nils-herrmann/clean_scirepeval huggingface dataset:
FADEWICH: Fast Deauthentication Over the Wireless Channel

Both authentication and deauthentication are instrumental for preventing unauthorized access to computers and other resources. While there are obvious motivating factors for using strong authentication mechanisms, convincing users to deauthenticate is not straight-forward, since deauthentication is not considered mandatory. A user who leaves a logged-in workstation unattended (especially for a short time) is typically not inconvenienced in any way; in fact, the other way around - no annoying reauthentication is needed upon return. However, an unattended workstation is trivially susceptible to the well-known "lunchtime attack" by any nearby adversary who simply takes over the departed user's log-in session. At the same time, since deauthentication does not intrinsically require user secrets, it can, in principle, be made unobtrusive. To this end, this paper designs the first automatic user deauthentication system - FADEWICH - that does not rely on biometric-or behavior-based techniques (e.g., keystroke dynamics) and does not require users to carry any devices. It uses physical properties of wireless signals and the effect of human bodies on their propagation. To assess FADEWICH's feasibility and performance, extensive experiments were conducted with its prototype. Results show that it suffices to have nine inexpensive wireless sensors deployed in a shared office setting to correctly deauthenticate all users within six seconds (90% within four seconds) after they leave their workstation's vicinity. We considered two realistic scenarios where the adversary attempts to subvert FADEWICH and showed that lunchtime attacks fail.
BER analysis over alpha-mu fading channel using proposed novel MGF

In this paper, closed-form expressions of Bit Error Rate (BER) for different modulation techniques such as BPSK, BFSK, DQPSK, BDPSK and MPSK over alpha-mu (α-μ) fading distribution are presented, followed by proposing a novel Moment Generating Function (MGF). Specifically, we have proposed ‘A Novel MGF for Alpha-mu Fading Distribution’. The proposed MGF is a modification of the MGF in Magableh and Matalgah’s (2009) article as proposed MGF is valid for all values of alpha, whereas, the MGF presented in Magableh and Matalgah’s article is valid only for non-integer values of alpha. Further, various closed-form expressions of BER using the proposed MGF are presented in this paper. Also, BER of various modulation schemes based on proposed MGF has been compared with similar results presented in Shin and Lee’s (2004) article as special case of alpha-mu distribution. This shows perfect agreement of our results with that of Shin and Lee.
The application of Safe Scrum to IEC 61508 certifiable software

In order to develop a better understanding of the application of Scrum to IEC61508 certifiable software, we assessed the standard to see how Scrum could conform. Each section of part 3 of the standard was assigned one of the categories: (1) “OK” – no modification needed to Scrum or IEC61508, (2) “?” – need to be discussed, (3) “Not OK” – need adaptation of Scrum Based on our assessment we proposed the Safe Scrum where the main idea is separation of concerns. Everything that is not part of the software development process is kept outside Scrum and will thus not be influenced by our choice of paradigm. In Safe Scrum, all requirements are split into safety critical requirements and other requirements and inserted into separate product backlogs. We then did a new assessment where we took the Safe Scrum into consideration. We found 15 issues where we need changes in order to make the process acceptable to Scrum and the safety assessors: how to structure development, plan for validating safety, create, review, select, design and ensure safety, write requirements for module testing, and test and evaluate the outputs from the safety lifecycle The first part of our model consists of the IEC61508 steps of developing the environment description and the SSRS phases 1-4. These initial steps result in the initial requirements of the system that is to be developed and is the key input to the second part of the model – the Safe Scrum process. Using an iterative and incremental approach means that the project can be continuously re-planned based on recent product experience. Between the iterations, experience can be used to re-prioritize the product backlogs. This makes the process flexible. When the sprints are completed, a final RAMS validation will be done. Since most of the system has been incrementally validated during the sprints, we expect the final RAMS validation to be less extensive than when using other development paradigms. This will also help us to reduce the time and cost needed for certification.
State-based decoding of hand and finger kinematics using neuronal ensemble and LFP activity during dexterous reach-to-grasp movements.

The performance of brain-machine interfaces (BMIs) that continuously control upper limb neuroprostheses may benefit from distinguishing periods of posture and movement so as to prevent inappropriate movement of the prosthesis. Few studies, however, have investigated how decoding behavioral states and detecting the transitions between posture and movement could be used autonomously to trigger a kinematic decoder. We recorded simultaneous neuronal ensemble and local field potential (LFP) activity from microelectrode arrays in primary motor cortex (M1) and dorsal (PMd) and ventral (PMv) premotor areas of two male rhesus monkeys performing a center-out reach-and-grasp task, while upper limb kinematics were tracked with a motion capture system with markers on the dorsal aspect of the forearm, hand, and fingers. A state decoder was trained to distinguish four behavioral states (baseline, reaction, movement, hold), while a kinematic decoder was trained to continuously decode hand end point position and 18 joint angles of the wrist and fingers. LFP amplitude most accurately predicted transition into the reaction (62%) and movement (73%) states, while spikes most accurately decoded arm, hand, and finger kinematics during movement. Using an LFP-based state decoder to trigger a spike-based kinematic decoder [r = 0.72, root mean squared error (RMSE) = 0.15] significantly improved decoding of reach-to-grasp movements from baseline to final hold, compared with either a spike-based state decoder combined with a spike-based kinematic decoder (r = 0.70, RMSE = 0.17) or a spike-based kinematic decoder alone (r = 0.67, RMSE = 0.17). Combining LFP-based state decoding with spike-based kinematic decoding may be a valuable step toward the realization of BMI control of a multifingered neuroprosthesis performing dexterous manipulation.
A Performance and Scalability Analysis of Actor Message Passing and Migration in SALSA Lite

This paper presents a newly developed implementation of remote message passing, remote actor creation and actor migration in SALSA Lite. The new runtime and protocols are implemented using SALSA Lite’s lightweight actors and asynchronous message passing, and provide significant performance improvements over SALSA version 1.1.5. Actors in SALSA Lite can now be local, the default lightweight actor implementation; remote, actors which can be referenced remotely and send remote messages, but cannot migrate; or mobile, actors that can be remotely referenced, send remote messages and migrate to different locations. Remote message passing in SALSA Lite is twice as fast, actor migration is over 17 times as fast, and remote actor creation is two orders of magnitude faster. Two new benchmarks for remote message passing and migration show this implementation has strong scalability in terms of concurrent actor message passing and migration. The costs of using remote and mobile actors are also investigated. For local message passing, remote actors resulted in no overhead, and mobile actors resulted in 30% overhead. Local creation of remote and mobile actors was more expensive with 54% overhead for remote actors and 438% for mobile actors. In distributed scenarios, creating mobile actors remotely was only 6% slower than creating remote actors remotely, and passing messages between mobile actors on different theaters was only 5.55% slower than passing messages between remote actors. These results highlight the benefits of our approach in implementing the distributed runtime over a core set of efficient lightweight actors, as well as provide insights into the costs of implementing remote message passing and actor mobility.
Alar setback technique: a controlled method of nasal tip deprojection.

To describe an alar cartilage-modifying technique aimed at decreasing nasal tip projection in cases with overdeveloped alar cartilages and to compare it with other deprojection techniques used to correct such deformity.



Selected case series.



University and private practice settings in Alexandria, Egypt.



Twenty patients presenting for rhinoplasty who had overprojected nasal tips primarily due to overdeveloped alar cartilages. All cases were primary cases except for one patient, who had undergone 2 previous rhinoplasties.



An external rhinoplasty approach was used to set back the alar cartilages by shortening their medial and lateral crura. The choice of performing a high or low setback depended on the preexisting lobule-to-columella ratio. Following the setback, the alar cartilages were reconstructed in a fashion that increased the strength and stability of the tip complex.



Subjective evaluation included clinical examination, analysis of preoperative and postoperative photographs, and patient satisfaction. Objective evaluation of nasal tip projection, using the Goode ratio and the nasofacial angle, was performed preoperatively and repeated at least 6 months postoperatively.



A low setback was performed in 16 cases (80%) and a high setback in 4 (20%). The mean follow-up period was 18 months (range, 6-36 months). The technique effectively deprojected the nasal tip as evidenced by the considerable postoperative decrease in values of the Goode ratio and the nasofacial angle. No complications were encountered and no revision surgical procedures were required.



The alar setback technique has many advantages; it results in precise predictable amounts of deprojection, controls the degree of tip rotation, preserves the natural contour of the nasal tip, respects the tip support mechanisms, increases the strength and stability of nasal tip complex, preserves or restores the normal lobule-to-columella proportion, and does not lead to alar flaring. However, the technique requires an external rhinoplasty approach and fine technical precision.
Collection and comparison of driver/passenger physiologic and behavioural data in simulation and on-road driving

The i.Drive Lab has developed inter-disciplinary methodology for the analysis and modelling of behavioral and physiological responses related to the interaction between driver, vehicle, infrastructure, and virtual environment. The present research outlines the development of a validation study for the combination of virtual and real-life research methodologies. i.Drive driving simulator was set up to replicate the data acquisition of environmental and physiological information coming from an equipped i.Drive electric vehicle with same sensors. i.Drive tests are focused on the identification of driver's affective states that are able to define recurring situations and psychophysical conditions that are relevant for road-safety and drivers' comfort. Results show that it is possible to combine different research paradigms to collect low-level vehicle control behavior and higher-level cognitive measures, in order to develop data collection and elaboration for future mobility challenges.
A Wearable Two-Antenna System on a Life Jacket for Cospas-Sarsat Personal Locator Beacons

A wearable two-antenna system to be integrated on a life jacket and connected to Personal Locator Beacons (PLBs) of the Cospas-Sarsat system is presented. Each radiating element is a folded meandered dipole resonating at 406 MHz and includes a planar reflector realized by a metallic foil. The folded dipole and the metallic foil are attached on the opposite sides of the floating elements of the life jacket itself, so resulting in a mechanically stable antenna. The metallic foil improves antenna radiation properties even when the latter is close to the sea surface, shields the human body from EM radiation and makes the radiating system less sensitive to the human body movements. Prototypes have been realized and a measurement campaign has been carried out. The antennas show satisfactory performance also when the life jacket is worn by a user. The proposed radiating elements are intended for the use in a two-antenna scheme in which the transmitter can switch between them in order to meet Cospas-Sarsat system specifications. Indeed, the two antennas provide complementary radiation patterns so that Cospas-Sarsat requirements (satellite constellation coverage and EIRP profile) are fully satisfied.
Resting-state networks distinguish locked-in from vegetative state patients☆

Locked-in syndrome and vegetative state are distinct outcomes from coma. Despite their differences, they are clinically difficult to distinguish at the early stage and current diagnostic tools remain insufficient. Since some brain functions are preserved in locked-in syndrome, we postulated that networks of spontaneously co-activated brain areas might be present in locked-in patients, similar to healthy controls, but not in patients in a vegetative state.



Five patients with locked-in syndrome, 12 patients in a vegetative state and 19 healthy controls underwent a resting-state fMRI scan. Individual spatial independent component analysis was used to separate spontaneous brain co-activations from noise. These co-activity maps were selected and then classified by two raters as either one of eight resting-state networks commonly shared across subjects or as specific to a subject.



The numbers of spontaneous co-activity maps, total resting-state networks, and resting-state networks underlying high-level cognitive activity were shown to differentiate controls and locked-in patients from patients in a vegetative state. Analyses of each common resting-state network revealed that the default mode network accurately distinguished locked-in from vegetative-state patients. The frontoparietal network also had maximum specificity but more limited sensitivity.



This study reinforces previous reports on the preservation of the default mode network in locked-in syndrome in contrast to vegetative state but extends them by suggesting that other networks might be relevant to the diagnosis of locked-in syndrome. The aforementioned analysis of fMRI brain activity at rest might be a step in the development of a diagnostic biomarker to distinguish locked-in syndrome from vegetative state.
'Viral' Turing Machines, Computation from Noise and Combinatorial Hierarchies

The interactive computation paradigm is reviewed and a particular example is extended to form the stochastic analog of a computational process via a transcription of a minimal Turing Machine into an equivalent asynchronous Cellular Automaton with an exponential waiting times distribution of effective transitions. Furthermore, a special toolbox for analytic derivation of recursive relations of important statistical and other quantities is introduced in the form of an Inductive Combinatorial Hierarchy.
Revealing Alzheimer’s disease genes spectrum in the whole-genome by machine learning

Alzheimer's disease (AD) is an important, progressive neurodegenerative disease, with a complex genetic architecture. A key goal of biomedical research is to seek out disease risk genes, and to elucidate the function of these risk genes in the development of disease. For this purpose, expanding the AD-associated gene set is necessary. In past research, the prediction methods for AD related genes has been limited in their exploration of the target genome regions. We here present a genome-wide method for AD candidate genes predictions.



We present a machine learning approach (SVM), based upon integrating gene expression data with human brain-specific gene network data, to discover the full spectrum of AD genes across the whole genome.



We classified AD candidate genes with an accuracy and the area under the receiver operating characteristic (ROC) curve of 84.56% and 94%. Our approach provides a supplement for the spectrum of AD-associated genes extracted from more than 20,000 genes in a genome wide scale.



In this study, we have elucidated the whole-genome spectrum of AD, using a machine learning approach. Through this method, we expect for the candidate gene catalogue to provide a more comprehensive annotation of AD for researchers.
Discovering author impact: A PageRank perspective

This article provides an alternative perspective for measuring author impact by applying PageRank algorithm to a coauthorship network. A weighted PageRank algorithm considering citation and coauthorship network topology is proposed. We test this algorithm under different damping factors by evaluating author impact in the informetrics research community. In addition, we also compare this weighted PageRank with the h-index, citation, and program committee (PC) membership of the International Society for Scientometrics and Informetrics (ISSI) conferences. Findings show that this weighted PageRank algorithm provides reliable results in measuring author impact.
Rolling Guidance Filter

Images containmany levels of important structures and edges. Compared to masses of research to make filters edge preserving, finding scale-aware local operations was seldom addressed in a practical way, albeit similarly vital in image processing and computer vision. We propose a new framework to filter images with the complete control of detail smoothing under a scale measure. It is based on a rolling guidance implemented in an iterative manner that converges quickly. Ourmethod is simple in implementation, easy to understand, fully extensible to accommodate various data operations, and fast to produce results. Our implementation achieves realtime performance and produces artifact-free results in separating different scale structures. This filter also introduces several inspiring properties different from previous edge-preserving ones.
Understanding and leveraging social networks for crowdfunding: opportunities and challenges

Crowdfunding provides a new way for creatives to share their work and acquire resources from their social network to influence what new ideas are realized. Yet, we understand very little about this growing phenomenon. Grounded in existing work on social network analysis, we interview 58 crowdfunding project creators to investigate how crowdfunders use their social network to reach their campaign goals. We identified three main challenges, which include understanding network capabilities, activating network connections, and expanding network reach. From our findings, we develop initial design implications for support tools to help crowdfunding project creators better understand and leverage their social network.
Sex, trauma, stress hormones and depression

Although few studies dispute that there are gender differences in depression, the etiology is still unknown. In this review, we cover a number of proposed factors and the evidences for and against these factors that may account for gender differences in depression. These include the possible role of estrogens at puberty, differences in exposure to childhood trauma, differences in stress perception between men and women and the biological differences in stress response. None of these factors seem to explain gender differences in depression. Finally, we do know that when depressed, women show greater hypothalamic–pituitary–adrenal (HPA) axis activation than men and that menopause with loss of estrogens show the greatest HPA axis dysregulation. It may be the constantly changing steroid milieu that contributes to these phenomena and vulnerability to depression.
Correlation between Business Process Management and Organizational Performance : A Study of Bank X

Business process management is multidimensional tool which utilizes several methods to examine processes from a holistic perspective, transcending the narrow borders of specific functions. It undertakes fundamental reconsideration and radical redesign of organizational processes in order to achieve drastic improvement of current performance in terms of cost, service and speed. Business process management tries to encourage a radical change rather than an incremental change. An analytical approach has been applied for the current study. For this study, the case of Bank X, which is a leading public sector bank operating in the state, has been taken into consideration. A sample of 250 customers was selected randomly from Alwar, Dausa and Bharatpur districts. For policy framework, corporate headquarters were consulted. For the research a self-designed survey instrument, looking for information from the customers on several parameters like cost, quality, services and performance, was used. This article tries to take a critical account of existent business process management in Bank X and to study the relationship between business process management and organizational performance. The data has been tested by correlation analysis. The findings of the study show that business process management exists in the Bank X and there is a significant relationship between business process management and organizational performance. Business Process Management; Business Process Reengineering; Organizational Performance
Phase Conductor on Multi-layered Attentions for Machine Comprehension

Attention models have been intensively studied to improve NLP tasks such as machine comprehension via both question-aware passage attention model and selfmatching attention model. Our research proposes phase conductor (PhaseCond) for attention models in two meaningful ways. First, PhaseCond, an architecture of multi-layered attention models, consists of multiple phases each implementing a stack of attention layers producing passage representations and a stack of inner or outer fusion layers regulating the information flow. Second, we extend and improve the dot-product attention function for PhaseCond by simultaneously encoding multiple question and passage embedding layers from different perspectives. We demonstrate the effectiveness of our proposed model PhaseCond on the SQuAD dataset, showing that our model significantly outperforms both stateof-the-art single-layered and multiple-layered attention models. We deepen our results with new findings via both detailed qualitative analysis and visualized examples showing the dynamic changes through multi-layered attention models.