nils-herrmann/clean_scirepeval huggingface dataset:
The trade-off between taxi time and fuel consumption in airport ground movement

Environmental issues play an important role across many sectors. This is particularly the case in the air transportation industry. One area which has remained relatively unexplored in this context is the ground movement problem for aircraft on the airport’s surface. Aircraft have to be routed from a gate to a runway and vice versa and a key area of study is whether fuel burn and environmental impact improvements will best result from purely minimising the taxi times or whether it is also important to avoid multiple acceleration phases. This paper presents a newly developed multiobjective approach for analysing the trade-off between taxi time and fuel consumption during taxiing. The approach consists of a combination of a graph-based routing algorithm and a population adaptive immune algorithm to discover different speed profiles of aircraft. Analysis with data from a European hub airport has highlighted the impressive performance of the new approach. Furthermore, it is shown that the S. Ravizza ( ) · J.A.D. Atkin School of Computer Science, University of Nottingham, Jubilee Campus, Nottingham NG8 1BB, UK e-mail: smr@cs.nott.ac.uk J.A.D. Atkin e-mail: jaa@cs.nott.ac.uk J. Chen · P. Stewart School of Engineering, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK J. Chen e-mail: juchen@lincoln.ac.uk P. Stewart e-mail: pstewart@lincoln.ac.uk E.K. Burke Department of Computing and Mathematics, University of Stirling, Cottrell Building, Stirling FK9 4LA, UK e-mail: e.k.burke@stir.ac.uk 26 S. Ravizza et al. trade-off between taxi time and fuel consumption is very sensitive to the fuel-related objective function which is used.
DangSan: Scalable Use-after-free Detection

Use-after-free vulnerabilities due to dangling pointers are an important and growing threat to systems security. While various solutions exist to address this problem, none of them is sufficiently practical for real-world adoption. Some can be bypassed by attackers, others cannot support complex multithreaded applications prone to dangling pointers, and the remainder have prohibitively high overhead. One major source of overhead is the need to synchronize threads on every pointer write due to pointer tracking.
 In this paper, we present DangSan, a use-after-free detection system that scales efficiently to large numbers of pointer writes as well as to many concurrent threads. To significantly reduce the overhead of existing solutions, we observe that pointer tracking is write-intensive but requires very few reads. Moreover, there is no need for strong consistency guarantees as inconsistencies can be reconciled at read (i.e., object deallocation) time. Building on these intuitions, DangSan's design mimics that of log-structured file systems, which are ideally suited for similar workloads. Our results show that DangSan can run heavily multithreaded applications, while introducing only half the overhead of previous multithreaded use-after-free detectors.
Reading and Interpreting Ethnography

Although ethnographic methods are still regarded, to an extent, as new aspects of HCI research practice, they have been part of HCI research almost since its inception, and certainly since the early 1980s, about the same time as the CHI conference was founded. What, then, accounts for this sense of novelty and the mystery that goes along with it? One reason is that ethnographic methods have generally been associated with what we might call non-traditional settings in relation to HCI’s cognitive science roots, emerging at first particular in organizational studies of collaborative work (in the domain of CSCW), being applied later in studies of alternative interaction patterns in ubiquitous computing, and being associated with domains such as domestic life, experience design, and cultural analysis that have been more recent arrivals on the scene. Another is that ethnographic methods are often associated with forms of analysis and theorizing of human action – ethnomethodology stands out as an example here – that are themselves alien to HCI’s intellectual traditions and which have not always been clearly explained. Indeed, debates within the field have often founded on these sorts of confusions, so that in the internecine battles amongst social theorists, ethnographic methods suffer collateral damage (e.g. Crabtree et al. 2009). Finally, in a discipline that has often proceeded with something of a mix-and-match approach, liberally and creatively borrowing ideas and elements from different places, ethnography has often been seen instrumentally as a way of understanding important aspects of technological practice while its own epistemological commitments have remained somewhat murky.
On Training Classifiers for Linking Event Templates

The paper reports on exploring various machine learning techniques and a range of textual and meta-data features to train classifiers for linking related event templates automatically extracted from online news. With the best model using textual features only we achieved 94.7% (92.9%) F1 score on GOLD (SILVER) dataset. These figures were further improved to 98.6% (GOLD) and 97% (SILVER) F1 score by adding meta-data features, mainly thanks to the strong discriminatory power of automatically extracted geographical information related to events.
A strategic integration between Agile and traditional project management approaches for a clear view on Project

This thesis seeks to better understand how a combination of different project management approaches could lead organisations to cope with project closure in more effective ways. More specifically, a coexistence of Waterfall and Agile project management is examined and presented as positive contribution to insurance and investment organisations for more effective transitions from project management to business-as-usual. A comprehensive framework combines within the theoretical chapters the hybrid approach between Agile and traditional project management for successfully closing projects. It represents the lens through which the empirical material can be analysed. The empirical work is based on a single-holistic case study of Intesa Sanpaolo Life dac, incorporating seven semi-structured interviews with the most authoritative individuals of this company in relation to the topic of this paper. This case study provides a deep insight on project closure management which is addressed by investigating challenges and highlighting effective practices of the company in question. Throughout the analysis of the data gathered, the authors managed to highlight findings which provide managerial and theoretical contributions. The originality and the value of this research is given by the fact that this work expects to enrich project-based organisations which use a combination between Agile and traditional project management and struggle to get a proper project closure and transit to the operation phase. Consequently, this represents a completely new point of view in the literature related to project management, which sees project closure as the most understudied phase of the project life-cycle.
An ultra-wideband absorber based on multiple resonators in 3-D frequency-selective structure

An ultra-wideband absorber based on employing multiple resonators in the unit cell of a 3-D frequency-selective structure is proposed. The original design consists of two-dimensional periodic array of three-dimensional unit cells and lumped components to provide matching with free space and absorb the incident electromagnetic wave. By introducing one more resonator in the unit cell, an ultra-wideband absorber can be constructed. It has a fractional bandwidth of 155.7 % for −10 dB of reflection coefficient under the normal incidence with an absorber thickness of 0.12 λ0 at the lowest absorption frequency. This absorber works for TE polarization at which two quasi-TEM modes are excited in the air and substrate regions. The proposed absorber shows a stable performance under oblique angles of incidence.
A New Prime and Probe Cache Side-Channel Attack for Cloud Computing

Cloud computing is considered one of the most dominant paradigms in the Information Technology (IT) industry nowadays. It supports multi-tenancy to fulfil future increasing demands for accessing and using resources provisioned over the Internet. However, multi-tenancy in cloud computing has unique vulnerabilities such as clients' co-residence and virtual machine physical co-residency. Physical co-residency of virtual machines can facilitate attackers with an ability to interfere with another virtual machine running on the same physical machine due to an insufficient logical isolation. In the worst scenario, attackers can exfiltrate sensitive information of victims on the same physical machine by using hardware side-channels. There are various types of side-channels attacks, which are classified according to hardware medium they target and exploit, for instance, cache side-channel attacks. CPU caches are one of the most hardware devices targeted by adversaries because it has high-rate interactions and sharing between processes. This paper presents a new Prime and Probe cache side-channel attack, which can prime physical addresses. These addresses are translated form virtual addresses used by a virtual machine. Then, time is measured to access these addresses and it will be varied according to where the data is located. If it is in the CPU cache, the time will be less than in the main memory. The attack was implemented in a server machine comparable to cloud environment servers. The results show that the attack needs less effort and time than other types and is easy to be launched.
Video surveillance robot control using smartphone and Raspberry pi

This paper proposes a method for controlling a wireless robot for surveillance using an application built on Android platform. The Android application will open a web-page which has video screen for surveillance and buttons to control robot and camera. Android Smartphone and Raspberry pi board is connected to Wi-Fi. An Android Smartphone sends a wireless command which is received by Raspberry pi board and accordingly robot moves. The Video Streaming is done using MJPG streamer program that gets mjpeg data and sends it through a HTTP session. The Raspberry pi programming is done in python language. The experimental result shows that the video streamed up to 15 frames per second.
Heterogeneity of multiple sclerosis lesions: implications for the pathogenesis of demyelination.

Multiple sclerosis (MS) is a disease with profound heterogeneity in clinical course, neuroradiological appearance of the lesions, involvement of susceptibility gene loci, and response to therapy. These features are supported by experimental evidence, which demonstrates that fundamentally different processes, such as autoimmunity or virus infection, may induce MS-like inflammatory demyelinating plaques and suggest that MS may be a disease with heterogeneous pathogenetic mechanisms. From a large pathology sample of MS, collected in three international centers, we selected 51 biopsies and 32 autopsies that contained actively demyelinating lesions defined by stringent criteria. The pathology of the lesions was analyzed using a broad spectrum of immunological and neurobiological markers. Four fundamentally different patterns of demyelination were found, defined on the basis of myelin protein loss, the geography and extension of plaques, the patterns of oligodendrocyte destruction, and the immunopathological evidence of complement activation. Two patterns (I and II) showed close similarities to T-cell-mediated or T-cell plus antibody-mediated autoimmune encephalomyelitis, respectively. The other patterns (III and IV) were highly suggestive of a primary oligodendrocyte dystrophy, reminiscent of virus- or toxin-induced demyelination rather than autoimmunity. At a given time point of the disease--as reflected in autopsy cases--the patterns of demyelination were heterogeneous between patients, but were homogenous within multiple active lesions from the same patient. This pathogenetic heterogeneity of plaques from different MS patients may have fundamental implications for the diagnosis and therapy of this disease.
An Analysis of Stochastic Shortest Path Problems

We consider a stochastic version of the classical shortest path problem whereby for each node of a graph, we must choose a probability distribution over the set of successor nodes so as to reach a certain destination node with minimum expected cost. The costs of transition between successive nodes can be positive as well as negative. We prove natural generalizations of the standard results for the deterministic shortest path problem, and we extend the corresponding theory for undiscounted finite state Markovian decision problems by removing the usual restriction that costs are either all nonnegative or all nonpositive.  Supported by the National Science Foundation under Grant NSF-ECS-8519058, the Army Research Office under Grant DAAL03-86-K-0171, and a Presidential Young Investigator Award to the second author with matching funds from IBM, Inc. and Dupont, Inc. ** Massachusetts Institute of Technology, Laboratory for Information and Decision Systems, Cambridge, Mass. 02139.
An efficient iris segmentation model based on eyelids and eyelashes detection in iris recognition system

This paper presents an efficient noise reduction scheme to remove localized high frequency information from segmented iris region for personal authentication based on radial suppression. Eyelash and eyelids of localized iris area is considered as noisy information. Accuracy of iris recognition system generally depends on accurate segmentation and noise deduction. Proposed method not only removes eyelash and eyelids by suppressing localized frequency using radial suppression but also detects the pupil and iris center accurately as well as localizes the iris and pupil region. Finally, this paper also designates a prototype of automated iris recognition system for personnel authentication. For iris feature extraction purpose, one dimensional Log Gabor wavelet has been used where the feature vector length has been reduced without less loss of Information. It has also been showed here that the proposed detection model has a stable matching score. The proposed automated iris recognition system with maximum suppression of eyelashes has less equal error rate which indicates the superiority of the performance compared to the other existing methods.
Discrimination and racial disparities in health: evidence and needed research

This paper provides a review and critique of empirical research on perceived discrimination and health. The patterns of racial disparities in health suggest that there are multiple ways by which racism can affect health. Perceived discrimination is one such pathway and the paper reviews the published research on discrimination and health that appeared in PubMed between 2005 and 2007. This recent research continues to document an inverse association between discrimination and health. This pattern is now evident in a wider range of contexts and for a broader array of outcomes. Advancing our understanding of the relationship between perceived discrimination and health will require more attention to situating discrimination within the context of other health-relevant aspects of racism, measuring it comprehensively and accurately, assessing its stressful dimensions, and identifying the mechanisms that link discrimination to health.
The self in action: Lessons from delusions of control

Patients with delusions of control are abnormally aware of the sensory consequences of their actions and have difficulty with on-line corrections of movement. As a result they do not feel in control of their movements. At the same time they are strongly aware of the action being intentional. This leads them to believe that their actions are being controlled by an external agent. In contrast, the normal mark of the self in action is that we have very little experience of it. Most of the time we are not aware of the sensory consequences of our actions or of the various subtle corrections that we make during the course of goal-directed actions. We know that we are agents and that we are successfully causing the world to change. But as actors we move through the world like shadows glimpsed only occasional from the corner of an eye.
FOR LEAP MOTION CONTROLLER

This thesis studies the new possibilities to gesture interfaces that emerged with a Leap Motion sensor. The Leap Motion is an innovative, 3D motion capturing device designed especially for hands and fingers tracking with precision up to 0.01mm. The outcome of the thesis is the LeapGesture library dedicated to the developers for Leap Motion Controller that contains algorithms allowing to learn and recognize gestures. The authors examined the data provided by the sensor in context of recognition of hand poses (static gestures), hand movements (dynamic gestures) and in task of a finger recognition. The static gestures are recognized using the Support Vector Machine (SVM) with median filtering an input data and using the correspondences between consecutive recognitions. The thesis contains evaluation of different feature sets, which have a significant impact on the recognition rate. The chosen feature set allowed to recognize a set of five gestures with 99% accuracy and a set of ten gestures with 85%. The dynamic gestures (movements of a hand and fingers) are recognized with the Hidden Markov Models (HMM). Recognition with HMMs allowed to achieve accuracy of 80% for a set containing six classes of dynamic gestures. Finger recognition algorithms proposed in this thesis works with 93% accuracy on a recorded dataset. The LeapGesture library contains presented approaches using a C++ interface, that can be easily used in any application for many purposes.
G3D: A gaming action dataset and real time action recognition evaluation framework

In this paper a novel evaluation framework for measuring the performance of real-time action recognition methods is presented. The evaluation framework will extend the time-based event detection metric to model multiple distinct action classes. The proposed metric provides more accurate indications of the performance of action recognition algorithms for games and other similar applications since it takes into consideration restrictions related to time and consecutive repetitions. Furthermore, a new dataset, G3D for real-time action recognition in gaming containing synchronised video, depth and skeleton data is provided. Our results indicate the need of an advanced metric especially designed for games and other similar real-time applications.
MS-TWSVM: Mahalanobis distance-based Structural Twin Support Vector Machine

The distribution information of data points in two classes as the structural information is inserted into the classifiers to improve their generalization performance. Recently many algorithms such as S-TWSVM has used this information to construct two nonparallel hyperplanes which each one lies as close as possible to one class and being far away from the other. It is well known that different classes have different data distribution in real world problems, thus the covariance matrices of these classes are not the same. In these situations, the Mahalanobis is often more popular than Euclidean as a measure of distance. In this paper, in addition to apply the idea of S-TWSVM, the classical Euclidean distance is replaced by Mahalanobis distance which leads to simultaneously consider the covariance matrices of the two classes. By this modification, the orientation information in two classes can be better exploited than S-TWSVM. The experiments indicate our proposed algorithm is often superior to other learning algorithms in terms of generalization performance.
Handwriting development, competency, and intervention.

Failure to attain handwriting competency during the school-age years often has far-reaching negative effects on both academic success and self-esteem. This complex occupational task has many underlying component skills that may interfere with handwriting performance. Fine motor control, bilateral and visual-motor integration, motor planning, in-hand manipulation, proprioception, visual perception, sustained attention, and sensory awareness of the fingers are some of the component skills identified. Poor handwriting may be related to intrinsic factors, which refer to the child's actual handwriting capabilities, or extrinsic factors which are related to environmental or biomechanical components, or both. It is important that handwriting performance be evaluated using a valid, reliable, standardized tool combined with informal classroom observation and teacher consultation. Studies of handwriting remediation suggest that intervention is effective. There is evidence to indicate that handwriting difficulties do not resolve without intervention and affect between 10 and 30% of school-aged children. Despite the widespread use of computers, legible handwriting remains an important life skill that deserves greater attention from educators and health practitioners.
Searching Rules of Acupuncture on Periarthritis of Shoulder by Data Slicing Algorithm

Acupuncture is an important component in traditional Chinese medicine. It is efficient in dealing with some diseases, esp. periarthritis of shoulder. In this paper, focused on periarthritis of shoulder, we mined the data set of literature with data slicing algorithm. Acupoints are calculated on two dimensions. The one-dimension calculates the frequencies of acupuncture points existed in literature. The two-dimension calculates the frequencies of acupoint pairs co-existed in literature. By examining the results, we found the sets of acupuncture points in dealing with this disease. By checking these results, not only regular acupoints in the textbook are mined out, but also some other acupoints which are widely used in the clinical practices are also found. What's more, these acupoints might be taken as complementarities for the textbook.
Analysis and Design of an Ultrabroadband Stacked Power Amplifier in CMOS Technology

This brief presents the analysis and design of a two-stage stacked power amplifier (PA) with very broadband gain frequency response and power performance in a small chip size. The broadband load impedance match is realized using modified stacked field-effect transistors (FETs) with a resistive feedback by analyzing the matching condition of the source input impedance of the stacked FET. In order to further improve the broadband gain frequency response, the effectiveness of a gain expansion from a stacked driver amplifier is demonstrated to compensate the gain compression of the last-stage amplifier. To verify the design concept, a two-stage three-stacked PA has been implemented in a 0.18-μm CMOS technology. The PA achieves a saturated output power of 22-24.3 dBm and a power added efficiency of 13%-20% within a 194% fractional bandwidth from 0.1 to 6.5 GHz. It also demonstrates better than 11-dB input return loss (RL) and better than 5.1-dB output RL. This PA occupies a chip size of 0.64 mm2 including pads.
Dual Encoding for Abstractive Text Summarization.

Recurrent neural network-based sequence-to-sequence attentional models have proven effective in abstractive text summarization. In this paper, we model abstractive text summarization using a dual encoding model. Different from the previous works only using a single encoder, the proposed method employs a dual encoder including the primary and the secondary encoders. Specifically, the primary encoder conducts coarse encoding in a regular way, while the secondary encoder models the importance of words and generates more fine encoding based on the input raw text and the previously generated output text summarization. The two level encodings are combined and fed into the decoder to generate more diverse summary that can decrease repetition phenomenon for long sequence generation. The experimental results on two challenging datasets (i.e., CNN/DailyMail and DUC 2004) demonstrate that our dual encoding model performs against existing methods.