nils-herrmann/clean_scirepeval huggingface dataset:
Ground-Truth Adversarial Examples

The ability to deploy neural networks in real-world, safety-critical systems is severely limited by the presence of adversarial examples: slightly perturbed inputs that are misclassified by the network. In recent years, several techniques have been proposed for training networks that are robust to such examples; and each time stronger attacks have been devised, demonstrating the shortcomings of existing defenses. This highlights a key difficulty in designing an effective defense: the inability to assess a network’s robustness against future attacks. We propose to address this difficulty through formal verification techniques. We construct ground truths: adversarial examples with provably minimal perturbation. We demonstrate how ground truths can serve to assess the effectiveness of attack techniques, by comparing the adversarial examples produced to the ground truths; and also of defense techniques, by measuring the increase in distortion to ground truths in the hardened network versus the original. We use this technique to assess recently suggested attack and defense techniques.
Sensorized soft robotic glove for continuous passive motion therapy

This paper presents the design and development of a sensorized soft robotic glove based on pneumatic soft-and-rigid hybrid actuators for providing continuous passive motion (CPM) in hand rehabilitation. This hybrid actuator is comprised of bellow-type soft actuator sections connected through block-shaped semi-rigid sections to form robotic digits. The actuators were designed to satisfy the anatomical range of motion for each joint. Each digit was sensorized at the tip with an inertial measurement unit sensor in order to track the rotation of the distal end. A pneumatic feedback control system was developed to control the motion of the soft robotic digit in following desired trajectories. The performance of the soft robotic glove and the associated control system were examined on an able-bodied subject during flexion and extension to show the glove's applicability to CPM applications.
Code Randomization: Haven’t We Solved This Problem Yet?

Two decades since the idea of using software diversity for security was put forward, ASLR is the only technique to see widespread deployment. This is puzzling since academic security researchers have published scores of papers claiming to advance the state of the art in the area of code randomization. Unfortunately, these improved diversity techniques are generally less deployable than integrity-based techniques, such as control-flow integrity, due to their limited compatibility with existing optimization, development, and distribution practices. This paper contributes yet another diversity technique called pagerando. Rather than trading off practicality for security, we first and foremost aim for deployability and interoperability. Most code randomization techniques interfere with memory sharing and deduplication optimization across processes and virtual machines, ours does not. We randomize at the granularity of individual code pages but never rewrite page contents. This also avoids incompatibilities with code integrity mechanisms that only allow signed code to be mapped into memory and prevent any subsequent changes. On Android, pagerando fully adheres to the default SELinux policies. All practical mitigations must interoperate with unprotected legacy code, our implementation transparently interoperates with unmodified applications and libraries. To support our claims of practicality, we demonstrate that our technique can be integrated into and protect all shared libraries shipped with stock Android 6.0. We also consider hardening of non-shared libraries and executables and other concerns that must be addressed to put software diversity defenses on par with integrity-based mitigations such as CFI.
Pigmentation of the Fungiform Papillae of the Tongue: A Report of 2 Cases

8. Koizumi H, Kumakiri M, Ishizuka M, Ohkawara A, Okabe S. Leukaemia cutis in acute myelomonocytic leukaemia: infiltration of minor traumas and scars.  Kristensen IB, Moller H, Kjaershov MW, Yderstraede K, Moller MB, Bergmann OJ. Myeloid sarcoma developing in pre-existing pyoderma gangrenoso.  Carrascosa JM, Ferrándiz C. Leucemia cutis desarrollada en la zona de inoculación de una dosis de recuerdo de la vacuna del tétanos. Actas Dermosifiliogr. 2010;101:727--9. 1. Youssef AH, Zanetto U, Kaur MR, Chan SY. Granulocytic sarcoma (leukaemia cutis) in association with basal cell carcinoma. Br J Dermatol. 2005;154:201--2.
Cloud User-Centric Enhancements of the Simulator CloudSim to Improve Cloud Deployment Option Analysis

Cloud environments can be simulated using the toolkit CloudSim. By employing concepts such as physical servers in datacenters, virtual machine allocation policies, or coarse-grained models of deployed software, it focuses on a cloud provider perspective. In contrast, a cloud user who wants to migrate complex systems to the cloud typically strives to find a cloud deployment option that is best suited for its sophisticated system architecture, is interested in determining the best trade-off between costs and performance, or wants to compare runtime reconfiguration plans, for instance. We present significant enhancements of CloudSim that allow to follow this cloud user perspective and enable the frictionless integration of fine-grained application models that, to a great extent, can be derived automatically from software systems. Our quantitative evaluation demonstrates the applicability and accuracy of our approach by comparing its simulation results with actual deployments that utilize the cloud environment Amazon EC2.
Meta-analytic evidence for effects of mindfulness training on dimensions of self-reported dispositional mindfulness.

Improvements in stable, or dispositional, mindfulness are often assumed to accrue from mindfulness training and to account for many of its beneficial effects. However, research examining these assumptions has produced mixed findings, and the relation between dispositional mindfulness and mindfulness training is actively debated. A comprehensive meta-analysis was conducted on randomized controlled trials (RCTs) of mindfulness training published from 2003-2014 to investigate whether (a) different self-reported mindfulness scale dimensions change as a result of mindfulness training, (b) key aspects of study design (e.g., control condition type, population type, and intervention type) moderate training-related changes in dispositional mindfulness scale dimensions, and (c) changes in mindfulness scale dimensions are associated with beneficial changes in mental health outcomes. Scales from widely used dispositional mindfulness measures were combined into 5 categories for analysis: Attention, Description, Nonjudgment, Nonreactivity, and Observation. A total of 88 studies (n = 5,787) were included. Changes in scale dimensions of mindfulness from pre to post mindfulness training produced mean difference effect sizes ranging from small to moderate (g = 0.28-0.49). Consistent with the theorized role of improvements in mindfulness in training outcomes, changes in dispositional mindfulness scale dimensions were moderately correlated with beneficial intervention outcomes (r = .27-0.30), except for the Observation dimension (r = .16). Overall, moderation analyses revealed inconsistent results, and limitations of moderator analyses suggest important directions for future research. We discuss how the findings can inform the next generation of mindfulness assessment.
EVA: Visual Analytics to Identify Fraudulent Events

Financial institutions are interested in ensuring security and quality for their customers. Banks, for instance, need to identify and stop harmful transactions in a timely manner. In order to detect fraudulent operations, data mining techniques and customer profile analysis are commonly used. However, these approaches are not supported by Visual Analytics techniques yet. Visual Analytics techniques have potential to considerably enhance the knowledge discovery process and increase the detection and prediction accuracy of financial fraud detection systems. Thus, we propose EVA, a Visual Analytics approach for supporting fraud investigation, fine-tuning fraud detection algorithms, and thus, reducing false positive alarms.
Evaluation of dysuria in adults.

Dysuria, defined as pain, burning, or discomfort on urination, is more common in women than in men. Although urinary tract infection is the most frequent cause of dysuria, empiric treatment with antibiotics is not always appropriate. Dysuria occurs more often in younger women, probably because of their greater frequency of sexual activity. Older men are more likely to have dysuria because of an increased incidence of prostatic hyperplasia with accompanying inflammation and infection. A comprehensive history and physical examination can often reveal the cause of dysuria. Urinalysis may not be needed in healthier patients who have uncomplicated medical histories and symptoms. In most patients, however, urinalysis can help to determine the presence of infection and confirm a suspected diagnosis. Urine cultures and both urethral and vaginal smears and cultures can help to identify sites of infection and causative agents. Coliform organisms, notably Escherichia coli, are the most common pathogens in urinary tract infection. Dysuria can also be caused by noninfectious inflammation or trauma, neoplasm, calculi, hypoestrogenism, interstitial cystitis, or psychogenic disorders. Although radiography and other forms of imaging are rarely needed, these studies may identify abnormalities in the upper urinary tract when symptoms are more complex.
Transient Cognitive Dynamics, Metastability, and Decision Making

The idea that cognitive activity can be understood using nonlinear dynamics has been intensively discussed at length for the last 15 years. One of the popular points of view is that metastable states play a key role in the execution of cognitive functions. Experimental and modeling studies suggest that most of these functions are the result of transient activity of large-scale brain networks in the presence of noise. Such transients may consist of a sequential switching between different metastable cognitive states. The main problem faced when using dynamical theory to describe transient cognitive processes is the fundamental contradiction between reproducibility and flexibility of transient behavior. In this paper, we propose a theoretical description of transient cognitive dynamics based on the interaction of functionally dependent metastable cognitive states. The mathematical image of such transient activity is a stable heteroclinic channel, i.e., a set of trajectories in the vicinity of a heteroclinic skeleton that consists of saddles and unstable separatrices that connect their surroundings. We suggest a basic mathematical model, a strongly dissipative dynamical system, and formulate the conditions for the robustness and reproducibility of cognitive transients that satisfy the competing requirements for stability and flexibility. Based on this approach, we describe here an effective solution for the problem of sequential decision making, represented as a fixed time game: a player takes sequential actions in a changing noisy environment so as to maximize a cumulative reward. As we predict and verify in computer simulations, noise plays an important role in optimizing the gain.
Low-voltage DC input, high-voltage pulse generator using nano-crystalline transformer and sequentially charged MMC sub-modules, for water treatment applications

This paper proposes a new high-voltage Pulse Generator (PG), fed from low voltage dc supply Vs. This input supply voltage is utilized to charge two arms of N series-connected modular multilevel converter sub-module capacitors sequentially through a resistive-inductive branch, such that each arm is charged to NVS. With a step-up nano-crystalline transformer of n turns ratio, the proposed PG is able to generate bipolar rectangular pulses of peak ±nNVs, at high repetition rates. However, equal voltage-second area of consecutive pulse pair polarities should be assured to avoid transformer saturation. Not only symmetrical pulses can be generated, but also asymmetrical pulses with equal voltage-second areas are possible. The proposed topology is tested via simulations and a scaled-down experimentation, which establish the viability of the topology for water treatment applications.
Learning from History and Present: Next-item Recommendation via Discriminatively Exploiting User Behaviors

In the modern e-commerce, the behaviors of customers contain rich information, e.g., consumption habits, the dynamics of preferences. Recently, session-based recommendationsare becoming popular to explore the temporal characteristics of customers' interactive behaviors. However, existing works mainly exploit the short-term behaviors without fully taking the customers' long-term stable preferences and evolutions into account. In this paper, we propose a novel Behavior-Intensive Neural Network (BINN) for next-item recommendation by incorporating both users' historical stable preferences and present consumption motivations. Specifically, BINN contains two main components, i.e., Neural Item Embedding, and Discriminative Behaviors Learning. Firstly, a novel item embedding method based on user interactions is developed for obtaining an unified representation for each item. Then, with the embedded items and the interactive behaviors over item sequences, BINN discriminatively learns the historical preferences and present motivations of the target users. Thus, BINN could better perform recommendations of the next items for the target users. Finally, for evaluating the performances of BINN, we conduct extensive experiments on two real-world datasets, i.e., Tianchi and JD. The experimental results clearly demonstrate the effectiveness of BINN compared with several state-of-the-art methods.
FPGA Implementation of AHB to APB Protocol

The field of technology is evolving at a very fast pace. The competition is very intense. So the need of the hour is to produce efficient system. In accomplishing this objective we are required to establish better interaction among all the components of the system. This requirement is fulfilled by the Advanced Microcontroller Bus Architecture (AMBA) protocol from Advanced RISC Machines (ARM).The AMBA is the on-chip standard for the communication among components in Application Specific Integrated Circuits (ASIC) or System on Chip (SoC). This paper focuses on the 2 protocols of AMBA which are Advanced High Performance Bus (AHB) and Advanced Peripheral Bus (APB) and theAPB bridge. The coding is done in Verilog synthesis on Xilinx 14.7 ISE and simulation on ISim simulator and FPGA implementation on Spartan 3.
Augmented Reality behind the wheel - Human Interactive Assistance by Mobile Robots

Novel approaches have taken Augmented Reality (AR) beyond traditional body-worn or hand-held displays, leading to the creation of a new branch of AR: Spatial Augmented Reality (SAR) providing additional application areas. SAR is a rapidly emerging field that uses digital projectors to render virtual objects onto 3D objects in the real space. When mounting digital projectors on robots, this collaboration paves the way for unique Human-Robot Interactions (HRI) that otherwise would not be possible. Adding to robots the capability of projecting interactive Augmented Reality content enables new forms of interactions between humans, robots, and virtual objects, enabling new applications. In this work it is investigated the use of SAR techniques on mobile robots for better enabling this to interact in the future with elderly or injured people during rehabilitation, or with children in the pediatric ward of a hospital.
Information management in vehicular ad hoc networks: A review

Vehicular Ad Hoc Network (VANET) is a highly mobile self-organizing network based on Vehicle-toVehicle (V2V), Vehicle-to-Infrastructure (V2I) and hybrid architecture. Recently VANETs have gained a lot of attention by industry and academia due to wide range of applications including safety, convenience, commerce, entertainment and infotainment. Information management requires technologies and techniques for communication, fault tolerance, storage, coding, multi-modal interactions, gathering, aggregation, validation, dissemination, etc. In VANETs, information can be classified into safety and nonsafety information. Driver or vehicle safety information is required in applications offering intelligent transport services like identification of road bends, traffic congestion, accident spots, collision warning, environmental conditions, approaching vehicles, etc. The major concerns in safety applications are reliability, security, trust, real time delivery, and latency. This paper brings out current research efforts on information management techniques employed for safety related applications in VANETs, which includes gathering, aggregation, validation and dissemination, and also provide directions for future research and
Performance Analysis of a Part of Speech Tagging Task

In this paper, we attempt to make a formal analysis of the performance in automatic part of speech tagging. Lower and upper bounds in tagging precision using existing taggers or their combination are provided. Since we show that with existing taggers, automatic perfect tagging is not possible, we offer two solutions for applications requiring very high precision: (1) a solution involving minimum human intervention for a precision of over 98.7%, and (2) a combination of taggers using a memory based learning algorithm that succeeds in reducing the error rate with 11.6% with respect to the best tagger involved.
OOFM - A feature modeling approach to implement MPLs and DSPLs

This paper uses the Object Oriented Feature Modeling (OOFM) technique to develop Multiple Product Lines (MPLs) and Dynamic SPLs (DSPLs). The idea is combine defined OOFM resources in a Model-View-Controller (MVC) architectural style. As result, a pattern-based Product Line Architecture (PLA) is provided, a kind of middleware that performs an advanced usage of multiple and dynamic OOFM features able to generate desired MPLs and DSPLs.
Monitoring of the Hill and the Circuit Wall of the Athenian Acropolis Utilizing Optical Fibre Sensors and Accelerographs

The Acropolis of Athens is one of the most prestigious ancient monuments in the world, attracting daily many visitors, and therefore its structural integrity is of paramount importance. During the last decade an accelerographic array has been installed at the Archaeological Site, in order to monitor the seismic response of the Acropolis Hill and the dynamic behaviour of the monuments (including the Circuit Wall), while several optical fibre sensors have been attached at a middle-vertical section of the Wall. In this study, indicative real time recordings of strain and acceleration on the Wall and the Hill with the use of optical fibre sensors and accelerographs, respectively, are presented and discussed. The records aim to investigate the static and dynamic behaviour – distress of the Wall and the Acropolis Hill, taking also into account the prevailing geological conditions. The optical fibre technology, the location of the sensors, as well as the installation methodology applied is also presented. Emphasis is given to the application of real time instrumental monitoring which can be used as a valuable tool to predict potential structural
Smatch: an Evaluation Metric for Semantic Feature Structures

The evaluation of whole-sentence semantic structures plays an important role in semantic parsing and large-scale semantic structure annotation. However, there is no widely-used metric to evaluate wholesentence semantic structures. In this paper, we present smatch, a metric that calculates the degree of overlap between two semantic feature structures. We give an efficient algorithm to compute the metric and show the results of an inter-annotator agreement study.
Hand posture and gesture recognition technology

Hand gestures that are performed by one or two hands can be categorized according to their applications into different categories including conversational, controlling, manipulative and communicative gestures. Generally, hand gesture recognition aims to identify specific human gestures and use them to convey information. The process of hand gesture recognition composes mainly of four stages: hand gesture images collection, gesture image preprocessing using some techniques including edge detection, filtering and normalization, capture the main characteristics of the gesture images and the evaluation (or classification) stage where the image is classified to its corresponding gesture class. There are many methods that have been used in the classification stage of hand gesture recognition such as Artificial Neural Networks, template matching, Hidden Markov Models and Dynamic Time Warping. This exploratory survey aims to provide a progress report on hand posture and gesture recognition technology.
Magic Quadrant for IT Event Correlation and Analysis

Gartner’s Magic Quadrant for IT Event Correlation and Analysis (ECA), 2009  evaluates vendors’ ability to execute and their completeness of vision relative to a defined set of evaluation criteria regarding current and future market requirements. A Magic Quadrant should not be the only criterion for selecting a vendor, because the right solution for a given situation can be in any quadrant, depending on the specific needs of the enterprise. Enterprises considering the purchase of an ECA product should develop their own list of evaluation criteria and functional requirements in the categories of event collection/ consolidation, processing/correlation and presentation. Large enterprises should consider a multitier event management hierarchy, pushing some event processing and correlation out to the managed IT element at the bottom of the hierarchy. These enterprises should use specialized event management tools in the middle, and should place a “manager of managers” or a business service management (BSM) product on top.
Understanding Users' Health Information Privacy Concerns for Health Wearables

Health information privacy concerns (HIPC) are commonly cited as primary barrier to the ongoing growth of health wearables (HW) for private users. However, little is known about the driving factors of HIPC and the nature of users’ privacy perception. Seven semi-structured focus groups with current users of HWs were conducted to empirically explore factors driving users’ HIPC. Based on an iterative thematic analysis approach, where the interview codes were systematically matched with literature, I develop a thematic map that visualizes the privacy perception of HW users. In particular this map uncovers three central factors (Dilemma of Forced Acceptance, State-Trait Data Sensitivity and Transparency) on HIPC, which HW users have to deal with.