nils-herrmann/clean_scirepeval huggingface dataset:
Fast locality-sensitive hashing

Locality-sensitive hashing (LSH) is a basic primitive in several large-scale data processing applications, including nearest-neighbor search, de-duplication, clustering, etc. In this paper we propose a new and simple method to speed up the widely-used Euclidean realization of LSH. At the heart of our method is a fast way to estimate the Euclidean distance between two d-dimensional vectors; this is achieved by the use of randomized Hadamard transforms in a non-linear setting. This decreases the running time of a (k, L)-parameterized LSH from O(dkL) to O(dlog d + kL). Our experiments show that using the new LSH in nearest-neighbor applications can improve their running times by significant amounts. To the best of our knowledge, this is the first running time improvement to LSH that is both provable and practical.
Comparison of Relational Database with Document-Oriented Database (MongoDB) for Big Data Applications

Database can accommodate a very large number of users on an on-demand basis. The main limitations with conventional relational database management systems (RDBMS) are that they are hard to scale with Data warehousing, Grid, Web 2.0 and Cloud applications, have non-linear query execution time, have unstable query plans and have static schema. Even though RDBMS's have provided database users with the best mix of simplicity, robustness, flexibility, performance, scalability and compatibility but they are not able to satisfy the present day users and applications for the reasons mentioned above. The next generation NonSQL (NoSQL) databases are mostly non-relational, distributed and horizontally scalable and are able to satisfy most of the needs of the present day applications. The main characteristics of these databases are schema-free, no join, non-relational, easy replication support, simple API and eventually consistent. The aim of this paper is to illustrate how a problem being solved using MySQL will perform when MongoDB is used on a Big data dataset. The results are encouraging and clearly showcase the comparisons made. Queries are executed on a big data airlines database using both MongoDB and MySQL. Select, update, delete and insert queries are executed and performance is evaluated.
Narcissism and the use of personal pronouns.

In this study we explored the relationship between narcissism and the individual's use of personal pronouns during extemporaneous monologues. The subjects, 24 males and 24 females, were asked to talk for approximately 5 minutes on any topic they chose. Following the monologues the subjects were administered the Narcissistic Personality Inventory, the Eysenck Personality Questionnaire, and the Rotter Internal-External Locus of Control Scale. The monologues were tape-recorded and later transcribed and analyzed for the subjects' use of personal pronouns. As hypothesized, individuals who scored higher on narcissism tended to use more first person singular pronouns and fewer first person plural pronouns. Discriminant validity for the relationship between narcissism and first person pronoun usage was exhibited in that narcissism did not show a relationship with subjects' use of second and third person pronouns, nor did the personality variables of extraversion, neuroticism, or locus of control exhibit any relationship with the subjects' personal pronoun usage.
Platform-Based Design and Software Design Methodology for Embedded Systems

0740-7475/01/$10.00  The choice of implementation architecture determines whether designers will implement a function as a hardware component or as software running on a programmable component. In recent years, the functions demanded for embedded systems have grown so numerous and complex that development time is increasingly difficult to predict and control. This complexity, coupled with constantly evolving specifications, has forced designers to consider intrinsically flexible implementations—those they can change rapidly. For this reason, and because hardware-manufacturing cycles are more expensive and time-consuming, softwarebased implementation has become more popular. Processors’ increased computational power and correspondingly decreased size and cost let designers move increasingly more functionality to software. However, along with this move comes increasing difficulty in verifying design correctness. This verification is critical due to safety considerations in several application domains— transportation and environment monitoring, for example. In traditional, PC-like software applications, these safety issues typically don’t come up. In addition, the software world has paid little attention to hard constraints on software’s reaction speed, memory footprint, and power consumption—all crucial issues for embedded systems—because they are relatively unimportant in traditional software development. In embedded-systems design, such hard software characteristics are unavoidable. It is no wonder, then, that there is a crisis in embedded-software design. Along with the pressure on system designers to choose flexible implementations, the industry is also witnessing IC manufacturers’ growing preference for chips that will work for several designs. This lets manufacturers amortize development cost over a large number of units, as discussed in the sidebar, “Motivations for platform-based design.” This alignment of designers and manufacturers has resulted in the birth of platform-based design,1,2 in which reuse and programmability are key. We believe that addressing the embedded Platform-Based Design and Software Design Methodology for Embedded Systems
Cloud Terminal: Secure Access to Sensitive Applications from Untrusted Systems

Current PCand web-based applications provide insufficient security for the information they access, because vulnerabilities anywhere in a large client software stack can compromise confidentiality and integrity. We propose a new architecture for secure applications, Cloud Terminal, in which the only software running on the end host is a lightweight secure thin terminal, and most application logic is in a remote cloud rendering engine. The secure thin terminal has a very small TCB (23 KLOC) and no dependence on the untrusted OS, so it can be easily checked and remotely attested to. The terminal is also general-purpose: it simply supplies a secure display and input path to remote software. The cloud rendering engine runs an off-the-shelf application in a restricted VM hosted by the provider, but resource sharing between VMs lets one server support hundreds of users. We implement a secure thin terminal that runs on standard PC hardware and provides a responsive interface to applications like banking, email, and document editing. We also show that our cloud rendering engine can provide secure online banking for 5–10 cents per user per month.
Keeping Authorities "Honest or Bust" with Decentralized Witness Cosigning

The secret keys of critical network authorities -- such as time, name, certificate, and software update services -- represent high-value targets for hackers, criminals, and spy agencies wishing to use these keys secretly to compromise other hosts. To protect authorities and their clients proactively from undetected exploits and misuse, we introduce CoSi, a scalable witness cosigning protocol ensuring that every authoritative statement is validated and publicly logged by a diverse group of witnesses before any client will accept it. A statement S collectively signed by W witnesses assures clients that S has been seen, and not immediately found erroneous, by those W observers. Even if S is compromised in a fashion not readily detectable by the witnesses, CoSi still guarantees S's exposure to public scrutiny, forcing secrecy-minded attackers to risk that the compromise will soon be detected by one of the W witnesses. Because clients can verify collective signatures efficiently without communication, CoSi protects clients' privacy, and offers the first transparency mechanism effective against persistent man-in-the-middle attackers who control a victim's Internet access, the authority's secret key, and several witnesses' secret keys. CoSi builds on existing cryptographic multisignature methods, scaling them to support thousands of witnesses via signature aggregation over efficient communication trees. A working prototype demonstrates CoSi in the context of timestamping and logging authorities, enabling groups of over 8,000 distributed witnesses to cosign authoritative statements in under two seconds.
Fingerprint Matrices: Uncovering the dynamics of social networks in prose literature

In prose literature often complex dynamics of interpersonal relationships can be observed between the different characters. Traditionally, node-link diagrams are used to depict the social network of a novel. However, static graphs can only visualize the overall social network structure but not the development of the networks over the course of the story, while dynamic graphs have the serious problem that there are many sudden changes between different portions of the overall social network. In this paper we explore means to show the relationships between the characters of a plot and at the same time their development over the course of a novel. Based on a careful exploration of the design space, we suggest a new visualization technique called Fingerprint Matrices. A case study exemplifies the usage of Fingerprint Matrices and shows that they are an effective means to analyze prose literature with respect to the development of relationships between the different characters.
5G Radio Access: Requirements, Concept and Experimental Trials

Currently, many operators worldwide are deploying Long Term Evolution (LTE) to provide much faster access with lower latency and higher efficiency than its predecessors 3G and 3.5G. Meanwhile, the service rollout of LTE-Advanced, which is an evolution of LTE and a “true 4G” mobile broadband, is being underway to further enhance LTE performance. However, the anticipated challenges of the next decade (2020s) are so tremendous and diverse that there is a vastly increased need for a new generation mobile communications system with even further enhanced capabilities and new functionalities, namely a fifth generation (5G) system. Envisioning the development of a 5G system by 2020, at DOCOMO we started studies on future radio access as early as 2010, just after the launch of LTE service. The aim at that time was to anticipate the future user needs and the requirements of 10 years later (2020s) in order to identify the right concept and radio access technologies for the next generation system. The identified 5G concept consists of an efficient integration of existing spectrum bands for current cellular mobile and future new spectrum bands including higher frequency bands, e.g., millimeter wave, with a set of spectrum specific and spectrum agnostic technologies. Since a few years ago, we have been conducting several proof-of-concept activities and investigations on our 5G concept and its key technologies, including the development of a 5G real-time simulator, experimental trials of a wide range of frequency bands and technologies and channel measurements for higher frequency bands. In this paper, we introduce an overview of our views on the requirements, concept and promising technologies for 5G radio access, in addition to our ongoing activities for paving the way toward the realization of 5G by 2020. key words: next generation mobile communications system, 5G, 4G, LTE, LTE-advanced
Resin bond to indirect composite and new ceramic/polymer materials: a review of the literature.

Resin bonding is essential for clinical longevity of indirect restorations. Especially in light of the increasing popularity of computer-aided design/computer-aided manufacturing-fabricated indirect restorations, there is a need to assess optimal bonding protocols for new ceramic/polymer materials and indirect composites.



The aim of this article was to review and assess the current scientific evidence on the resin bond to indirect composite and new ceramic/polymer materials.



An electronic PubMed database search was conducted from 1966 to September 2013 for in vitro studies pertaining the resin bond to indirect composite and new ceramic/polymer materials.



The search revealed 198 titles. Full-text screening was carried out for 43 studies, yielding 18 relevant articles that complied with inclusion criteria. No relevant studies could be identified regarding new ceramic/polymer materials. Most common surface treatments are aluminum-oxide air-abrasion, silane treatment, and hydrofluoric acid-etching for indirect composite restoration. Self-adhesive cements achieve lower bond strengths in comparison with etch-and-rinse systems. Thermocycling has a greater impact on bonding behavior than water storage.



Air-particle abrasion and additional silane treatment should be applied to enhance the resin bond to laboratory-processed composites. However, there is an urgent need for in vitro studies that evaluate the bond strength to new ceramic/polymer materials.



This article reviews the available dental literature on resin bond of laboratory composites and gives scientifically based guidance for their successful placement. Furthermore, this review demonstrated that future research for new ceramic/polymer materials is required.
Different Users, Different Opinions: Predicting Search Satisfaction with Mouse Movement Information

Satisfaction prediction is one of the prime concerns in search performance evaluation. It is a non-trivial task for two major reasons: (1) The definition of satisfaction is rather subjective and different users may have different opinions in satisfaction judgement. (2) Most existing studies on satisfaction prediction mainly rely on users' click-through or query reformulation behaviors but there are many sessions without such kind of interactions. To shed light on these research questions, we construct an experimental search engine that could collect users' satisfaction feedback as well as mouse click-through/movement data. Different from existing studies, we compare for the first time search users' and external assessors' opinions on satisfaction. We find that search users pay more attention to the utility of results while external assessors emphasize on the efforts spent in search sessions. Inspired by recent studies in predicting result relevance based on mouse movement patterns (namely motifs), we propose to estimate the utilities of search results and the efforts in search sessions with motifs extracted from mouse movement data on search result pages (SERPs). Besides the existing frequency-based motif selection method, two novel selection strategies (distance-based and distribution-based) are also adopted to extract high quality motifs for satisfaction prediction. Experimental results on over 1,000 user sessions show that the proposed strategies outperform existing methods and also have promising generalization capability for different users and queries.
Shake, rattle, ‘n’ roll: the representation of motion in language and cognition

Languages vary strikingly in how they encode motion events. In some languages (e.g. English), manner of motion is typically encoded within the verb, while direction of motion information appears in modifiers. In other languages (e.g. Greek), the verb usually encodes the direction of motion, while the manner information is often omitted, or encoded in modifiers. We designed two studies to investigate whether these language-specific patterns affect speakers' reasoning about motion. We compared the performance of English and Greek children and adults (a) in nonlinguistic (memory and categorization) tasks involving motion events, and (b) in their linguistic descriptions of these same motion events. Even though the two linguistic groups differed significantly in terms of their linguistic preferences, their performance in the nonlinguistic tasks was identical. More surprisingly, the linguistic descriptions given by subjects within language also failed to correlate consistently with their memory and categorization performance in the relevant regards. For the domain studied, these results are consistent with the view that conceptual development and organization are largely independent of language-specific labeling practices. The discussion emphasizes that the necessarily sketchy nature of language use assures that it will be at best a crude index of thought.
A virtual memory based runtime to support multi-tenancy in clusters with GPUs

Graphics Processing Units (GPUs) are increasingly becoming part of HPC clusters. Nevertheless, cloud computing services and resource management frameworks targeting heterogeneous clusters including GPUs are still in their infancy. Further, GPU software stacks (e.g., CUDA driver and runtime) currently provide very limited support to concurrency.
 In this paper, we propose a runtime system that provides abstraction and sharing of GPUs, while allowing isolation of concurrent applications. A central component of our runtime is a memory manager that provides a virtual memory abstraction to the applications. Our runtime is flexible in terms of scheduling policies, and allows dynamic (as opposed to programmer-defined) binding of applications to GPUs. In addition, our framework supports dynamic load balancing, dynamic upgrade and downgrade of GPUs, and is resilient to their failures. Our runtime can be deployed in combination with VM-based cloud computing services to allow virtualization of heterogeneous clusters, or in combination with HPC cluster resource managers to form an integrated resource management infrastructure for heterogeneous clusters. Experiments conducted on a three-node cluster show that our GPU sharing scheme allows up to a 28% and a 50% performance improvement over serialized execution on short- and long-running jobs, respectively. Further, dynamic inter-node load balancing leads to an additional 18-20% performance benefit.
The evolution matrix: recovering software evolution using software visualization techniques

One of the major problems in software evolution is coping with the complexity which stems from the huge amount of data that must be considered. The current approaches to deal with that problem all aim at a reduction of complexity and a filtering of the relevant information. In this paper we propose an approach based on a combination of software visualization and software metrics which we have already successfully applied in the field of software reverse engineering. Using this approach we discuss a simple and effective way to visualize the evolution of software systems which helps to recover the evolution of object oriented software systems.
Attribute-Based Secure Data Sharing with Hidden Policies in Smart Grid

Smart grid uses intelligent transmission and distribution networks to deliver electricity. It aims to improve the electric system's reliability, security, and efficiency through two-way communication of consumption data and dynamic optimization of electric-system operations, maintenance, and planning. The smart grid systems use fine-grained power grid measurements to provide increased grid stability and reliability. Key to achieving this is securely sharing the measurements among grid entities over wide area networks. Typically, such sharing follows policies that depend on data generator and consumer preferences and on time-sensitive contexts. In smart grid, as well as the data, policies for sharing the data may be sensitive because they directly contain sensitive information, and reveal information about underlying data protected by the policy, or about the data owner or recipients. In this study, we propose an attribute-based data sharing scheme in smart grid. Not only the data but also the access policies are obfuscated in grid operators' point of view during the data sharing process. Thus, the data privacy and policy privacy are preserved in the proposed scheme. The access policy can be expressed with any arbitrary access formula. Thus, the expressiveness of the policy is enhanced. The security is also improved such that the unauthorized key generation center or the grid manage systems that store the data cannot decrypt the data to be shared. The computation overhead of recipients are also reduced by delegating most of the laborious decryption operations to the more powerful grid manage systems.
Femtocell networks: a survey

The surest way to increase the system capacity of a wireless link is by getting the transmitter and receiver closer to each other, which creates the dual benefits of higher-quality links and more spatial reuse. In a network with nomadic users, this inevitably involves deploying more infrastructure, typically in the form of microcells, hot spots, distributed antennas, or relays. A less expensive alternative is the recent concept of femtocells - also called home base stations - which are data access points installed by home users to get better indoor voice and data coverage. In this article we overview the technical and business arguments for femtocells and describe the state of the art on each front. We also describe the technical challenges facing femtocell networks and give some preliminary ideas for how to overcome them.
Novelty Detection with GAN

The ability of a classifier to recognize unknown inputs is important for many classification-based systems. We discuss the problem of simultaneous classification and novelty detection, i.e. determining whether an input is from the known set of classes and from which specific class, or from an unknown domain and does not belong to any of the known classes. We propose a method based on the Generative Adversarial Networks (GAN) framework. We show that a multi-class discriminator trained with a generator that generates samples from a mixture of nominal and novel data distributions is the optimal novelty detector. We approximate that generator with a mixture generator trained with the Feature Matching loss and empirically show that the proposed method outperforms conventional methods for novelty detection. Our findings demonstrate a simple, yet powerful new application of the GAN framework for the task of novelty detection.
A Fast Algorithm and System for the Inverse Kinematics of General Serial Manipulators

We present fast and robust algorithms for the inverse kinematics of serial manipulators consisting of six or fewer joints. When stated mathematically, the problem of inverse kinematics reduces to simultaneously solving a system of algebraic equations. In this paper, we use a series of algebraic and numeric transformations to reduce the problem to computing the eigenstructure of a matrix pencil. To e ciently compute the eigenstructure, we make use of the symbolic formulation of the matrix and use a number of techniques from linear algebra and matrix computations. The resulting algorithm computes all the solution of a serial manipulator with six or fewer joints in the order of tens of milliseconds on the current workstations. It has been implemented as part of a generic package, KINEM, for the inverse kinematics of serial manipulators.
MegaFace: A Million Faces for Recognition at Scale

Recent face recognition experiments on the LFW [13] benchmark show that face recognition is performing stunningly well, surpassing human recognition rates. In this paper, we study face recognition at scale. Specifically, we have collected from Flickr a Million faces and evaluated state of the art face recognition algorithms on this dataset. We found that the performance of algorithms varies–while all perform great on LFW, once evaluated at scale recognition rates drop drastically for most algorithms. Interestingly, deep learning based approach by [23] performs much better, but still gets less robust at scale. We consider both verification and identification problems, and evaluate how pose affects recognition at scale. Moreover, we ran an extensive human study on Mechanical Turk to evaluate human recognition at scale, and report results. All the photos are creative commons photos and are released for research and further experiments on http://megaface. cs.washington.edu.