nils-herrmann/clean_scirepeval huggingface dataset:
The Expression of Conflict in Computer-Mediated and Face-To-Face Groups

can be found at: Small Group Research Additional services and information for http://sgr.sagepub.com/cgi/alerts  Email Alerts: http://sgr.sagepub.com/subscriptions  Subscriptions: http://www.sagepub.com/journalsReprints.nav Reprints: http://www.sagepub.com/journalsPermissions.nav Permissions: http://sgr.sagepub.com/cgi/content/refs/33/4/439 SAGE Journals Online and HighWire Press platforms): (this article cites 25 articles hosted on the Citations
Tree Structured Data Analysis : AID , CHAID and CART

Classification and regression trees are becoming increasingly popular for partitioning data and identifying local structure in small and large datasets. Classification trees include those models in which the dependent variable (the predicted variable) is categorical. Regression trees include those in which it is continuous. This paper discusses pitfalls in the use of these methods and highlights where they are especially suitable. Paper presented at the 1992 Sun Valley, ID, Sawtooth/SYSTAT Joint Software Conference.
Detection of bone fractures using image processing techniques and artificial neural networks

The use of computer technology in medical sciences is spreading with technology. The use of computers especially for imaging has become a third eye for physicians. In orthopedic surgeons, after simple roentgenograms for fracture detection, the use of computerized tomography and magnetic resonance has provided great convenience in the detection of fracture, typing, and therefore the appropriate treatment of the patient. The advancing technology has increased the quality of the images in the x-rayograms, reduced artifacts and enabled digital measurements. In this study, image processing and learning techniques were used to diagnose long bone fractures. The proposed artificial neural network has 89% success rate.
Lay Theories About White Racists : What Constitutes Racism ( and What Doesn ’ t )

Psychological theories of racial bias assume a pervasive motivation to avoid appearing racist, yet researchers know little regarding laypeople’s theories about what constitutes racism. By investigating lay theories of White racism across both college and community samples, we seek to develop a more complete understanding of the nature of race-related norms, motivations, and processes of social perception in the contemporary United States. Factor analyses in Studies 1 and 1a indicated three factors underlying the traits laypeople associate with White racism: evaluative, psychological, and demographic. Studies 2 and 2a revealed a three-factor solution for behaviors associated with White racism: discomfort/unfamiliarity, overt racism, and denial of problem. For both traits and behaviors, lay theories varied by participants’ race and their race-related attitudes and motivations. Specifically, support emerged for the prediction that lay theories of racism reflect a desire to distance the self from any aspect of the category ‘racist’.
A Deep Learning Approach to Network Intrusion Detection

Network intrusion detection systems (NIDSs) play a crucial role in defending computer networks. However, there are concerns regarding the feasibility and sustainability of current approaches when faced with the demands of modern networks. More specifically, these concerns relate to the increasing levels of required human interaction and the decreasing levels of detection accuracy. This paper presents a novel deep learning technique for intrusion detection, which addresses these concerns. We detail our proposed nonsymmetric deep autoencoder (NDAE) for unsupervised feature learning. Furthermore, we also propose our novel deep learning classification model constructed using stacked NDAEs. Our proposed classifier has been implemented in graphics processing unit (GPU)-enabled TensorFlow and evaluated using the benchmark KDD Cup ’99 and NSL-KDD datasets. Promising results have been obtained from our model thus far, demonstrating improvements over existing approaches and the strong potential for use in modern NIDSs.
Data Flow Analysis and Visualization for Spatiotemporal Statistical Data without Trajectory Information

Geographic visualization research has focused on a variety of techniques to represent and explore spatiotemporal data. The goal of those techniques is to enable users to explore events and interactions over space and time in order to facilitate the discovery of patterns, anomalies and relationships within the data. However, it is difficult to extract and visualize data flow patterns over time for non-directional statistical data without trajectory information. In this work, we develop a novel flow analysis technique to extract, represent, and analyze flow maps of non-directional spatiotemporal data unaccompanied by trajectory information. We estimate a continuous distribution of these events over space and time, and extract flow fields for spatial and temporal changes utilizing a gravity model. Then, we visualize the spatiotemporal patterns in the data by employing flow visualization techniques. The user is presented with temporal trends of geo-referenced discrete events on a map. As such, overall spatiotemporal data flow patterns help users analyze geo-referenced temporal events, such as disease outbreaks, crime patterns, etc. To validate our model, we discard the trajectory information in an origin-destination dataset and apply our technique to the data and compare the derived trajectories and the original. Finally, we present spatiotemporal trend analysis for statistical datasets including twitter data, maritime search and rescue events, and syndromic surveillance.
Agile Development and User Experience Design Integration as an Ongoing Achievement in Practice

Little is known about how Agile developers and UX designers integrate their work on a day-to-day basis. While accounts in the literature attempt to integrate Agile development and UX design by combining their processes and tools, the contradicting claims found in the accounts complicate extracting advice from such accounts. This paper reports on three ethnographically-informed field studies of the day-today practice of developers and designers in organisational settings. Our results show that integration is achieved in practice through (1) mutual awareness, (2) expectations about acceptable behaviour, (3) negotiating progress and (4) engaging with each other. Successful integration relies on practices that support and maintain these four aspects in the day-to-day work of developers and designers.
Knock-Knock: The unbearable lightness of Android Notifications

Android Notifications can be considered as essential parts in Human-Smartphone interaction and inextricable modules of modern mobile applications that can facilitate User Interaction and improve User Experience. This paper presents how this well-crafted and thoroughly documented mechanism, provided by the OS can be exploited by an adversary. More precisely, we present attacks that result either in forging smartphone application notifications to lure the user in disclosing sensitive information, or manipulate Android Notifications to launch a Denial of Service attack to the users’ device, locally and remotely, rendering them unusable. This paper concludes by proposing generic countermeasures for the discussed security threats.
IL-6 as a keystone cytokine in health and disease

Interleukin 6 (IL-6) has a broad effect on cells of the immune system and those not of the immune system and often displays hormone-like characteristics that affect homeostatic processes. IL-6 has context-dependent pro- and anti-inflammatory properties and is now regarded as a prominent target for clinical intervention. However, the signaling cassette that controls the activity of IL-6 is complicated, and distinct intervention strategies can inhibit this pathway. Clinical experience with antagonists of IL-6 has raised new questions about how and when to block this cytokine to improve disease outcome and patient wellbeing. Here we discuss the effect of IL-6 on innate and adaptive immunity and the possible advantages of various antagonists of IL-6 and consider how the immunobiology of IL-6 may inform clinical decisions.
Introducing a New Benchmarked Dataset for Activity Monitoring

This paper addresses the lack of a commonly used, standard dataset and established benchmarking problems for physical activity monitoring. A new dataset - recorded from 18 activities performed by 9 subjects, wearing 3 IMUs and a HR-monitor - is created and made publicly available. Moreover, 4 classification problems are benchmarked on the dataset, using a standard data processing chain and 5 different classifiers. The benchmark shows the difficulty of the classification tasks and exposes new challenges for physical activity monitoring.
Web localization: The Spanish SMEs as case of study

Constant changes in the economic environment, where globalization and the development of the knowledge economy act as drivers, are systematically pushing companies towards the challenge of accessing external markets. Web localization constitutes a new field of study and professional intervention. From the translation perspective, localization equates to the website being adjusted to the typological, discursive and genre conventions of the target culture, adapting that website to a different language and culture. This entails much more than simply translating the content of the pages. The content of a webpage is made up of text, images and other multimedia elements, all of which have to be translated and subjected to cultural adaptation. A case study has been carried out to analyze the current presence of localization within Spanish SMEs from the chemical sector. Two types of indicator have been established for evaluating the sample: indicators for evaluating company websites (with a Likert scale from 0–4) and indicators for evaluating web localization (0–2 scale). The results show overall website quality is acceptable (2.5 points out of 4). The higher rating has been obtained by the system quality (with 2.9), followed by information quality (2.7 points) and, lastly, service quality (1.9 points). In the web localization evaluation, the contact information aspects obtain 1.4 points, the visual aspect 1.04, and the navigation aspect was the worse considered (0.37). These types of analysis facilitate the establishment of practical recommendations aimed at SMEs in order to increase their international presence through the localization of their websites.
ListNet-based object proposals ranking

In object detection, object proposal methods have been widely used to generate candidate regions which may contain objects. Object proposal based on superpixel merging is one kind of object proposal methods, and the merging strategies of superpixels have been extensively explored. However, the ranking of generated candidate proposals still remains to be further studied. In this paper, we formulate the ranking of object proposals as a learning to rank problem, and propose a novel object proposals ranking method based on ListNet. In the proposed method, Selective Search, which is one of the state-of-the-art object proposal methods based on superpixel merging, is adopted to generate the candidate proposals. During the superpixel merging process, five discriminative objectness features are extracted from superpixel sets and the corresponding bounding boxes. Then, to weight each feature, a linear neural network is learned based on ListNet. Consequently, objectness scores can be computed for final candidate proposals ranking. Extensive experiments demonstrate the effectiveness and robustness of the proposed method.  to Neurocomputing June 8, 2017
International Journal of Advanced Robotic Systems Embedded Face Detection and Recognition Regular Paper

The  need  to  increase  security   With sensors  and  Digital  Signal  Processors  (DSPs),  smart cameras generate ad hoc results by analysing the numeric images transmitted from the sensor by means of a variety of  image‐processing  algorithms. Since  the  images  are not transmitted  to  a  distance  processing  unit  but  rather  are processed  inside  the  camera,  it does not necessitate high‐ bandwidth networks or high processor powered systems; it  can  instantaneously  decide  on  the  required  access. Nonetheless, on account of restricted memory, processing power  and  overall  power,  image  processing  algorithms need  to  be  developed  and  optimized  for  embedded processors.  Among  these  algorithms,  one  of  the  most important is for face detection and recognition. A number of  face  detection  and  recognition  methods  have  been proposed  recently and many of  these methods have been tested on general‐purpose processors.  In  smart  cameras  ‐ which  are  real‐life  applications  of  such  methods  ‐  the widest use is on DSPs. In the present study, the Viola‐Jones face detection method   with the developed sub‐region and mask‐based  DCT  (As  the employed  DSP  is  a  fixed‐point  processor,  the  processes were performed with integers insofar as it was possible. To enable  face  recognition,  the  image was divided  into  sub‐ regions  and  from  each  sub‐region  the  robust  coefficients against  disruptive  elements  ‐  like  face  expression, illumination,  etc.  ‐  were  selected  as  the  features.  The discrimination  of  the  selected  features was  enhanced  via LDA  (Linear Discriminant Analysis)  and  then  employed for  recognition.  Thanks  to  its  operational  convenience, codes that were optimized for a DSP received a functional test after the computer simulation. In these functional tests, the face recognition system attained a 97.4% success rate on the most popular face database: the FRGC.
AC-Powered Pulse Generator

Electric pulse field methods are wildly used in biotechnology and industrial applications. A pulse generator (PG) is the device that provides the desired electric pulse field. In this paper, a novel ac-powered PG (ACPG) that is directly powered by normal ac power (i.e., utility power) is proposed. Since there is no high-voltage dc power supply in the proposed ACPG, the circuit complexity and cost are effectively reduced. Furthermore, the voltage and duration of the generated pulse of the ACPG can easily be controlled to match specific applications. In order to assess the performance of the proposed ACPG, a prototype for providing a unipolar and a bipolar pulse train is designed and implemented. Experimental results show that the ACPG can actually generate a 0-1040-V pulse with a 750-ns to 118-mus duration without overshooting and ringing
Guidelines for the management of hiatal hernia

The guidelines for the management of hiatal hernia are a series of systematically developed statements to assist physicians’ and patients’ decisions about the appropriate use of laparoscopic surgery for hiatal hernia. The statements included in this guideline are the product of a systematic review of published literature on the topic, and the recommendations are explicitly linked to the supporting evidence. The strengths and weaknesses of the available evidence are highlighted and expert opinion sought where the evidence is lacking.
On the Implementation and Usage of SDPT3 – A Matlab Software Package for Semidefinite-Quadratic-Linear Programming, Version 4.0

This software is designed to solve conic programming problems whose constraint cone is a product of semidefinite cones, second-order cones, nonnegative orthants and Euclidean spaces; and whose objective function is the sum of linear functions and log-barrier terms associated with the constraint cones. This includes the special case of determinant maximization problems with linear matrix inequalities. It employs an infeasible primal-dual predictor-corrector path-following method, with either the HKM or the NT search direction. The basic code is written in Matlab, but key subroutines in C are incorporated via Mex files. Routines are provided to read in problems in either SDPA or SeDuMi format. Sparsity and block diagonal structure are exploited. We also exploit low-rank structures in the constraint matrices associated the semidefinite blocks if such structures are explicitly given. To help the users in using our software, we also include some examples to illustrate the coding of problem data for our SQLP solver. Various techniques to improve the efficiency and stability of the algorithm are incorporated. For example, step-lengths associated with semidefinite cones are calculated via the Lanczos method. Numerical experiments show that this general purpose code can solve more than 80% of a total of about 300 test problems to an accuracy of at least 10−6 in relative duality gap and infeasibilities. Department of Mathematics, National University of Singapore, 2 Science Drive 2, Singapore 117543 (mattohkc@nus.edu.sg); and Singapore-MIT Alliance, E4-04-10, 4 Engineering Drive 3, Singapore 117576. Research supported in parts by NUS Research Grant R146-000-076-112 and SMA IUP Research Grant. Department of Mathematical Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA (reha@cmu.edu). Research supported in part by NSF through grants CCR-9875559, CCF-0430868 and by ONR through grant N00014-05-1-0147 School of Operations Research and Industrial Engineering, Cornell University, Ithaca, New York 14853, USA (miketodd@cs.cornell.edu). Research supported in part by NSF through grant DMS-0209457 and by ONR through grant N00014-02-1-0057.
Picking Pesky Parameters: Optimizing Regular Expression Matching in Practice

Network security systems inspect packet payloads for signatures of attacks. These systems use regular expression matching at their core. Many techniques for implementing regular expression matching at line rate have been proposed. Solutions differ in the type of automaton used (i.e., deterministic vs. non-deterministic) and in the configuration of implementation-specific parameters. While each solution has been shown to perform well on specific rule sets and traffic patterns, there has been no systematic comparison across a large set of solutions, rule sets and traffic patterns. Thus, it is extremely challenging for a practitioner to make an informed decision within the plethora of existing algorithmic and architectural proposals. To address this problem, we present a comprehensive evaluation of a broad set of regular expression matching techniques. We consider both algorithmic and architectural aspects. Specifically, we explore the performance, area requirements, and power consumption of implementations targeting processors and field programmable gate arrays using rule sets of practical size and complexity. We present detailed performance results and specific guidelines for determining optimal configurations based on a simple evaluation of the rule set. These guidelines can help significantly when implementing regular expression matching systems in practice.
Itrustpage: a user-assisted anti-phishing tool

Despite the many solutions proposed by industry and the research community to address phishing attacks, this problem continues to cause enormous damage. Because of our inability to deter phishing attacks, the research community needs to develop new approaches to anti-phishing solutions. Most of today's anti-phishing technologies focus on automatically detecting and preventing phishing attacks. While automation makes anti-phishing tools user-friendly, automation also makes them suffer from false positives, false negatives, and various practical hurdles. As a result, attackers often find simple ways to escape automatic detection.
 This paper presents iTrustPage - an anti-phishing tool that does not rely completely on automation to detect phishing. Instead, iTrustPage relies on user input and external repositories of information to prevent users from filling out phishing Web forms. With iTrustPage, users help to decide whether or not a Web page is legitimate. Because iTrustPage is user-assisted, iTrustPage avoids the false positives and the false negatives associated with automatic phishing detection. We implemented iTrustPage as a downloadable extension to FireFox. After being featured on the Mozilla website for FireFox extensions, iTrustPage was downloaded by more than 5,000 users in a two week period. We present an analysis of our tool's effectiveness and ease of use based on our examination of usage logs collected from the 2,050 users who used iTrustPage for more than two weeks. Based on these logs, we find that iTrustPage disrupts users on fewer than 2% of the pages they visit, and the number of disruptions decreases over time.
Chronic intestinal pseudo-obstruction: clinical features, diagnosis, and therapy.

CIPO is the very “tip of the iceberg” of functional gastrointestinal disorders, being a rare and frequently misdiagnosed condition characterized by an overall poor outcome. Diagnosis should be based on clinical features, natural history and radiologic findings. There is no cure for CIPO and management strategies include a wide array of nutritional, pharmacologic, and surgical options which are directed to minimize malnutrition, promote gut motility and reduce complications of stasis (ie, bacterial overgrowth). Pain may become so severe to necessitate major analgesic drugs. Underlying causes of secondary CIPO should be thoroughly investigated and, if detected, treated accordingly. Surgery should be indicated only in a highly selected, well characterized subset of patients, while isolated intestinal or multivisceral transplantation is a rescue therapy only in those patients with intestinal failure unsuitable for or unable to continue with TPN/HPN. Future perspectives in CIPO will be directed toward an accurate genomic/proteomic phenotying of these rare, challenging patients. Unveiling causative mechanisms of neuro-ICC-muscular abnormalities will pave the way for targeted therapeutic options for patients with CIPO.
Experimental Validation of a Cardiac Simulator for in
vitro Evaluation of Prosthetic Heart Valves

This work describes the experimental validation of a cardiac simulator for three heart rates (60, 80 and 100 beats per minute), under physiological conditions, as a suitable environment for prosthetic heart valves testing in the mitral or aortic position.



In the experiment, an aortic bileaflet mechanical valve and a mitral bioprosthesis were employed in the left ventricular model. A test fluid of 47.6% by volume of glycerin solution in water at 36.5ºC was used as blood analogue fluid. A supervisory control and data acquisition system implemented previously in LabVIEW was applied to induce the ventricular operation and to acquire the ventricular signals. The parameters of the left ventricular model operation were based on in vivo and in vitro data. The waves of ventricular and systemic pressures, aortic flow, stroke volume, among others, were acquired while manual adjustments in the arterial impedance model were also established.



The acquired waves showed good results concerning some in vivo data and requirements from the ISO 5840 standard.



The experimental validation was performed, allowing, in future studies, characterizing the hydrodynamic performance of prosthetic heart valves.
Truck Scheduling in the Postal Service Industry

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