nils-herrmann/clean_scirepeval huggingface dataset:
Bayesian just-so stories in psychology and neuroscience.

According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak. This weakness relates to the many arbitrary ways that priors, likelihoods, and utility functions can be altered in order to account for the data that are obtained, making the models unfalsifiable. It further relates to the fact that Bayesian theories are rarely better at predicting data compared with alternative (and simpler) non-Bayesian theories. Second, we show that the empirical evidence for Bayesian theories in neuroscience is weaker still. There are impressive mathematical analyses showing how populations of neurons could compute in a Bayesian manner but little or no evidence that they do. Third, we challenge the general scientific approach that characterizes Bayesian theorizing in cognitive science. A common premise is that theories in psychology should largely be constrained by a rational analysis of what the mind ought to do. We question this claim and argue that many of the important constraints come from biological, evolutionary, and processing (algorithmic) considerations that have no adaptive relevance to the problem per se. In our view, these factors have contributed to the development of many Bayesian "just so" stories in psychology and neuroscience; that is, mathematical analyses of cognition that can be used to explain almost any behavior as optimal.
Design of low-pass filters using defected ground structure

A method to design low-pass filters (LPF) having a defected ground structure (DGS) and broadened transmission-line elements is proposed. The previously presented technique for obtaining a three-stage LPF using DGS by Lim et al. is generalized to propose a method that can be applied in design N-pole LPFs for N/spl les/5. As an example, a five-pole LPF having a DGS is designed and measured. Accurate curve-fitting results and the successive design process to determine the required size of the DGS corresponding to the LPF prototype elements are described. The proposed LPF having a DGS, called a DGS-LPF, includes transmission-line elements with very low impedance instead of open stubs in realizing the required shunt capacitance. Therefore, open stubs, teeor cross-junction elements, and high-impedance line sections are not required for the proposed LPF, while they all have been essential in conventional LPFs. Due to the widely broadened transmission-line elements, the size of the DGS-LPF is compact.
A new depression scale designed to be sensitive to change.

The construction of a depression rating scale designed to be particularly sensitive to treatment effects is described. Ratings of 54 English and 52 Swedish patients on a 65 item comprehensive psychopathology scale were used to identify the 17 most commonly occurring symptoms in primary depressive illness in the combined sample. Ratings on these 17 items for 64 patients participating in studies of four different antidepressant drugs were used to create a depression scale consisting of the 10 items which showed the largest changes with treatment and the highest correlation to overall change. The inner-rater reliability of the new depression scale was high. Scores on the scale correlated significantly with scores on a standard rating scale for depression, the Hamilton Rating Scale (HRS), indicating its validity as a general severity estimate. Its capacity to differentiate between responders and non-responders to antidepressant treatment was better than the HRS, indicating greater sensitivity to change. The practical and ethical implications in terms of smaller sample sizes in clinical trials are discussed.
A Novel Active Gate Driver for Improving SiC MOSFET Switching Trajectory

The trend in power electronic applications is to reach higher power density and higher efficiency. Currently, the wide band-gap devices such as silicon carbide MOSFET (SiC MOSFET) are of great interest because they can work at higher switching frequency with low losses. The increase of the switching speed in power devices leads to high power density systems. However, this can generate problems such as overshoots, oscillations, additional losses, and electromagnetic interference (EMI). In this paper, a novel active gate driver (AGD) for improving the SiC MOSFET switching trajectory with high performance is presented. The AGD is an open-loop control system and its principle is based on gate energy decrease with a gate resistance increment during the Miller plateau effect on gate–source voltage. The proposed AGD has been designed and validated through experimental tests for high-frequency operation. Moreover, an EMI discussion and a performance analysis were realized for the AGD. The results show that the AGD can reduce the overshoots, oscillations, and losses without compromising the EMI. In addition, the AGD can control the turn-on and turn-off transitions separately, and it is suitable for working with asymmetrical supplies required by SiC MOSFETs.
Graph structure in the Web

The study of the web as a graph is not only fascinating in its own right, but also yields valuable insight into web algorithms for crawling, searching and community discovery, and the sociological phenomena which characterize its evolution. We report on experiments on local and global properties of the web graph using two Altavista crawls each with over 200 million pages and 1.5 billion links. Our study indicates that the macroscopic structure of the web is considerably more intricate than suggested by earlier experiments on a smaller scale.
Self-Reported Symptoms of Depression and PTSD Are Associated with Reduced Vowel Space in Screening Interviews

Reduced frequency range in vowel production is a well documented speech characteristic of individuals with psychological and neurological disorders. Affective disorders such as depression and post-traumatic stress disorder (PTSD) are known to influence motor control and in particular speech production. The assessment and documentation of reduced vowel space and reduced expressivity often either rely on subjective assessments or on analysis of speech under constrained laboratory conditions (e.g. sustained vowel production, reading tasks). These constraints render the analysis of such measures expensive and impractical. Within this work, we investigate an automatic unsupervised machine learning based approach to assess a speaker's vowel space. Our experiments are based on recordings of 253 individuals. Symptoms of depression and PTSD are assessed using standard self-assessment questionnaires and their cut-off scores. The experiments show a significantly reduced vowel space in subjects that scored positively on the questionnaires. We show the measure's statistical robustness against varying demographics of individuals and articulation rate. The reduced vowel space for subjects with symptoms of depression can be explained by the common condition of psychomotor retardation influencing articulation and motor control. These findings could potentially support treatment of affective disorders, like depression and PTSD in the future.
Differentiation Mechanisms for IEEE 802.11

The IETF is currently working on service differentiation in the Internet. However, in wireless environments where bandwidth is scarce and channel conditions are variable, IP differentiated services are suboptimal without lower layers’ support. In this paper we present three service differentiation schemes for IEEE 802.11. The first one is based on scaling the contention window according to the priority of each flow or user. The second one assigns different inter frame spacings to different users. Finally, the last one uses different maximum frame lengths for different users. We simulate and analyze the performance of each scheme with TCP and UDP flows. QoS, DiffServ, TCP, UDP, CBR, Wireless communications.
Toward Large-Scale Face Recognition Using Social Network Context

Personal photographs are being captured in digital form at an accelerating rate, and our computational tools for searching, browsing, and sharing these photos are struggling to keep pace. One promising approach is automatic face recognition, which would allow photos to be organized by the identities of the individuals they contain. However, achieving accurate recognition at the scale of the Web requires discriminating among hundreds of millions of individuals and would seem to be a daunting task. This paper argues that social network context may be the key for large-scale face recognition to succeed. Many personal photographs are shared on the Web through online social network sites, and we can leverage the resources and structure of such social networks to improve face recognition rates on the images shared. Drawing upon real photo collections from volunteers who are members of a popular online social network, we asses the availability of resources to improve face recognition and discuss techniques for applying these resources.
Optimal rectangle packing

We consider the NP-complete problem of finding an enclosing rectangle of minimum area that will contain a given a set of rectangles. We present two different constraintsatisfaction formulations of this problem. The first searches a space of absolute placements of rectangles in the enclosing rectangle, while the other searches a space of relative placements between pairs of rectangles. Both approaches dramatically outperform previous approaches to optimal rectangle packing. For problems where the rectangle dimensions have low precision, such as small integers, absolute placement is generally more efficient, whereas for rectangles with high-precision dimensions, relative placement will be more effective. In two sets of experiments, we find both the smallest rectangles and squares that can contain the set of squares of size 1 × 1, 2 × 2, . . . ,N × N , for N up to 27. In addition, we solve an open problem dating to 1966, concerning packing the set of consecutive squares up to 24 × 24 in a square of size 70 × 70. Finally, we find the smallest enclosing rectangles that can contain a set of unoriented rectangles of size 1 × 2, 2 × 3, 3 × 4, . . . ,N × (N + 1), for N up to 25.
A Systematic Review on the Practice of Evaluating Visualization

We present an assessment of the state and historic development of evaluation practices as reported in papers published at the IEEE Visualization conference. Our goal is to reflect on a meta-level about evaluation in our community through a systematic understanding of the characteristics and goals of presented evaluations. For this purpose we conducted a systematic review of ten years of evaluations in the published papers using and extending a coding scheme previously established by Lam et al. [2012]. The results of our review include an overview of the most common evaluation goals in the community, how they evolved over time, and how they contrast or align to those of the IEEE Information Visualization conference. In particular, we found that evaluations specific to assessing resulting images and algorithm performance are the most prevalent (with consistently 80-90% of all papers since 1997). However, especially over the last six years there is a steady increase in evaluation methods that include participants, either by evaluating their performances and subjective feedback or by evaluating their work practices and their improved analysis and reasoning capabilities using visual tools. Up to 2010, this trend in the IEEE Visualization conference was much more pronounced than in the IEEE Information Visualization conference which only showed an increasing percentage of evaluation through user performance and experience testing. Since 2011, however, also papers in IEEE Information Visualization show such an increase of evaluations of work practices and analysis as well as reasoning using visual tools. Further, we found that generally the studies reporting requirements analyses and domain-specific work practices are too informally reported which hinders cross-comparison and lowers external validity.
Addressing the cold-start problem in location recommendation using geo-social correlations

Location-based social networks (LBSNs) have attracted an increasing number of users in recent years, resulting in large amounts of geographical and social data. Such LBSN data provide an unprecedented opportunity to study the human movement from their socio-spatial behavior, in order to improve location-based applications like location recommendation. As users can check-in at new places, traditional work on location prediction that relies on mining a user’s historical moving trajectories fails as it is not designed for the cold-start problem of recommending new check-ins. While previous work on LBSNs attempting to utilize a user’s social connections for location recommendation observed limited help from social network information. In this work, we propose to address the cold-start location recommendation problem by capturing the correlations between social networks and geographical distance on LBSNs with a geo-social correlation model. The experimental results on a real-world LBSN dataset demonstrate that our approach properly models the geo-social correlations of a user’s cold-start check-ins and significantly improves the location recommendation performance.
6-DOF Multi-session Visual SLAM using Anchor Nodes

This paper describes a system for performing multisession visual mapping in large-scale environments. Multi-session mapping considers the problem of combining the results of multiple Simultaneous Localisation and Mapping (SLAM) missions performed repeatedly over time in the same environment. The goal is to robustly combine multiple maps in a common metrical coordinate system, with consistent estimates of uncertainty. Our work employs incremental Smoothing and Mapping (iSAM) as the underlying SLAM state estimator and uses an improved appearance-based method for detecting loop closures within single mapping sessions and across multiple sessions. To stitch together pose graph maps from multiple visual mapping sessions, we employ spatial separator variables, called anchor nodes, to link together multiple relative pose graphs. We provide experimental results for multi-session visual mapping in the MIT Stata Center, demonstrating key capabilities that will serve as a foundation for future work in large-scale persistent visual mapping.
Abstractive Multi-Document Summarization via Phrase Selection and Merging

ive Multi-Document Summarization via Phrase Selection and Merging∗ Lidong Bing§ Piji Li Yi Liao Wai Lam Weiwei Guo† Rebecca J. Passonneau‡ §Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA USA Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong †Yahoo Labs, Sunnyvale, CA, USA ‡Center for Computational Learning Systems, Columbia University, New York, NY, USA §lbing@cs.cmu.edu, {pjli, yliao, wlam}@se.cuhk.edu.hk †wguo@yahoo-inc.com, ‡becky@ccls.columbia.edu
Reasoning about Linguistic Regularities in Word Embeddings using Matrix Manifolds

Recent work has explored methods for learning continuous vector space word representations reflecting the underlying semantics of words. Simple vector space arithmetic using cosine distances has been shown to capture certain types of analogies, such as reasoning about plurals from singulars, past tense from present tense, etc. In this paper, we introduce a new approach to capture analogies in continuous word representations, based on modeling not just individual word vectors, but rather the subspaces spanned by groups of words. We exploit the property that the set of subspaces in n-dimensional Euclidean space form a curved manifold space called the Grassmannian, a quotient subgroup of the Lie group of rotations in ndimensions. Based on this mathematical model, we develop a modified cosine distance model based on geodesic kernels that captures relation-specific distances across word categories. Our experiments on analogy tasks show that our approach performs significantly better than the previous approaches for the given task.
The ImageCLEF 2013 Plant Identification Task

The ImageCLEF’s plant identification task provides a testbed for the system-oriented evaluation of plant identification, more precisely on the 126 tree species identification based on leaf images. Three types of image content are considered: Scan, Scan-like (leaf photographs with a white uniform background), and Photograph (unconstrained leaf with natural background). The main originality of this data is that it was specifically built through a citizen sciences initiative conducted by Tela Botanica, a French social network of amateur and expert botanists. This makes the task closer to the conditions of a real-world application. This overview presents more precisely the resources and assessments of task, summarizes the retrieval approaches employed by the participating groups, and provides an analysis of the main evaluation results. With a total of eleven groups from eight countries and with a total of 30 runs submitted, involving distinct and original methods, this second year pilot task confirms Image Retrieval community interest for biodiversity and botany, and highlights further challenging studies in plant identification.
Smoking prevalence among women in the European community 1950-1990.

The paper reviews trends in tobacco use among women in the European Community (EC) between 1950 and 1990. The data suggest that EC countries occupy different points on what appears to be a common prevalence curve. Southern EC countries are represented in the early phases of this curve, marked out by sharply rising prevalence. In northern EC countries, female smoking prevalence appears to have peaked. Across the EC, the commodification of tobacco use, and the production and promotion of manufactured cigarettes in particular, underlies this prevalence curve. Young women in higher socio-economic groups have led the way into cigarette smoking in both northern and southern Europe, with smoking prevalence declining first among women who are privileged in terms of their education, occupation and income. Because the decline in prevalence has yet to be repeated among women in more disadvantaged circumstances, cigarette smoking among women in the EC is likely to become a habit increasingly linked to low socio-economic status.
Investigating a Generic Paraphrase-Based Approach for Relation Extraction

Unsupervised paraphrase acquisition has been an active research field in recent years, but its effective coverage and performance have rarely been evaluated. We propose a generic paraphrase-based approach for Relation Extraction (RE), aiming at a dual goal: obtaining an applicative evaluation scheme for paraphrase acquisition and obtaining a generic and largely unsupervised configuration for RE. We analyze the potential of our approach and evaluate an implemented prototype of it using an RE dataset. Our findings reveal a high potential for unsupervised paraphrase acquisition. We also identify the need for novel robust models for matching paraphrases in texts, which should address syntactic complexity and variability.
Android : From Reversing to Decompilation

This talk deals with Android’s bytecode analysis. The Android system is now widespread, and lots of applications are developed each days. These applications are mostly written in Java, though it is possible to do calls to binaries or shared libraries. To be executed on the DVM the Java source code is translated into Java bytecode (.class files) and then a tool named ‘dx’ is used to convert it into the Dalvik format (.dex files). Such a conversion is needed as the DVM is a register-based machine whereas the JVM is a stack-based one, and as such they have different opcodes. Due to the nature of the bytecode, its reversing is somewhat easier than machine code. Indeed, unlike machine code, (Dalvik) bytecode contains semantic information that allows us to do a better analysis. We can get useful details on variables, fields, methods. . . We can create signatures for a method, or we can use the android permissions to see where a specific one is used in an application. The analysis part allows us to extract the control flow graph (which is composed of basic blocks, and which cannot be modified dynamically due to the virtual machine) which is used to represent the different possibles paths of an application. Furthermore, we have implemented new algorithms to calculate the similarity distance between two applications, a useful information to know if your application has been stolen from the android market. It’s also possible to use similarity to do ‘diffing’ of Android applications is useful to see patches of bugs or insertion of evil code, this is why we have developed a combination of techniques to quickly see the differences between two applications. Moreover it’s interesting to have the ability to manipulate in a simple way all these new formats (APK, DEX, Dalvik bytecode, Android’s binary xml) to automate testing directly in a program or in a specific interpreter. There are some ways to retrieve the Java source code of an application from the bytecode, for instance some people use a software which transforms Dex bytecode into Java bytecode and then combine it with a regular Java decompiler. But the resulting code often looks like an obfuscated version which does not compile than real source code. That’s why we developed a new decompiler which uses only Dalvik bytecode to create an original Java source code. We present a new open-source tool (Androguard) written in Python (and some parts of C language) which help the reversing of Android applications, as well as our decompiler.
Optical cloaking with metamaterials

Artificially structured metamaterials have enabled unprecedented flexibility in manipulating electromagnetic waves and producing new functionalities, including the cloak of invisibility based on coordinate transformation. Unlike other cloaking approaches4–6, which are typically limited to subwavelength objects, the transformation method allows the design of cloaking devices that render a macroscopic object invisible. In addition, the design is not sensitive to the object that is being cloaked. The first experimental demonstration of such a cloak at microwave frequencies was recently reported7. We note, however, that that design cannot be implemented for an optical cloak, which is certainly of particular interest because optical frequencies are where the word ‘invisibility’ is conventionally defined. Here we present the design of a non-magnetic cloak operating at optical frequencies. The principle and structure of the proposed cylindrical cloak are analysed, and the general recipe for the implementation of such a device is provided. The coordinate transformation used in the proposed nonmagnetic optical cloak of cylindrical geometry is similar to that in ref. 7, by which a cylindrical region r , b is compressed into a concentric cylindrical shell a , r , b as shown in Fig. 1a. This transformation results in the following requirements for anisotropic permittivity and permeability in the cloaking shell:
How to Login from an Internet Cafe Without Worrying about Keyloggers

Roaming users who use untrusted machines to access password protected accounts have few good options. An internet café machine can easily be running a keylogger. The roaming user has no reliable way of determining whether it is safe, and has no alternative to typing the password. We describe a simple trick the user can employ that is entirely effective in concealing the password. We verify its efficacy against the most popular keylogging programs.