nils-herrmann/clean_scirepeval huggingface dataset:
IMSI-catch me if you can: IMSI-catcher-catchers

IMSI Catchers are used in mobile networks to identify and eavesdrop on phones. When, the number of vendors increased and prices dropped, the device became available to much larger audiences. Self-made devices based on open source software are available for about US$ 1,500.
 In this paper, we identify and describe multiple methods of detecting artifacts in the mobile network produced by such devices. We present two independent novel implementations of an IMSI Catcher Catcher (ICC) to detect this threat against everyone's privacy. The first one employs a network of stationary (sICC) measurement units installed in a geographical area and constantly scanning all frequency bands for cell announcements and fingerprinting the cell network parameters. These rooftop-mounted devices can cover large areas. The second implementation is an app for standard consumer grade mobile phones (mICC), without the need to root or jailbreak them. Its core principle is based upon geographical network topology correlation, facilitating the ubiquitous built-in GPS receiver in today's phones and a network cell capabilities fingerprinting technique. The latter works for the vicinity of the phone by first learning the cell landscape and than matching it against the learned data. We implemented and evaluated both solutions for digital self-defense and deployed several of the stationary units for a long term field-test. Finally, we describe how to detect recently published denial of service attacks.
Pilot study: Investigating the effects of Kinesio Taping® on functional activities in children with cerebral palsy.

To investigate the immediate effects of Kinesio Taping® (KT) on sit-to-stand (STS) movement, balance and dynamic postural control in children with cerebral palsy (CP).



Four children diagnosed with left hemiplegic CP level I by the Gross Motor Function Classification System were evaluated under conditions without taping as control condition (CC); and with KT as kinesio condition. A motion analysis system was used to measure total duration of STS movement and angular movements of each joint. Clinical instruments such as Pediatric Balance Scale (PBS) and Timed up and Go (TUG) were also applied.



Compared to CC, decreased total duration of STS, lower peak ankle flexion, higher knee extension at the end of STS, and decreased total time in TUG; but no differences were obtained on PBS score in KT.



Neuromuscular taping seems to be beneficial on dynamic activities, but not have the same performance in predominantly static activities studied.
An empirical framework for defect prediction using machine learning techniques with Android software

Software defect prediction is important for identification of defect-prone parts of a software. Defect prediction models can be developed using software metrics in combination with defect data for predicting defective classes. Various studies have been conducted to find the relationship between software metrics and defect proneness, but there are few studies that statistically determine the effectiveness of the results.  The main objectives of the study are (i) comparison of the machine-learning techniques using data sets obtained from popular open source software (ii) use of appropriate performance measures for measuring the performance of defect prediction models (iii) use of statistical tests for effective comparison of machine-learning techniques and (iv) validation of models over different releases of data sets.  In this study we use object-oriented metrics for predicting defective classes using 18 machinelearning techniques. The proposed framework has been applied to seven application packages of well known, widely used Android operating system viz. Contact, MMS, Bluetooth, Email, Calendar, Gallery2 and Telephony. The results are validated using 10-fold and inter-release validation methods. The reliability and significance of the results are evaluated using statistical test and post-hoc analysis.  The results show that the area under the curve measure for Naïve Bayes, LogitBoost and Multilayer Perceptron is above 0.7 in most of the cases. The results also depict that the difference between the ML techniques is statistically significant. However, it is also proved that the Support Vector Machines based techniques such as Support Vector Machines and voted perceptron do not possess the predictive capability for predicting defects.  The results confirm the predictive capability of various ML techniques for developing defect prediction models. The results also confirm the superiority of one ML technique over the other ML techniques. Thus, the software engineers can use the results obtained from this study in the early phases of the software development for identifying defect-prone classes of given software.
Trauma and suicide behaviour histories among a Canadian indigenous population: an empirical exploration of the potential role of Canada's residential school system.

It has been theorized that suicide behaviours amongst indigenous peoples may be an outcome of mass trauma experienced as a result of colonization. In Canada, qualitative evidence has suggested that the Indian Residential School System set in motion a cycle of trauma, with some survivors reporting subsequent abuse, suicide, and other related behaviours. It has been further postulated that the effects of trauma can also be passed inter-generationally. Today, there are four generations of Canadian First Nations residential school survivors who may have transmitted the trauma they experienced to their own children and grandchildren. No empirical study has ever been undertaken to demonstrate this dynamic. This study is therefore the first to investigate whether a direct or indirect exposure to Canada's residential school system is associated with trauma and suicide behaviour histories. Data were collected in 2002/2003 from a representative sample of Manitoba, Canada, First Nations adults (N = 2953), including residential (N = 611) and non-residential school attendees (N = 2342). Regression analyses showed that for residential school attendees negative experiences in residential school were associated with a history of abuse, and that this history and being of younger age was associated with a history of suicide thoughts, whereas abuse history only was associated with a history of suicide attempts. For First Nations adults who did not attend a residential school, we found that age 28-44, female sex, not having a partner, and having a parent or grandparent who attended a residential school was associated with a history of abuse. This history, along with age and having had a parent or grandparent who attended residential school was associated with a history of suicide thoughts and attempts. In conclusion, this is the first study to empirically demonstrate, at the population level, the mental health impact of the residential school system on survivors and their children.
Factors contributing to the rapid rise of caesarean section: a prospective study of primiparous Chinese women in Shanghai

To identify factors contributing to the rapid rise of caesarean section in Shanghai through the prospective observation of changes in the preferred mode of delivery in pregnancy among primiparous Chinese women.



Prospective study.



Two general hospitals in Shanghai.



A cohort of 832 low-risk primiparous women participated in the investigation from 2010-2012 three consecutive times, from their second to third trimester and, finally, 1-2 days post partum.



Participants were interviewed, using standard questionnaires, for information on demographic characteristics, maternal childbirth self-efficacy, their preference of delivery mode before childbirth and on the people most influential to them when making decisions on delivery mode. Caesarean section indications in the medical records were extracted by the investigators and assessed against clinical guidelines. Caesarean sections were categorised into three groups: guideline-defined indications, doctor-defined indications and maternal request.



Preferred mode of delivery; indications for caesarean section; actual mode of delivery; determinants of caesarean section.



Of 832 pregnant women enrolled, 13.2% preferred caesarean section in the second trimester. This figure rose to 17.0% in the third trimester among 599 followed women. Of 523 women completing all three interviews, 58.1% underwent caesarean section. However, 34.9% of women undergoing caesarean section did not have any indications listed in the clinical guidelines nor based on maternal request. Multinomial regression analysis showed that doctors' influence was one of the significant risk factors of undergoing caesarean section, with doctor-defined indications. Participants with low maternal childbirth self-efficacy were more likely to request caesarean sections themselves.



When deciding to deliver via caesarean section without justified clinical indications in the guideline, Chinese doctors played an important role in decision-making. Among primiparous Chinese women, decisions to use caesarean sections were often made during the third trimester or during the process of labour.
The State of the Art in Visualizing Dynamic Graphs

Dynamic graph visualization focuses on the challenge of representing the evolution of relationships between entities in readable, scalable, and effective diagrams. This work surveys the growing number of approaches in this discipline. We derive a hierarchical taxonomy of techniques by systematically categorizing and tagging publications. While static graph visualizations are often divided into node-link and matrix representations, we identify the representation of time as the major distinguishing feature for dynamic graph visualizations: either graphs are represented as animated diagrams or as static charts based on a timeline. Evaluations of animated approaches focus on dynamic stability for preserving the viewer’s mental map or, in general, compare animated diagrams to timeline-based ones. Finally, we identify and discuss challenges for future research.
Linking Virtual Machine Mobility to User Mobility

Cloud applications heavily rely on the network communication infrastructure, whose stability and latency directly affect the quality of experience. As mobile devices need to rapidly retrieve data from the cloud, it becomes an extremely important goal to deliver the lowest possible access latency at the best reliability. In this paper, we specify a cloud access overlay protocol architecture to improve the cloud access performance in distributed data-center (DC) cloud fabrics. We explore how linking virtual machine (VM) mobility and routing to user mobility can compensate performance decrease due to increased user-cloud network distance, by building an online cloud scheduling solution to optimally switch VM routing locators and to relocate VMs across DC sites, as a function of user-DC overlay network states. We evaluate our solution: 1) on a real distributed DC testbed spanning all of France, showing that we can grant a very high transfer time gain and 2) by emulating the situation of Internet service providers (ISPs) and over-the-top (OTT) cloud providers, exploiting thousands of real France-wide user displacement traces, finding a median throughput gain from 30% for OTT scenarii to 40% for ISP scenarii, the large majority of this gain being granted by adaptive VM mobility.
CHECK-THEN-ACT Misuse of Java Concurrent Collections

Concurrent collections provide thread-safe, highly-scalable operations, and are widely used in practice. However, programmers can misuse these concurrent collections when composing two operations where a check on the collection (such as non-emptiness) precedes an action (such as removing an entry). Unless the whole composition is atomic, the program contains an atomicity violation bug. In this paper we present the first empirical study of CHECK-THEN-ACT idioms of Java concurrent collections in a large corpus of open-source applications. We catalog nine commonly misused CHECK-THEN-ACT idioms and show the correct usage. We quantitatively and qualitatively analyze 28 widely-used open source Java projects that use Java concurrency collections - comprising 6.4M lines of code. We classify the commonly used idioms, the ones that are the most error-prone, and the evolution of the programs with respect to misused idioms. We implemented a tool, CTADetector, to detect and correct misused CHECK-THEN-ACT idioms. Using CTADetector we found 282 buggy instances. We reported 155 to the developers, who examined 90 of them. The developers confirmed 60 as new bugs and accepted our patch. This shows that CHECK-THEN-ACT idioms are commonly misused in practice, and correcting them is important.
Rendering Subdivision Surfaces using Hardware Tessellation

Computer-generated images are an essential part of today's life where an increasing demand for richer images requires more and more visual detail. e quality of resulting images is strongly dependent on the representation of the underlying surface geometry. is is particularly important in the movie industry where subdivision surfaces have evolved into an industry standard. While subdivision surfaces provide artists with a sophisticated level of exibility for modeling, the corresponding image generation is computationally expensive. For this reason, movie productions perform rendering offline on large-scale render farms. In this thesis we present techniques that facilitate the use of high-quality movie content in real-time applications that run on commodity desktop computers. We utilize modern graphics hardware and use hardware tessellation to generate surface geometry on-they based on patches. e key advantage of hardware tessellation is the ability to generate geometry on-chip and to rasterize obtained polygons directly, thus minimizing memory I/O and enabling cost-effective animations since only patch control points need to be updated every frame. We rst convert subdivision surfaces into patch primitives that can be processed by the tessellation unit. en patches are directly evaluated rather than by iterative subdivision. In addition, we add highfrequency surface detail on top of a base surface by using an analytic displacement function. Both displaced surface positions and corresponding normals are obtained from this function and the underlying subdivision surface. We further present techniques to speed up rendering by culling hidden patches, thus avoiding unnecessary computations. For interaction amongst objects themselves we also present a method that performs collision detection on hardware-tessellated dynamic objects. In conclusion, we provide a comprehensive solution for using subdivision surfaces in realtime applications. We believe that the next generation of games and authoring tools will bene t from our techniques in order to allow for rendering and animating highly detailed surfaces.
What Influences Consumers ’ Intention to Use Mobile Payments ?

Mobile payments represent an extremely interesting paradox in the world of mobile telecommunications, still not showing success in most markets. Customer acceptance turned out to be a decisive factor. In order to gain a deeper understanding of consumer behavior this paper introduces a consumer acceptance model that addresses perceived usefulness, perceived ease of use, subjective security, and task-technology fit. Our empirical research was conducted online operating as a mix between an experiment and an online survey instrument to measure the constructs. The research (N = 1104) confirms findings from technology acceptance and task-technology fit literature, whereas subjective security was not confirmed as driver of mobile payment acceptance.
Comparison between the unscented Kalman filter and the extended Kalman filter for the position estimation module of an integrated navigation information system

An integrated navigation information system must know continuously the current position with a good precision. The required performance of the positioning module is achieved by using a cluster of heterogeneous sensors whose measurements are fused. The most popular data fusion method for positioning problems is the extended Kalman filter. The extended Kalman filter is a variation of the Kalman filter used to solve non-linear problems. Recently, an improvement to the extended Kalman filter has been proposed, the unscented Kalman filter. This paper describes an empirical analysis evaluating the performances of the unscented Kalman filter and comparing them with the extended Kalman filter's performances.
Website quality impact on customers' purchase intention through social commerce website

Social Commerce as a result of the advancement of Social Networking Sites and Web 2.0 is increasing as a new model of online shopping. With techniques to improve the website using AJAX, Adobe Flash, XML, and RSS, Social Media era has changed the internet user behavior to be more communicative and active in internet, they love to share information and recommendation among communities. Social commerce also changes the way people shopping through online. Social commerce will be the new way of online shopping nowadays. But the new challenge is business has to provide the interactive website yet interesting website for internet users, the website should give experience to satisfy their needs. This purpose of research is to analyze the website quality (System Quality, Information Quality, and System Quality) as well as interaction feature (communication feature) impact on social commerce website and customers purchase intention. Data from 134 customers of social commerce website were used to test the model. Multiple linear regression is used to calculate the statistic result while confirmatory factor analysis was also conducted to test the validity from each variable. The result shows that website quality and communication feature are important aspect for customer purchase intention while purchasing in social commerce website.
Unsupervised Feature Selection on Networks: A Generative View

In the past decade, social and information networks have become prevalent, and research on the network data has attracted much attention. Besides the link structure, network data are often equipped with the content information (i.e, node attributes) that is usually noisy and characterized by high dimensionality. As the curse of dimensionality could hamper the performance of many machine learning tasks on networks (e.g., community detection and link prediction), feature selection can be a useful technique for alleviating such issue. In this paper, we investigate the problem of unsupervised feature selection on networks. Most existing feature selection methods fail to incorporate the linkage information, and the state-of-the-art approaches usually rely on pseudo labels generated from clustering. Such cluster labels may be far from accurate and can mislead the feature selection process. To address these issues, we propose a generative point of view for unsupervised features selection on networks that can seamlessly exploit the linkage and content information in a more effective manner. We assume that the link structures and node content are generated from a succinct set of high-quality features, and we find these features through maximizing the likelihood of the generation process. Experimental results on three real-world datasets show that our approach can select more discriminative features than state-of-the-art methods.
Design, fabrication, and implementation of self-sealing suction cup arrays for grasping

Suction cups have long been used as a means to grasp and manipulate objects. They enable active control of grasp, enhance grasp stability, and handle some objects such as large flat plates more easily than standard graspers. However, the application of suction cups to object manipulation has been confined to a relatively small, well-defined problem set. Their potential for grasping a large range of unknown objects remains relatively unexplored. This seems in part due to the complexity involved with the design and fabrication of various materials comprising the grasper as well as actuators used to enable grasping. This paper introduces the design of a suction cup that is “self-selecting.” In other words, the suction cups comprising the grasper do not exert any suction force when the cup(s) are not in contact with the object, but instead exert a suction force only when they are in physical contact with the object. Since grasping is achieved purely by passive means, the cost and weight associated with individual sensors, valves, and/or actuators are essentially eliminated. Furthermore, the design permits the use of a central vacuum pump, thereby maximizing the suction force on an object and enabling some suction on surfaces that may prohibit tight seals. This paper presents the design, analysis, fabrication, and experimental results of such a “self-selecting” suction cup array.
How well are hypertension, hyperlipidemia, diabetes, and smoking managed after a stroke or transient ischemic attack?

Stroke prevention clinics (SPCs) are not usually involved with the active management of hypertension, hyperlipidemia, diabetes, and smoking. The effect of consultations generated at SPCs on the adequacy of the management of these risk factors for stroke has not been well described, and few studies have long-term follow-up.



We performed a prospective study of 119 consecutive patients referred to an SPC for secondary prevention. One year after their baseline visit, patients were re-evaluated for the adequacy of the management of the above risk factors, and the proportion of improvement was assessed.



One-hundred twelve patients returned for their 1-year follow-up visit. Sixty-six were male, and the average age was 65 years. Hypertension was present in 83 patients, hyperlipidemia in 92, diabetes in 26, and smoking in 38, and 80 had multiple risk factors. At baseline, 66% of patients with hypertension, 17% of patients with hyperlipidemia, and 23% of diabetics had adequate management of their respective risk factors. During 1 year of follow-up, hypertension management improved 20% (P<0.001) and lipid management improved 32% (P<0.001). There was no significant improvement in diabetes management or smoking cessation.



Although our understanding of the benefit of addressing hypertension, hyperlipidemia, diabetes, and smoking for secondary prevention of stroke is evolving, we found marked room for improvement in the management of these four risk factors. SPCs may need to be more actively involved in the management of these modifiable risk factors, if we are to significantly impact the risk of recurrent stroke.
The hippocampus as a "stupid," domain-specific module: Implications for theories of recent and remote memory, and of imagination.

The hippocampus and surrounding regions of the medial temporal lobe play a central role in all neuropsychological theories of memory. It is still a matter of debate, however, how best to characterise the functions of these regions, the hippocampus in particular. In this article, I examine the proposal that the hippocampus is a "stupid" module whose specific domain is consciously apprehended information. A number of interesting consequences for the organisation of memory and the brain follow from this proposal and the assumptions it entails. These, in turn, have important implications for neuropsychological theories of recent and remote episodic, semantic, and spatial memory and for the functions that episodic memory may serve in perception, comprehension, planning, imagination, and problem solving. I consider these implications by selectively reviewing the literature and primarily drawing on research my collaborators and I have conducted.