nils-herrmann/clean_scirepeval huggingface dataset:
3D Lidar-based static and moving obstacle detection in driving environments: An approach based on voxels and multi-region ground planes

Artificial perception, in the context of autonomous driving, is the process by which an intelligent system translates sensory data into an effective model of the environment surrounding a vehicle. In this paper, and considering data from a 3D-LIDAR mounted onboard an intelligent vehicle, a 3D perception system based on voxels and planes is proposed for ground modeling and obstacle detection in urban environments. The system, which incorporates time-dependent data, is composed of two main modules: (i) an effective ground surface estimation using a piecewise plane fitting algorithm and RANSAC-method, and (ii) a voxel-grid model for static and moving obstacles detection using discriminative analysis and ego-motion information. This perception system has direct application in safety systems for intelligent vehicles, particularly in collision avoidance and vulnerable road users detection, namely pedestrians and cyclists. Experiments, using point-cloud data from a Velodyne LIDAR and localization data from an Inertial Navigation System were conducted for both a quantitative and a qualitative assessment of the static/moving obstacle detection module and for the surface estimation approach. Reported results, from experiments using the KITTI database, demonstrate the applicability and efficiency of the proposed approach in urban scenarios.
Distributed Key Generation in the Wild

Distributed key generation (DKG) has been studied extensively in the cryptographic literature. However, it has never been examined outside of the synchronous setting, and the known DKG protocols cannot guarantee safety or liveness over the Internet. In this work, we present the first realistic DKG protocol for use over the Internet. We propose a practical system model for the Internet and define an efficient verifiable secret sharing (VSS) scheme in it. We observe the necessity of Byzantine agreement for asynchronous DKG and analyze the difficulty of using a randomized protocol for it. Using our VSS scheme and a leader-based agreement protocol, we then design a provably secure DKG protocol. We also consider and achieve cryptographic properties such as uniform randomness of the shared secret and compare static versus adaptive adversary models. Finally, we implement our DKG protocol, and establish its efficiency and reliability by extensively testing it on the PlanetLab platform. Counter to a general non-scalability perception about asynchronous systems, our experiments demonstrate that our asynchronous DKG protocol scales well with the system size and it is suitable for realizing multiparty computation and threshold cryptography over the Internet.
A more nuanced view of reliability: specificity in the trait hierarchy.

Retest reliability is a better predictor of validity than is internal consistency. One explanation for this is item-specific variance, which distinguishes different nuances of a facet and contributes to retest reliability but not internal consistency. Specific variance at the facet level is temporally stable, consensually validated, and heritable; a consideration of the role of specific variance in personality measures leads to a distinction between traits as the intersection (∩) versus the union (∪) of their constituents. I discuss specific variance at the item level and its implications for scale development and argue that retest reliability outpredicts internal consistency because item-specific variance has been shown to be observable, and is probably heritable and stable. I consider some implications of these ideas for the use of single-item scales, the causal interpretation of traits, and the notion of scalar equivalence. Finally, I note that the sources of random error in scales are still poorly understood.
Post-natal ontogeny of the mandible and ventral cranium in Marmota species (Rodentia, Sciuridae): allometry and phylogeny

Post-natal ontogenetic variation of the marmot mandible and ventral cranium is investigated in two species of the subgenus Petromarmota (M. caligata, M. flaviventris) and four species of the subgenus Marmota (M. caudata, M. himalayana, M. marmota, M. monax). Relationships between size and shape are analysed using geometric morphometric techniques. Sexual dimorphism is negligible, allometry explains the main changes in shape during growth, and males and females manifest similar allometric trajectories. Anatomical regions affected by size-related shape variation are similar in different species, but allometric trajectories are divergent. The largest modifications of the mandible and ventral cranium occur in regions directly involved in the mechanics of mastication. Relative to other anatomical regions, the size of areas of muscle insertion increases, while the size of sense organs, nerves and teeth generally decreases. Epigenetic factors, developmental constraints and size variation were found to be the major contributors in producing the observed allometric patterns. A phylogenetic signal was not evident in the comparison of allometric trajectories, but traits that allow discrimination of the Palaearctic marmots from the Nearctic species of Petromarmota are present early in development and are conserved during post-natal ontogeny.
Proposal of bioinstrumentation using flex sensor for amputated upper limb

We previously proposed a new bioinstrumentation using the shape deformation of the amputated upper limbs without using the myoelectricity generated on the skin of the upper limbs. However many electronic parts were required owing to a bridge circuit and multi-amplifier circuits so as to amplify a tiny voltage of strain gages. Moreover, the surplus heat might occur by the overcurrent owing to low resistance value of strain gages. Therefore, in this study, we apply a flex sensor to this system instead of strain gages to solve the above problems.
Horizontal Pyramid Matching for Person Re-identification

Despite the remarkable recent progress, person reidentification (Re-ID) approaches are still suffering from the failure cases where the discriminative body parts are missing. To mitigate such cases, we propose a simple yet effective Horizontal Pyramid Matching (HPM) approach to fully exploit various partial information of a given person, so that correct person candidates can be still identified even even some key parts are missing. Within the HPM, we make the following contributions to produce a more robust feature representation for the Re-ID task: 1) we learn to classify using partial feature representations at different horizontal pyramid scales, which successfully enhance the discriminative capabilities of various person parts; 2) we exploit average and max pooling strategies to account for person-specific discriminative information in a global-local manner. To validate the effectiveness of the proposed HPM, extensive experiments are conducted on three popular benchmarks, including Market-1501, DukeMTMC-ReID and CUHK03. In particular, we achieve mAP scores of 83.1%, 74.5% and 59.7% on these benchmarks, which are the new state-of-the-arts. Our code is available on Github .
KNOWROB-MAP - knowledge-linked semantic object maps

Autonomous household robots are supposed to accomplish complex tasks like cleaning the dishes which involve both navigation and manipulation within the environment. For navigation, spatial information is mostly sufficient, but manipulation tasks raise the demand for deeper knowledge about objects, such as their types, their functions, or the way how they can be used. We present KNOWROB-MAP, a system for building environment models for robots by combining spatial information about objects in the environment with encyclopedic knowledge about the types and properties of objects, with common-sense knowledge describing what the objects can be used for, and with knowledge derived from observations of human activities by learning statistical relational models. In this paper, we describe the concept and implementation of KNOWROB-MAP and present several examples demonstrating the range of information the system can provide to autonomous robots.
Makers of the early Aurignacian of Europe.

Despite intensive study and a number of remarkable discoveries in the last two decades of the 20th century, our understanding of the cultural and biological processes that resulted in the emergence of the Upper Paleolithic and the establishment of modern humans in Interpleniglacial Europe remains far from complete. There is active debate concerning the timing and location of the origins of the Aurignacian, the nature of the origins of Initial Upper Paleolithic industries (whether by autochthonous development or through acculturation by Aurignacian peoples), the timing of the appearance of early modern humans and the disappearance of the Neandertals, and the relationship of archeologically defined cultures to these different types of hominids. Frustrating our attempts to address these latter two questions is a general paucity of taxonomically diagnostic human fossil material from early Upper Paleolithic contexts. We undertake here a review of the human fossil record of Interpleniglacial Europe, and its archeological and chronological context, to clarify to the extent possible the nature of the relationship between hominid groups and the earliest Upper Paleolithic artifact industries, particularly the early Aurignacian. Although substantial difficulties involved in interpreting the fossil, archeological, and geochronological records of this time period prohibit making any definitive statements, a number of observations are suggested by the current data: 1) the Middle Paleolithic of Europe appears to have been made exclusively by Neandertals; 2) Initial Upper Paleolithic industries (with the exception of the Bachokirian) appear to have their roots in the late Middle Paleolithic industries of their respective regions; 3) all of the human fossils yet recovered from Initial Upper Paleolithic (except the Bachokirian) contexts for which any diagnostic morphology is present have their greatest morphological affinities with Neandertals and not early modern humans; 4) modern humans were almost certainly established in Europe by ca. 32 ky BP, with a strong possibility that they were there by ca. 36 ky BP. Claims for an appearance before 36 ky BP cannot be substantiated with currently available evidence; 5) the hypothesis that modern humans are uniquely associated with the Aurignacian cannot yet be refuted. Aurignacian-associated human fossils (including those from the Bachokirian) for which any diagnostic morphology is present have their greatest affinities with early modern Europeans and not Neandertals; and 6) Neandertals and modern humans coexisted in Europe for at least 2,000-4,000 years, and perhaps for 8,000-10,000 years or longer. The overall picture is one of an extended period of cultural contact, involving some degree of genetic exchange, between Neandertals and early modern Europeans.
Questioning, promoting and evaluating the use of streaming video to support student learning

This paper uses case studies to describe how streaming video is currently used to support student learning in post compulsory education in the UK. It describes the current role of streaming video and identifies processes that could extend the application of streaming in education. It attempts to establish a case for more formal evaluation and communication of educational processes involving streaming and identifies elements of a research agenda that could further develop the application of streaming technology in education. Questioning, promoting and evaluating the use of streaming video to support student learning
Hardware Random number Generator for cryptography

One of the key requirement of many schemes is that of random numbers. Sequence of random numbers are used at several stages of a standard cryptographic protocol. A simple example is of a Vernam cipher, where a string of random numbers is added to massage string to generate the encrypted code. It is represented as C = M ⊕ K where M is the message, K is the key and C is the ciphertext. It has been mathematically shown that this simple scheme is unbreakable is key K as long as M and is used only once. For a good cryptosystem, the security of the cryptosystem is not be based on keeping the algorithm secret but solely on keeping the key secret. The quality and unpredictability of secret data is critical to securing communication by modern cryptographic techniques. Generation of such data for cryptographic purposes typically requires an unpredictable physical source of random data. In this manuscript, we present studies of three different methods for producing random number. We have tested them by studying its frequency, correlation as well as using the test suit from NIST.
Survey of scaling platforms for Deep Neural Networks

Deep Neural Networks have become a state of the art approach in perception processing like speech recognition, image processing and natural language processing. Many state of the art benchmarks for these algorithms are using deep learning techniques. The deep neural networks in today's applications need to process very large amount of data. Different approaches have been proposed to solve scaling these algorithms. Few approach look for providing a solution over existing big data processing platform which usually runs over a large scale commodity cpu cluster. As training deep learning workload require many small computations to be done and large communication to pass the data between layers, General  GPUs seems to the best platforms to train these networks. Different approaches have been proposed to scale processing on cluster of GPU servers. We have summarized various approaches used in this regard.
Real-time eye state detection system using haar cascade classifier and circular hough transform

This paper proposes an eye state detection system using Haar Cascade Classifier and Circular Hough Transform. Our proposed system first detects the face and then the eyes using Haar Cascade Classifiers, which differentiate between opened and closed eyes. Circular Hough Transform (CHT) is used to detect the circular shape of the eye and make sure that the eye is detected correctly by the classifiers. The accuracy of the eye detection is 98.56% on our database which contains 2856 images for opened eye and 2384 images for closed eye. The system works on several stages and is fully automatic. The eye state detection system was tested by several people, and the accuracy of the proposed system is 96.96%.
Automated Bone Age Assessment: Motivation, Taxonomies, and Challenges

Bone age assessment (BAA) of unknown people is one of the most important topics in clinical procedure for evaluation of biological maturity of children. BAA is performed usually by comparing an X-ray of left hand wrist with an atlas of known sample bones. Recently, BAA has gained remarkable ground from academia and medicine. Manual methods of BAA are time-consuming and prone to observer variability. This is a motivation for developing automated methods of BAA. However, there is considerable research on the automated assessment, much of which are still in the experimental stage. This survey provides taxonomy of automated BAA approaches and discusses the challenges. Finally, we present suggestions for future research.
Secure Multi-Authority Data Access Control Scheme in Cloud Storage System Based on Attribute-Based Signcryption

Nowadays, secure data access control has become one of the major concerns in a cloud storage system. As a logical combination of attribute-based encryption and attribute-based signature, attribute-based signcryption (ABSC) can provide confidentiality and an anonymous authentication for sensitive data and is more efficient than traditional “encrypt-then-sign” or “sign-then-encrypt” strategies. Thus, ABSC is suitable for fine-grained access control in a semi-trusted cloud environment and is gaining more and more attention in recent years. However, in many previous ABSC schemes, user’s sensitive attributes can be disclosed to the authority, and only a single authority that is responsible for attribute management and key generation exists in the system. In this paper, we propose PMDAC-ABSC, a novel privacy-preserving data access control scheme based on Ciphertext-Policy ABSC, to provide a fine-grained control measure and attribute privacy protection simultaneously in a multi-authority cloud storage system. The attributes of both the signcryptor and the designcryptor can be protected to be known by the authorities and cloud server. Furthermore, the decryption overhead for user is significantly reduced by outsourcing the undesirable bilinear pairing operations to the cloud server without degrading the attribute privacy. The proposed scheme is proven to be secure in the standard model and has the ability to provide confidentiality, unforgeability, anonymous authentication, and public verifiability. The security analysis, asymptotic complexity comparison, and implementation results indicate that our construction can balance the security goals with practical efficiency in computation.
Blueprint for implementing USP chapter 797 for compounding sterile preparations.

Guidelines for adopting and successfully implementing the requirements of the United States Pharmacopeia (USP) chapter 797 for compounding sterile preparations are presented.



The quality of a compounded sterile preparation (CSP) is directly related to the methods used to ensure that the CSP achieves the desired goal of purity, potency, and sterility. A properly designed, constructed, and maintained cleanroom contributes to the quality of CSPs. Design criteria of a sample clean-room are supplied, as are a summary and comparison of the liquid disinfectants that can be used to clean and sanitize the facility and maintain environmental controls. All activities associated with cleaning the cleanroom, including air and surface sampling, must be properly documented in logs, examples of which are provided. A robust employee-training program for properly teaching aseptic technique and a method to verify that personnel have successfully completed the program are integral to compliance with chapter 797 and thoroughly discussed herein. Emerging compounding and testing technology is also discussed.



Although the task of compliance with the requirements of USP chapter 797 may appear overwhelming, complicated, expensive, and even unattainable, quality can be established via a methodical and organized approach. After the systems have been implemented, maintaining them requires vigilance and follow-up. Compliance with chapter 797 involves up-front and ongoing costs associated with establishing these systems, but the time, energy, and cost required to maintain them are far less than those of retrospective or manual systems of collecting, reviewing, and collating quality assurance data on a monthly basis.
Simultaneous homicide-suicide: a case report of double drowning.

Homicide-suicide is a tragic phenomenon which typically does not result in a criminal charge or trial. However, correct diagnosis and classification of homicide-suicide cases are important to determine the perpetrators and dynamics of each category properly. The deaths in the homicide-suicide acts can be divided into two categories with respect to the number of involved individuals: dyadic deaths and triple or multiple deaths. These two categories can also be divided into two subgroups according to the chronology of the incidents: simultaneous deaths and consecutive deaths. Herein, a simultaneous homicide-suicide case of a father and daughter where both deaths occurred through drowning which was not found in the selected literature review and where the victim was a child is presented. The article aims to clarify the term discrepancies about multiple death cases in the literature and to discuss the pathological and psychosocial characteristics of the simultaneous dyadic death cases.
Automated Broadband High-Dynamic-Range Nonlinear Distortion Measurement System

This paper presents an intermodulation distortion measurement system based on automated feedforward cancellation that achieves 113 dB of broadband spurious-free dynamic range for discrete tone separations down to 100 Hz. For 1-Hz tone separation, the dynamic range is 106 dB, limited by carrier phase noise. A single-tone cancellation formula is developed requiring only the power of the probing signal and the power of the combined probe and cancellation signal so that the phase shift required for cancellation can be predicted. The technique is applied to a two-path feedforward cancellation system in a bridge configuration. The effects of reflected signals and of group delay on system performance is discussed. Spurious frequency content and interchannel coupling are analyzed with respect to system linearity. Feedforward cancellation and consideration of electromagnetic radiation coupling and reverse-wave isolation effects extends the dynamic range of spectrum and vector analyzers by at least 40 dB. Application of the technique to the measurement of correlated and uncorrelated nonlinear distortion of an amplified wideband code-division multiple-access signal is presented.
Argument Extraction from News

Argument extraction is the task of identifying arguments, along with their components in text. Arguments can be usually decomposed into a claim and one or more premises justifying it. The proposed approach tries to identify segments that represent argument elements (claims and premises) on social Web texts (mainly news and blogs) in the Greek language, for a small set of thematic domains, including articles on politics, economics, culture, various social issues, and sports. The proposed approach exploits distributed representations of words, extracted from a large non-annotated corpus. Among the novel aspects of this work is the thematic domain itself which relates to social Web, in contrast to traditional research in the area, which concentrates mainly on law documents and scientific publications. The huge increase of social web communities, along with their user tendency to debate, makes the identification of arguments in these texts a necessity. In addition, a new manually annotated corpus has been constructed that can be used freely for research purposes. Evaluation results are quite promising, suggesting that distributed representations can contribute positively to the task of argument extraction.
Massive MIMO: survey and future research topics

Massive multiple-input multiple-output technology has been considered a breakthrough in wireless communication systems. It consists of equipping a base station with a large number of antennas to serve many active users in the same time-frequency block. Among its underlying advantages is the possibility to focus transmitted signal energy into very short-range areas, which will provide huge improvements in terms of system capacity. However, while this new concept renders many interesting benefits, it brings up new challenges that have called the attention of both industry and academia: channel state information acquisition, channel feedback, instantaneous reciprocity, statistical reciprocity, architectures, and hardware impairments, just to mention a few. This paper presents an overview of the basic concepts of massive multiple-input multiple-output, with a focus on the challenges and opportunities, based on contemporary research.