nils-herrmann/clean_scirepeval huggingface dataset:
Network forensic frameworks: Survey and research challenges

Network forensics is the science that deals with capture, recording, and analysis of network traffic for detecting intrusions and investigating them. This paper makes an exhaustive survey of various network forensic frameworks proposed till date. A generic process model for network forensics is proposed which is built on various existing models of digital forensics. Definition, categorization and motivation for network forensics are clearly stated. The functionality of various Network Forensic Analysis Tools (NFATs) and network security monitoring tools, available for forensics examiners is discussed. The specific research gaps existing in implementation frameworks, process models and analysis tools are identified and major challenges are highlighted. The significance of this work is that it presents an overview on network forensics covering tools, process models and framework implementations, which will be very much useful for security practitioners and researchers in exploring this upcoming and young discipline. a 2010 Elsevier Ltd. All rights reserved.
Laser spotlight detection and interpretation of its movement behavior in laser pointer interface

A laser pointer can be used as an input interface in human-machine interaction. Such utilization, however, can be problematic and one of the main issues is the lack of good reliability in the laser spotlight detection. Another problem is how to interpret the user's movement of the spotlight into commands for the application. This paper proposes a method for a laser spotlight detection. The aim is to improve the practicality and reliability of the previous approaches. We use the maximum pixel value as a multiplier in determining the threshold. Maximum pixel value is obtained from environment brightness at a specified time. For the second problem we propose a simple interpretation of incidents that allows the user to use the application, with three main events: laser-move, hover, and single-click. There is no need for users and program to wait a specified time span to be able to interact with each other, and the user can directly give commands to the application after the single-click event. These approaches result in better reliability, easier operation of the application by the user, and allow opportunity for development of a system for rehabilitative, recreation, and input interface devices in the future.
Retrograde amnesia and remote memory impairment

-The status of remote memory in case N.A., patients receiving bilateral ECT, and patients with KorsakoBsyndrome was assessed using seven different tests. The extent and pattern of remote memory impairment depended upon the etiology of amnesia, appearing as a relatively brief retrograde amnesia for N.A. and patients receiving ECT and as an extensive impairment covering many decades for patients with KorsakoB syndrome. Differences in remote memory impairment could not be explained by differences in the severity ofanterograde amnesia, indicating that amnesia is not a unitary disorder. We suggest that brief retrograde amnesia is typically present whenever amnesia occurs and that extensive remote memory impairment is a distinct entity related to superimposed cognitive deficits. These ideas and a review of previous studies lead to a comprehensive proposal for understanding retrograde amnesia and remote memory impairment. THE AMNESIC syndrome has been the subject of much interest in neuropsychology because of what it might reveal about the organization and neurological foundations of normal memory. The phenomenon of retrograde amnesia, that loss of memory can occur for the period before the precipitating incident, has had a particularly large impact on ideas about normal memory function [l-5]. However, conflicting views exist regarding both the extent and pattern of retrograde amnesia and these have been used to support different ideas about the nature of amnesia. Specifically, clinical assessment of memory loss in patients with medial temporal lobectomy has suggested that a relatively brief retrograde amnesia extends at least to several months and at most to a few years prior to surgery [6, 71. Formal testing of patients receiving bilateral electroconvulsive therapy (ECT) has revealed a brief retrograde amnesia affecting memory for public events and former television programs that occurred during the few years prior to treatment [8-lo]. These findings, together with studies of anterograde amnesia, are consistent with theories of amnesia that emphasize deficiency in the storage or consolidation of new information [l, 11, 121. By contrast, formal testing of patients with Korsakoff syndrome has revealed an extensive impairment of remote memory for public events [13-l 51, famous faces [2,13,15], and famous voices [16] that covers several decades. These *Now at Department of Psychology, Massachusetts Institute of Technology, Cambridge, MA 02139. ICorrespondence to Larry R. Squire, Veterans Administration Medical Center, 3350 La Jolla Village Drive, V-l 16A, San Diego, CA 92161, U.S.A.
Robust Non-Rigid Motion Tracking and Surface Reconstruction Using $L_0$ Regularization

We present a new motion tracking technique to robustly reconstruct non-rigid geometries and motions from a single view depth input recorded by a consumer depth sensor. The idea is based on the observation that most non-rigid motions (especially human-related motions) are intrinsically involved in articulate motion subspace. To take this advantage, we propose a novel <inline-formula><tex-math notation="LaTeX">$L_0$</tex-math><alternatives> <inline-graphic xlink:href="xu-ieq2-2688331.gif"/></alternatives></inline-formula> based motion regularizer with an iterative solver that implicitly constrains local deformations with articulate structures, leading to reduced solution space and physical plausible deformations. The <inline-formula><tex-math notation="LaTeX">$L_0$</tex-math> <alternatives><inline-graphic xlink:href="xu-ieq3-2688331.gif"/></alternatives></inline-formula> strategy is integrated into the available non-rigid motion tracking pipeline, and gradually extracts articulate joints information online with the tracking, which corrects the tracking errors in the results. The information of the articulate joints is used in the following tracking procedure to further improve the tracking accuracy and prevent tracking failures. Extensive experiments over complex human body motions with occlusions, facial and hand motions demonstrate that our approach substantially improves the robustness and accuracy in motion tracking.
Data Mining and Opinion Mining: A Tool in Educational Context

The use of the web as a universal communication platform generates large volumes of data (Big data), which in many cases, need to be processed so that they can become useful knowledge in face of the sceptics who have doubts about the credibility of such information. The use of web data that comes from educational contexts needs to be addressed, since that large amount of unstructured information is not being valued, losing valuable information that can be used. To solve this problem, we propose the use of data mining techniques such as sentiment analysis to validate the information that comes from the educational platforms. The objective of this research is to propose a methodology that allows the user to apply sentiment analysis in a simple way, because although some researchers have done it, very few do with data in the educational context. The results obtained prove that the proposal can be used in similar cases.
Arioc: high-throughput read alignment with GPU-accelerated exploration of the seed-and-extend search space

When computing alignments of DNA sequences to a large genome, a key element in achieving high processing throughput is to prioritize locations in the genome where high-scoring mappings might be expected. We formulated this task as a series of list-processing operations that can be efficiently performed on graphics processing unit (GPU) hardware.We followed this approach in implementing a read aligner called Arioc that uses GPU-based parallel sort and reduction techniques to identify high-priority locations where potential alignments may be found. We then carried out a read-by-read comparison of Arioc's reported alignments with the alignments found by several leading read aligners. With simulated reads, Arioc has comparable or better accuracy than the other read aligners we tested. With human sequencing reads, Arioc demonstrates significantly greater throughput than the other aligners we evaluated across a wide range of sensitivity settings. The Arioc software is available at https://github.com/RWilton/Arioc. It is released under a BSD open-source license.
Syngnathia and obstructive apnea in a case of popliteal pterygium syndrome

We describe an infant with popliteal pterygia, syngnathia, cleft lip and palate, and retrognathia diagnosed with popliteal pterygium syndrome (PPS). The neonatal course was complicated by severe obstructive apnea necessitating tracheostomy.  This report illustrates the potential for airway compromise in PPS patients and the need for thorough neonatal airway assessment.
Structured Perceptron with Inexact Search

Structured learning with inexact inference is a fundamental problem. We propose variants of the structured perceptron algorithm under a general “violation-fixing” framework that guarantees convergence. This framework subsumes previous remedies including “early update” as special cases, and also explains why standard perceptron may fail with inexact search. We also propose new update methods within this framework which learn better models with dramatically reduced training times on state-of-the-art part-of-speech tagging and incremental parsing systems.
Multiband mobile phone antenna for GNSS application

In this article we have presented a new design of a monopole antenna mobile phone, which covers several bands with circular polarization. The proposed antenna generates five resonant frequencies. Our antenna has a bandwidth band that has bands of wireless communication systems such as GSM (880 960 MHz), DCS (1710 1880 MHz), PCS (1850 1990 MHz), UMTS (1920 2170 MHz), WiBro (2300 2390 MHz) and ISM (2400 2483 MHz) and GNSS, including COMPASS (1559.052 1591.788 MHz), GPS (1575.42 5MHz), GLONASS (1602 1615.5 MHz), Galileo (1189 1214 MHz). We discussed the various parameters of the antenna, such as return loss, radiation pattern and axial ratio AR.
A graph-based recommender system for digital library

Research shows that recommendations comprise a valuable service for users of a digital library [11]. While most existing recommender systems rely either on a content-based approach or a collaborative approach to make recommendations, there is potential to improve recommendation quality by using a combination of both approaches (a hybrid approach). In this paper, we report how we tested the idea of using a graph-based recommender system that naturally combines the content-based and collaborative approaches. Due to the similarity between our problem and a concept retrieval task, a Hopfield net algorithm was used to exploit high-degree book-book, user-user and book-user associations. Sample hold-out testing and preliminary subject testing were conducted to evaluate the system, by which it was found that the system gained improvement with respect to both precision and recall by combining content-based and collaborative approaches. However, no significant improvement was observed by exploiting high-degree associations.
Planar High-Gain Dielectric-Loaded Antipodal Linearly Tapered Slot Antenna for $E$ - and $W$ -Band Gigabyte Point-to-Point Wireless Services

The concept of substrated integrated waveguide (SIW)-fed horn and antipodal linearly tapered slot antenna (ALTSA) are jointly used to design a low-cost, high-gain, and efficient planar dielectric-loaded antenna for ultra-wideband gigabyte wireless services, which are demonstrated over <formula formulatype="inline"><tex Notation="TeX">$E$</tex></formula>- and <formula formulatype="inline"><tex Notation="TeX">$W$</tex></formula>-bands. SIW is used to feed the proposed antenna. To increase the gain of the antenna, a dielectric-loaded slab is used in front of the antenna and works as a dielectric guiding structure. The SIW feed, the proposed antenna, and the loaded dielectric are all integrated in a planar single layer substrate, resulting in low cost and easy fabrication. Low-cost printed circuit board (PCB) process is utilized to fabricate the antenna structure with rectangular and elliptical shaped loaded dielectrics. Measured bandwidth of the antenna covers both <formula formulatype="inline"><tex Notation="TeX">$E$</tex></formula>- and <formula formulatype="inline"><tex Notation="TeX">$W$</tex></formula>-bands (70–110 GHz). Measured gain of the single-element antenna is <formula formulatype="inline"> <tex Notation="TeX">${\hbox{14}}\pm {\hbox{0.5}}$</tex></formula> dBi, while the measured radiation efficiency of 84.23% is obtained at 80 GHz. Wideband SIW power dividers are used to form a 1<formula formulatype="inline"><tex Notation="TeX">$\,\times\,$</tex></formula>4 array structure. Measured gain of the 1<formula formulatype="inline"><tex Notation="TeX">$\,\times\,$</tex> </formula>4 array antenna is <formula formulatype="inline"><tex Notation="TeX">${\hbox{19}}\pm {\hbox{1}}$</tex></formula> dBi, while the measured radiation pattern and gain are almost constant within the wide bandwidth of the antenna.
Uniform circular array with integrated microstrip tapered baluns

This paper presents the design, simulation, and measurement results of a 4-element uniform circular array (UCA) using dipole antenna elements with integrated microstrip tapered baluns to convert between balanced and unbalanced signals. These baluns are compact, integrated into the array support structure, and can provide a balanced signal over a relatively wide bandwidth. Simulation results are shown for the amplitude and phase balance of the balun from 1.6 GHz to 2.2 GHz. The array was fabricated and its manifold was measured in an anechoic chamber at a frequency of 1.7 GHz. The gain and phase responses of the array are presented and are compared to a simulated ideal dipole UCA in free-space.
Comparing White-Box and Black-Box Test Prioritization

Although white-box regression test prioritization has been well-studied, the more recently introduced black-box prioritization approaches have neither been compared against each other nor against more well-established white-box techniques. We present a comprehensive experimental comparison of several test prioritization techniques, including well-established white-box strategies and more recently introduced black-box approaches. We found that Combinatorial Interaction Testing and diversity-based techniques (Input Model Diversity and Input Test Set Diameter) perform best among the black-box approaches. Perhaps surprisingly, we found little difference between black-box and white-box performance (at most 4% fault detection rate difference). We also found the overlap between black- and white-box faults to be high: the first 10% of the prioritized test suites already agree on at least 60% of the faults found. These are positive findings for practicing regression testers who may not have source code available, thereby making white-box techniques inapplicable. We also found evidence that both black-box and white-box prioritization remain robust over multiple system releases.
Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans.

Brain-computer interfaces (BCIs) can provide communication and control to people who are totally paralyzed. BCIs can use noninvasive or invasive methods for recording the brain signals that convey the user's commands. Whereas noninvasive BCIs are already in use for simple applications, it has been widely assumed that only invasive BCIs, which use electrodes implanted in the brain, can provide multidimensional movement control of a robotic arm or a neuroprosthesis. We now show that a noninvasive BCI that uses scalp-recorded electroencephalographic activity and an adaptive algorithm can provide humans, including people with spinal cord injuries, with multidimensional point-to-point movement control that falls within the range of that reported with invasive methods in monkeys. In movement time, precision, and accuracy, the results are comparable to those with invasive BCIs. The adaptive algorithm used in this noninvasive BCI identifies and focuses on the electroencephalographic features that the person is best able to control and encourages further improvement in that control. The results suggest that people with severe motor disabilities could use brain signals to operate a robotic arm or a neuroprosthesis without needing to have electrodes implanted in their brains.
Structure-aware QR Code abstraction

Quick Response Codes (QR Codes) have proved to be a great success in both automotive industry and general commercial use. However, in most cases, QR Codes are not identified as aesthetical, since the original motivation to invent QR Codes is to achieve high speed and high readability in scanning. This paper proposes a solution framework for QR Code abstraction, which produces machine readable QR Code that is visually similar to the input image. Unlike the existing schemes for QR Code abstraction, which produces QR Codes of low resolution, the framework aims to resolve the high computation complexity of producing halftone QR Codes of high resolution with both similarity and readability preserved. The solution framework has been implemented and tested on various input texts and images, and a user study was conducted to evaluate its performance in preserving similarity. The experimental results show that the framework can produce QR Codes of high resolution and high similarity without compromising readability.
Utilizing Neural Networks and Linguistic Metadata for Early Detection of Depression Indications in Text Sequences

Depression is ranked as the largest contributor to global disability and is also a major reason for suicide. Still, many individuals suffering from forms of depression are not treated for various reasons. Previous studies have shown that depression also has an effect on language usage and that many depressed individuals use social media platforms or the internet in general to get information or discuss their problems. This paper addresses the early detection of depression using machine learning models based on messages on a social platform. In particular, a convolutional neural network based on different word embeddings is evaluated and compared to a classification based on user-level linguistic metadata. An ensemble of both approaches is shown to achieve state-of-the-art results in a current early detection task. Furthermore, the currently popular ERDE score as metric for early detection systems is examined in detail and its drawbacks in the context of shared tasks are illustrated. A slightly modified metric is proposed and compared to the original score. Finally, a new word embedding was trained on a large corpus of the same domain as the described task and is evaluated as well.
The principles of software QRS detection

The QRS complex is the most striking waveform within the electrocardiogram (ECG). Since it reflects the electrical activity within the heart during the ventricular contraction, the time of its occurrence as well as its shape provide much information about the current state of the heart. Due to its characteristic shape it serves as the basis for the automated determination of the heart rate, as an entry point for classification schemes of the cardiac cycle, and often it is also used in ECG data compression algorithms. In that sense, QRS detection provides the fundamentals for almost all automated ECG analysis algorithms. Software QRS detection has been a research topic for more than 30 years. The evolution of these algorithms clearly reflects the great advances in computer technology. Within the last decade many new approaches to QRS detection have been proposed; for example, algorithms from the field of artificial neural networks genetic algorithms wavelet transforms, filter banks as well as heuristic methods mostly based on nonlinear transforms. The authors provide an overview of these recent developments as well as of formerly proposed algorithms.
Mobile Multimedia Recommendation in Smart Communities: A Survey

Due to the rapid growth of Internet broadband access and proliferation of modern mobile devices, various types of multimedia (e.g., text, images, audios, and videos) have become ubiquitously available anytime. Mobile device users usually store and use multimedia contents based on their personal interests and preferences. Mobile device challenges such as storage limitation have, however, introduced the problem of mobile multimedia overload to users. To tackle this problem, researchers have developed various techniques that recommend multimedia for mobile users. In this paper, we examine the importance of mobile multimedia recommendation systems from the perspective of three smart communities, namely mobile social learning, mobile event guide, and context-aware services. A cautious analysis of existing research reveals that the implementation of proactive, sensor-based and hybrid recommender systems can improve mobile multimedia recommendations. Nevertheless, there are still challenges and open issues such as the incorporation of context and social properties, which need to be tackled to generate accurate and trustworthy mobile multimedia recommendations.
Cancer statistics in China, 2015.

With increasing incidence and mortality, cancer is the leading cause of death in China and is a major public health problem. Because of China's massive population (1.37 billion), previous national incidence and mortality estimates have been limited to small samples of the population using data from the 1990s or based on a specific year. With high-quality data from an additional number of population-based registries now available through the National Central Cancer Registry of China, the authors analyzed data from 72 local, population-based cancer registries (2009-2011), representing 6.5% of the population, to estimate the number of new cases and cancer deaths for 2015. Data from 22 registries were used for trend analyses (2000-2011). The results indicated that an estimated 4292,000 new cancer cases and 2814,000 cancer deaths would occur in China in 2015, with lung cancer being the most common incident cancer and the leading cause of cancer death. Stomach, esophageal, and liver cancers were also commonly diagnosed and were identified as leading causes of cancer death. Residents of rural areas had significantly higher age-standardized (Segi population) incidence and mortality rates for all cancers combined than urban residents (213.6 per 100,000 vs 191.5 per 100,000 for incidence; 149.0 per 100,000 vs 109.5 per 100,000 for mortality, respectively). For all cancers combined, the incidence rates were stable during 2000 through 2011 for males (+0.2% per year; P = .1), whereas they increased significantly (+2.2% per year; P < .05) among females. In contrast, the mortality rates since 2006 have decreased significantly for both males (-1.4% per year; P < .05) and females (-1.1% per year; P < .05). Many of the estimated cancer cases and deaths can be prevented through reducing the prevalence of risk factors, while increasing the effectiveness of clinical care delivery, particularly for those living in rural areas and in disadvantaged populations.