nils-herrmann/clean_scirepeval huggingface dataset:
Grasp Pose Detection in Point Clouds

Recently, a number of grasp detection methods have been proposed that can be used to localize robotic grasp configurations directly from sensor data without estimating object pose. The underlying idea is to treat grasp perception analogously to object detection in computer vision. These methods take as input a noisy and partially occluded RGBD image or point cloud and produce as output pose estimates of viable grasps, without assuming a known CAD model of the object. Although these methods generalize grasp knowledge to new objects well, they have not yet been demonstrated to be reliable enough for wide use. Many grasp detection methods achieve grasp success rates (grasp successes as a fraction of the total number of grasp attempts) between 75% and 95% for novel objects presented in isolation or in light clutter. Not only are these success rates too low for practical grasping applications, but the light clutter scenarios that are evaluated often do not reflect the realities of real world grasping. This paper proposes a number of innovations that together result in a significant improvement in grasp detection performance. The specific improvement in performance due to each of our contributions is quantitatively measured either in simulation or on robotic hardware. Ultimately, we report a series of robotic experiments that average a 93% end-to-end grasp success rate for novel objects presented in dense clutter.
Hardware Enforcement of Application Security Policies Using Tagged Memory

Computers are notoriously insecure, in part because application security policies do not map well onto traditional protection mechanisms such as Unix user accounts or hardware page tables. Recent work has shown that application policies can be expressed in terms of information flow restrictions and enforced in an OS kernel, providing a strong assurance of security. This paper shows that enforcement of these policies can be pushed largely into the processor itself, by using tagged memory support, which can provide stronger security guarantees by enforcing application security even if the OS kernel is compromised. We present the Loki tagged memory architecture, along with a novel operating system structure that takes advantage of tagged memory to enforce application security policies in hardware. We built a full-system prototype of Loki by modifying a synthesizable SPARC core, mapping it to an FPGA board, and porting HiStar, a Unix-like operating system, to run on it. One result is that Loki allows HiStar, an OS already designed to have a small trusted kernel, to further reduce the amount of trusted code by a factor of two, and to enforce security despite kernel compromises. Using various workloads, we also demonstrate that HiStar running on Loki incurs a low performance overhead.
Factored Neural Machine Translation

We present a new approach for neural machine translation (NMT) using the morphological and grammatical decomposition of the words (factors) in the output side of the neural network. This architecture addresses two main problems occurring in MT, namely dealing with a large target language vocabulary and the out of vocabulary (OOV) words. By the means of factors, we are able to handle larger vocabulary and reduce the training time (for systems with equivalent target language vocabulary size). In addition, we can produce new words that are not in the vocabulary. We use a morphological analyser to get a factored representation of each word (lemmas, Part of Speech tag, tense, person, gender and number). We have extended the NMT approach with attention mechanism (Bahdanau et al., 2014) in order to have two different outputs , one for the lemmas and the other for the rest of the factors. The final translation is built using some a priori linguistic information. We compare our extension with a word-based NMT system. The experiments, performed on the IWSLT’15 dataset translating from English to French, show that while the performance do not always increase, the system can manage a much larger vocabulary and consistently reduce the OOV rate. We observe up to 2% BLEU point improvement in a simulated out of domain translation setup.
Error management theory: a new perspective on biases in cross-sex mind reading.

A new theory of cognitive biases, called error management theory (EMT), proposes that psychological mechanisms are designed to be predictably biased when the costs of false-positive and false-negative errors were asymmetrical over evolutionary history. This theory explains known phenomena such as men's overperception of women's sexual intent, and it predicts new biases in social inference such as women's underestimation of men's commitment. In Study 1 (N = 217), the authors documented the commitment underperception effect predicted by EMT. In Study 2 (N = 289), the authors replicated the commitment bias and documented a condition in which men's sexual overperception bias is corrected.  EMT with the heuristics and biases approach and suggests additional testable hypotheses based on EMT.
Automatic Translation between English and Persian Texts

PEnTrans is an automatic bidirectional English/ Persian text translator. It contains two main modules, PEnT1,2. PEnT1 translates English sentences into Persian and PEnT2 performs translation from Persian to English. WSD which is an important part in translation is done in both systems by employing a combination of extended dictionary and corpus based approaches in PEnT1 and employing a combination of rule based, knowledge based and corpus based approaches in PEnT2. In this paper, introducing PEnTrans and its components, we propose a new WSD method by presenting a hybrid measure to score different senses of a word according to its condition in a sentence and other words in the sentence.
Flash Cookies and Privacy

This is a pilot study of the use of “Flash cookies” by popular websites. We find that more than 50% of the sites in our sample are using Flash cookies to store information about the user. Some are using it to “respawn” or re-instantiate HTTP cookies deleted by the user. Flash cookies often share the same values as HTTP cookies, and are even used on government websites to assign unique values to users. Privacy policies rarely disclose the presence of Flash cookies, and user controls for effectuating privacy preferences are
Open R & D and open innovation : exploring the phenomenon

Dr. Manfred Bischoff Institute of Innovation Management of EADS, Zeppelin University, Am Seemoser Horn 20, D-88045 Friedrichshafen, Germany. ellen.enkel@zeppelin-university.de Institute of Technology Management, University of St. Gallen, Dufourstrasse 40a, CH-9000 St. Gallen, Switzerland. oliver.gassmann@unisg.ch Center for Open Innovation, Haas School of Business, Faculty Wing, F402, University of California, Berkeley, Berkeley, CA 94720-1930, USA.
A deep language model for software code

Existing language models such as n-grams for software code often fail to capture a long context where dependent code elements scatter far apart. In this paper, we propose a novel approach to build a language model for software code to address this particular issue. Our language model, partly inspired by human memory, is built upon the powerful deep learning-based Long Short Term Memory architecture that is capable of learning long-term dependencies which occur frequently in software code. Results from our intrinsic evaluation on a corpus of Java projects have demonstrated the effectiveness of our language model. This work contributes to realizing our vision for DeepSoft, an end-to-end, generic deep learning-based framework for modeling software and its development process.
NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation.
Efficient Big Data Processing in Hadoop MapReduce

This tutorial is motivated by the clear need of many organizations, companies, and researchers to deal with big data volumes efficiently. Examples include web analytics applications, scientific applications, and social networks. A popular data processing engine for big data is Hadoop MapReduce. Early versions of Hadoop MapReduce suffered from severe performance problems. Today, this is becoming history. There are many techniques that can be used with Hadoop MapReduce jobs to boost performance by orders of magnitude. In this tutorial we teach such techniques. First, we will briefly familiarize the audience with Hadoop MapReduce and motivate its use for big data processing. Then, we will focus on different data management techniques, going from job optimization to physical data organization like data layouts and indexes. Throughout this tutorial, we will highlight the similarities and differences between Hadoop MapReduce and Parallel DBMS. Furthermore, we will point out unresolved research problems and open issues.
Inferring Taxi Status Using GPS Trajectories

In this paper, we infer the statuses of a taxi, consisting of occupied, non-occupied and parked, in terms of its GPS trajectory. The status information can enable urban computing for improving a city’s transportation systems and land use planning. In our solution, we first identify and extract a set of effective features incorporating the knowledge of a single trajectory, historical trajectories and geographic data like road network. Second, a parking status detection algorithm is devised to find parking places (from a given trajectory), dividing a trajectory into segments (i.e., sub-trajectories). Third, we propose a two-phase inference model to learn the status (occupied or non-occupied) of each point from a taxi segment. This model first uses the identified features to train a local probabilistic classifier and then carries out a Hidden SemiMarkov Model (HSMM) for globally considering long term travel patterns. We evaluated our method with a large-scale real-world trajectory dataset generated by 600 taxis, showing the advantages of our method over baselines.
Intelligent Fashion Recommender System: Fuzzy Logic in Personalized Garment Design

This paper proposes a new intelligent fashion recommender system to select the most relevant garment design scheme for a specific consumer in order to deliver new personalized garment products. This system integrates emotional fashion themes and human perception on personalized body shapes and professional designers' knowledge. The corresponding perceptual data are systematically collected from professional using sensory evaluation techniques. The perceptual data of consumers and designers are formalized mathematically using fuzzy sets and fuzzy relations. The complex relation between human body measurements and basic sensory descriptors, provided by designers, is modeled using fuzzy decision trees. The fuzzy decision trees constitute an empirical model based on learning data measured and evaluated on a set of representative samples. The complex relation between basic sensory descriptors and fashion themes, given by consumers, is modeled using fuzzy cognitive maps. The combination of the two models can provide more complete information to the fashion recommender system, making it possible to evaluate if a specific body shape is relevant to a desired emotional fashion theme and which garment design scheme can improve the image of the body shape. The proposed system has been validated in a customized design and mass market selection through the evaluations of target consumers and fashion experts using a method frequently used in marketing study.
What Makes the Difference ? A Practical Analysis of Research on the Effectiveness of Distance Education

This article reports findings of a meta-analytical study of research on distance education. The purpose of this study was to identify factors that affect the effectiveness of distance education. The results show that although the aggregated data of available studies show no significant difference in outcomes between distance education and face-to-face education as previous research reviews suggest, there is remarkable difference across the studies. Further examination of the difference reveals that distance education programs, just like traditional education programs, vary a great deal in their outcomes, and the outcome of distance education is associated with a number of pedagogical and technological factors. This study led to some important data-driven suggestions for and about distance education.
Automatic online news topic ranking using media focus and user attention based on aging theory

News topics, which are constructed from news stories using the techniques of Topic Detection and Tracking (TDT), bring convenience to users who intend to see what is going on through the Internet. However, it is almost impossible to view all the generated topics, because of the large amount. So it will be helpful if all topics are ranked and the top ones, which are both timely and important, can be viewed with high priority. Generally, topic ranking is determined by two primary factors. One is how frequently and recently a topic is reported by the media; the other is how much attention users pay to it. Both media focus and user attention varies as time goes on, so the effect of time on topic ranking has already been included. However, inconsistency exists between both factors. In this paper, an automatic online news topic ranking algorithm is proposed based on inconsistency analysis between media focus and user attention. News stories are organized into topics, which are ranked in terms of both media focus and user attention. Experiments performed on practical Web datasets show that the topic ranking result reflects the influence of time, the media and users. The main contributions of this paper are as follows. First, we present the quantitative measure of the inconsistency between media focus and user attention, which provides a basis for topic ranking and an experimental evidence to show that there is a gap between what the media provide and what users view. Second, to the best of our knowledge, it is the first attempt to synthesize the two factors into one algorithm for automatic online topic ranking.
Unsupervised segmentation and classification of cervical cell images

The Pap smear test is a manual screening procedure that is used to detect precancerous changes in cervical cells based on color and shape properties of their nuclei and cytoplasms. Automating this procedure is still an open problem due to the complexities of cell structures. In this paper, we propose an unsupervised approach for the segmentation and classification of cervical cells. The segmentation process involves automatic thresholding to separate the cell regions from the background, a multi-scale hierarchical segmentation algorithm to partition these regions based on homogeneity and circularity, and a binary classifier to finalize the separation of nuclei from cytoplasm within the cell regions. Classification is posed as a grouping problem by ranking the cells based on their feature characteristics modeling abnormality degrees. The proposed procedure constructs a tree using hierarchical clustering, and then arranges the cells in a linear order by using an optimal leaf ordering algorithm that maximizes the similarity of adjacent leaves without any requirement for training examples or parameter adjustment. Performance evaluation using two data sets show the effectiveness of the proposed approach in images having inconsistent staining, poor contrast, and overlapping cells.
Theory and Application of Digital Signal Processing

sprightly style and is interesting from cover to cover. The comments, critiques, and summaries that accompany the chapters are very helpful in crystalizing the ideas and answering questions that may arise, particularly to the self-learner. The transparency in the presentation of the material in the book equips the reader to proceed quickly to a wealth of problems included at the end of each chapter. These problems ranging from elementary to research-level are very valuable in that a solid working knowledge of the invariant imbedding techniques is acquired as well as good insight in attacking problems in various applied areas. Furthermore, a useful selection of references is given at the end of each chapter. This book may not appeal to those mathematicians who are interested primarily in the sophistication of mathematical theory, because the authors have deliberately avoided all pseudo-sophistication in attaining transparency of exposition. Precisely for the same reason the majority of the intended readers who are applications-oriented and are eager to use the techniques quickly in their own fields will welcome and appreciate the efforts put into writing this book. From a purely mathematical point of view, some of the invariant imbedding results may be considered to be generalizations of the classical theory of first-order partial differential equations, and a part of the analysis of invariant imbedding is still at a somewhat heuristic stage despite successes in many computational applications. However, those who are concerned with mathematical rigor will find opportunities to explore the foundations of the invariant imbedding method. In conclusion, let me quote the following: "What is the best method to obtain the solution to a problem'? The answer is, any way that works." (Richard P. Feyman, Engineering and Science, March 1965,  In this well-written book, Bellman and Wing have indeed accomplished the task of introducing the simplicity of the invariant imbedding method to tackle various problems of interest to engineers, physicists, applied mathematicians, and numerical analysts.
3D eWLB (embedded wafer level BGA) technology for 3D-packaging/3D-SiP (Systems-in-Package) applications

Demand for wafer level packaging (WLP) is being driven by the need to shrink package size and height, simplify the supply chain and provide a lower overall cost by using the infrastructure of a batch process. There are some restrictions in possible applications for Fan-In WLPs since global chip trends tend toward smaller chip areas with an increasing number of interconnects. The shrinkage of the pitches and pads at the chip to package interface is happening much faster than the shrinkage at the package to board interface. This interconnection gap requires fan-out packaging, where the package size is larger than the chip size in order to provide a sufficient area to accommodate the 2nd level interconnects. eWLB (embedded Wafer Level BGA) is a type of fan-out WLP that has the potential to realize any number of interconnects with standard pitches at any shrink stage of the wafer node technology. Furthermore, 3D eWLB technology enables 3D IC and 3D SiP packaging with vertical interconnection. 3D eWLB can be implemented with through silicon via (TSV) applications as well as discrete component embedding. In this paper, there will be discussion of the recent advancements in 3D eWLB packaging and integration as well as what is being envisioned and developed to address future technology requirements in 3D packaging and 3D SIP. The advantage of 3D eWLB technology and applications of 3D packaging will be presented with several examples. The process flow of 3D eWLB fabrication, assembly and packaging challenges, and performance characteristics will be also discussed.
An Audio-based Real-time Beat Tracking System for Music With or Without Drum-sounds

This paper describes a real-time beat tracking system that recognizes a hierarchical beat structure comprising the quarter-note, half-note, and measure levels in real-world audio signals sampled from popular-music compact discs. Most previous beat-tracking systems dealt with MIDI signals and had difficulty in processing, in real time, audio signals containing sounds of various instruments and in tracking beats above the quarter-note level. The system described here can process music with drums and music without drums and can recognize the hierarchical beat structure by using three kinds of musical knowledge: of onset times, of chord changes, and of drum patterns. This paper also describes several applications of beat tracking, such as beat-driven real-time computer graphics and lighting control.
Physical Unclonable Functions and Applications: A Tutorial

This paper describes the use of physical unclonable functions (PUFs) in low-cost authentication and key generation applications. First, it motivates the use of PUFs versus conventional secure nonvolatile memories and defines the two primary PUF types: “strong PUFs” and “weak PUFs.” It describes strong PUF implementations and their use for low-cost authentication. After this description, the paper covers both attacks and protocols to address errors. Next, the paper covers weak PUF implementations and their use in key generation applications. It covers error-correction schemes such as pattern matching and index-based coding. Finally, this paper reviews several emerging concepts in PUF technologies such as public model PUFs and new PUF implementation technologies.
Knowledge of the Firm , Combinative Capabilities , and the Replication of Technology

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