nils-herrmann/clean_scirepeval huggingface dataset:
Dealing with the evaluation of supervised classification algorithms

Performance assessment of a learning method related to its prediction ability on independent data is extremely important in supervised classification. This process provides the information to evaluate the quality of a classification model and to choose the most appropriate technique to solve the specific supervised classification problem at hand. This paper aims to review the most important aspects of the evaluation process of supervised classification algorithms. Thus the overall evaluation process is put in perspective to lead the reader to a deep understanding of it. Additionally, different recommendations about their use and limitations as well as a critical view of the reviewed methods are presented according to the specific characteristics of the supervised classification problem scenario.
Unified temporal and spatial calibration for multi-sensor systems

In order to increase accuracy and robustness in state estimation for robotics, a growing number of applications rely on data from multiple complementary sensors. For the best performance in sensor fusion, these different sensors must be spatially and temporally registered with respect to each other. To this end, a number of approaches have been developed to estimate these system parameters in a two stage process, first estimating the time offset and subsequently solving for the spatial transformation between sensors. In this work, we present on a novel framework for jointly estimating the temporal offset between measurements of different sensors and their spatial displacements with respect to each other. The approach is enabled by continuous-time batch estimation and extends previous work by seamlessly incorporating time offsets within the rigorous theoretical framework of maximum likelihood estimation. Experimental results for a camera to inertial measurement unit (IMU) calibration prove the ability of this framework to accurately estimate time offsets up to a fraction of the smallest measurement period.
Self-compassion and adaptive psychological functioning

Two studies are presented to examine the relation of self-compassion to psychological health. Selfcompassion entails being kind and understanding toward oneself in instances of pain or failure rather than being harshly self-critical; perceiving one’s experiences as part of the larger human experience rather than seeing them as isolating; and holding painful thoughts and feelings in mindful awareness rather than over-identifying with them. Study 1 found that self-compassion (unlike self-esteem) helps buVer against anxiety when faced with an ego-threat in a laboratory setting. Self-compassion was also linked to connected versus separate language use when writing about weaknesses. Study 2 found that increases in self-compassion occurring over a one-month interval were associated with increased psychological well-being, and that therapist ratings of self-compassion were signiWcantly correlated with selfreports of self-compassion. Self-compassion is a potentially important, measurable quality that oVers a conceptual alternative to Western, more egocentric concepts of self-related processes and feelings.
Data-Warehousing 3.0 - Die Rolle von Data-Warehouse-Systemen auf Basis von In-Memory Technologie

In diesem Beitrag widmen wir uns der Frage, welche Rolle aktuelle Trends der Hardund Software für Datenbanksysteme spielen, um als Enabler für neuartige Konzepte im Umfeld des Data-Warehousing zu dienen. Als zentraler Schritt der Evolution im Kontext des Data-Warehousing wird dabei die enge Kopplung zu operativen Systemen gesehen, um eine direkte Rückkopplung bzw. Einbettung in operationale Geschäftsprozesse zu realisieren. In diesem Papier diskutieren wir die Fragen, wie In-Memory-Technologie das Konzept von Echtzeit-DWH-Systemen unterstützt bzw. ermöglicht. Dazu stellen wir zum einen eine Referenzarchitektur für DWH-Systeme vor, die insbesondere pushund pullbasierte Datenversorgung berücksichtigt. Zum anderen diskutieren wir die konkrete Rolle von In-Memory-Systemen mit Blick auf konkrete Aspekte wie der Frage optionaler Persistenzschichten, Reduktion der Batchgröße, Positionierung von In-Memory-Techniken für den Aufbau eines Corporate Memorys und die schnelle Bereitstellung externer Datenbestände zur Unterstützung situativer BISzenarien.
A Robust Mid-Level Representation for Harmonic Content in Music Signals

When considering the problem of audio-to-audio matching, determining musical similarity using low-level features such as Fourier transforms and MFCCs is an extremely difficult task, as there is little semantic information available. Full semantic transcription of audio is an unreliable and imperfect task in the best case, an unsolved problem in the worst. To this end we propose a robust mid-level representation that incorporates both harmonic and rhythmic information, without attempting full transcription. We describe a process for creating this representation automatically, directly from multi-timbral and polyphonic music signals, with an emphasis on popular music. We also offer various evaluations of our techniques. Moreso than most approaches working from raw audio, we incorporate musical knowledge into our assumptions, our models, and our processes. Our hope is that by utilizing this notion of a musically-motivated mid-level representation we may help bridge the gap between symbolic and audio research.
Pors: proofs of retrievability for large files

In this paper, we define and explore proofs of retrievability (PORs). A POR scheme enables an archive or back-up service (prover) to produce a concise proof that a user (verifier) can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.
 A POR may be viewed as a kind of cryptographic proof of knowledge (POK), but one specially designed to handle a large file (or bitstring) F. We explore POR protocols here in which the communication costs, number of memory accesses for the prover, and storage requirements of the user (verifier) are small parameters essentially independent of the length of F. In addition to proposing new, practical POR constructions, we explore implementation considerations and optimizations that bear on previously explored, related schemes.
 In a POR, unlike a POK, neither the prover nor the verifier need actually have knowledge of F. PORs give rise to a new and unusual security definition whose formulation is another contribution of our work.
 We view PORs as an important tool for semi-trusted online archives. Existing cryptographic techniques help users ensure the privacy and integrity of files they retrieve. It is also natural, however, for users to want to verify that archives do not delete or modify files prior to retrieval. The goal of a POR is to accomplish these checks without users having to download the files themselves. A POR can also provide quality-of-service guarantees, i.e., show that a file is retrievable within a certain time bound.
Data association for multi-object Tracking-by-Detection in multi-camera networks

Multi-object tracking is still a challenging task in computer vision. We propose a robust approach to realize multi-object tracking using multi-camera networks. Detection algorithms are utilized to detect object regions with confidence scores for initialization of individual particle filters. Since data association is the key issue in Tracking-by-Detection mechanism, we present an efficient greedy matching algorithm considering multiple judgments based on likelihood functions. Furthermore, tracking in single cameras is realized by a greedy matching method. Afterwards, 3D geometry positions are obtained from the triangulation relationship between cameras. Corresponding objects are tracked in multiple cameras to take the advantages of multi-camera based tracking. Our algorithm performs online and does not need any information about the scene, no restrictions of enter-and-exit zones, no assumption of areas where objects are moving on and can be extended to any class of object tracking. Experimental results show the benefits of using multiple cameras by the higher accuracy and precision rates.
Disney's Aladdin: First Steps toward Storytelling in Virtual Reality

Disney Imagineering has developed a high-fidelity virtual reality (VR) attraction where guests fly a magic carpet through a virtual world based on the animated film “Aladdin.” Unlike most existing work on VR, which has focused on hardware and systems software, we assumed high fidelity and focused on using VR as a new medium to tell stories. We fielded our system at EPCOT Center for a period of fourteen months and conducted controlled experiments, observing the reactions of over 45,000 guests. contact author: Randy Pausch, Computer Science Department, Thornton Hall, University of Virginia, Charlottesville, VA 22903.  804/982-2211 Permission to make digital or hard copies of part or all of this work or personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to st on servers, or to redistribute to lists, requires prior sion and/or a fee. -89791-746-4/96/008...$3.50 193 Riders filled out an exit survey after the experience, and with select groups we used a number of other data-gathering techniques, including interviews and mechanically logging where guests looked and flew. Our major finding is that in a high fidelity VR experience, men and women of all ages suspend disbelief and accept the illusion that they are in a different place. We have found that in VR, as in all media, content matters. Novices are unimpressed with the technology for its own sake; they care about what there is to do in the virtual world. We can improve the experience by telling a pre-immersion “background story” and by giving the guest a concrete goal to perform in the virtual environment. Our eventual goal is to develop the lexicon for this new storytelling medium: the set of communication techniques shared between directors and the audience. We conclude with a discussion of our second version of the Aladdin project, which contains a large number of synthetic characters and a narrative story line.  A Guest’s View of the Virtual Environment
Touching the void: direct-touch interaction for intangible displays

In this paper, we explore the challenges in applying and investigate methodologies to improve direct-touch interaction on intangible displays. Direct-touch interaction simplifies object manipulation, because it combines the input and display into a single integrated interface. While traditional tangible display-based direct-touch technology is commonplace, similar direct-touch interaction within an intangible display paradigm presents many challenges. Given the lack of tactile feedback, direct-touch interaction on an intangible display may show poor performance even on the simplest of target acquisition tasks. In order to study this problem, we have created a prototype of an intangible display. In the initial study, we collected user discrepancy data corresponding to the interpretation of 3D location of targets shown on our intangible display. The result showed that participants performed poorly in determining the z-coordinate of the targets and were imprecise in their execution of screen touches within the system. Thirty percent of positioning operations showed errors larger than 30mm from the actual surface. This finding triggered our interest to design a second study, in which we quantified task time in the presence of visual and audio feedback. The pseudo-shadow visual feedback was shown to be helpful both in improving user performance and satisfaction.
Evaluation of Multi-view 3D Reconstruction Software

A number of software solutions for reconstructing 3D models from multi-view image sets have been released in recent years. Based on an unordered collection of photographs, most of these solutions extract 3D models using structure-from-motion (SFM) algorithms. In this work, we compare the resulting 3D models qualitatively and quantitatively. To achieve these objectives, we have developed different methods of comparison for all software solutions. We discuss the perfomance and existing drawbacks. Particular attention is paid to the ability to create printable 3D models or 3D models usable for other applications.
Improving speech recognition by revising gated recurrent units

Speech recognition is largely taking advantage of deep learning, showing that substantial benefits can be obtained by modern Recurrent Neural Networks (RNNs). The most popular RNNs are Long Short-Term Memory (LSTMs), which typically reach state-of-the-art performance in many tasks thanks to their ability to learn long-term dependencies and robustness to vanishing gradients. Nevertheless, LSTMs have a rather complex design with three multiplicative gates, that might impair their efficient implementation. An attempt to simplify LSTMs has recently led to Gated Recurrent Units (GRUs), which are based on just two multiplicative gates. This paper builds on these efforts by further revising GRUs and proposing a simplified architecture potentially more suitable for speech recognition. The contribution of this work is two-fold. First, we suggest to remove the reset gate in the GRU design, resulting in a more efficient single-gate architecture. Second, we propose to replace tanh with ReLU activations in the state update equations. Results show that, in our implementation, the revised architecture reduces the per-epoch training time with more than 30% and consistently improves recognition performance across different tasks, input features, and noisy conditions when compared to a standard GRU.
Global contrast based salient region detection

Reliable estimation of visual saliency allows appropriate processing of images without prior knowledge of their contents, and thus remains an important step in many computer vision tasks including image segmentation, object recognition, and adaptive compression. We propose a regional contrast based saliency extraction algorithm, which simultaneously evaluates global contrast differences and spatial coherence. The proposed algorithm is simple, efficient, and yields full resolution saliency maps. Our algorithm consistently outperformed existing saliency detection methods, yielding higher precision and better recall rates, when evaluated using one of the largest publicly available data sets. We also demonstrate how the extracted saliency map can be used to create high quality segmentation masks for subsequent image processing.
A neural theory of visual attention: bridging cognition and neurophysiology.

A neural theory of visual attention (NTVA) is presented. NTVA is a neural interpretation of C. Bundesen's (1990) theory of visual attention (TVA). In NTVA, visual processing capacity is distributed across stimuli by dynamic remapping of receptive fields of cortical cells such that more processing resources (cells) are devoted to behaviorally important objects than to less important ones. By use of the same basic equations used in TVA, NTVA accounts for a wide range of known attentional effects in human performance (reaction times and error rates) and a wide range of effects observed in firing rates of single cells in the primate visual system. NTVA provides a mathematical framework to unify the 2 fields of research--formulas bridging cognition and neurophysiology.
Correction of intensity flicker in old film sequences

Temporal intensity flicker is a common artifact in old film sequences. Removing disturbing temporal fluctuations in image intensities is desirable because it increases both the subjective quality and, where image sequences are stored in a compressed format, the coding efficiency. We describe a robust technique that corrects intensity flicker automatically by equalizing local frame means and variances in the temporal sense. The low complexity of our method makes it suitable for hardware implementation. We tested the proposed method on sequences with artificially added intensity flicker and on original film material. The results show a great improvement .
Design Considerations for Battery-Powered Electronics

 In this paper, we consider the problem of maximizing the battery life (or duration of service) in battery-powered CMOS circuits. We first show that the battery efficiency (or utilization factor) decreases as the average discharge current from the battery increases. The implication is that the battery life is a super-linear function of the average discharge current. Next we show that even when the average discharge current remains the same, different discharge current profiles (distributions) may result in very different battery lifetimes. In particular, the maximum battery life is achieved when the variance of the discharge current distribution is minimized. Analytical derivations and experimental results underline importance of the correct modeling of the battery-hardware system as a whole and provide a more accurate basis (i.e., the battery discharge times delay product) for comparing various low power optimization methodologies and techniques targeted toward battery-powered electronics. Finally, we calculate the optimal value of V dd for a battery-powered VLSI circuit so as to minimize the product of the battery discharge times the circuit delay.
Rule based Autonomous Citation Mining with TIERL

Citations management is an important task in managing digital libraries. Citations provide valuable information e.g., used in evaluating an author's influences or scholarly quality (the impact factor of research journals). But although a reliable and effective autonomous citation management is essential, manual citation management can be extremely costly. Automatic citation mining on the other hand is a non-trivial task mainly due to non-conforming citation styles, spelling errors and the difficulty of reliably extracting text from PDF documents. In this paper we propose a novel rule-based autonomous citation mining technique, to address this important task. We define a set of common heuristics that together allow to improve the state of the art in automatic citation mining. Moreover, by first disambiguating citations based on venues, our technique significantly enhances the correct discovery of citations. Our experiments show that the proposed approach is indeed able to overcome limitations of current leading citation indexes such as ISI Web of Knowledge , Citeseer and Google Scholar.
Fast Pattern Matching in Strings

テキストの中から与えられたパターンを見つけ出すと いう,いわゆる文字列探索のアルゴリズムを調べようと アルゴリズムの教科書をひもとくと,必ずといってよい ほど,力まかせの方法,Knuth,Morris,Prattによる 方法,BoyerとMooreによる方法 の 3つが紹介され ている.本論文は 2番目の方法-著者の頭文字をとっ て KMPアルゴリズムと省略される について述べて いる. 文字列探索が必要とされる代表的な例に,テキストエ ディタの探索コマンドがある.実際のテキストエディタ の探索コマンドでは,探索する文字列がきわめて短い場 合には力まかせの方法が用いられることがある以外は, 第 3の方法これも著者の頭文字から BMアルゴリズ ムと省略されるが利用される場合が多いようではあ るが,KMPアルゴリズムは BMアルゴリズムと並び,ア イディア 1つで計算量が改善されるというアルゴリズム の面白さを,我々に十分教えてくれる. 本論文は,KMPアルゴリズムの動作を例を用いて解 説することから始まり,具体的なアルゴリズムの提示, アルゴリズムの改良と拡張,計算量に関する理論的な考 察と続く.アルゴリズムを提案する論文としてはここま でで十分なのだが,本論文はさらに,長さが偶数の回文 文字列の話,KMPアルゴリズム発明の歴史,ついには 後書きと称して BMアルゴリズムに関する考察にまで話 が及ぶという,特異とも思える構成となっている. ここで述べられている歴史によると,KMPアルゴリズ ムは,元々はMorris,および,Knuth,Prattチームによ り独立に発明された.Morrisは,1969年に CDC 6400と いう計算機上のテキストエディタを作成していた際,有 限オートマトン理論を利用して,このアルゴリズムの原 形を考えた.またこれとは別に,Knuthは 1970年に, 長さが偶数の回文文字列の 2方向プッシュダウンオート マトンによる認識の理論の調査をしているうちに,その 背後の文字列探索アルゴリズムの存在に気づき,本アル ゴリズムの発明に至ったという.これは,Knuthにとっ て,オートマトン理論が現実のプログラミングの問題の 解決に役に立った初めての経験であったらしい.Robert Sedgewickは,その有名なアルゴリズムの教科書 の文 字列探索の章の中で,このことを「理論的な結果が思い がけず直接実用と結びついた稀な実例である」と指摘し ているが,実際この経験は,Knuthにとってきわめて印 象深いものであったに違いない.そう考えると,上で述 べたような本論文の特異とも思える構成も,著者による 思いの発露と思えて興味深い.ちなみに,本論文が掲載 されている SIAM Journal on Computingの同じ号には, Sedgewickの論文も掲載されている. Morrisがこのアルゴリズムを思いついた背景には, CDC 6400でのバッファリング処理が複雑であるため, テキストの「後戻り」を必要としない方法が求められて いたことがあった.最近のように主記憶をふんだんに使 うことができなかったという不自由さが,新しいアルゴ リズムの発明に結びついたといえよう. 本論文の KMPアルゴリズムの改良の章には,番兵を 用いた高速化の話も述べられている.力ずく的に記述さ れたプログラムが多い現在では,番兵は以前ほどは使わ れなくなってしまったが,本論文が発表された 1970年代 後半では,番兵は美しく高速なプログラムを記述するた めの重宝な技術であった.このようなところにも,時代 の流れを感じさせるものがある. KMPアルゴリズムは,素朴なアルゴリズムから賢いア ルゴリズムをプログラム変換によって導出する例題とし てもよく用いられる.このような題材としても KMPア ルゴリズムが役に立つことになろうとは,著者たちは想 定していなかったであろう.
Wideband Millimeter-Wave Substrate Integrated Waveguide Cavity-Backed Rectangular Patch Antenna

In this letter, a new type of wideband substrate integrated waveguide (SIW) cavity-backed patch antenna and array for millimeter wave (mmW) are investigated and implemented. The proposed antenna is composed of a rectangular patch with a backed SIW cavity. In order to enhance the bandwidth and radiation efficiency, the cavity is designed to resonate at its TE210 mode. Based on the proposed antenna, a 4 × 4 array is also designed. Both the proposed antenna and array are fabricated with standard printed circuit board (PCB) process, which possess the advantage of easy integration with planar circuits. The measured bandwidth (|S11| ≤ -10 dB) of the antenna element is larger than 15%, and that of the antenna array is about 8.7%. The measured peak gains are 6.5 dBi for the element and 17.8 dBi for the array, and the corresponding simulated radiation efficiencies are 83.9% and 74.9%, respectively. The proposed antenna and array are promising for millimeter-wave applications due to its merits of wide band, high efficiency, low cost, low profile, etc.
Standing Out from the Crowd: Emotional Labor, Body Labor, and Temporal Labor in Ridesharing

CSCW researchers have become interested in crowd work as a new form of collaborative engagement, that is, as a new way in which peopleâs actions are coordinated in order to achieve collective effects. We address this area but from a different perspective â that of the labor practices involved in taking crowd work as a form of work. Using empirical materials from a study of ride-sharing, we draw inspiration from studies of the immaterial forms of labor and alternate analyses of political economy that can cast a new light on the context of crowd labor that might matter for CSCW researchers.
A General Theory of Equivariant CNNs on Homogeneous Spaces

Group equivariant convolutional neural networks (G-CNNs) have recently emerged as a very effective model class for learning from signals in the context of known symmetries. A wide variety of equivariant layers has been proposed for signals on 2D and 3D Euclidean space, graphs, and the sphere, and it has become difficult to see how all of these methods are related, and how they may be generalized. In this paper, we present a fairly general theory of equivariant convolutional networks. Convolutional feature spaces are described as fields over a homogeneous base space, such as the plane R, sphere S or a graph G. The theory enables a systematic classification of all existing G-CNNs in terms of their group of symmetry, base space, and field type (e.g. scalar, vector, or tensor field, etc.). In addition to this classification, we use Mackey theory to show that convolutions with equivariant kernels are the most general class of equivariant maps between such fields, thus establishing G-CNNs as a universal class of equivariant networks. The theory also explains how the space of equivariant kernels can be parameterized for learning, thereby simplifying the development of G-CNNs for new spaces and symmetries. Finally, the theory introduces a rich geometric semantics to learned feature spaces, thus improving interpretability of deep networks, and establishing a connection to central ideas in mathematics and physics.