nils-herrmann/clean_scirepeval huggingface dataset:
Efficient Hardware Hashing Functions for High Performance Computers

Hashing is critical for high performance computer architecture. Hashing is used extensively in hardware applications, such as page tables, for address translation. Bit extraction and exclusive ORing hashing “methods” are two commonly used hashing functions for hardware applications. There is no study of the performance of these functions and no mention anywhere of the practical performance of the hashing functions in comparison with the theoretical performance prediction of hashing schemes. In this paper, we show that, by choosing hashing functions at random from a particular class, called H3, of hashing functions, the analytical performance of hashing can be achieved in practice on real-life data. Our results about the expected worst case performance of hashing are of special significance, as they provide evidence for earlier theoretical predictions. Index Terms —Hashing in hardware, high performance computer architecture, page address translation, signature functions, high speed information storage and retrieval.
Current-Sensorless Power-Decoupling Phase-Shift Dual-Half-Bridge Converter for DC–AC Power Conversion Systems Without Electrolytic Capacitor

In this paper, a novel DHB power-decoupling control scheme without current sensor is proposed for single-phase inverters. As electrolyte capacitors are conventionally used; however, these capacitors limit ripple current capability and circuit reliability. Film capacitors improve the ripple current capability, size reduction, and circuit reliability. Conventionally, non-isolated topologies are used for power decoupling. The volume of the decoupling capacitor per unit energy in isolated bidirectional power decoupling topologies is reduced as compared to nonisolated due to unrestricted voltage across the decoupling capacitor. Voltage-fed Phase-Shift Dual Half-Bridge (DHB) is preferred with film capacitors as it has the least number of components in isolated bidirectional topologies. However, in DHB, power decoupling controller is a challenge as current control is conventionally required. The challenge has been overcome with novel current-sensorless dc link ripple rejection control. The controller has the advantage of current-sensorless configuration especially when it needs information from inverter phase-lock-loop (PLL). The proposed power decoupling control scheme is independent of the inverter control and universal. A new dynamic analysis has been carried out by taking into account the input-voltage dynamics. The advantage of the DHB is that it has single pole behavior and, hence, sufficient bandwidth can be obtained. Simulations and experiments have been performed to verify the analysis of the power decoupling control scheme and the capability of film-capacitor DHB for power decoupling.
Metamorphic Malware Detection Using Statistical Analysis

49   Typically, computer viruses and other malware are detected by searching for a string of bits found in the virus or malware. Such a string can be viewed as a " fingerprint " of the virus identified as the signature of the virus. The technique of detecting viruses using signatures is known as signature based detection. Today, virus writers often camouflage their viruses by using code obfuscation techniques in an effort to defeat signature-based detection schemes. So-called metamorphic viruses transform their code as they propagate, thus evading detection by static signature-based virus scanners, while keeping their functionality but differing in internal structure. Many dynamic analysis based detection have been proposed to detect metamorphic viruses but dynamic analysis technique have limitations like difficult to learn normal behavior, high run time overhead and high false positive rate compare to static detection technique. A similarity measure method has been successfully applied in the field of document classification problem. We want to apply similarity measures methods on static feature, API calls of executable to classify it as malware or benign. In this paper we present limitations of signature based detection for detecting metamorphic viruses. We focus on statically analyzing an executable to extract API calls and count the frequency this API calls to generate the feature set. These feature set is used to classify unknown executable as malware or benign by applying various similarity function.  In today's age, where a majority of the transactions involving sensitive information access happen on computers and over the internet, it is absolutely imperative to treat information security as a concern of paramount importance. Computer viruses and other malware have been in existence from the very early days of the personal computer and continue to pose a threat to home and enterprise users alike. A computer virus by definition is " A program that recursively and explicitly copies a possibly evolved version of itself " . A virus copies itself to a host file or system area. Once it gets control, it multiplies itself to form newer generations. A virus may carry out damaging activities on the host machine such as corrupting or erasing files, overwriting the whole hard disk, or crashing the computer. These viruses remain harmless but
A survey on Adversarial Attacks and Defenses in Text

Deep neural networks (DNNs) have shown an inherent vulnerability to adversarial examples which are maliciously crafted on real examples by attackers, aiming at making target DNNs misbehave. The threats of adversarial examples are widely existed in image, voice, speech, and text recognition and classification. Inspired by the previous work, researches on adversarial attacks and defenses in text domain develop rapidly. In order to make people have a general understanding about the field, this article presents a comprehensive review on adversarial examples in text, including attack and defense approaches. We analyze the advantages and shortcomings of recent adversarial examples generation methods and elaborate the efficiency and limitations on the countermeasures. Finally, we discuss the challenges in adversarial texts and provide a research direction of this aspect.
Personalized interactive faceted search

Faceted search is becoming a popular method to allow users to interactively search and navigate complex information spaces. A faceted search system presents users with key-value metadata that is used for query refinement. While popular in e-commerce and digital libraries, not much research has been conducted on which metadata to present to a user in order to improve the search experience. Nor are there repeatable benchmarks for evaluating a faceted search engine. This paper proposes the use of collaborative filtering and personalization to customize the search interface to each user's behavior. This paper also proposes a utility based framework to evaluate the faceted interface. In order to demonstrate these ideas and better understand personalized faceted search, several faceted search algorithms are proposed and evaluated using the novel evaluation methodology.
Hybrid Recommender Systems: A Systematic Literature Review

Recommender systems are software tools used to generate and provide suggestions for items and other entities to the users by exploiting various strategies. Hybrid recommender systems combine two or more recommendation strategies in different ways to benefit from their complementary advantages. This systematic literature review presents the state of the art in hybrid recommender systems of the last decade. It is the first quantitative review work completely focused in hybrid recommenders. We address the most relevant problems considered and present the associated data mining and recommendation techniques used to overcome them. We also explore the hybridization classes each hybrid recommender belongs to, the application domains, the evaluation process and proposed future research directions. Based on our findings, most of the studies combine collaborative filtering with another technique often in a weighted way. Also cold-start and data sparsity are the two traditional and top problems being addressed in 23 and 22 studies each, while movies and movie datasets are still widely used by most of the authors. As most of the studies are evaluated by comparisons with similar methods using accuracy metrics, providing more credible and user oriented evaluations remains a typical challenge. Besides this, newer challenges were also identified such as responding to the variation of user context, evolving user tastes or providing cross-domain recommendations. Being a hot topic, hybrid recommenders represent a good basis with which to respond accordingly by exploring newer opportunities such as contextualizing recommendations, involving parallel hybrid algorithms, processing larger datasets, etc.
Using Social Media for Actionable Disease Surveillance and Outbreak Management: A Systematic Literature Review.

Research studies show that social media may be valuable tools in the disease surveillance toolkit used for improving public health professionals' ability to detect disease outbreaks faster than traditional methods and to enhance outbreak response. A social media work group, consisting of surveillance practitioners, academic researchers, and other subject matter experts convened by the International Society for Disease Surveillance, conducted a systematic primary literature review using the PRISMA framework to identify research, published through February 2013, answering either of the following questions: Can social media be integrated into disease surveillance practice and outbreak management to support and improve public health?Can social media be used to effectively target populations, specifically vulnerable populations, to test an intervention and interact with a community to improve health outcomes?Examples of social media included are Facebook, MySpace, microblogs (e.g., Twitter), blogs, and discussion forums. For Question 1, 33 manuscripts were identified, starting in 2009 with topics on Influenza-like Illnesses (n = 15), Infectious Diseases (n = 6), Non-infectious Diseases (n = 4), Medication and Vaccines (n = 3), and Other (n = 5). For Question 2, 32 manuscripts were identified, the first in 2000 with topics on Health Risk Behaviors (n = 10), Infectious Diseases (n = 3), Non-infectious Diseases (n = 9), and Other (n = 10).



The literature on the use of social media to support public health practice has identified many gaps and biases in current knowledge. Despite the potential for success identified in exploratory studies, there are limited studies on interventions and little use of social media in practice. However, information gleaned from the articles demonstrates the effectiveness of social media in supporting and improving public health and in identifying target populations for intervention. A primary recommendation resulting from the review is to identify opportunities that enable public health professionals to integrate social media analytics into disease surveillance and outbreak management practice.
Media refusal and conspicuous non-consumption: The performative and political dimensions of Facebook abstention

This paper is a study of consumer resistance among active abstainers of the Facebook social network site. I analyze the discourses invoked by individuals who consciously choose to abstain from participation on the ubiquitous Facebook platform. This discourse analysis draws from approximately 100 web and print publications from 2006 to early 2012, as well as personal interviews conducted with 20 Facebook abstainers. I conceptualize Facebook abstention as a performative mode of resistance, which must be understood within the context of a neoliberal consumer culture, in which subjects are empowered to act through consumption choices – or in this case non-consumption choices – and through the public display of those choices. I argue that such public displays are always at risk of misinterpretation due to the dominant discursive frameworks through which abstention is given meaning. This paper gives particular attention to the ways in which connotations of taste and distinction are invoked by refusers through their conspicuous displays of non-consumption. This has the effect of framing refusal as a performance of elitism, which may work against observers interpreting conscientious refusal as a persuasive and emulable practice of critique. The implication of this is that refusal is a limited tactic of political engagement where media platforms are concerned.
Material recognition in the wild with the Materials in Context Database

Recognizing materials in real-world images is a challenging task. Real-world materials have rich surface texture, geometry, lighting conditions, and clutter, which combine to make the problem particularly difficult. In this paper, we introduce a new, large-scale, open dataset of materials in the wild, the Materials in Context Database (MINC), and combine this dataset with deep learning to achieve material recognition and segmentation of images in the wild. MINC is an order of magnitude larger than previous material databases, while being more diverse and well-sampled across its 23 categories. Using MINC, we train convolutional neural networks (CNNs) for two tasks: classifying materials from patches, and simultaneous material recognition and segmentation in full images. For patch-based classification on MINC we found that the best performing CNN architectures can achieve 85.2% mean class accuracy. We convert these trained CNN classifiers into an efficient fully convolutional framework combined with a fully connected conditional random field (CRF) to predict the material at every pixel in an image, achieving 73.1% mean class accuracy. Our experiments demonstrate that having a large, well-sampled dataset such as MINC is crucial for real-world material recognition and segmentation.
A 20 watt micro-strip X-Band AlGaN/GaN HPA MMIC for advanced radar applications

In this paper a first iteration design, fabrication and test of a two-stage X-band MMIC HPA in micro-strip AlGaN/GaN technology is reported. With 20 V drain voltage operating bias point, at 3 dB compression point, the HPA delivers a pulsed output power ranging from 21 to 28.5 W, an associated gain from 12.9 to 16.5 dB and an associated PAE from circa 30% to 40%, over the 8-10.5 GHz frequency bandwidth. In the best performance frequency points (8.5 and 9 GHz) the HPA exhibits a saturated output power of 30 W with an associated PAE of 40%.
Bilingual Chronological Classification of Hafez's Poems

We present a novel task: the chronological classification of Hafez’s poems (ghazals). We compiled a bilingual corpus in digital form, with consistent idiosyncratic properties. We have used Hooman’s labeled ghazals in order to train automatic classifiers to classify the remaining ghazals. Our classification framework uses a Support Vector Machine (SVM) classifier with similarity features based on Latent Dirichlet Allocation (LDA). In our analysis of the results we use the LDA topics’ main terms that are passed on to a Principal Component Analysis (PCA) module.
Jacobsen syndrome without thrombocytopenia: a case report and review of the literature.

Jacobsen syndrome (JS), a rare disorder with multiple dysmorphic features, is caused by the terminal deletion of chromosome 11q. Typical features include mild to moderate psychomotor retardation, trigonocephaly, facial dysmorphism, cardiac defects, and thrombocytopenia, though none of these features are invariably present. The estimated occurrence of JS is about 1/100,000 births. The female/male ratio is 2:1. The patient admitted to our clinic at 3.5 years of age with a cardiac murmur and facial anomalies. Facial anomalies included trigonocephaly with bulging forehead, hypertelorism, telecanthus, downward slanting palpebral fissures, and a carp-shaped mouth. The patient also had strabismus. An echocardiogram demonstrated perimembranous aneurysmatic ventricular septal defect and a secundum atrial defect. The patient was <3rd percentile for height and weight and showed some developmental delay. Magnetic resonance imaging (MRI) showed hyperintensive gliotic signal changes in periventricular cerebral white matter, and leukodystrophy was suspected. Chromosomal analysis of the patient showed terminal deletion of chromosome 11. The karyotype was designated 46, XX, del(11) (q24.1). A review of published reports shows that the severity of the observed clinical abnormalities in patients with JS is not clearly correlated with the extent of the deletion. Most of the patients with JS had short stature, and some of them had documented growth hormone deficiency, or central or primary hypothyroidism. In patients with the classical phenotype, the diagnosis is suspected on the basis of clinical findings: intellectual disability, facial dysmorphic features and thrombocytopenia. The diagnosis must be confirmed by cytogenetic analysis. For patients who survive the neonatal period and infancy, the life expectancy remains unknown. In this report, we describe a patient with the clinical features of JS without thrombocytopenia. To our knowledge, this is the first case reported from Turkey.
Class Steiner Trees and VLSI-design

We consider a generalized version of the Steiner problem in graphs, motivated by the wire routing phase in physical VLSI design: given a connected, undirected distance graph with required classes of vertices and Steiner vertices, find a shortest connected subgraph containing at least one vertex of each required class. We show that this problem is NP-hard, even if there are no Steiner vertices and the graph is a tree. Moreover, the same complexity result holds if the input class Steiner graph additionally is embedded in a unit grid, if each vertex has degree at most three, and each class consists of no more than three vertices. For similar restricted versions, we prove MAX SNP-hardness and we show that there exists no polynomial-time approximation algorithm with a constant bound on the relative error, unless P = NP. We propose two efficient heuristics computing different approximate solutions in time 0(/E] + /VI log IV]) and in time O(c(lEl + IV1 log (VI)), respectively, where E is the set of edges in the given graph, V is the set of vertices, and c is the number of classes. We present some promising implementation results.
Performance Analysis and Optimization of Clang's OpenMP 4.5 GPU Support

The Clang implementation of OpenMP® 4.5 now provides full support for the specification, offering the only open source option for targeting NVIDIA® GPUs. While using OpenMP allows portability across different architectures, matching native CUDA® performance without major code restructuring is an open research issue.In order to analyze the current performance, we port a suite of representative benchmarks, and the mature mini-apps TeaLeaf, CloverLeaf, and SNAP to the Clang OpenMP 4.5 compiler. We then collect performance results for those ports, and their equivalent CUDA ports, on an NVIDIA Kepler GPU. Through manual analysis of the generated code, we are able to discover the root cause of the performance differences between OpenMP and CUDA.A number of improvements can be made to the existing compiler implementation to enable performance that approaches that of hand-optimized CUDA. Our first observation was that the generated code did not use fused-multiply-add instructions, which was resolved using an existing flag. Next we saw that the compiler was not passing any loads through non-coherent cache, and added a new flag to the compiler to assist with this problem.We then observed that the compiler partitioning of threads and teams could be improved upon for the majority of kernels, which guided work to ensure that the compiler can pick more optimal defaults. We uncovered a register allocation issue with the existing implementation that, when fixed alongside the other issues, enables performance that is close to CUDA.Finally, we use some different kernels to emphasize that support for managing memory hierarchies needs to be introduced into the specification, and propose a simple option for programming shared caches.
Exploring the Impact of Knowledge Management Capabilities on Organizational Effectiveness

Research on knowledge management success often focuses on aggregate concepts of knowledge management capabilities when assessing their impact on organizational effectiveness. As such, little is known about the role of the individual resources that make up an organization's knowledge management capability and their impact on organizational effectiveness. To better understand these relationships, this study investigates a component model of knowledge management capabilities. Data collected from 189 managers and structural equation modeling are used to assess the research model. The results show that individual resources are differentially related to organizational effectiveness, with only some resources (e.g. organizational structure) having significant relationships vis-à-vis organizational effectiveness and others exhibiting null effects. Implications for practice and future research are discussed.
Testing the reliability of frontal sinuses in positive identification.

The use of frontal sinus radiographs in positive identification has become an increasingly applied and accepted technique among forensic anthropologists, radiologists, and pathologists. From an evidentiary standpoint, however, it is important to know whether frontal sinus radiographs are a reliable method for confirming or rejecting an identification, and standardized methods should be applied when making comparisons. The purpose of the following study is to develop an objective, standardized comparison method, and investigate the reliability of that method. Elliptic Fourier analysis (EFA) was used to assess the variation in 808 outlines of frontal sinuses by calculating likelihood ratios and posterior probabilities from EFA coefficients. Results show that using EFA coefficient comparison to estimate the probability of a correct identification is a reliable technique, and EFA comparison of frontal sinus outlines is recommended when it may be necessary to provide quantitative substantiation for a forensic identification based on these structures.
The critical hitch angle for jackknife avoidance during slow backing up of vehicle – trailer systems

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