Imperfect Information in Logic and Concurrent Games

Abstract. This paper builds on a recent definition of concurrent games as event structures and an application giving a concurrent-game model for predicate calculus. An extension to concurrent games with imperfect information, through the introduction of ‘access levels ’ to restrict the allowable strategies, leads to a concurrent-game semantics for a variant of Hintikka and Sandu’s Independence-Friendly (IF) logic

Accidental finding of a toothpick in the porta hepatis during laparoscopic cholecystectomy: a case report

<p>Abstract</p> <p>Introduction</p> <p>Unintentional ingestion of a toothpick is not an uncommon event. Often the ingested toothpicks spontaneously pass through the gut without sequelae. However, serious complications can happen when these sharp objects migrate through the gastrointestinal wall.</p> <p>Case presentation</p> <p>In the current report, we describe the case of a 37-year-old Caucasian woman with an incidental finding of a toothpick in the porta hepatis during laparoscopic cholecystectomy for symptomatic gall stones.</p> <p>Conclusion</p> <p>Toothpick ingestion is not an uncommon event and can predispose patients to serious complications. In this particular case, the toothpick was only discovered at the time of unrelated surgery. Therefore, it was important during surgery to exclude any related or missed injury to the adjacent structures by this sharp object.</p

intensitynet: Intensity-based Analysis of Spatial Point Patterns Occurring on Complex Networks Structures in R

The statistical analysis of structured spatial point process data where the event locations are determined by an underlying spatially embedded relational system has become a vivid field of research. Despite a growing literature on different extensions of point process characteristics to linear network domains, most software implementations remain restricted to either directed or undirected network structures and are of limited use for the analysis of rather complex real-world systems consisting of both undirected and directed parts. Formalizing the network through a graph theoretic perspective, this paper discusses a complementary approach for the analysis of network-based event data through generic network intensity functions and gives a general introduction to the intensitynet package implemented in R covering both computational details and applications. By treating the edges as fundamental entities, the implemented approach allows the computation of intensities and other related values related to different graph structures containing undirected, directed, or a combination of both edges as special cases. The package includes characteristics for network modeling, data manipulation, intensity estimation, computation of local and global autocorrelation statistics, visualization, and extensions to marked point process scenarios. All functionalities are accompanied by reproducible code examples using the chicago data as toy example to illustrate the application of the package.Comment: submitted for publicatio

Latin Synthetic Compounding and Distributed Morphology

The theory of Distributed Morphology (DM) has been applied to English synthetic compounds by Harley (2009), who proposes an analysis as incorporation structures. After a short introduction on the passage from lexicalism to DM in Latin morphology (par. 1), I will try to extend Haley\u2019s analysis to Latin synthetic compounds, suggesting some revisions (par. 2). In the first place, I will argue for the necessity to introduce verbal features in the structure of a compound like "agricola", in order to explain the special meanings associated to the root COL, that is the fact that the verbal head introduces a dynamic event, and that the nominalized root AGR is interpreted as undergoing a change of state (par. 3). This suggestion is confirmed by comparing the structures of verb phrases, e.g. "colere agrum", noun phrases with nominal derivatives, e.g. "cultor agri", and synthetic compounds, e.g. "agricola", where the crucial observation is that in Latin, unlike English, there is no overt agentive suffix in the compound, such as -er in "taxi-driver": in Latin synthetic compounds we do not find the typical agentive suffix -tor (par. 4). I will conclude with some general observations on the relationships between morphology and syntax (par. 5)

음향 이벤트 탐지를 위한 효율적 데이터 활용 및 약한 교사학습 기법

학위논문(박사)--서울대학교 대학원 :공과대학 전기·컴퓨터공학부,2020. 2. 김남수.Conventional audio event detection (AED) models are based on supervised approaches. For supervised approaches, strongly labeled data is required. However, collecting large-scale strongly labeled data of audio events is challenging due to the diversity of audio event types and labeling difficulties. In this thesis, we propose data-efficient and weakly supervised techniques for AED. In the first approach, a data-efficient AED system is proposed. In the proposed system, data augmentation is performed to deal with the data sparsity problem and generate polyphonic event examples. An exemplar-based noise reduction algorithm is proposed for feature enhancement. For polyphonic event detection, a multi-labeled deep neural network (DNN) classifier is employed. An adaptive thresholding algorithm is applied as a post-processing method for robust event detection in noisy conditions. From the experimental results, the proposed algorithm has shown promising performance for AED on a low-resource dataset. In the second approach, a convolutional neural network (CNN)-based audio tagging system is proposed. The proposed model consists of a local detector and a global classifier. The local detector detects local audio words that contain distinct characteristics of events, and the global classifier summarizes the information to predict audio events on the recording. From the experimental results, we have found that the proposed model outperforms conventional artificial neural network models. In the final approach, we propose a weakly supervised AED model. The proposed model takes advantage of strengthening feature propagation from DenseNet and modeling channel-wise relationships by SENet. Also, the correlations among segments in audio recordings are represented by a recurrent neural network (RNN) and conditional random field (CRF). RNN utilizes contextual information and CRF post-processing helps to refine segment-level predictions. We evaluate our proposed method and compare its performance with a CNN based baseline approach. From a number of experiments, it has been shown that the proposed method is effective both on audio tagging and weakly supervised AED.일반적인 음향 이벤트 탐지 시스템은 교사학습을 통해 훈련된다. 교사학습을 위해서는 강한 레이블 데이터가 요구된다. 하지만 강한 레이블 데이터는 음향 이벤트의 다양성 및 레이블의 난이도로 인해 큰 데이터베이스를 구축하기 어렵다는 문제가 있다. 본 논문에서는 이러한 문제를 해결하기 위해 음향 이벤트 탐지를 위한 데이터 효율적 활용 및 약한 교사학습 기법에 대해 제안한다. 첫 번째 접근법으로서, 데이터 효율적인 음향 이벤트 탐지 시스템을 제안한다. 제안된 시스템에서는 데이터 증대 기법을 사용해 데이터 희소성 문제에 대응하고 중첩 이벤트 데이터를 생성하였다. 특징 벡터 향상을 위해 잡음 억제 기법이 사용되었고 중첩 음향 이벤트 탐지를 위해 다중 레이블 심층 인공신경망(DNN) 분류기가 사용되었다. 실험 결과, 제안된 알고리즘은 불충분한 데이터에서도 우수한 음향 이벤트 탐지 성능을 나타내었다. 두 번째 접근법으로서, 컨볼루션 신경망(CNN) 기반 오디오 태깅 시스템을 제안한다. 제안된 모델은 로컬 검출기와 글로벌 분류기로 구성된다. 로컬 검출기는 고유한 음향 이벤트 특성을 포함하는 로컬 오디오 단어를 감지하고 글로벌 분류기는 탐지된 정보를 요약하여 오디오 이벤트를 예측한다. 실험 결과, 제안된 모델이 기존 인공신경망 기법보다 우수한 성능을 나타내었다. 마지막 접근법으로서, 약한 교사학습 음향 이벤트 탐지 모델을 제안한다. 제안된 모델은 DenseNet의 구조를 활용하여 정보의 원활한 흐름을 가능하게 하고 SENet을 활용해 채널간의 상관관계를 모델링 한다. 또한, 오디오 신호에서 부분 간의 상관관계 정보를 재순환 신경망(RNN) 및 조건부 무작위 필드(CRF)를 사용해 활용하였다. 여러 실험을 통해 제안된 모델이 기존 CNN 기반 기법보다 오디오 태깅 및 음향 이벤트 탐지 모두에서 더 나은 성능을 나타냄을 보였다.1 Introduction 1 2 Audio Event Detection 5 2.1 Data-Ecient Audio Event Detection 6 2.2 Audio Tagging 7 2.3 Weakly Supervised Audio Event Detection 9 2.4 Metrics 10 3 Data-Ecient Techniques for Audio Event Detection 17 3.1 Introduction 17 3.2 DNN-Based AED system 18 3.2.1 Data Augmentation 20 3.2.2 Exemplar-Based Approach for Noise Reduction 21 3.2.3 DNN Classier 22 3.2.4 Post-Processing 23 3.3 Experiments 24 3.4 Summary 27 4 Audio Tagging using Local Detector and Global Classier 29 4.1 Introduction 29 4.2 CNN-Based Audio Tagging Model 31 4.2.1 Local Detector and Global Classier 32 4.2.2 Temporal Localization of Events 34 4.3 Experiments 34 4.3.1 Dataset and Feature 34 4.3.2 Model Training 35 4.3.3 Results 36 4.4 Summary 39 5 Deep Convolutional Neural Network with Structured Prediction for Weakly Supervised Audio Event Detection 41 5.1 Introduction 41 5.2 CNN with Structured Prediction for Weakly Supervised AED 46 5.2.1 DenseNet 47 5.2.2 Squeeze-and-Excitation 48 5.2.3 Global Pooling for Aggregation 49 5.2.4 Structured Prediction for Accurate Event Localization 50 5.3 Experiments 53 5.3.1 Dataset 53 5.3.2 Feature Extraction 54 5.3.3 DSNet and DSNet-RNN Structures 54 5.3.4 Baseline CNN Structure 56 5.3.5 Training and Evaluation 57 5.3.6 Metrics 57 5.3.7 Results and Discussion 58 5.3.8 Comparison with the DCASE 2017 task 4 Results 61 5.4 Summary 62 6 Conclusions 65 Bibliography 67 요 약 77 감사의 글 79Docto

Extended Recurrence Plot Analysis and its Application to ERP Data

We present new measures of complexity and their application to event related potential data. The new measures base on structures of recurrence plots and makes the identification of chaos-chaos transitions possible. The application of these measures to data from single-trials of the Oddball experiment can identify laminar states therein. This offers a new way of analyzing event-related activity on a single-trial basis.Comment: 21 pages, 8 figures; article for the workshop ''Analyzing and Modelling Event-Related Brain Potentials: Cognitive and Neural Approaches`` at November 29 - December 01, 2001 in Potsdam, German

Forecast, observation and modelling of a deep stratospheric intrusion event over Europe

A wide range of measurements was carried out in central and southeastern Europe within the framework of the EU-project STACCATO (Influence of Stratosphere-Troposphere Exchange in a Changing Climate on Atmospheric Transport and Oxidation Capacity) with the principle goal to create a comprehensive data set on stratospheric air intrusions into the troposphere along a rather frequently observed pathway over central Europe from the North Sea to the Mediterranean Sea. The measurements were based on predictions by suitable quasi-operational trajectory calculations using ECMWF forecast data. A predicted deep Stratosphere to Troposphere Transport (STT) event, encountered during the STACCATO period on 20-21 June 2001, could be followed by the measurements network almost from its inception. Observations provide evidence that the intrusion affected large parts of central and southeastern Europe. Especially, the ozone lidar observations on 20-21 June 2001 at Garmisch-Partenkirchen, Germany captured the evolution of two marked tongues of high ozone with the first one reaching almost a height of 2 km, thus providing an excellent data set for model intercomparisons and validation. In addition, for the first time to our knowledge concurrent measurements of the cosmogenic radionuclides &lt;sup&gt;10&lt;/sup&gt;Be and &lt;sup&gt;7&lt;/sup&gt;Be and their ratio &lt;sup&gt;10&lt;/sup&gt;Be/&lt;sup&gt;7&lt;/sup&gt;Be are presented together as stratospheric tracers in a case study of a stratospheric intrusion. The ozone tracer columns calculated with the FLEXPART model were found to be in good agreement with water vapour satellite images, capturing the evolution of the observed dry streamers of stratospheric origin. Furthermore, the time-height cross section of ozone tracer simulated with FLEXPART over Garmisch-Partenkirchen captures with many details the evolution of the two observed high-ozone filaments measured with the IFU lidar, thus demonstrating the considerable progress in model simulations. Finally, the modelled ozone (operationally available since October 1999) from the ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric model is shown to be in very good agreement with the observations during this case study, which provides the first successful validation of a chemical tracer that is used operationally in a weather forecast model. This suggests that coupling chemistry and weather forecast models may significantly improve both weather and chemical forecasts in the future

On Thin Air Reads: Towards an Event Structures Model of Relaxed Memory

To model relaxed memory, we propose confusion-free event structures over an alphabet with a justification relation. Executions are modeled by justified configurations, where every read event has a justifying write event. Justification alone is too weak a criterion, since it allows cycles of the kind that result in so-called thin-air reads. Acyclic justification forbids such cycles, but also invalidates event reorderings that result from compiler optimizations and dynamic instruction scheduling. We propose the notion of well-justification, based on a game-like model, which strikes a middle ground. We show that well-justified configurations satisfy the DRF theorem: in any data-race free program, all well-justified configurations are sequentially consistent. We also show that rely-guarantee reasoning is sound for well-justified configurations, but not for justified configurations. For example, well-justified configurations are type-safe. Well-justification allows many, but not all reorderings performed by relaxed memory. In particular, it fails to validate the commutation of independent reads. We discuss variations that may address these shortcomings