nils-herrmann/clean_scirepeval huggingface dataset:
The role of satellites in 5G

The next generation of mobile radio communication systems - so called 5G - will provide some major changes to those generations to date. The ability to cope with huge increases in data traffic at reduced latencies and improved quality of user experience together with major reduction in energy usage are big challenges. In addition future systems will need to embody connections to billions of objects - the so called Internet of Things (IoT) which raise new challenges. Visions of 5G are now available from regions across the World and research is ongoing towards new standards. The consensus is a flatter architecture that adds a dense network of small cells operating in the millimetre wave bands and which are adaptable and software controlled. But what place for satellites in such a vision? The paper examines several potential roles for satellite including coverage extension, content distribution, providing resilience, improved spectrum utilisation and integrated signalling systems.
Enhancing Security Event Management Systems with Unsupervised Anomaly Detection

Security Information and Event Management (SIEM) systems are today a key component of complex enterprise networks. They usually aggregate and correlate events from different machines and perform a rule-based analysis to detect threats. In this paper we present an enhancement of such systems which makes use of unsupervised anomaly detection algorithms without the need for any prior training of the system. For data acquisition, events are exported from an existing SIEM appliance, parsed, unified and preprocessed to fit the requirements of unsupervised anomaly detection algorithms. Six different algorithms are evaluated qualitatively and finally a global k-NN approach was selected for a practical deployment. The new system was able to detect misconfigurations and gave the security operation center team more insight about processes in the
Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks

This paper presents an end-to-end approach for tracking static and dynamic objects for an autonomous vehicle driving through crowded urban environments. Unlike traditional approaches to tracking, this method is learned end-to-end, and is able to directly predict a full unoccluded occupancy grid map from raw laser input data. Inspired by the recently presented DeepTracking approach (, ), we employ a recurrent neural network (RNN) to capture the temporal evolution of the state of the environment, and propose to use Spatial Transformer modules to exploit estimates of the egomotion of the vehicle. Our results demonstrate the ability to track a range of objects, including cars, buses, pedestrians, and cyclists through occlusion, from both moving and stationary platforms, using a single learned model. Experimental results demonstrate that the model can also predict the future states of objects from current inputs, with greater accuracy than previous work.
QuickRec: prototyping an intel architecture extension for record and replay of multithreaded programs

There has been significant interest in hardware-assisted deterministic Record and Replay (RnR) systems for multithreaded programs on multiprocessors. However, no proposal has implemented this technique in a hardware prototype with full operating system support. Such an implementation is needed to assess RnR practicality.
 This paper presents QuickRec, the first multicore Intel Architecture (IA) prototype of RnR for multithreaded programs. QuickRec is based on QuickIA, an Intel emulation platform for rapid prototyping of new IA extensions. QuickRec is composed of a Xeon server platform with FPGA-emulated second-generation Pentium cores, and Capo3, a full software stack for managing the recording hardware from within a modified Linux kernel.
 This paper's focus is understanding and evaluating the implementation issues of RnR on a real platform. Our effort leads to some lessons learned, as well as to some pointers for future research. We demonstrate that RnR can be implemented efficiently on a real multicore IA system. In particular, we show that the rate of memory log generation is insignificant, and that the recording hardware has negligible performance overhead. However, the software stack incurs an average recording overhead of nearly 13%, which must be reduced to enable always-on use of RnR.
IJ CS Differences in Individualistic and Collectivistic Tendencies among College Students in Japan and the United States Emiko

It is a worldwide stereotype that Japanese, compared to Americans, are oriented more toward collectivism. But this stereotypical notion of more collectivism among Japanese, which typically stems from a view that individualism and collectivism stand at opposite ends of a continuum, has been filled with dashed empirical findings, especially in a sample of college students. In the current study, following the view that individualism and collectivism are two separate concepts rather than one with two extremes, we test and compare both individualistic and collectivistic tendencies among college students in Japan and the United States. A review of theories and research on this dimension of cultural variability across the two diverse cultures and the literature on societal pressure of collectivity and on parents as primary socialization agents of culturally expected values lead to two hypotheses: 1) Japanese college students tend less toward individualism than do Americans, and 2) Japanese college students tend less toward collectivism than do Americans. Analysis of identical survey data from college students in Japan and in the United States provides strong support for both hypotheses.
A Wireless Design of Low-Cost Irrigation System Using ZigBee Technology

At present, labor-saving and water-saving technology is a key issue in irrigation. A wireless solution for intelligent field irrigation system dedicated to Jew's-ear planting in Lishui, Zhejiang, China, based on ZigBee technology was proposed in this paper. Instead of conventional wired connection, the wireless design made the system easy installation and maintenance. The hardware architecture and software algorithm of wireless sensor/actuator node and portable controller, acting as the end device and coordinator in ZigBee wireless sensor network respectively, were elaborated in detail. The performance of the whole system was evaluated in the end. The long-time smooth and proper running of the system in the field proved its high reliability and practicability. As an explorative application of wireless sensor network in irrigation management, this paper offered a methodology to establish large-scale remote intelligent irrigation system.
Face video based touchless blood pressure and heart rate estimation

Hypertension (high blood pressure) is the leading cause for increasing number of premature deaths due to cardiovascular diseases. Continuous hypertension screening seems to be a promising approach in order to take appropriate steps to alleviate hypertension-related diseases. Many studies have shown that physiological signal like Photoplethysmogram (PPG) can be reliably used for predicting the Blood Pressure (BP) and Heart Rate (HR). However, the existing approaches use a transmission or reflective type wearable sensor to collect the PPG signal. These sensors are bulky and mostly require an assistance of a trained medical practitioner; which preclude these approaches from continuous BP monitoring outside the medical centers. In this paper, we propose a novel touchless approach that predicts BP and HR using the face video based PPG. Since the facial video can easily be captured using a consumer grade camera, this approach is a convenient way for continuous hypertension monitoring outside the medical centers. The approach is validated using the face video data collected in our lab, with the ground truth BP and HR measured using a clinically approved BP monitor OMRON HBP1300. Accuracy of the method is measured in terms of normalized mean square error, mean absolute error and error standard deviation; which complies with the standards mentioned by Association for the Advancement of Medical Instrumentation. Two-tailed dependent sample t-test is also conducted to verify that there is no statistically significant difference between the BP and HR predicted using the proposed approach and the BP and HR measured using OMRON.
iSleep: unobtrusive sleep quality monitoring using smartphones

The quality of sleep is an important factor in maintaining a healthy life style. To date, technology has not enabled personalized, in-place sleep quality monitoring and analysis. Current sleep monitoring systems are often difficult to use and hence limited to sleep clinics, or invasive to users, e.g., requiring users to wear a device during sleep. This paper presents iSleep -- a practical system to monitor an individual's sleep quality using off-the-shelf smartphone. iSleep uses the built-in microphone of the smartphone to detect the events that are closely related to sleep quality, including body movement, couch and snore, and infers quantitative measures of sleep quality. iSleep adopts a lightweight decision-tree-based algorithm to classify various events based on carefully selected acoustic features, and tracks the dynamic ambient noise characteristics to improve the robustness of classification. We have evaluated iSleep based on the experiment that involves 7 participants and total 51 nights of sleep, as well the data collected from real iSleep users. Our results show that iSleep achieves consistently above 90% accuracy for event classification in a variety of different settings. By providing a fine-grained sleep profile that depicts details of sleep-related events, iSleep allows the user to track the sleep efficiency over time and relate irregular sleep patterns to possible causes.
Observer-based inertial identification for auto-tuning servo motor drives

In servo motor drive applications variation of inertia degrades drive's performance. Motor response is affected not only by external disturbance input but also by mechanical parameters such as inertia and friction. These factors must all be considered in order for accurate inertia identification and drive tuning. In this paper, an observer-based auto-tuning scheme for servo motor drives is presented. This scheme is consisted of a state estimator to estimate motor disturbance and two adaptive controllers to separately adjust drive inertia and friction to their correct value. The servo control loop is tuned automatically with the inertia found. The experimental results show that this auto-tuning scheme can achieve good performance and that the scheme is able to estimate the mechanical parameters accurately.
Skin Microbiome: Looking Back to Move Forward

Trillions of bacteria, fungi, viruses, archaea, and small arthropods colonize the skin surface, collectively comprising the skin microbiome. Generations of researchers have classified these microbes as transient versus resident, beneficial versus pathogenic, and collaborators versus adversaries. Culturing and direct sequencing of microbial inhabitants identified distinct populations present at skin surface sites. Herein, we explore the history of this field, describe findings from the current molecular sequencing era, and consider the future of investigating how microbes and antimicrobial therapy contribute to human health.
A Single-Actuator Gripper with a Working Mode Switching Mechanism for Grasping and Rolling Manipulation

This paper presents a three-fingered gripper with a working mode switching mechanism for both grasping and rolling manipulation tasks, actuated by only one motor. A newly proposed Continuum Differential Mechanism (CDM) was utilized with an underactuated finger design to generate adaptive grasps. A switching mechanism was designed to change the gripper's working mode between grasping and rolling manipulation under the actuation of the same motor. Besides being expected to grasp various objects, the gripper can roll grasped objects with its two fingers, utilizing the CDM's elasticity, in the rolling manipulation mode. Experimental results verified that the gripper can adaptively grasp various objects in the grasping mode and can also perform in-hand rolling tasks using two of its fingers in the manipulation mode, demonstrating the effectiveness of the proposed idea.
State of the Art: Embedding Security in Vehicles

For new automotive applications and services, information technology (IT) has gained central importance. IT-related costs in car manufacturing are already high and they will increase dramatically in the future. Yet whereas safety and reliability have become a relatively well-established field, the protection of vehicular IT systems against systematic manipulation or intrusion has only recently started to emerge. Nevertheless, IT security is already the base of some vehicular applications such as immobilizers or digital tachographs. To securely enable future automotive applications and business models, IT security will be one of the central technologies for the next generation of vehicles. After a state-of-the-art overview of IT security in vehicles, we give a short introduction into cryptographic terminology and functionality. This contribution will then identify the need for automotive IT security while presenting typical attacks, resulting security objectives, and characteristic constraints within the automotive area. We will introduce core security technologies and relevant security mechanisms followed by a detailed description of critical vehicular applications, business models, and components relying on IT security. We conclude our contribution with a detailed statement about challenges and opportunities for the automotive IT community for embedding IT security in vehicles.
ICIET ’ 14 Image Steganography Method Using Integer Wavelet Transform

Digital Steganography explains the art and science of writing hidden messages in such a way that, apart from the sender and intended recipient, no one suspects the existence of the message, a form of security through the state of being unknown. The main two famous schemes used for image steganography are spatial domain embedding and transform domain embedding. The main aim of Wavelet Transform is used to transform original image (cover image) from spatial domain to frequency domain. But here in our proposed work, Integer Wavelet Transform is performed on a gray level cover image and in turn embeds the message bitstream into the LSB's of the integer wavelet coefficients of a the image . The main purpose of the proposed work is to focus on improving embedding capacity and bring down the distortion occurring to the stego image. The refinement of the algorithm plays an important role for accomplishing higher embedding capacity and low distortion rate. The experimental results prove that the assessment metric such as PSNR is improved in a high manner. The experimental results show that the algorithm has a high capacity and a good invisibility.
Mobile Apps in Cardiology: Review

Cardiovascular diseases are the deadliest diseases worldwide, with 17.3 million deaths in 2008 alone. Among them, heart-related deaths are of the utmost relevance; a fact easily proven by the 7.25 million deaths caused by ischemic heart disease alone in that year. The latest advances in smartphones and mHealth have been used in the creation of thousands of medical apps related to cardiology, which can help to reduce these mortality rates.



The aim of this paper is to study the literature on mobile systems and applications currently available, as well as the existing apps related to cardiology from the leading app stores and to then classify the results to see what is available and what is missing, focusing particularly on commercial apps.



Two reviews have been developed. One is a literature review of mobile systems and applications, retrieved from several databases and systems such as Scopus, PubMed, IEEE Xplore, and Web of Knowledge. The other is a review of mobile apps in the leading app stores, Google play for Android and Apple's App Store for iOS.



Search queries up to May 2013 located 406 papers and 710 apps related to cardiology and heart disease. The most researched section in the literature associated with cardiology is related to mobile heart (and vital signs) monitoring systems and the methods involved in the classification of heart signs in order to detect abnormal functions. Other systems with a significant number of papers are mobile cardiac rehabilitation systems, blood pressure measurement, and systems for the detection of heart failure. The majority of apps for cardiology are heart monitors and medical calculators. Other categories with a high number of apps are those for ECG education and interpretation, cardiology news and journals, blood pressure tracking, heart rate monitoring using an external device, and CPR instruction. There are very few guides on cardiac rehabilitation and apps for the management of the cardiac condition, and there were no apps that assist people who have undergone a heart transplant.



The distribution of work in the field of cardiology apps is considerably disproportionate. Whereas some systems have significant research and apps are available, other important systems lack such research and lack apps, even though the contribution they could provide is significant.
Algorithms for Infinitely Many-Armed Bandits

We consider multi-armed bandit problems where the number of arms is larger than the possible number of experiments. We make a stochastic assumption on the mean-reward of a new selected arm which characterizes its probability of being a near-optimal arm. Our assumption is weaker than in previous works. We describe algorithms based on upper-confidence-bounds applied to a restricted set of randomly selected arms and provide upper-bounds on the resulting expected regret. We also derive a lower-bound which matches (up to a logarithmic factor) the upper-bound in some cases.
Tensegrity II. How structural networks influence cellular information processing networks.

The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion) can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.
Vision-Based Gesture Recognition: A Review

The use of gesture as a natural interface serves as a motivating force for research in modeling, analyzing and recognition of gestures. In particular, human computer intelligent interaction needs vision-based gesture recognition, which involves many interdisciplinary studies. A survey on recent vision-based gesture recognition approaches is given in this paper. We shall review methods of static hand posture and temporal gesture recognition. Several application systems of gesture recognition are also described in this paper. We conclude with some thoughts about future research directions.
Online continuous stereo extrinsic parameter estimation

Stereo visual odometry and dense scene reconstruction depend critically on accurate calibration of the extrinsic (relative) stereo camera poses. We present an algorithm for continuous, online stereo extrinsic re-calibration operating only on sparse stereo correspondences on a per-frame basis. We obtain the 5 degree of freedom extrinsic pose for each frame, with a fixed baseline, making it possible to model time-dependent variations. The initial extrinsic estimates are found by minimizing epipolar errors, and are refined via a Kalman Filter (KF). Observation covariances are derived from the Cramer-Rao lower bound of the solution uncertainty. The algorithm operates at frame rate with unoptimized Matlab code with over 1000 correspondences per frame. We validate its performance using a variety of real stereo datasets and simulations.
Accurate and Efficient On-Chip Spectral Analysis for Built-In Testing and Calibration Approaches

The fast Fourier transform (FFT) algorithm is widely used as a standard tool to carry out spectral analysis because of its computational efficiency. However, the presence of multiple tones frequently requires a fine frequency resolution to achieve sufficient accuracy, which imposes the use of a large number of FFT points that results in large area and power overheads. In this paper, an FFT method is proposed for on-chip spectral analysis of multi-tone signals with particular harmonic and intermodulation components. This accurate FFT analysis approach is based on coherent sampling, but it requires a significantly smaller number of points to make the FFT realization more suitable for on-chip built-in testing and calibration applications that require area and power efficiency. The technique was assessed by comparing the simulation results from the proposed method of single and multiple tones with the simulation results obtained from the FFT of coherently sampled tones. The results indicate that the proper selection of test tone frequencies can avoid spectral leakage even with multiple narrowly spaced tones. When low-frequency signals are captured with an analog-to-digital converter (ADC) for on-chip analysis, the overall accuracy is limited by the ADC's resolution, linearity, noise, and bandwidth limitations. Post-layout simulations of a 16-point FFT showed that third-order intermodulation (IM3) testing with two tones can be performed with 1.5-dB accuracy for IM3 levels of up to 50 dB below the fundamental tones that are quantized with a 10-bit resolution. In a 45-nm CMOS technology, the layout area of the 16-point FFT for on-chip built-in testing is 0.073 mm2, and its estimated power consumption is 6.47 mW.