nils-herrmann/clean_scirepeval huggingface dataset:
Innovative Technology for CPU Based Attestation and Sealing Ittai

Intel is developing the Intel® Software Guard Extensions (Intel® SGX) technology, an extension to Intel® Architecture for generating protected software containers. The container is referred to as an enclave. Inside the enclave, software’s code, data, and stack are protected by hardware enforced access control policies that prevent attacks against the enclave’s content. In an era where software and services are deployed over the Internet, it is critical to be able to securely provision enclaves remotely, over the wire or air, to know with confidence that the secrets are protected and to be able to save secrets in non-volatile memory for future use. This paper describes the technology components that allow provisioning of secrets to an enclave. These components include a method to generate a hardware based attestation of the software running inside an enclave and a means for enclave software to seal secrets and export them outside of the enclave (for example store them in non-volatile memory) such that only the same enclave software would be able un-seal them back to their original form.
Query-Oriented Data Cleaning with Oracles

As key decisions are often made based on information contained in a database, it is important for the database to be as complete and correct as possible. For this reason, many data cleaning tools have been developed to automatically resolve inconsistencies in databases. However, data cleaning tools provide only best-effort results and usually cannot eradicate all errors that may exist in a database. Even more importantly, existing data cleaning tools do not typically address the problem of determining what information is missing from a database.
 To overcome the limitations of existing data cleaning techniques, we present QOCO, a novel query-oriented system for cleaning data with oracles. Under this framework, incorrect (resp. missing) tuples are removed from (added to) the result of a query through edits that are applied to the underlying database, where the edits are derived by interacting with domain experts which we model as oracle crowds. We show that the problem of determining minimal interactions with oracle crowds to derive database edits for removing (adding) incorrect (missing) tuples to the result of a query is NP-hard in general and present heuristic algorithms that interact with oracle crowds. Finally, we implement our algorithms in our prototype system QOCO and show that it is effective and efficient through a comprehensive suite of experiments.
Prevention and management of vision loss relating to facial filler injections.

With the increased use of filler and fat injections for aesthetic purposes, there has been a corresponding increase in the incidence of complications. Vision loss as an uncommon but devastating vascular side effect of filler injections was the focus of this paper.



A review committee, consisting of plastic surgeons, aesthetic medical practitioners, ophthalmologists and dermatologists from Singapore, was convened by the Society of Aesthetic Medicine (Singapore) to review and recommend methods for the prevention and management of vision loss secondary to filler injections.



The committee agreed that prevention through proper understanding of facial anatomy and good injection techniques was of foremost importance. The committee acknowledged that there is currently no standard management for these cases. Based on existing knowledge, injectors may follow a proposed course of action, which can be divided into immediate, definitive and supportive. The goals were to reduce intraocular pressure, dislodge the embolus to a more peripheral location, remove or reverse central ischaemia, preserve residual retinal function, and prevent the deterioration of vision. Dissolving a hyaluronic acid embolus remains a controversial option. It is proposed that injectors must be trained to recognise symptoms, institute immediate actions and refer patients without delay to dedicated specialists for definitive and supportive management.



Steps to prevent and manage vision loss based on current evidence and best clinical practices are outlined in this paper. Empirical referral to any emergency department or untrained doctors may lead to inordinate delays and poor outcomes for the affected eye.
Consumer responsiveness to mobile marketing

From a marketing communication point of view, new digital marketing channels, such as Internet and mobile phones, are considered to be powerful opportunities to reach consumers by allowing interactivity and personalisation of the content and context of the message. The increased number of media has, however, led to a harder competition for consumers’ attention. Given the potential of digital media it is interesting to understand how consumers are going to relate to mobile marketing efforts. The purpose of the paper was to explore consumers’ responsiveness to mobile marketing communication. With mobile marketing we refer to the use of SMS and MMS as marketing media in push campaigns. It is argued in the paper that consumer responsiveness is a function of personally perceived relevance of the marketing message as well as on the disturbance/acceptance of the context of receiving the message. A relevance/disturbance framework can thus measure the effectiveness of mobile marketing communication. An empirical study was conducted in Finland, where responsiveness to mobile marketing was benchmarked against e-mail communication. Findings from this study indicated that responsiveness to mobile marketing communication varies among consumers. Compared to traditional direct mail and commercial email communication, the responsiveness to mobile marketing was considerably lower. However, even if the majority of consumers showed low responsiveness to mobile marketing there were also consumers who welcome such messages.
The five W's of "bullying" on Twitter: Who, What, Why, Where, and When

This paper explores the utility of machine learning methods for understanding bullying, a significant social-psychological issue in the United States, through social media data. Machine learning methods were applied to all public mentions of bullying on Twitter between September 1, 2011 and August 31, 2013 to extract the posts that referred to discrete bullying episodes (N = 9,764,583) to address five key questions. Most posts were authored by victims and reporters and referred to general forms of bullying. Posts frequently reflected self-disclosure about personal involvement in bullying. The number of posts that originated from a state was positively associated with the state population size; the timing of the posts reveal that more posts were made on weekdays than on Saturdays and more posts were made during the evening compared to daytime hours. Potential benefits of merging social science and computer science methods to enhance the study of bullying are discussed.
Chemical Reactant Recommendation Using a Network of Organic Chemistry

This paper focuses on the overall task of recommending to the chemist candidate molecules (reactants) necessary to synthesize a given target molecule (product), which is a novel application as well as an important step for the chemist to find a synthesis route to generate the product. We formulate this task as a link-prediction problem over a so-called Network of Organic Chemistry (NOC) that we have constructed from 8 million chemical reactions described in the US patent literature between 1976 and 2013. We leverage state-of-the-art factorization algorithms for recommender systems to solve this task. Our empirical evaluation demonstrates that Factorization Machines, trained with chemistry-specific knowledge, outperforms current methods based on similarity of chemical structures.
The prize collecting Steiner tree problem: theory and practice

We consider variants on the Prize Collecting Steiner Tree problem and on the primal-dual 2-approximation algorithm devised for it by Goemans and Williamson. We introduce an improved pruning rule for the algorithm that is slightly faster and provides solutions that are at least as good and typically significantly better. On a selection of real-world instances whose underlying graphs are county street maps, the improvement in the standard objective function ranges from 1.7% to 9.2%. Substantially better improvements are obtained for the complementary "net worth" objective function and for randomly generated instances. We also show that modifying the growth phase of the GoemansWilliamson algorithm to make it independent of the choice of root vertex does not significantly affect the algorithm's worst-case guarantee or behavior in practice. The resulting algorithm can be fttrther modified so that, without an increase in running time, it becomes a 2-approximation algorithm for finding the best subtree over all choices of root. In the second part of the paper, we consider quota and budget versions of the problem. In the first, one is looking for the tree with minimum edge cost that contains vertices whose total prize is at least a given quota; in the second one is looking for the tree with maximum prize, given that the total edge cost is within a given budget. The quota problem is a generalization of the k-MST problem, and we observe how constant-factor approximation algorithms for that problem can be extended to it. We also show how a (5 ÷ e)approximation algorithm for the (unrooted) budget problem can be derived from Gaxg's 3-approximation algorithm for the k-MST. None of these algorithms are likely to be used in ~ ractice, but we show how the general approach behind them which involves performing multiple runs of the GoemansWiUiamson algorithm using an increasing sequence of prizemultipliers) can be incorporated into a practical heuristic. We also uncover some surprising properties of the cost/prize tradeoff curves generated (and used) by this approach. 1 Prob lem Def in i t ions In the Prize Collecting Steiner Tree" (PCST) problem, one is given a graph G = (V, E) , a non-negative edge cost c(e) for each edge e 6 E , a non-negative vertex prize p(v) for each vertex v 6 V, and a specified root vertex vo 6 V. In this paper we shall consider four different optimization problems based on this scenario, the first being the one initially studied in [6, 7]: " ¢ / ~ T Labs, Room C239, 180 Park Avenue, Florham Park, NJ 07932.  dsj@research.att.com ?MIT Lab. for Computer Science, 545 Tech Square, Cambridge, MA 02139.  The Goemans-WiUiamson Minimization problem: Find a subtree T ' = (V',E') of G tha t minimizes the cost of the edges in the tree plus the prizes of the vertices not in the tree, i.e., tha t minimizes GW(T') = Z c(e) + Z p(v)
Vision based terrain recovery for landing unmanned aerial vehicles

We propose a system for landing unmanned aerial vehicles (UAV), specifically an autonomous rotorcraft, in uncontrolled, arbitrary, terrains. We present plans for and progress on a vision-based system for the recovery of the geometry and material properties of local terrain from a mounted stereo rig for the purposes of finding an optimal landing site. A system is developed which integrates motion estimation from tracked features, and an algorithm for approximate estimation of a dense elevation map in a world coordinate system.
Visual and semantic similarity in ImageNet

Many computer vision approaches take for granted positive answers to questions such as “Are semantic categories visually separable?” and “Is visual similarity correlated to semantic similarity?”. In this paper, we study experimentally whether these assumptions hold and show parallels to questions investigated in cognitive science about the human visual system. The insights gained from our analysis enable building a novel distance function between images assessing whether they are from the same basic-level category. This function goes beyond direct visual distance as it also exploits semantic similarity measured through ImageNet. We demonstrate experimentally that it outperforms purely visual distances.
A Scalable Distributed Graph Partitioner

We present Scalable Host-tree Embeddings for Efficient Partitioning (Sheep), a distributed graph partitioning algorithm capable of handling graphs that far exceed main memory. Sheep produces high quality edge partitions an order of magnitude faster than both state of the art offline (e.g., METIS) and streaming partitioners (e.g., Fennel). Sheep’s partitions are independent of the input graph distribution, which means that graph elements can be assigned to processing nodes arbitrarily without affecting the partition quality. Sheep transforms the input graph into a strictly smaller elimination tree via a distributed map-reduce operation. By partitioning this tree, Sheep finds an upper-bounded communication volume partitioning of the original graph. We describe the Sheep algorithm and analyze its spacetime requirements, partition quality, and intuitive characteristics and limitations. We compare Sheep to contemporary partitioners and demonstrate that Sheep creates competitive partitions, scales to larger graphs, and has better runtime.
A Hybrid Cloud Approach for Secure Authorized Deduplication

Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. To protect the confidentiality been proposed to encrypt the data before outsourcing. To better protect data security, this paper makes the first attempt to formally address the problem of authorized data deduplication. Different from traditional deduplication systems, the differential privileges of users are further considered in duplicate check besides the data itself. We also present several new deduplication constructions supporting authorized duplicate check in a hybrid cloud architecture. Security analysis demonstrates that our scheme is secure in terms of the definitions specified in the proposed security model. As a proof of concept, we implement a prototype of our proposed authorized duplicate check scheme and conduct testbed experiments using our prototype. We show that our proposed authorized duplicate check scheme incurs minimal overhead compared to normal operations.
INTEGRATED BRAKING AND STEERING MODEL PREDICTIVE CONTROL APPROACH IN AUTONOMOUS VEHICLES

In this paper we present a Model Predictive Control (MPC) approach for combined braking and steering systems in autonomous vehicles. We start from the result presented in (Borrelli et al. (2005)) and (Falcone et al. (2007a)), where a Model Predictive Controller (MPC) for autonomous steering systems has been presented. As in (Borrelli et al. (2005)) and (Falcone et al. (2007a)) we formulate an MPC control problem in order to stabilize a vehicle along a desired path. In the present paper, the control objective is to best follow a given path by controlling the front steering angle and the brakes at the four wheels independently, while fulfilling various physical and design constraints.
ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation

We propose a structured prediction architecture, which exploits the local generic features extracted by Convolutional Neural Networks and the capacity of Recurrent Neural Networks (RNN) to retrieve distant dependencies. The proposed architecture, called ReSeg, is based on the recently introduced ReNet model for image classification. We modify and extend it to perform the more challenging task of semantic segmentation. Each ReNet layer is composed of four RNN that sweep the image horizontally and vertically in both directions, encoding patches or activations, and providing relevant global information. Moreover, ReNet layers are stacked on top of pre-trained convolutional layers, benefiting from generic local features. Upsampling layers follow ReNet layers to recover the original image resolution in the final predictions. The proposed ReSeg architecture is efficient, flexible and suitable for a variety of semantic segmentation tasks. We evaluate ReSeg on several widely-used semantic segmentation datasets: Weizmann Horse, Oxford Flower, and CamVid, achieving stateof-the-art performance. Results show that ReSeg can act as a suitable architecture for semantic segmentation tasks, and may have further applications in other structured prediction problems. The source code and model hyperparameters are available on https://github.com/fvisin/reseg.
Description Logic for Vision-Based Intersection Understanding

Road recognition from video sequences has been solved robustly only for small, often simplified subsets of possible road configurations. A massive augmentation of the amount of prior knowledge may pave the way towards a generation of estimators of more general applicability. This contribution introduces Description Logic extended by rules as a promising knowledge representation formalism for scene understanding. A Description Logic knowledge base for arbitrary road and intersection geometries and configurations is set up. Logically stated geometric constraints and road building regulations constrain the hypothesis space. Sensor data from an in-vehicle vision sensor and from a digital map provide evidence for a particular intersection. Partial observability and different abstraction layers of the input data are naturally handled. Deductive inference services – namely classification, entailment, satisfiability and consistency – are then used to narrow down the intersection hypothesis space based on the evidence and the background knowledge, and to retrieve intersection information relevant to a user, i.e. a human or a driver assistance system. The paper concludes with an outlook towards non-deductive inference, namely model construction, and probabilistic inference.
Middleware for Mobile Computing

Recent advances in wireless networking technologies and the growing success of mobile computing devices, such as laptop computers, third generation mobile phones, personal digital assistants, watches and the like, are enabling new classes of applications that present challenging problems to designers. Mobile devices face temporary loss of network connectivity when they move; they are likely to have scarce resources, such as low battery power, slow CPU speed and little memory; they are required to react to frequent and unannounced changes in the environment, such as high variability of network bandwidth, and in the remote resources availability, and so on. To support designers building mobile applications, research in the field of middleware systems has proliferated. Middleware aims at facilitating communication and coordination of distributed components, concealing difficulties raised by mobility from application engineers as much as possible. In this survey, we examine characteristics of mobile distributed systems and distinguish them from their fixed counterpart. We introduce a framework and a categorization of the various middleware systems designed to support mobility, and we present a detailed and comparative review of the major results reached in this field. An analysis of current trends inside the mobile middleware community and a discussion of further directions of research conclude the survey.
An improved GA and a novel PSO-GA-based hybrid algorithm

Inspired by the natural features of the variable size of the population, we present a variable population-size genetic (VPGA) by introducing the “dying probab ility” for the i ndividuals and the “war/disease pro cess” for the population. Based o the VPGA and the particle swarm optimization (PSO) algor ithms, a novel PSO-GA-based hybrid algorithm (PGHA) is a proposed in this paper. Simulation results show that both VPGA and PGHA are effective for the optimization problems  2004 Elsevier B.V. All rights reserved.
1.8 mΩcm2, 10 A Power MOSFET in 4H-SiC

The power MOSFET on 4H-SiC is an attractive high-speed and low-dissipation power switching device. The problem to be solved before realizing the 4H-SiC power MOSFET with low on-resistance is low channel mobility at the SiO2/SiC interface. This work has succeeded in increasing the channel mobility in the buried channel IEMOSFET on carbon-face substrate, and has achieved an extremely low on-resistance of 1.8 mΩcm2 with a blocking voltage of 660 V
Design of Ultra-Wideband Three-Way Arbitrary Power Dividers

A method to design arbitrary three-way power dividers with ultra-wideband performance is presented. The proposed devices utilize a broadside-coupled structure, which has three coupled layers. The method assumes general asymmetric coupled layers. The design approach exploits the three fundamental modes of propagation: even-even, odd-odd, and odd-even, and the conformal mapping technique to find the coupling factors between the different layers. The method is used to design 1 : 1 : 1, 2 : 1 : 1, and 4 : 2 : 1 three-way power dividers. The designed devices feature a multilayer broadside-coupled microstrip-slot-microstrip configuration using elliptical-shaped structures. The developed power dividers have a compact size with an overall dimension of 20 mm 30 mm. The simulated and measured results of the manufactured devices show an insertion loss equal to the nominated value 1 dB. The return loss for the input/output ports of the devices is better than 17, 18, and 13 dB, whereas the isolation between the output ports is better than 17, 14, and 15 dB for the 1 : 1 : 1, 2 : 1 : 1, and 4 : 2 : 1 dividers, respectively, across the 3.1-10.6-GHz band.
HeteSim: A General Framework for Relevance Measure in Heterogeneous Networks

Similarity search is an important function in many applications, which usually focuses on measuring the similarity between objects with the same type. However, in many scenarios, we need to measure the relatedness between objects with different types. With the surge of study on heterogeneous networks, the relevance measure on objects with different types becomes increasingly important. In this paper, we study the relevance search problem in heterogeneous networks, where the task is to measure the relatedness of heterogeneous objects (including objects with the same type or different types). A novel measure HeteSim is proposed, which has the following attributes: (1) a uniform measure: it can measure the relatedness of objects with the same or different types in a uniform framework; (2) a path-constrained measure: the relatedness of object pairs are defined based on the search path that connects two objects through following a sequence of node types; (3) a semi-metric measure: HeteSim has some good properties (e.g., selfmaximum and symmetric), which are crucial to many data mining tasks. Moreover, we analyze the computation characteristics of HeteSim and propose the corresponding quick computation strategies. Empirical studies show that HeteSim can effectively and efficiently evaluate the relatedness of heterogeneous objects.