nils-herrmann/clean_scirepeval huggingface dataset:
Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly

A new method of physical activity monitoring is presented, which is able to detect body postures (sifting, standing, and lying) and periods of walking in elderly persons using only one kinematic sensor attached to the chest. The wavelet transform, in conjunction with a simple kinematics model, was used to detect different postural transitions (PTs) and walking periods during daily physical activity. To evaluate the system, three studies were performed. The method was first tested on 11 community-dwelling elderly subjects in a gait laboratory where an optical motion system (Vicon) was used as a reference system. In the second study, the system was tested for classifying PTs (i.e., lying-to-sitting, sitting-to-lying, and turning the body in bed) in 24 hospitalized elderly persons. Finally, in a third study monitoring was performed on nine elderly persons for 45-60 min during their daily physical activity. Moreover, the possibility-to-perform long-term monitoring over 12 h has been shown. The first study revealed a close concordance between the ambulatory and reference systems. Overall, subjects performed 349 PTs during this study. Compared with the reference system, the ambulatory system had an overall sensitivity of 99% for detection of the different PTs. Sensitivities and specificities were 93% and 82% in sit-to-stand, and 82% and 94% in stand-to-sit, respectively. In both first and second studies, the ambulatory system also showed a very high accuracy (> 99%) in identifying the 62 transfers or rolling out of bed, as well as 144 different posture changes to the back, ventral, right and left sides. Relatively high sensitivity (> 90%) was obtained for the classification of usual physical activities in the third study in comparison with visual observation. Sensitivities and specificities were, respectively, 90.2% and 93.4% in sitting, 92.2% and 92.1% in "standing + walking," and, finally, 98.4% and 99.7% in lying. Overall detection errors (as percent of range) were 3.9% for "standing + walking," 4.1% for sitting, and 0.3% for lying. Finally, overall symmetric mean average errors were 12% for "standing + walking." 8.2% for sifting, and 1.3% for lying.
Miniature 6-DOF inertial system for tracking HMDs

Current HMD applications are hampered by the limitations of head-tracking technologies now in use. Commercially available magnetic, optical, acoustic, and mechanical head-trackers suffer from various problems such as vulnerability to interference, line-of-sight restrictions, jitter, latency, small range, and high cost. This paper presents inertial-sensor-based hybrid tracking technology that was developed to combat all these problems. Two commercially available products, the IS-300 and the IS600, are described, both based on the same miniature triaxial inertial sensor device. The IS-300 is a sourceless 3-DOF orientation tracker, using gravimetric tilt-sensing to prevent any gyroscopic drift in pitch and roll, and optional geo-magnetic compassing to prevent any gyroscopic drift in yaw. The IS-600 is a hybrid acousto-inertial 6-DOF position and orientation tracking system. It tracks changes in orientation and position by integrating the outputs of its gyros and accelerometers, and corrects drift using a room-referenced ultrasonic time-of-flight range measuring system. This paper overviews the theory of operation of both systems, and reports bench-testing results designed to evaluate the resolution, accuracy, and latency of each system.
Neural Models for Information Retrieval

Neural ranking models for information retrieval (IR) use shallow or deep neural networks to rank search results in response to a query. Traditional learning to rank models employ machine learning techniques over hand-crafted IR features. By contrast, neural models learn representations of language from raw text that can bridge the gap between query and document vocabulary. Unlike classical IR models, these new machine learning based approaches are data-hungry, requiring large scale training data before they can be deployed. This tutorial introduces basic concepts and intuitions behind neural IR models, and places them in the context of traditional retrieval models. We begin by introducing fundamental concepts of IR and different neural and non-neural approaches to learning vector representations of text. We then review shallow neural IR methods that employ pre-trained neural term embeddings without learning the IR task end-to-end. We introduce deep neural networks next, discussing popular deep architectures. Finally, we review the current DNN models for information retrieval. We conclude with a discussion on potential future directions for neural IR.
Perceived e-service quality ( PeSQ ) Measurement validation and effects on consumer satisfaction and web site loyalty

The objectives of this article are to develop a multiple-item scale for measuring e-service quality and to study the influence of perceived quality on consumer satisfaction levels and the level of web site loyalty.  First, there is an explanation of the main attributes of the concepts examined, with special attention being paid to the multi-dimensional nature of the variables and the relationships between them. This is followed by an examination of the validation processes of the measuring instruments.  The validation process of scales suggested that perceived quality is a multidimensional construct: web design, customer service, assurance and order management; that perceived quality influences on satisfaction; and that satisfaction influences on consumer loyalty. Moreover, no differences in these conclusions were observed if the total sample is divided between buyers and information searchers.  First, the need to develop user-friendly web sites which ease consumer purchasing and searching, thus creating a suitable framework for the generation of higher satisfaction and loyalty levels. Second, the web site manager should enhance service loyalty, customer sensitivity, personalised service and a quick response to complaints. Third, the web site should uphold sufficient security levels in communications and meet data protection requirements regarding the privacy. Lastly, the need for correct product delivery and product manipulation or service is recommended.  Most relevant studies about perceived quality in the internet have focused on web design aspects. Moreover, the existing literature regarding internet consumer behaviour has not fully analysed profits generated by higher perceived quality in terms of user satisfaction and loyalty.
StyLit: illumination-guided example-based stylization of 3D renderings

We present an approach to example-based stylization of 3D renderings that better preserves the rich expressiveness of hand-created artwork. Unlike previous techniques, which are mainly guided by colors and normals, our approach is based on light propagation in the scene. This novel type of guidance can distinguish among context-dependent illumination effects, for which artists typically use different stylization techniques, and delivers a look closer to realistic artwork. In addition, we demonstrate that the current state of the art in guided texture synthesis produces artifacts that can significantly decrease the fidelity of the synthesized imagery, and propose an improved algorithm that alleviates them. Finally, we demonstrate our method's effectiveness on a variety of scenes and styles, in applications like interactive shading study or autocompletion.
DBToaster: A SQL Compiler for High-Performance Delta Processing in Main-Memory Databases

We present DBToaster, a novel query compilation framework for producing high performance compiled query executors that incrementally and continuously answer standing aggregate queries using in-memory views. DBToaster targets applications that require efficient main-memory processing of standing queries (views) fed by high-volume data streams, recursively compiling view maintenance (VM) queries into simple C++ functions for evaluating database updates (deltas). While today’s VM algorithms consider the impact of single deltas on view queries to produce maintenance queries, we recursively consider deltas of maintenance queries and compile to thoroughly transform queries into code. Recursive compilation successively elides certain scans and joins, and eliminates significant query plan interpreter overheads. In this demonstration, we walk through our compilation algorithm, and show the significant performance advantages of our compiled executors over other query processors. We are able to demonstrate 1-3 orders of magnitude improvements in processing times for a financial application and a data warehouse loading application, both implemented across a wide range of database systems, including PostgreSQL, HSQLDB, a commercial DBMS ’A’, the Stanford STREAM engine, and a commercial stream processor ’B’.
Design and control of a wearable hand exoskeleton with force-controllable and compact actuator modules

In this paper, a wearable hand exoskeleton with force-controllable and compact actuator modules is proposed. In order to apply force feedback accurately while allowing natural finger motions, the exoskeleton linkage structure with three degrees of freedom (DOFs) was designed, which was inspired by the muscular skeletal structure of the finger. As an actuating system, a series elastic actuator (SEA) mechanism, which consisted of a small linear motor, a manually designed motor driver, a spring and potentiometers, was applied. The friction of the motor was identified and compensated for obtaining a linearized model of the actuating system. Using a LQ (linear quadratic) tuned PD (proportional and derivative) controller and a disturbance observer (DOB), the proposed actuator module could generate the desired force accurately with actual finger movements. By integrating together the proposed exoskeleton structure, actuator modules and control algorithms, a wearable hand exoskeleton with force-controllable and compact actuator modules was developed to deliver accurate force to the fingertips for flexion/extension motions.
"They brought in the horrible key ring thing!" Analysing the Usability of Two-Factor Authentication in UK Online Banking

To prevent password breaches and guessing attacks, banks increasingly turn to two-factor authentication (2FA), requiring users to present at least one more factor, such as a one-time password generated by a hardware token or received via SMS, besides a password. We can expect some solutions – especially those adding a token – to create extra work for users, but little research has investigated usability, user acceptance, and perceived security of deployed 2FA. This paper presents an in-depth study of 2FA usability with 21 UK online banking customers, 16 of whom had accounts with more than one bank. We collected a rich set of qualitative and quantitative data through two rounds of semi-structured interviews, and an authentication diary over an average of 11 days. Our participants reported a wide range of usability issues, especially with the use of hardware tokens, showing that the mental and physical workload involved shapes how they use online banking. Key targets for improvements are (i) the reduction in the number of authentication steps, and (ii) removing features that do not add any security but negatively affect the user experience.
Dual-Layer Ridged Waveguide Slot Array Fed by a Butler Matrix With Sidelobe Control in the 60-GHz Band

A novel multibeam antenna based on a 4 × 4 Butler matrix with sidelobe level (SLL) control is proposed in the 60-GHz band. The SLL is controlled using a dedicated circuit composed by four 90-degree couplers with different coupling factors and several cross couplers. This dual-layer antenna is made by hollow waveguides and is assembled using diffusion bonding technique. The radiating part is a compact array of ridged waveguides designed to avoid appearance of grating lobes in the visible range for large scanning angles. The antenna field of view is ±43° with sidelobes lower than -17.5 dB over the entire scanning range. The isolation between the input ports of the Butler matrix is better than 25 dB at the design frequency of 61.5 GHz. The reflection bandwidth for VSWR <; 2 is larger than 6.5%. At the design frequency, the measured conductor losses of the antenna are estimated lower than 0.64 dB for all ports.
Sexual and physical health after sex reassignment surgery.

A long-term follow-up study of 55 transsexual patients (32 male-to-female and 23 female-to-male) post-sex reassignment surgery (SRS) was carried out to evaluate sexual and general health outcome. Relatively few and minor morbidities were observed in our group of patients, and they were mostly reversible with appropriate treatment. A trend toward more general health problems in male-to-females was seen, possibly explained by older age and smoking habits. Although all male-to-females, treated with estrogens continuously, had total testosterone levels within the normal female range because of estrogen effects on sex hormone binding globulin, only 32.1% reached normal free testosterone levels. After SRS, the transsexual person's expectations were met at an emotional and social level, but less so at the physical and sexual level even though a large number of transsexuals (80%) reported improvement of their sexuality. The female-to-males masturbated significantly more frequently than the male-to-females, and a trend to more sexual satisfaction, more sexual excitement, and more easily reaching orgasm was seen in the female-to-male group. The majority of participants reported a change in orgasmic feeling, toward more powerful and shorter for female-to-males and more intense, smoother, and longer in male-to-females. Over two-thirds of male-to-females reported the secretion of a vaginal fluid during sexual excitation, originating from the Cowper's glands, left in place during surgery. In female-to-males with erection prosthesis, sexual expectations were more realized (compared to those without), but pain during intercourse was more often reported.
Data Protection from Insider Threats

As data represent a key asset for today’s organizations, the problem of how to protect this data from theft and misuse is at the forefront of these organizations’ minds. Even though today several data security techniques are available to protect data and computing infrastructures, many such techniques—such as firewalls and network security tools—are unable to protect data from attacks posed by those working on an organization’s “inside.” These “insiders” usually have authorized access to relevant information systems, making it extremely challenging to block the misuse of information while still allowing them to do their jobs. This book discusses several techniques that can provide effective protection against attacks posed by people working on the inside of an organization. Chapter 1 introduces the notion of insider threat and reports some data about data breaches due to insider threats. Chapter 2 covers authentication and access control techniques, and Chapter 3 shows how these general security techniques can be extended and used in the context of protection from insider threats. Chapter 4 addresses anomaly detection techniques that are used to determine anomalies in data accesses by insiders. These anomalies are often indicative of potential insider data attacks and therefore play an important role in protection from these attacks. Security information and event management (SIEM) tools and fine-grained auditing are discussed in Chapter 5. These tools aim at collecting, analyzing, and correlating—in real-time—any information and event that may be relevant for the security of an organization. As such, they can be a key element in finding a solution to such undesirable insider threats. Chapter 6 goes on to provide a survey of techniques for separation-of-duty (SoD). SoD is an important principle that, when implemented in systems and tools, can strengthen data protection from malicious insiders. However, to date, very few approaches have been proposed for implementing SoD in systems. In Chapter 7, a short survey of a commercial product is presented, which provides different techniques for protection from malicious users with system privileges—such as a DBA in database management systems. Finally, in Chapter 8, the book concludes with a few remarks and additional research directions.
Robust facial expression classification using shape and appearance features

Facial expression recognition has many potential applications which has attracted the attention of researchers in the last decade. Feature extraction is one important step in expression analysis which contributes toward fast and accurate expression recognition. This paper represents an approach of combining the shape and appearance features to form a hybrid feature vector. We have extracted Pyramid of Histogram of Gradients (PHOG) as shape descriptors and Local Binary Patterns (LBP) as appearance features. The proposed framework involves a novel approach of extracting hybrid features from active facial patches. The active facial patches are located on the face regions which undergo a major change during different expressions. After detection of facial landmarks, the active patches are localized and hybrid features are calculated from these patches. The use of small parts of face instead of the whole face for extracting features reduces the computational cost and prevents the over-fitting of the features for classification. By using linear discriminant analysis, the dimensionality of the feature is reduced which is further classified by using the support vector machine (SVM). The experimental results on two publicly available databases show promising accuracy in recognizing all expression classes.
Autonomous precision agriculture through integration of wireless underground sensor networks with center pivot irrigation systems

Precision agriculture (PA) refers to a series of practices and tools necessary to correctly evaluate farming needs. The accuracy and effectiveness of PA solutions are highly dependent on accurate and timely analysis of the soil conditions. In this paper, a proof-of-concept towards an autonomous precision irrigation system is provided through the integration of a center pivot (CP) irrigation system with wireless underground sensor networks (WUSNs). This Wireless Underground Sensor-Aided Center Pivot (WUSACP) system will provide autonomous irrigation management capabilities by monitoring the soil conditions in real time using wireless underground sensors. To this end, field experiments with a hydraulic drive and continuousmove center pivot irrigation system are conducted. The results are used to evaluate empirical channel models for soil-air communications. The experiment results show that the concept of WUSA-CP is feasible. Through the design of an underground antenna, communication ranges can be improved by up to 400% compared to conventional antenna designs. The results also highlight that the wireless communication channel between soil and air is significantly affected by many spatio-temporal aspects, such as the location and burial depth of the sensors, soil texture and physical properties, soil moisture, and the vegetation canopy height. To the best of our knowledge, This work is supported in part by the National Science Foundation CAREER Award CNS-0953900, U.S. Geological Survey Award 2010NE209B, and UNL Water Center. The authors would like to thank William Rathje for his support during the experiments at Clay Center, Nebraska.  xdong@cse.unl.edu (Xin Dong), mcvuran@cse.unl.edu (Mehmet C. Vuran), sirmak2@unl.edu (Suat Irmak)  2012 this is the first work on the development of an autonomous precision irrigation system with WUSNs.
Design of an Efficient X-Band Waveguide-Fed Microstrip Patch Array

The design and fabrication of a 10.5 GHz microstrip patch array fed by a waveguide is presented. The gain of this antenna is 29 dB and its efficiency is 65%. Commonly, the efficiency of conventional microstrip arrays at X-band is not more than 50%. This antenna demonstrates the ability to accomplish a very high efficiency at X-band in a simple structure. This is achieved by using a slotted waveguide to feed the planar array. To allow symmetrical feed of this antenna, the waveguide is a center-fed slotted waveguide, the two ends of which are shorted. The design procedure is expatiated, which contains the study and design of the waveguide-fed subarray structure and of the coax-to- waveguide transition structure. For designing this entire antenna, a three-dimensional electromagnetic field simulation software CST Microwave Studio is applied. Good agreement is achieved between measurement and simulation results.
A Tale of Two Kernels: Towards Ending Kernel Hardening Wars with Split Kernel

Software security practitioners are often torn between choosing performance or security. In particular, OS kernels are sensitive to the smallest performance regressions. This makes it difficult to develop innovative kernel hardening mechanisms: they may inevitably incur some run-time performance overhead. Here, we propose building each kernel function with and without hardening, within a single split kernel. In particular, this allows trusted processes to be run under unmodified kernel code, while system calls of untrusted processes are directed to the hardened kernel code. We show such trusted processes run with no overhead when compared to an unmodified kernel. This allows deferring the decision of making use of hardening to the run-time. This means kernel distributors, system administrators and users can selectively enable hardening according to their needs: we give examples of such cases. Although this approach cannot be directly applied to arbitrary kernel hardening mechanisms, we show cases where it can. Finally, our implementation in the Linux kernel requires few changes to the kernel sources and no application source changes. Thus, it is both maintainable and easy to use.
Flattened Convolutional Neural Networks for Feedforward Acceleration

We present flattened convolutional neural networks that are designed for fast feedforward execution. The redundancy of the parameters, especially weights of the convolutional filters in convolutional neural networks has been extensively studied and different heuristics have been proposed to construct a low rank basis of the filters after training. In this work, we train flattened networks that consist of consecutive sequence of one-dimensional filters across all directions in 3D space to obtain comparable performance as conventional convolutional networks. We tested flattened model on different datasets and found that the flattened layer can effectively substitute for the 3D filters without loss of accuracy. The flattened convolution pipelines provide around two times speed-up during feedforward pass compared to the baseline model due to the significant reduction of learning parameters. Furthermore, the proposed method does not require efforts in manual tuning or post processing once the model is trained.
Adversarial Phenomenon in the Eyes of Bayesian Deep Learning

Deep Learning models are vulnerable to adversarial examples, i.e. images obtained via deliberate imperceptible perturbations, such that the model misclassifies them with high confidence. However, class confidence by itself is an incomplete picture of uncertainty. We therefore use principled Bayesian methods to capture model uncertainty in prediction for observing adversarial misclassification. We provide an extensive study with different Bayesian neural networks attacked in both white-box and black-box setups. The behaviour of the networks for noise, attacks and clean test data is compared. We observe that Bayesian neural networks are uncertain in their predictions for adversarial perturbations, a behaviour similar to the one observed for random Gaussian perturbations. Thus, we conclude that Bayesian neural networks can be considered for detecting adversarial examples.