nils-herrmann/clean_scirepeval huggingface dataset:
Stereo Acoustic Echo Cancellation Employing Frequency-Domain Preprocessing and Adaptive Filter

This paper proposes a windowing frequency domain adaptive filter and an upsampling block transform preprocessing to solve the stereo acoustic echo cancellation problem. The proposed adaptive filter uses windowing functions with smooth cutoff property to reduce the spectral leakage during filter updating, so the utilization of the independent noise introduced by preprocessing in stereo acoustic echo cancellation can be increased. The proposed preprocessing is operated in short blocks with low processing delay, and it uses frequency-domain upsampling to meet the minimal block length requirement given by the band limit of simultaneous masking. Therefore, the simultaneous masking can be well utilized to improve the audio quality. The acoustic echo cancellation simulations and the audio quality evaluation show that, the proposed windowing frequency domain adaptive filter performs better than the conventional frequency domain adaptive filter in both mono and stereo cases, and the upsampling block transform preprocessing provides better audio quality and stereo acoustic echo cancellation performance than the half-wave preprocessing at the same noise level.
Emerging tobacco hazards in China: 1. Retrospective proportional mortality study of one million deaths.

To assess the hazards at an early phase of the growing epidemic of deaths from tobacco in China.



Smoking habits before 1980 (obtained from family or other informants) of 0.7 million adults who had died of neoplastic, respiratory, or vascular causes were compared with those of a reference group of 0.2 million who had died of other causes.



24 urban and 74 rural areas of China.



One million people who had died during 1986-8 and whose families could be interviewed.



Tobacco attributable mortality in middle or old age from neoplastic, respiratory, or vascular disease.



Among male smokers aged 35-69 there was a 51% (SE 2) excess of neoplastic deaths, a 31% (2) excess of respiratory deaths, and a 15% (2) excess of vascular deaths. All three excesses were significant (P<0.0001). Among male smokers aged >/70 there was a 39% (3) excess of neoplastic deaths, a 54% (2) excess of respiratory deaths, and a 6% (2) excess of vascular deaths. Fewer women smoked, but those who did had tobacco attributable risks of lung cancer and respiratory disease about the same as men. For both sexes, the lung cancer rates at ages 35-69 were about three times as great in smokers as in non-smokers, but because the rates among non-smokers in different parts of China varied widely the absolute excesses of lung cancer in smokers also varied. Of all deaths attributed to tobacco, 45% were due to chronic obstructive pulmonary disease and 15% to lung cancer; oesophageal cancer, stomach cancer, liver cancer, tuberculosis, stroke, and ischaemic heart disease each caused 5-8%. Tobacco caused about 0.6 million Chinese deaths in 1990 (0.5 million men). This will rise to 0.8 million in 2000 (0.4 million at ages 35-69) or to more if the tobacco attributed fractions increase.



At current age specific death rates in smokers and non-smokers one in four smokers would be killed by tobacco, but as the epidemic grows this proportion will roughly double. If current smoking uptake rates persist in China (where about two thirds of men but few women become smokers) tobacco will kill about 100 million of the 0.3 billion males now aged 0-29, with half these deaths in middle age and half in old age.
A DIRT-T A PPROACH TO U NSUPERVISED D OMAIN

Domain adaptation refers to the problem of leveraging labeled data in a source domain to learn an accurate model in a target domain where labels are scarce or unavailable. A recent approach for finding a common representation of the two domains is via domain adversarial training (Ganin & Lempitsky, 2015), which attempts to induce a feature extractor that matches the source and target feature distributions in some feature space. However, domain adversarial training faces two critical limitations: 1) if the feature extraction function has high-capacity, then feature distribution matching is a weak constraint, 2) in non-conservative domain adaptation (where no single classifier can perform well in both the source and target domains), training the model to do well on the source domain hurts performance on the target domain. In this paper, we address these issues through the lens of the cluster assumption, i.e., decision boundaries should not cross high-density data regions. We propose two novel and related models: 1) the Virtual Adversarial Domain Adaptation (VADA) model, which combines domain adversarial training with a penalty term that punishes violation of the cluster assumption; 2) the Decision-boundary Iterative Refinement Training with a Teacher (DIRT-T)1 model, which takes the VADA model as initialization and employs natural gradient steps to further minimize the cluster assumption violation. Extensive empirical results demonstrate that the combination of these two models significantly improve the state-of-the-art performance on the digit, traffic sign, and Wi-Fi recognition domain adaptation benchmarks.
Image flower recognition based on a new method for color feature extraction

In this paper, we present, first, a new method for color feature extraction based on SURF detectors. Then, we proved its efficiency for flower image classification. Therefore, we described visual content of the flower images using compact and accurate descriptors. These features are combined and the learning process is performed using a multiple kernel framework with a SVM classifier. The proposed method has been tested on the dataset provided by the university of oxford and achieved better results than our implementation of the method proposed by Nilsback and Zisserman (Nilsback and Zisserman, 2008) in terms of classification rate and execution time.
Vital Sign Detection Method Based on Multiple Higher Order Cumulant for Ultrawideband Radar

The research on vital information extraction meets a lot challenges due to the narrow bandwidth and low signal-to-noise ratio of a vital sign in real environment. In this paper, a novel noncontract vital sign detection method based on multiple higher order cumulant is presented. According to the characteristic of vital sign for impulse ultrawideband radar, the quasi-periodic reflected echo in slow-time is analyzed. The novel method is theoretically deduced from fourth-order cumulant. It is proved to be better than the reference fast Fourier transform method by simulation and experiment. By using the new method, the range position and frequency information of life can be extracted accurately and automatically.
Improved direct back EMF detection for sensorless brushless DC (BLDC) motor drives

Improved back EMF detection circuits for low voltage/low speed and high voltage sensorless BLDC motor drives are presented in this paper. The improvements are based on the direct back EMF sensing method from our previous research work described in reference, which describes a technique for directly extracting phase back EMF information without the need to sense or re-construct the motor neutral. The reference method is not sensitive to switching noise and requires no filtering, achieving much better performance than traditional back EMF sensing scheme. A complementary PWM (synchronous rectification) is proposed to reduce the power dissipation in power devices for low voltage applications. In order to further extend the sensorless BLDC system to lower speed, a pre-conditioning circuit is proposed to amplify the back EMFs at very low speed. As a result, the brushless DC motor can run at lower speed with the improved back EMF sensing scheme. On the other hand, another improved detection circuit is presented for high voltage applications to overcome the delaying problem caused by large sensing resistors. The detailed circuit models are analyzed and experimental results verify the analysis.
Imaging the intervertebral disk: age-related changes, herniations, and radicular pain.

The articulations of the spinal motion segment, the intervertebral disk, and the zygapophyseal joints, inevitably undergo age-related changes. This article focuses on the intervertebral disk, specifically when fissures sufficiently weaken the posterior annulus so as to allow herniation of nuclear material into the outer annular structure as a contained protrusion or breach the annulus and pass into the epidural space as an extrusion. This article examines the imaging of the age-related changes of the disk and disk herniation: nomenclature, the reliability and relative merits of imaging modalities, the imaging natural history of disk herniations, and, most importantly, the clinical significance.
A MODEL FOR SUSTAINABLE WAREHOUSING : FROM THEORY TO BEST PRACTICES

Sustainable Warehousing has tremendous potential to achieve goals of sustainable development but it is not well-researched for its impact on environmental, social and economic dimensions of sustainability. The authors have examined both academic literature and industry publications to extract high level constructs and operational elements for a sustainable warehouse. Content analysis was used to identify and develop sustainable warehousing themes which were then rigorously tested against industry standards to ensure their validity and reliability. These constructs and elements led to the development of a ‘sustainable warehousing model’ that is then translated into best practices to achieve environmental quality, social well-being and economic value in a warehouse.
Norms for word lists that create false memories.

Roediger and McDermott (1995) induced false recall and false recognition for words that were not presented in lists. They had subjects study 24 lists of 15 words that were associates of a common word (called the critical target or critical lure) that was not presented in the list. False recall and false recognition of the critical target occurred frequently in response to these lists. The purpose of the current work was to provide a set of normative data for the lists Roediger and McDermott used and for 12 others developed more recently. We tested false recall and false recognition for critical targets from 36 lists. Despite the fact that all lists were constructed to produce false remembering, the diversity in their effectiveness was large--60% or more of subjects falsely recalled window and sleep following the appropriate lists, and false recognition for these items was greater than 80%. However, the list generated from king led to 10% false recall and 27% false recognition. Possible reasons for these wide differences in effectiveness of the lists are discussed. These norms serve as a useful benchmark for designing experiments about false recall and false recognition in this paradigm.
iMecho: an associative memory based desktop search system

Traditional desktop search engines only support keyword based search that needs exact keyword matching to find resources. However, users generally have a vague picture of what is stored but forget the exact location and keywords of the resource. According to observations of human associative memory, people tend to remember things from some memory fragments in their brains and these memory fragments are connected by memory cues of user activity context. We developed iMecho (My Memory Echo), an associative memory based desktop search system, which exploits such associations and contexts to enhance traditional desktop search. Desktop resources are connected with semantic links mined from explicit and implicit user activities according to specific access patterns. Using these semantic links, associations among memory fragments can be built or rebuilt in a user's brain during a search. Moreover, our personalized ranking scheme uses these links together with a user's personal preferences to rank results by both relevance and importance to the user. In addition, the system provides a faceted search feature and association graph navigation to help users refine and associate search results generated by full-text keyword search. Our experiments investigating precision and recall quality of iMecho prototype show that the association-based search system is superior to the traditional keyword search in personal search engines since it is closer to the way that human associative memory works.
Computer Generated Celtic Design

We present a technique for automating the construction of Celtic knotwork and decorations similar to those in illuminated manuscripts such as the Lindisfarne Gospels. Our method eliminates restrictions imposed by previous methods which limited the class of knots that could be produced correctly by introducing new methods for smoothing and orienting threads. Additionally, we present techniques for interweaving and attaching images to the knotwork and techniques to encapsulate knot patterns to simplify the design process. Finally we show how to use such knotwork in 3D and demonstrate a variety of applications including artwork and transforming the designs into 3D models for fabrication.
Secure Surfing: Privacy-Preserving Speeded-Up Robust Feature Extractor

Large-scale multimedia data are being exponentially generated, stored and processed continuously nowadays. Along with the data explosion, the data owner is highly motivated to outsource his/her huge amount of data storage and computation-expensive processing jobs to the cloud by leveraging its abundant resources for cost reduction and flexibility. Despite the fascinating advantages, security and privacy concerns are the primary obstacles that prevent the wide adoption of this promising information technology paradigm. In this work, we aim at outsourcing Speeded-up Robust Features (SURF), a widely-used feature extraction algorithm, to the intrinsically untrusted cloud, while protecting data owner's private information on the outsourced image data. We, for the first time, propose a practical privacy-preserving outsoucing scheme for SURF that can preserve its key characteristics in terms of distinctiveness and robustness. By randomly splitting the original image data and distributing the encrypted data shares to two independent cloud servers, we first design two novel efficient protocols for secure multiplication and comparison by leveraging somewhat homomorphic encryption (SHE) and single-instruction multiple-data (SIMD). We then carefully tune every step of the original SURF to adapt it to the ciphertext domain. A thorough theoretical analysis of effectiveness and security shows that our scheme is practically secure and approximates well the performance of the original SURF executed in the plaintext domain. Extensive experiments are also conducted over real-world image datasets to show that our scheme outperforms the existing solution and indeed performs comparably to the original SURF in preserving its various characteristics including image scale invariance, rotation invariance and robust matching across 3D viewpoint change etc.
A model for high school computer science education: the four key elements that make it!

This paper presents a model program for high school computer science education. It is based on an analysis of the structure of the Israeli high school computer science curriculum considered to be one of the leading curricula worldwide. The model consists of four key elements as well as interconnections between these elements. It is proposed that such a model be considered and/or adapted when a country wishes to implement a nation-wide program for high school computer science education.
The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces

We present an unsupervised algorithm for registering 3D surface scans of a deformable object in very different configurations. Our algorithm does not use markers, nor does it assume prior knowledge about object shape, the dynamics of its deformation, or its alignment. The algorithm finds the correspondences between points in the two meshes using a joint probabilistic model over all point correspondences. This model combines preservation of local mesh geometry with more global constraints that capture the preservation of geodesic distance between corresponding pairs of points in the two meshes. Our approach successfully registers scans that exhibit large transformations, including both movement of articulate parts and non-rigid surface deformations. It applies even when one of the meshes is an incomplete range scan; thus, it can be used to automatically fill in the remaining surfaces for this partial scan, even if those surfaces were previously only seen in a different configuration. We also show how our results can be used to interpolate between two scans of a non-rigid object in a way that preserves surface geometry, leading to natural motion paths. Finally, we show that a registration of multiple scans in different configurations allows us to automatically identify components in articulate objects.
ACT-R/PM and menu selection: applying a cognitive architecture to HCI

Understanding the interaction of a user with a designed device such as a GUI requires clear understanding of three components: the cognitive, perceptual, and motor capabilities of the user, the task to be accomplished, and the artifact used to accomplish the task. Computational modeling systems which enable serious consideration all of these constraints have only recently begun to emerge. One such system is ACT-R/PM, which is described in detail. ACT-R/PM is a production system architecture that has been augmented with a set of perceptual-motor modules designed to enable the detailed modeling of interactive tasks. Nilsen’s (1991) random menu selection task serves two goals: to illustrate the promise of this system and to help further our understanding of the processes underlying menu selection and visual search. Nilsen’s original study, two earlier models of the task, and recent eye-tracking data are all considered. Drawing from the best properties of the previous models and guided by information from the eye-tracking experiment, a series of new models of random menu selection were constructed using ACTR/PM. The final model provides a zero-parameter fit to the data that does an acceptable, though imperfect, job of capturing the data. ACT-R/PM for HCI 2
A Generic Coordinate Descent Framework for Learning from Implicit Feedback

In recent years, interest in recommender research has shifted from explicit feedback towards implicit feedback data. A diversity of complex models has been proposed for a wide variety of applications. Despite this, learning from implicit feedback is still computationally challenging. So far, most work relies on stochastic gradient descent (SGD) solvers which are easy to derive, but in practice challenging to apply, especially for tasks with many items. For the simple matrix factorization model, an efficient coordinate descent (CD) solver has been previously proposed. However, efficient CD approaches have not been derived for more complex models. In this paper, we provide a new framework for deriving efficient CD algorithms for complex recommender models. We identify and introduce the property of k-separable models. We show that k-separability is a sufficient property to allow efficient optimization of implicit recommender problems with CD. We illustrate this framework on a variety of state-of-the-art models including factorization machines and Tucker decomposition. To summarize, our work provides the theory and building blocks to derive efficient implicit CD algorithms for complex recommender models.
The Effects of Overlearning and Distributed Practise on the Retention of Mathematics Knowledge

In two experiments, 216 college students learned to solve one kind of mathematics problem before completing one of various practise schedules. In Experiment 1, students either massed 10 problems in a single session or distributed these 10 problems across two sessions separated by 1 week. The benefit of distributed practise was nil among students who were tested 1 week later but extremely large among students tested 4 weeks later. In Experiment 2, students completed three or nine practise problems in one session. The additional six problems constituted a strategy known as overlearning, but this extra effort had no effect on test scores 1 or 4 weeks later. Thus, long-term retention was boosted by distributed practise and unaffected by overlearning. Unfortunately, most mathematics textbooks rely on a format that emphasises overlearning and minimises distributed practise. An easily adopted alternative format is advocated.
Workplace harassment: double jeopardy for minority women.

To date there have been no studies of how both sex and ethnicity might affect the incidence of both sexual and ethnic harassment at work. This article represents an effort to fill this gap. Data from employees at 5 organizations were used to test whether minority women are subject to double jeopardy at work, experiencing the most harassment because they are both women and members of a minority group. The results supported this prediction. Women experienced more sexual harassment than men, minorities experienced more ethnic harassment than Whites, and minority women experienced more harassment overall than majority men, minority men, and majority women.
Constraint-based equilibrium and stiffness control of variable stiffness actuators

Considerable research effort has gone into the design of variable passive stiffness actuators (VSAs). A number of different mechanical designs have been proposed, aimed at either a biomorphic (i.e., antagonistic) design, compactness, or simplified modelling and control. In this paper, we propose a (model-based) unified control methodology that is able to exploit the benefits of variable stiffness independent of the specifics of the mechanical design. Our approach is based on forming constraints on commands sent to the VSA to ensure that the equilibrium position and stiffness of the VSA are tracked to the desired values. We outline how our approach can be used for tracking stiffness and equilibrium position both in joint and task space, and how it may be used in the context of constrained local optimal control. In our experiments we illustrate the utility of our approach in the context of online teleoperation, to transfer compliant human behaviour to a variable stiffness device.
Digital Image Forgeries and Passive Image Authentication Techniques: A Survey

Digital images are present everywhere on magazine covers, in newspapers, in courtrooms as evidences, and all over the Internet signifying one of the major ways for communication nowadays. The trustworthiness of digital images has been questioned, because of the ease with which these images can be manipulated in both its origin & content as a result of tremendous growth of digital image manipulation tools. Digital image forensics is the latest research field which intends to authorize the genuineness of images. This survey attempts to provide an overview of various digital image forgeries and the state of art passive methods to authenticate digital images.