nils-herrmann/clean_scirepeval huggingface dataset:
T-bar reconstruction of constricted ears and a new classification.

For the correction of constricted ears, many techniques are described in the literature, the majority based on Tanzer's classification of 1975. The improvements in ear reconstruction published by Brent, Nagata, Firmin and Park make better outcomes possible. It is therefore that a new classification for constricted ears is proposed, together with an alternative technique for correction of group IIA and IIB deformities, using a T-strut of costal cartilage to reconstruct the underdeveloped or missing superior crus of the antihelix.
Millisecond Coupling of Local Field Potentials to Synaptic Currents in the Awake Visual Cortex

The cortical local field potential (LFP) is a common measure of population activity, but its relationship to synaptic activity in individual neurons is not fully established. This relationship has been typically studied during anesthesia and is obscured by shared slow fluctuations. Here, we used patch-clamp recordings in visual cortex of anesthetized and awake mice to measure intracellular activity; we then applied a simple method to reveal its coupling to the simultaneously recorded LFP. LFP predicted membrane potential as accurately as synaptic currents, indicating a major role for synaptic currents in the relationship between cortical LFP and intracellular activity. During anesthesia, cortical LFP predicted excitation far better than inhibition; during wakefulness, it predicted them equally well, and visual stimulation further enhanced predictions of inhibition. These findings reveal a central role for synaptic currents, and especially inhibition, in the relationship between the subthreshold activity of individual neurons and the cortical LFP during wakefulness.
Introduction to E-commerce Learning Objectives

● To understand the complexity of e-commerce and its many facets. ● To explore how e-business and e-commerce fit together. ● To identify the impact of e-commerce. ● To recognise the benefits and limitations of e-commerce. ● To use classification frameworks for analysing e-commerce. ● To identify the main barriers to the growth and development of e-commerce in organisations.  Even today, some considerable time after the so called 'dot com/Internet revolution', electronic commerce (e-commerce) remains a relatively new, emerging and constantly changing area of business management and information technology. There has been and continues to be much publicity and discussion about e-commerce. Library catalogues and shelves are filled with books and articles on the subject. However, there remains a sense of confusion, suspicion and misunderstanding surrounding the area, which has been exacerbated by the different contexts in which electronic commerce is used, coupled with the myriad related buzzwords and acronyms. This book aims to consolidate the major themes that have arisen from the new area of electronic commerce and to provide an understanding of its application and importance to management. In order to understand electronic commerce it is important to identify the different terms that are used, and to assess their origin and usage. According to the editor-in-chief of International Journal of Electronic Commerce , Vladimir Zwass, 'Electronic commerce is sharing business information , maintaining business relationships and conducting business transactions by means of telecommunications networks'. 1 He maintains that in its purest form, electronic commerce has existed for over 40 years, originating from the electronic transmission of messages during the Berlin airlift in 1948. 2 From this, electronic data interchange (EDI) was the next stage of e-commerce development. In the 1960s a cooperative effort between industry groups produced a first attempt at common electronic data formats. The formats, however, were only for purchasing, transportation and finance data, and were used primarily for intra-industry transactions. It was not until the late 1970s that work began for national Electronic Data Interchange (EDI) standards, which developed well into the early 1990s. EDI is the electronic transfer of a standardised business transaction between a sender and receiver computer, over some kind of private network or value added network (VAN). Both sides would have to have the same application software and the data would be exchanged in an extremely rigorous format. In sectors such as retail, automotive, defence and heavy manufacturing, EDI was …
Understanding Replication in Databases and Distributed Systems

Replication is an area of interest to both distributed systems and databases. The solutions developed from these two perspectives are conceptually similar but differ in many aspects: model, assumptions, mechanisms, guarantees provided, and implementation. In this paper, we provide an abstract and “neutral” framework to compare replication techniques from both communities in spite of the many subtle differences. The framework has been designed to emphasize the role played by different mechanisms and to facilitate comparisons. With this, it is possible to get a functional comparison of many ideas that is valuable for both didactic and practical purposes. The paper describes the replication techniques used in both communities, compares them, and points out ways in which they can be integrated to arrive to better, more robust replication protocols.
Markov Localization for Mobile Robots in Dynamic Environments

Localization, that is the estimation of a robot's location from sensor data, is a fundamental problem in mobile robotics. This papers presents a version of Markov localization which provides accurate position estimates and which is tailored towards dynamic environments. The key idea of Markov localization is to maintain a probability density over the space of all locations of a robot in its environment. Our approach represents this space metrically, using a fine-grained grid to approximate densities. It is able to globally localize the robot from scratch and to recover from localization failures. It is robust to approximate models of the environment (such as occupancy grid maps) and noisy sensors (such as ultrasound sensors). Our approach also includes a filtering technique which allows a mobile robot to reliably estimate its position even in densely populated environments in which crowds of people block the robot's sensors for extended periods of time. The method described here has been implemented and tested in several real-world applications of mobile robots, including the deployments of two mobile robots as interactive museum tour-guides.  The Basic Idea Basic Notation Recursive Localization 1 of 2 12/10/00 10:59 AM Markov Localization for Mobile Robots in Dynaic Environments http://www.cs.cmu.edu/afs/cs/project/jair/pub/volume11/fox99a-html/jair-localize.html
A common database approach for OLTP and OLAP using an in-memory column database

When SQL and the relational data model were introduced 25 years ago as a general data management concept, enterprise software migrated quickly to this new technology. It is fair to say that SQL and the various implementations of RDBMSs became the backbone of enterprise systems. In those days. we believed that business planning, transaction processing and analytics should reside in one single system. Despite the incredible improvements in computer hardware, high-speed networks, display devices and the associated software, speed and flexibility remained an issue.
 The nature of RDBMSs, being organized along rows, prohibited us from providing instant analytical insight and finally led to the introduction of so-called data warehouses. This paper will question some of the fundamentals of the OLAP and OLTP separation. Based on the analysis of real customer environments and experience in some prototype implementations, a new proposal for an enterprise data management concept will be presented.
 In our proposal, the participants in enterprise applications, customers, orders, accounting documents, products, employees etc. will be modeled as objects and also stored and maintained as such. Despite that, the vast majority of business functions will operate on an in memory representation of their objects. Using the relational algebra and a column-based organization of data storage will allow us to revolutionize transactional applications while providing an optimal platform for analytical data processing. The unification of OLTP and OLAP workloads on a shared architecture and the reintegration of planning activities promise significant gains in application development while simplifying enterprise systems drastically.
 The latest trends in computer technology -- e.g. blade architecture, multiple CPUs per blade with multiple cores per CPU allow for a significant parallelization of application processes. The organization of data in columns supports the parallel use of cores for filtering and aggregation. Elements of application logic can be implemented as highly efficient stored procedures operating on columns. The vast increase in main memory combined with improvements in L1--, L2--, L3--caching, together with the high data compression rate column storage will allow us to support substantial data volumes on one single blade. Distributing data across multiple blades using a shared nothing approach provides further scalability.
Automatic Stance Detection Using End-to-End Memory Networks

We present an effective end-to-end memory network model that jointly (i) predicts whether a given document can be considered as relevant evidence for a given claim, and (ii) extracts snippets of evidence that can be used to reason about the factuality of the target claim. Our model combines the advantages of convolutional and recurrent neural networks as part of a memory network. We further introduce a similarity matrix at the inference level of the memory network in order to extract snippets of evidence for input claims more accurately. Our experiments on a public benchmark dataset, FakeNewsChallenge, demonstrate the effectiveness of our approach.
On Minimal Sets to Destroy the k-Core in Random Networks

We study the problem of finding the smallest set of nodes in a network whose removal results in an empty k-core; where the k-core is the sub-network obtained after the iterative removal of all nodes of degree smaller than k. This problem is also known in the literature as finding the minimal contagious set. The main contribution of our work is an analysis of the performance of the recently introduced corehd algorithm [Scientific Reports, 6, 37954 (2016)] on random networks taken from the configuration model via a set of deterministic differential equations. Our analyses provides upper bounds on the size of the minimal contagious set that improve over previously known bounds. Our second contribution is a new heuristic called the weak-neighbor algorithm that outperforms all currently known local methods in the regimes considered.
Stochastic Tracking of 3 D Human Figures Using 2 D Image Motion

A probabilistic method for tracking 3D articulated human gures in monocular image sequences is presented. Within a Bayesian framework, we de ne a generative model of image appearance, a robust likelihood function based on image graylevel di erences, and a prior probability distribution over pose and joint angles that models how humans move. The posterior probability distribution over model parameters is represented using a discrete set of samples and is propagated over time using particle ltering. The approach extends previous work on parameterized optical ow estimation to exploit a complex 3D articulated motion model. It also extends previous work on human motion tracking by including a perspective camera model, by modeling limb self occlusion, and by recovering 3D motion from a monocular sequence. The explicit posterior probability distribution represents ambiguities due to image matching, model singularities, and perspective projection. The method relies only on a frame-to-frame assumption of brightness constancy and hence is able to track people under changing viewpoints, in grayscale image sequences, and with complex unknown backgrounds.
Color Adjustment for Seamless Cloning Based on Laplacian-Membrane Modulation

Image compositing aims to combine elements from multiple images producing natural-looking results. The Poisson image editing framework can generate seamless compositions, but tends to introduce color changes in the inserted objects, which may generate unrealistic and unpleasing results. We present an efficient approach for controlling the amount of color preservation in the inserted objects, while ensuring a seamless transition between the foreground and background elements. Our technique modulates a Laplacian membrane according to some automatically computed parameter, which results in more naturally-looking compositions.
Multiview Hessian Regularization for Image Annotation

The rapid development of computer hardware and Internet technology makes large scale data dependent models computationally tractable, and opens a bright avenue for annotating images through innovative machine learning algorithms. Semisupervised learning (SSL) therefore received intensive attention in recent years and was successfully deployed in image annotation. One representative work in SSL is Laplacian regularization (LR), which smoothes the conditional distribution for classification along the manifold encoded in the graph Laplacian, however, it is observed that LR biases the classification function toward a constant function that possibly results in poor generalization. In addition, LR is developed to handle uniformly distributed data (or single-view data), although instances or objects, such as images and videos, are usually represented by multiview features, such as color, shape, and texture. In this paper, we present multiview Hessian regularization (mHR) to address the above two problems in LR-based image annotation. In particular, mHR optimally combines multiple HR, each of which is obtained from a particular view of instances, and steers the classification function that varies linearly along the data manifold. We apply mHR to kernel least squares and support vector machines as two examples for image annotation. Extensive experiments on the PASCAL VOC'07 dataset validate the effectiveness of mHR by comparing it with baseline algorithms, including LR and HR.
QoS-aware middleware for Web services composition

The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online business-to-business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different quality of service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming.
Smart Kitchen : A User Centric Cooking Support System

Several cooking support systems have been studied to give users instructions based on the recipes stepby-step, using multi-media contents. These systems usually disturb users’ cooking process forcing them to provide information to the system in order to give them beneficial information. In this sense, these systems are considered to be ”system centric”. We propose a system called ”Smart Kitchen” considered to be in ”user centric”, in which a user can cook normally without being concerned about the system. Smart Kitchen can understand cooking processes, in other words, what the user is doing. In this paper, we discuss the design of the Smart Kitchen system and explain three essential modules of tracking food, recognizing food material, and recognizing cooking action.
Proofs of Work and Bread Pudding Protocols

We formalize the notion of a proof of work. In many cryptographic protocols, a prover seeks to convince a veriier that she possesses knowledge of a secret or that a certain mathematical relation holds true. By contrast, in a proof of work, a prover demonstrates that she has performed a certain amount of computational work in a speciied interval of time. Proofs of work have served as the basis of a number of security protocols in the literature, but have hitherto lacked careful characterization. We also introduce the dependent idea of a bread pudding protocol. Bread pudding is a dish that originated with the purpose of re-using bread that has gone stale 10]. In the same spirit, we deene a bread pudding protocol to be a proof of work such that the computational eeort invested in the proof may also be harvested to achieve a separate, useful, and veriiably correct computation. As an example of a bread pudding protocol, we show how the MicroMint scheme of Rivest and Shamir can be broken up into a collection of proofs of work. These proofs of work can not only serve in their own right as mechanisms for security protocols, but can also be harvested in order to shift the burden of the MicroMint minting operation onto a large group of un-trusted computational devices.
Embedding Images and Sentences in a Common Space with a Recurrent Capsule Network

Associating texts and images is an easy and intuitive task for a human being, but it raises some issues if we want that task to be accomplished by a computer. Among these issues, there is the problem of finding a common representation for images and sentences. Based on recent research about capsule networks, we define a novel model to tackle that issue. This model is trained and compared to other recent models on the Flickr8k database on Image Retrieval and Image Annotation (or Sentence Retrieval) tasks. We propose a new recurrent architecture inspired from capsule networks to replace the traditional LSTM/GRU and show how it leads to improved performances. Moreover, we show that the interest of our model goes beyond its performances and includes its intrinsic characteristics, which can explain why it performs particularly well on the Image Annotation task. In addition, we propose a routing procedure between capsules which is fully learned during the training of our model.
Inductive logic programming

A new research area, Inductive Logic Programming, is presently emerging. While inheriting various positive characteristics of the parent subjects of Logic Programming and Machine Learning, it is hoped that the new area will overcome many of the limitations of its forebears. The background to present developments within this area is discussed and various goals and aspirations for the increasing body of researchers are identified. Inductive Logic Programming needs to be based on sound principles from both Logic and Statistics. On the side of statistical justification of hypotheses we discuss the possible relationship between Algorithmic Complexity theory and Probably-Approximately-Correct (PAC) Learning. In terms of logic we provide a unifying framework for Muggleton and Buntine’s Inverse Resolution (IR) and Plotkin’s Relative Least General Generalisation (RLGG) by rederiving RLGG in terms of IR. This leads to a discussion of the feasibility of extending the RLGG framework to allow for the invention of new predicates, previously discussed only within the context of IR.
Entertainment , Culture , and Media Art

This chapter is dedicated to explore the relationship between entertainment, culture, and media art. Firstly, the positioning of entertainment will be described including the historical point of view and also focusing on recent digital entertainment technologies. It will be clarified that entertainment is closely related to the mental sustainability of human and therefore has a close relationship with culture and art. Then, based on this, further investigation will be carried out to explain how culture and technology could be combined together. Firstly, the relationship between culture and technology will be discussed proposing the concept of “cultural computing.” Then three typical research examples of cultural computing, “ALICE,” “ZENetic Computer,” and “Confucius Chat” will be described emphasizing how cultural issues could be treated using computer both in the Western culture and Eastern culture. As art is the core part of culture, as a next step the role of art, especially new art called media art where technology plays an important role, will be discussed. And, as an example, media art created by an Eastern media artist will be introduced as a good example of such media art treating cultural issues.
Anatomy of GPU Memory System for Multi-Application Execution

As GPUs make headway in the computing landscape spanning mobile platforms, supercomputers, cloud and virtual desktop platforms, supporting concurrent execution of multiple applications in GPUs becomes essential for unlocking their full potential. However, unlike CPUs, multi-application execution in GPUs is little explored. In this paper, we study the memory system of GPUs in a concurrently executing multi-application environment. We first present an analytical performance model for many-threaded architectures and show that the common use of misses-per-kilo-instruction (MPKI) as a proxy for performance is not accurate without considering the bandwidth usage of applications. We characterize the memory interference of applications and discuss the limitations of existing memory schedulers in mitigating this interference. We extend the analytical model to multiple applications and identify the key metrics to control various performance metrics. We conduct extensive simulations using an enhanced version of GPGPU-Sim targeted for concurrently executing multiple applications, and show that memory scheduling decisions based on MPKI and bandwidth information are more effective in enhancing throughput compared to the traditional FR-FCFS and the recently proposed RR FR-FCFS policies.
A theory of formal synthesis via inductive learning

Formal synthesis is the process of generating a program satisfying a high-level formal specification. In recent times, effective formal synthesis methods have been proposed based on the use of inductive learning. We refer to this class of methods that learn programs from examples as formal inductive synthesis. In this paper, we present a theoretical framework for formal inductive synthesis. We discuss how formal inductive synthesis differs from traditional machine learning. We then describe oracle-guided inductive synthesis (OGIS), a framework that captures a family of synthesizers that operate by iteratively querying an oracle. An instance of OGIS that has had much practical impact is counterexample-guided inductive synthesis (CEGIS). We present a theoretical characterization of CEGIS for learning any program that computes a recursive language. In particular, we analyze the relative power of CEGIS variants where the types of counterexamples generated by the oracle varies. We also consider the impact of bounded versus unbounded memory available to the learning algorithm. In the special case where the universe of candidate programs is finite, we relate the speed of convergence to the notion of teaching dimension studied in machine learning theory. Altogether, the results of the paper take a first step towards a theoretical foundation for the emerging field of formal inductive synthesis.