nils-herrmann/clean_scirepeval huggingface dataset:
High Confidence Visual Recognition of Persons by a Test of Statistical Independence

AbstructA method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person’s face is the detailed texture of each eye’s iris: An estimate of its statistical complexity in a sample of the human population reveals variation corresponding to several hundred independent degrees-of-freedom. Morphogenetic randomness in the texture expressed phenotypically in the iris trabecular meshwork ensures that a test of statistical independence on two coded patterns originating from different eyes is passed almost certainly, whereas the same test is failed almost certainly when the compared codes originate from the same eye. The visible texture of a person’s iris in a real-time video image is encoded into a compact sequence of multi-scale quadrature 2-D Gabor wavelet coefficients, whose most-significant bits comprise a 256-byte “iris code.” Statistical decision theory generates identification decisions from ExclusiveOR comparisons of complete iris codes at the rate of 4000 per second, including calculation of decision confidence levels. The distributions observed empirically in such comparisons imply a theoretical “cross-over” error rate of one in 131000 when a decision criterion is adopted that would equalize the false accept and false reject error rates. In the typical recognition case, given the mean observed degree of iris code agreement, the decision confidence levels correspond formally to a conditional false accept probability of one in about lo”’.
Managing Non-Volatile Memory in Database Systems

Non-volatile memory (NVM) is a new storage technology that combines the performance and byte addressability of DRAM with the persistence of traditional storage devices like flash (SSD). While these properties make NVM highly promising, it is not yet clear how to best integrate NVM into the storage layer of modern database systems. Two system designs have been proposed. The first is to use NVM exclusively, i.e., to store all data and index structures on it. However, because NVM has a higher latency than DRAM, this design can be less efficient than main-memory database systems. For this reason, the second approach uses a page-based DRAM cache in front of NVM. This approach, however, does not utilize the byte addressability of NVM and, as a result, accessing an uncached tuple on NVM requires retrieving an entire page.
 In this work, we evaluate these two approaches and compare them with in-memory databases as well as more traditional buffer managers that use main memory as a cache in front of SSDs. This allows us to determine how much performance gain can be expected from NVM. We also propose a lightweight storage manager that simultaneously supports DRAM, NVM, and flash. Our design utilizes the byte addressability of NVM and uses it as an additional caching layer that improves performance without losing the benefits from the even faster DRAM and the large capacities of SSDs.
Attributing Fake Images to GANs: Analyzing Fingerprints in Generated Images

Research in computer graphics has been in pursuit of realistic image generation for a long time. Recent advances in machine learning with deep generative models have shown increasing success of closing the realism gap by using datadriven and learned components. There is an increasing concern that real and fake images will become more and more difficult to tell apart. We take a first step towards this larger research challenge by asking the question if and to what extend a generated fake image can be attribute to a particular Generative Adversarial Networks (GANs) of a certain architecture and trained with particular data and random seed. Our analysis shows single samples from GANs carry highly characteristic fingerprints which make attribution of images to GANs possible. Surprisingly, this is even possible for GANs with same architecture and same training that only differ by the training seed.
Clinical Alarms in Intensive Care Units: Perceived Obstacles of Alarm Management and Alarm Fatigue in Nurses.

The purpose of this descriptive study was to investigate the current situation of clinical alarms in intensive care unit (ICU), nurses' recognition of and fatigue in relation to clinical alarms, and obstacles in alarm management.



Subjects were ICU nurses and devices from 48 critically ill patient cases. Data were collected through direct observation of alarm occurrence and questionnaires that were completed by the ICU nurses. The observation time unit was one hour block. One bed out of 56 ICU beds was randomly assigned to each observation time unit.



Overall 2,184 clinical alarms were counted for 48 hours of observation, and 45.5 clinical alarms occurred per hour per subject. Of these, 1,394 alarms (63.8%) were categorized as false alarms. The alarm fatigue score was 24.3 ± 4.0 out of 35. The highest scoring item was "always get bothered due to clinical alarms". The highest scoring item in obstacles was "frequent false alarms, which lead to reduced attention or response to alarms".



Nurses reported that they felt some fatigue due to clinical alarms, and false alarms were also obstacles to proper management. An appropriate hospital policy should be developed to reduce false alarms and nurses' alarm fatigue.
Visual Tracking: An Experimental Survey

There is a large variety of trackers, which have been proposed in the literature during the last two decades with some mixed success. Object tracking in realistic scenarios is a difficult problem, therefore, it remains a most active area of research in computer vision. A good tracker should perform well in a large number of videos involving illumination changes, occlusion, clutter, camera motion, low contrast, specularities, and at least six more aspects. However, the performance of proposed trackers have been evaluated typically on less than ten videos, or on the special purpose datasets. In this paper, we aim to evaluate trackers systematically and experimentally on 315 video fragments covering above aspects. We selected a set of nineteen trackers to include a wide variety of algorithms often cited in literature, supplemented with trackers appearing in 2010 and 2011 for which the code was publicly available. We demonstrate that trackers can be evaluated objectively by survival curves, Kaplan Meier statistics, and Grubs testing. We find that in the evaluation practice the F-score is as effective as the object tracking accuracy (OTA) score. The analysis under a large variety of circumstances provides objective insight into the strengths and weaknesses of trackers.
A novel lightweight URL phishing detection system using SVM and similarity index

The phishing is a technique used by cyber-criminals to impersonate legitimate websites in order to obtain personal information. This paper presents a novel lightweight phishing detection approach completely based on the URL (uniform resource locator). The mentioned system produces a very satisfying recognition rate which is 95.80%. This system, is an SVM (support vector machine) tested on a 2000 records data-set consisting of 1000 legitimate and 1000 phishing URLs records. In the literature, several works tackled the phishing attack. However those systems are not optimal to smartphones and other embed devices because of their complex computing and their high battery usage. The proposed system uses only six URL features to perform the recognition. The mentioned features are the URL size, the number of hyphens, the number of dots, the number of numeric characters plus a discrete variable that correspond to the presence of an IP address in the URL and finally the similarity index. Proven by the results of this study the similarity index, the feature we introduce for the first time as input to the phishing detection systems improves the overall recognition rate by 21.8%.
The relationship among receptive and expressive vocabulary, listening comprehension, pre-reading skills, word identification skills, and reading comprehension by children with reading disabilities.

Some researchers (F. R. Vellutino, F. M. Scanlon, & M. S. Tanzman, 1994) have argued that the different domains comprising language (e.g., phonology, semantics, and grammar) may influence reading development in a differential manner and at different developmental periods. The purpose of this study was to examine proposed causal relationships among different linguistic subsystems and different measures of reading achievement in a group of children with reading disabilities.



Participants were 279 students in 2nd to 3rd grade who met research criteria for reading disability. Of those students, 108 were girls and 171 were boys. In terms of heritage, 135 were African and 144 were Caucasian. Measures assessing pre-reading skills, word identification, reading comprehension, and general oral language skills were administered.



Structural equation modeling analyses indicated receptive and expressive vocabulary knowledge was independently related to pre-reading skills. Additionally, expressive vocabulary knowledge and listening comprehension skills were found to be independently related to word identification abilities.



Results are consistent with previous research indicating that oral language skills are related to reading achievement (e.g., A. Olofsson & J. Niedersoe, 1999; H. S. Scarborough, 1990). Results from this study suggest that receptive and expressive vocabulary knowledge influence pre-reading skills in differential ways. Further, results suggest that expressive vocabulary knowledge and listening comprehension skills facilitate word identification skills.
Propagation measurements and models for wireless communications channels

To achieve ubiquitous PCS, new and novel ways of classifying wireless environments will be needed that are both widely encompassing and reasonably compact. JGRGEN BACHANDER-SEN is u professor at Aalborh. Universip and head of thc Centerfor Personkommn-nikation. THEODORE S. RAPPA-PORT 0 un associareprafes-sor of electrical rngineenng at Viwnia Tech. profawr of electrical engineering at Kyoto Universip. ireless personal communica-tionscouldinprincipleusesev-era1 physical media, ranging from sound to radio to light. Since we want to overcome the limitations of acoustical communications , we shall concentrate on propagation of electromagnetic wavcs in the frequency range from some hundreds of MHz to a few GHz. Although thereisconsiderable interest atthe moment in millimeter wave communications in indoor environments, they will be mentioned only brieflyin this survey of propagation of signals. It is interesting to observe that propagation results influence personal communications systems in several ways. First there is obviously the distribution ofmeanpoweroveracertainareaorvolumeofinter-est, which is the basic requirement for reliable communications. The energy should be sufficient for the link in question, but not too strong, in order not to create cochannel interfcrcnce at a distance in another cell. Also, since the radio link is highly variable over short distances, not only the mean power is significant; the statistical distribution is also important. This is especially true when the fading distribution is dependent on thc bandwidth of the signal. Secondly. even if there is sufficient power available for communications, the quality of the signal may be such that large errors occur anyway. This results from rapid movement through thescatteringenvironment,or impairments due to long echoes leading to inter-symbol-interference. A basic understanding of the channel is important for finding modulation andcodingschemes that improve thc channel, for designing equalizers or, if this is not possible, for deploying basc station antcnnas in such a way that the detrimental effects are less likely to occur. In this article we will describe the type of signals that occur invarious cnvironments and the mod-eling of the propagation parameters. Models are essentially of two classes. The first class consists of parametric statistical models that on average describcthephenomenonwithinagivenerror.They are simple to use, but relativcly coarse. In the last few years a second class ofenvironment-specific mod-e1shasbeenintroduced.
SimpleQuestions Nearly Solved: A New Upperbound and Baseline Approach

The SimpleQuestions dataset is one of the most commonly used benchmarks for studying single-relation factoid questions. In this paper, we present new evidence that this benchmark can be nearly solved by standard methods. First, we show that ambiguity in the data bounds performance at 83.4%; many questions have more than one equally plausible interpretation. Second, we introduce a baseline that sets a new state-of-the-art performance level at 78.1% accuracy, despite using standard methods. Finally, we report an empirical analysis showing that the upperbound is loose; roughly a quarter of the remaining errors are also not resolvable from the linguistic signal. Together, these results suggest that the SimpleQuestions dataset is nearly solved.
Nutritional ecology of entomophagy in humans and other primates.

Entomophagy is widespread among nonhuman primates and is common among many human communities. However, the extent and patterns of entomophagy vary substantially both in humans and nonhuman primates. Here we synthesize the literature to examine why humans and other primates eat insects and what accounts for the variation in the extent to which they do so. Variation in the availability of insects is clearly important, but less understood is the role of nutrients in entomophagy. We apply a multidimensional analytical approach, the right-angled mixture triangle, to published data on the macronutrient compositions of insects to address this. Results showed that insects eaten by humans spanned a wide range of protein-to-fat ratios but were generally nutrient dense, whereas insects with high protein-to-fat ratios were eaten by nonhuman primates. Although suggestive, our survey exposes a need for additional, standardized, data.
Anthropomorphic Soft Robotics - From Torque Control to Variable Intrinsic Compliance

The paper gives an overview on the developments at the German Aerospace Center DLR towards anthropomorphic robots which not only tr y to approach the force and velocity performance of humans, but also have simi lar safety and robustness features based on a compliant behaviour. We achieve thi s compliance either by joint torque sensing and impedance control, or, in our newes t systems, by compliant mechanisms (so called VIA variable impedance actuators), whose intrinsic compliance can be adjusted by an additional actuator. Both appr o ches required highly integrated mechatronic design and advanced, nonlinear con trol a d planning strategies, which are presented in this paper.
Playing Both Sides of the Market: Success and Reciprocity on Crowdfunding Platforms

Crowdfunding, the process of directly financing projects and ventures over the internet, is gaining momentum. Industry reports estimate that sums raised on crowdfunding platforms have nearly doubled in 2012, totaling close to US$3.0B.1 Initially, crowdfunding was performed using social media such as mailing lists or social networks. The maturity of Web 2.0 technologies enabled and inspired the establishment of dedicated crowdfunding platforms. These platforms create a microenvironment where long term social interaction and accumulated information influence the success of crowdfunding projects.
Quantum-Dot Semiconductor Optical Amplifiers

This paper reviews the recent progress of quantum-dot semiconductor optical amplifiers developed as ultrawideband polarization-insensitive high-power amplifiers, high-speed signal regenerators, and wideband wavelength converters. A semiconductor optical amplifier having a gain of > 25 dB, noise figure of < 5 dB, and 3-dB saturation output power of > 20 dBm, over the record widest bandwidth of 90 nm among all kinds of optical amplifiers, and also having a penalty-free output power of 23 dBm, the record highest among all the semiconductor optical amplifiers, was realized by using quantum dots. By utilizing isotropically shaped quantum dots, the TM gain, which is absent in the standard Stranski-Krastanow QDs, has been drastically enhanced, and nearly polarization-insensitive SOAs have been realized for the first time. With an ultrafast gain response unique to quantum dots, an optical regenerator having receiver-sensitivity improving capability of 4 dB at a BER of 10-9 and operating speed of > 40 Gb/s has been successfully realized with an SOA chip. This performance achieved together with simplicity of structure suggests a potential for low-cost realization of regenerative transmission systems.
Reconfigurable Inverted Index

Existing approximate nearest neighbor search systems suffer from two fundamental problems that are of practical importance but have not received sufficient attention from the research community. First, although existing systems perform well for the whole database, it is difficult to run a search over a subset of the database. Second, there has been no discussion concerning the performance decrement after many items have been newly added to a system. We develop a reconfigurable inverted index (Rii) to resolve these two issues. Based on the standard IVFADC system, we design a data layout such that items are stored linearly. This enables us to efficiently run a subset search by switching the search method to a linear PQ scan if the size of a subset is small. Owing to the linear layout, the data structure can be dynamically adjusted after new items are added, maintaining the fast speed of the system. Extensive comparisons show that Rii achieves a comparable performance with state-of-the art systems such as Faiss.
User identification across multiple social networks

Today, more and more people have their virtual identities on the web. It is common that people are users of more than one social network and also their friends may be registered on multiple websites. A facility to aggregate our online friends into a single integrated environment would enable the user to keep up-to-date with their virtual contacts more easily, as well as to provide improved facility to search for people across different websites. In this paper, we propose a method to identify users based on profile matching. We use data from two popular social networks to study the similarity of profile definition. We evaluate the importance of fields in the web profile and develop a profile comparison tool. We demonstrate the effectiveness and efficiency of our tool in identifying and consolidating duplicated users on different websites.
Cause-Effect Knowledge Acquisition and Neural Association Model for Solving A Set of Winograd Schema Problems

This paper focuses on the investigations in Winograd Schema (WS), a challenging problem which has been proposed for measuring progress in commonsense reasoning. Due to the lack of commonsense knowledge and training data, very little work has been reported on the WS problems. This paper addresses a set of WS problems by proposing a knowledge acquisition method and a general neural association model. To avoid the sparseness issue, the knowledge we aim to collect is the cause-effect relationships between a collection of commonly used words. The knowledge acquisition method supports us to extract hundreds of thousands of cause-effect pairs from text corpora automatically. Meanwhile, a neural association model (NAM) is proposed to encode the association relationships between any two discrete events. Based on the extracted knowledge and the NAM models, we successfully build a system for solving a causal subset of WS problems from scratch and achieve 70% accuracy. Most importantly, this paper provides a flexible framework to solve WS problems based on event association and neural network methods.
Dopamine: A Research Framework for Deep Reinforcement Learning

Deep reinforcement learning (deep RL) research has grown significantly in recent years. A number of software offerings now exist that provide stable, comprehensive implementations for benchmarking. At the same time, recent deep RL research has become more diverse in its goals. In this paper we introduce Dopamine, a new research framework for deep RL that aims to support some of that diversity. Dopamine is open-source, TensorFlow-based, and provides compact and reliable implementations of some state-of-the-art deep RL agents. We complement this offering with a taxonomy of the different research objectives in deep RL research. While by no means exhaustive, our analysis highlights the heterogeneity of research in the field, and the value of frameworks such as ours.
Some new indexes of cluster validity

We review two clustering algorithms (hard c-means and single linkage) and three indexes of crisp cluster validity (Hubert's statistics, the Davies-Bouldin index, and Dunn's index). We illustrate two deficiencies of Dunn's index which make it overly sensitive to noisy clusters and propose several generalizations of it that are not as brittle to outliers in the clusters. Our numerical examples show that the standard measure of interset distance (the minimum distance between points in a pair of sets) is the worst (least reliable) measure upon which to base cluster validation indexes when the clusters are expected to form volumetric clouds. Experimental results also suggest that intercluster separation plays a more important role in cluster validation than cluster diameter. Our simulations show that while Dunn's original index has operational flaws, the concept it embodies provides a rich paradigm for validation of partitions that have cloud-like clusters. Five of our generalized Dunn's indexes provide the best validation results for the simulations presented.
Educational support for orphans and vulnerable children in primary schools : Challenges and interventions

Educational status is an important indicator of children’s wellbeing and future life opportunities. It can predict growth potential and economic viability of a state. While this is an ideal situation for all children, the case may be different for orphans and vulnerable children (OVC) due to the challenges they go through on a daily basis. This article aims to advance a debate on the findings of our study on the educational support provided for OVC through a critical engagement on the challenges experienced and the intervention measures to be taken in South African public primary schools context. The study involved one hundred and seven participants comprising sixty five OVC and forty two teachers. Questionnaires with structured and unstructured questions were utilised to collect descriptive and qualitative data. Findings suggest that, although the South African Government has put mechanisms in place to support OVC attain basic education, numerous challenges were found to be hindering some OVC from attaining quality education. Based on the findings, several intervention measures have been suggested.