in the SHR. We suggest that an increased expression of sEH is a futile central nervous system response in protection against hypertension.