nils-herrmann/clean_scirepeval huggingface dataset:
Why is sexual abuse declining ? A survey of state child protection administrators *

Cases of substantiated sexual abuse have declined approximately 39% nationwide from 1992 to 1999, according to estimates from the National Child Abuse and Neglect Data System (NCANDS). Despite the dramatic nature of the decline, little discussion of the trend has occurred at either the national or the state level. Aims of the research were to: (1) gather state-level information about possible sources of the sexual abuse deciine, (2) identify child protection trends that might be contributing to the decline, and (3) assess the level of awareness of the decline in state child protection offices.  Telephone interviews were conducted with child protection administrators in 43 states.  More than half of the officials in states with large declines were unaware of any discussion of the declines within their agency or in the public at large within their state. State officials cited a diverse array of possible causes for the decline, including: ( I ) increased evidentiary requirements to substantiate cases. (2) increased caseworker caution due to new legal rights for caregivers, and (3) increasing limitations on the lypes of cases that agencies accept for investigation. More than half also mentioned the effectiveness of prevention programs, increased prosecution, and public awareness campaigns: implying that a portion of the decline may result from a real decline in occurrence. This project was supported by a grant from the Office of Juvenile Justice and Delinquency Prevention (#98-JN-FX-0012).  Corresponding author. 0145-2134/01/$ see front matter O 2001 Elsevier  Pa: SOl45-2134(OI )00263-
Advanced Beamformers for Cochlear Implant Users: Acute Measurement of Speech Perception in Challenging Listening Conditions

To investigate the performance of monaural and binaural beamforming technology with an additional noise reduction algorithm, in cochlear implant recipients.



This experimental study was conducted as a single subject repeated measures design within a large German cochlear implant centre. Twelve experienced users of an Advanced Bionics HiRes90K or CII implant with a Harmony speech processor were enrolled. The cochlear implant processor of each subject was connected to one of two bilaterally placed state-of-the-art hearing aids (Phonak Ambra) providing three alternative directional processing options: an omnidirectional setting, an adaptive monaural beamformer, and a binaural beamformer. A further noise reduction algorithm (ClearVoice) was applied to the signal on the cochlear implant processor itself. The speech signal was presented from 0° and speech shaped noise presented from loudspeakers placed at ±70°, ±135° and 180°. The Oldenburg sentence test was used to determine the signal-to-noise ratio at which subjects scored 50% correct.



Both the adaptive and binaural beamformer were significantly better than the omnidirectional condition (5.3 dB±1.2 dB and 7.1 dB±1.6 dB (p<0.001) respectively). The best score was achieved with the binaural beamformer in combination with the ClearVoice noise reduction algorithm, with a significant improvement in SRT of 7.9 dB±2.4 dB (p<0.001) over the omnidirectional alone condition.



The study showed that the binaural beamformer implemented in the Phonak Ambra hearing aid could be used in conjunction with a Harmony speech processor to produce substantial average improvements in SRT of 7.1 dB. The monaural, adaptive beamformer provided an averaged SRT improvement of 5.3 dB.
Use of physiological signals to predict cybersickness

http://dx.doi.org/10.1016/j.displa.2016.07.002 0141-9382/ 2016 Elsevier B.V. All rights reserved.  This paper was recommended for publication by Richard H.Y. So. ⇑ Corresponding author at: University of California, Irvine, 2201 Social & Behavioral Sciences Gateway Building, Irvine, CA 92697-5100, USA. E-mail addresses: mdenniso@uci.edu (M.S. Dennison), awisti@uci.edu (A.Z. Wisti), mdzmura@uci.edu (M. D’Zmura). Mark S. Dennison ⇑, A. Zachary Wisti, Michael D’Zmura
Agenda-Based User Simulation for Bootstrapping a POMDP Dialogue System

This paper investigates the problem of bootstrapping a statistical dialogue manager without access to training data and proposes a new probabilistic agenda-based method for simulating user behaviour. In experiments with a statistical POMDP dialogue system, the simulator was realistic enough to successfully test the prototype system and train a dialogue policy. An extensive study with human subjects showed that the learned policy was highly competitive, with task completion rates above 90%. 1 Background and Introduction 1.1 Bootstrapping Statistical Dialogue Managers One of the key advantages of a statistical approach to Dialogue Manager (DM) design is the ability to formalise design criteria as objective reward functions and to learn an optimal dialogue policy from real dialogue data. In cases where a system is designed from scratch, however, it is often the case that no suitable in-domain data is available for training the DM. Collecting dialogue data without a working prototype is problematic, leaving the developer with a classic chicken-and-egg problem. Wizard-of-Oz (WoZ) experiments can be carried out to record dialogues, but they are often time-consuming and the recorded data may show characteristics of humanhuman conversation rather than typical human-computer dialogue. Alternatively, human-computer dialogues can be recorded with a handcrafted DM prototype but neither of these two methods enables the system designer to test the implementation of the statistical DM and the learning algorithm. Moreover, the size of the recorded corpus (typically 10 dialogues) usually falls short of the requirements for training a statistical DM (typically 10 dialogues). 1.2 User Simulation-Based Training In recent years, a number of research groups have investigated the use of a two-stage simulation-based setup. A statistical user model is first trained on a limited amount of dialogue data and the model is then used to simulate dialogues with the interactively learning DM (see Schatzmann et al. (2006) for a literature review). The simulation-based approach assumes the presence of a small corpus of suitably annotated in-domain dialogues or out-of-domain dialogues with a matching dialogue format (Lemon et al., 2006). In cases when no such data is available, handcrafted values can be assigned to the model parameters given that the model is sufficiently simple (Levin et al., 2000; Pietquin and Dutoit, 2005) but the performance of dialogue policies learned this way has not been evaluated using real users.
Funnel-structured cascade for multi-view face detection with alignment-awareness

Multi-view face detection in open environment is a challenging task due to diverse variations of face appearances and shapes. Most multi-view face detectors depend on multiple models and organize them in parallel, pyramid or tree structure, which compromise between the accuracy and time-cost. Aiming at a more favorable multi-view face detector, we propose a novel funnel-structured cascade (FuSt) detection framework. In a coarse-to-fine flavor, our FuSt consists of, from top to bottom, 1) multiple view-specific fast LAB cascade for extremely quick face proposal, 2) multiple coarse MLP cascade for further candidate window verification, and 3) a unified fine MLP cascade with shape-indexed features for accurate face detection. Compared with other structures, on the one hand, the proposed one uses multiple computationally efficient distributed classifiers to propose a small number of candidate windows but with a high recall of multi-view faces. On the other hand, by using a unified MLP cascade to examine proposals of all views in a centralized style, it provides a favorable solution for multiview face detection with high accuracy and low time-cost. Besides, the FuSt detector is alignment-aware and performs a coarse facial part prediction which is beneficial for subsequent face alignment. Extensive experiments on two challenging datasets, FDDB and AFW, demonstrate the effectiveness of our FuSt detector in both accuracy and speed.
Agronomy for sustainable agriculture. A review

Sustainability rests on the principle that we must meet the needs of the present without compromising the ability of future generations to meet their own needs. Starving people in poor nations, obesity in rich nations, increasing food prices, on-going climate changes, increasing fuel and transportation costs, flaws of the global market, worldwide pesticide pollution, pest adaptation and resistance, loss of soil fertility and organic carbon, soil erosion, decreasing biodiversity, desertification, and so on. Despite unprecedented advances in sciences allowing us to visit planets and disclose subatomic particles, serious terrestrial issues about food show clearly that conventional agriculture is no longer suited to feeding humans and preserving ecosystems. Sustainable agriculture is an alternative for solving fundamental and applied issues related to food production in an ecological way (Lal (2008) ). While conventional agriculture is driven almost solely by productivity and profit, sustainable agriculture integrates biological, chemical, physical, ecological, economic and social sciences in a comprehensive way to develop new farming practices that are safe and do not degrade our environment. To address current agronomical issues and to promote worldwide discussions and cooperation we implemented sharp changes at the journal Agronomy for Sustainable Development from 2003 to 2006. Here we report (1) the results of the renovation of the journal and (2) a short overview of current concepts of agronomical research for sustainable agriculture. Considered for a long time as a soft, side science, agronomy is rising fast as a central science because current issues are about food, and humans eat food. This report is the introductory article of the book Sustainable Agriculture, volume 1, published by EDP Sciences and Springer (Lichtfouse et al. (2009)
Recent advances in video-based human action recognition using deep learning: A review

Video-based human action recognition has become one of the most popular research areas in the field of computer vision and pattern recognition in recent years. It has a wide variety of applications such as surveillance, robotics, health care, video searching and human-computer interaction. There are many challenges involved in human action recognition in videos, such as cluttered backgrounds, occlusions, viewpoint variation, execution rate, and camera motion. A large number of techniques have been proposed to address the challenges over the decades. Three different types of datasets namely, single viewpoint, multiple viewpoint and RGB-depth videos, are used for research. This paper presents a review of various state-of-the-art deep learning-based techniques proposed for human action recognition on the three types of datasets. In light of the growing popularity and the recent developments in video-based human action recognition, this review imparts details of current trends and potential directions for future work to assist researchers.
Achieving lightweight trustworthy traceability

Despite the fact that traceability is a required element of almost all safety-critical software development processes, the trace data is often incomplete, inaccurate, redundant, conflicting, and outdated. As a result, it is neither trusted nor trustworthy. In this vision paper we propose a philosophical change in the traceability landscape which transforms traceability from a heavy-weight process producing untrusted trace links, to a light-weight results-oriented trustworthy solution. Current traceability practices which retard agility are cast away and replaced with a disciplined, just-in-time approach. The novelty of our solution lies in a clear separation of trusted trace links from untrusted ones, the change in perspective from `living-with' inacurate traces toward rigorous and ongoing debridement of stale links from the trusted pool, and the notion of synthesizing available `project exhaust' as evidence to systematically construct or reconstruct purposed, highly-focused trace links.
High-Isolation, Low Cross-Polarization, Dual- Polarization, Hybrid Feed Microstrip Patch Array Antenna for MPAR Application

This paper presents a high-isolation, low cross-polarization dual-polarized patch antenna for multifunction phased array radar applications. Its hybrid feed design has been implemented, and the vertical and horizontal polarizations are excited by a balanced-probe feed and a slot-coupled feed, respectively. Simulations and measurements have demonstrated an input isolation of 45 and 43 dB between the horizontal and vertical ports, respectively. For further improvement in the cross-polarization level, the image feed method is also implemented, and a <inline-formula> <tex-math notation="LaTeX">$2\times 2$ </tex-math></inline-formula>-element array made up of designed elements with image configuration has been fabricated. The simulated and measured S-parameter and radiation patterns of the horizontal and vertical polarizations of the designed <inline-formula> <tex-math notation="LaTeX">$2\times 2$ </tex-math></inline-formula>-element array are presented and the measured cross-polarization level of less than −37 dB is achieved. To examine the performance of the designed element in an array, a <inline-formula> <tex-math notation="LaTeX">$3\times 3$ </tex-math></inline-formula>-element array of designed <inline-formula> <tex-math notation="LaTeX">$2\times 2$ </tex-math></inline-formula>-element subarray is fabricated and tested. In the <inline-formula> <tex-math notation="LaTeX">$6\times 6$ </tex-math></inline-formula>-element measurements, −35.4 and −36 dB cross-polarization levels for horizontal and vertical polarizations are achieved, respectively. Also, using the measured embedded element patterns, the cross-polarization level lower than −36 dB for scan angles up to 45° is achieved.
Social network security: Issues, challenges, threats, and solutions

Social networks are very popular in today‘s world. Millions of people use various forms of social networks as they allow individuals to connect with friends and family, and share private information. However, issues related to maintaining the privacy and security of a user‘s information can occur, especially when the user‘s uploaded content is multimedia, such as photos, videos, and audios. Uploaded multimedia content carries information that can be transmitted virally and almost instantaneously within a social networking site and beyond. In this paper, we present a comprehensive survey of different security and privacy threats that target every user of social networking sites. In addition, we separately focus on various threats that arise due to the sharing of multimedia content within a social networking site. We also discuss current state-ofthe-art defense solutions that can protect social network users from these threats. We then present future direction and discuss some easy-to-apply response techniques to achieve the goal of a trustworthy and secure social network ecosystem. KeywordsSocial network service, Security and privacy, Multimedia data, Security threats
Coil design guidelines for high efficiency of wireless power transfer (WPT)

Efficient operation of a wireless power transfer (WPT) system is a major design challenge in many WPT applications. This paper presents a method for designing a high efficiency WPT system when restrictions are imposed on receiver coil (Rx) size. The optimum pitch of the transmitter (Tx) and Rx coils is evaluated by analyzing the coil quality factor and coupling coefficient. Empirical formulae are proposed to derive generalized design guidelines for a given Rx size. The proposed empirical approach can be directly used for the design of a WPT with miniaturized Rx coils without using time consuming optimization algorithms. The proposed empirical expressions are validated with experimental results.
Database Abstractions: Aggregation and Generalization

Two kinds of abstraction that are fundamentally important in database design and usage are defined. Aggregation is an abstraction which turns a relationship between objects into an aggregate object. Generalization is an abstraction which turns a class of objects into a generic object. It is suggested that all objects (individual, aggregate, generic) should be given uniform treatment in models of the real world. A new data type, called generic, is developed as a primitive for defining such models. Models defined with this primitive are structured as a set of aggregation hierarchies intersecting with a set of generalization hierarchies. Abstract objects occur at the points of intersection. This high level structure provides a discipline for the organization of relational databases. In particular this discipline allows: (i) an important class of views to be integrated and maintained; (ii) stability of data and programs under certain evolutionary changes; (iii) easier understanding of complex models and more natural query formulation; (iv) a more systematic approach to database design; (v) more optimization to be performed at lower implementation levels. The generic type is formalized by a set of invariant properties. These properties should be satisfied by all relations in a database if abstractions are to be preserved. A triggering mechanism for automatically maintaining these invariants during update operations is proposed. A simple mapping of aggregation/generalization hierarchies onto owner-coupled set structures is given.
A Survey of Non-conventional Techniques for Low-voltage Low-power Analog Circuit Design

Designing integrated circuits able to work under low-voltage (LV) low-power (LP) condition is currently undergoing a very considerable boom. Reducing voltage supply and power consumption of integrated circuits is crucial factor since in general it ensures the device reliability, prevents overheating of the circuits and in particular prolongs the operation period for battery powered devices. Recently, non-conventional techniques i.e. bulkdriven (BD), floating-gate (FG) and quasi-floating-gate (QFG) techniques have been proposed as powerful ways to reduce the design complexity and push the voltage supply towards threshold voltage of the MOS transistors (MOST). Therefore, this paper presents the operation principle, the advantages and disadvantages of each of these techniques, enabling circuit designers to choose the proper design technique based on application requirements. As an example of application three operational transconductance amplifiers (OTA) based on these non-conventional techniques are presented, the voltage supply is only ±0.4 V and the power consumption is 23.5 μW. PSpice simulation results using the 0.18 μm CMOS technology from TSMC are included to verify the design functionality and correspondence with theory.
Boosting energy efficiency with mirrored data block replication policy and energy scheduler

Energy efficiency is one of the major challenges in big datacenters. To facilitate processing of large data sets in a distributed fashion, the MapReduce programming model is employed in these datacenters. Hadoop is an open-source implementation of MapReduce which contains a distributed file system. Hadoop Distributed File System provides a data block replication scheme to preserve reliability and data availability. The distribution of the data block replicas over the nodes is performed randomly by meeting some constraints (e.g., preventing storage of two replicas of a data block on a single node). This study makes use of flexibility in the data block placement policy to increase energy efficiency in datacenters. Furthermore, inspired by Zaharia et al.'s delay scheduling algorithm, a scheduling algorithm is introduced, which takes into account energy efficiency in addition to fairness and data locality properties. Computer simulations of the proposed method suggest its superiority over Hadoop's standard settings.
Firefly: illuminating future network-on-chip with nanophotonics

Future many-core processors will require high-performance yet energy-efficient on-chip networks to provide a communication substrate for the increasing number of cores. Recent advances in silicon nanophotonics create new opportunities for on-chip networks. To efficiently exploit the benefits of nanophotonics, we propose Firefly - a hybrid, hierarchical network architecture. Firefly consists of clusters of nodes that are connected using conventional, electrical signaling while the inter-cluster communication is done using nanophotonics - exploiting the benefits of electrical signaling for short, local communication while nanophotonics is used only for global communication to realize an efficient on-chip network. Crossbar architecture is used for inter-cluster communication. However, to avoid global arbitration, the crossbar is partitioned into multiple, logical crossbars and their arbitration is localized. Our evaluations show that Firefly improves the performance by up to 57% compared to an all-electrical concentrated mesh (CMESH) topology on adversarial traffic patterns and up to 54% compared to an all-optical crossbar (OP XBAR) on traffic patterns with locality. If the energy-delay-product is compared, Firefly improves the efficiency of the on-chip network by up to 51% and 38% compared to CMESH and OP XBAR, respectively.
Unsupervised Context-Sensitive Spelling Correction of English and Dutch Clinical Free-Text with Word and Character N-Gram Embeddings

We present an unsupervised context-sensitive spelling correction method for clinical free-text that uses word and character n-gram embeddings. Our method generates misspelling replacement candidates and ranks them according to their semantic fit, by calculating a weighted cosine similarity between the vectorized representation of a candidate and the misspelling context. To tune the parameters of this model, we generate self-induced spelling error corpora. We perform our experiments for two languages. For English, we greatly outperform off-the-shelf spelling correction tools on a manually annotated MIMIC-III test set, and counter the frequency bias of a noisy channel model, showing that neural embeddings can be successfully exploited to improve upon the state-of-the-art. For Dutch, we also outperform an off-the-shelf spelling correction tool on manually annotated clinical records from the Antwerp University Hospital, but can offer no empirical evidence that our method counters the frequency bias of a noisy channel model in this case as well. However, both our context-sensitive model and our implementation of the noisy channel model obtain high scores on the test set, establishing a state-of-the-art for Dutch clinical spelling correction with the noisy channel model.