nils-herrmann/clean_scirepeval huggingface dataset:
Software security and privacy risks in mobile e-commerce

Most current e-commerce transactions are conducted by users in fixed locations using workstations and personal computers. Soon, we expect a significant portion of e-commerce will take place via wireless, Internet-enabled devices such as cellular phones and personal digital assistants. Wireless devices provide users mobility to research, communicate, and purchase goods and services from anywhere at anytime without being tethered to the desktop. Using the Internet from wireless devices has come to be known as mobile e-commerce, or simply “m-commerce,” and encompasses many more activities than merely online purchasing. One of the major wireless applications is Web access for retrieval of real-time information such as weather reports, sport scores, flight and reservation information, navigational maps, and stock quotes. While email will continue to dominate wireless applications, innovative online applications that, for instance, use location reference information of end users will drive new areas of mobile e-business growth. Strategy Analytics, among other market research groups, predicts that by 2004 there will be over one TE R Y M IU R A
The Enterprise Service Bus: Making service-oriented architecture real

M.-T. Schmidt B. Hutchison P. Lambros R. Phippen The Enterprise Service Bus (ESB) is the infrastructure which underpins a fully integrated and flexible end-to-end service-oriented architecture (SOA). This paper details the essential meta-data and capabilities of the ESB. It presents a summary of the key concepts of the ESB and defines the integration model for it, including key user roles. These roles are fulfilled using meta-data that describes the service endpoints, such as the service interface and policy requirements and capabilities. The ESB manages this meta-data through a registry, which supports configuration, connection, matchmaking, and discovery of service endpoints. Some typical mediation patterns that are used to satisfy endpoint policies are explored, and usage patterns are described in which the ESB is used to implement real SOAs.
Taking the Human Out of the Loop: A Review of Bayesian Optimization

Big Data applications are typically associated with systems involving large numbers of users, massive complex software systems, and large-scale heterogeneous computing and storage architectures. The construction of such systems involves many distributed design choices. The end products (e.g., recommendation systems, medical analysis tools, real-time game engines, speech recognizers) thus involve many tunable configuration parameters. These parameters are often specified and hard-coded into the software by various developers or teams. If optimized jointly, these parameters can result in significant improvements. Bayesian optimization is a powerful tool for the joint optimization of design choices that is gaining great popularity in recent years. It promises greater automation so as to increase both product quality and human productivity. This review paper introduces Bayesian optimization, highlights some of its methodological aspects, and showcases a wide range of applications.
"Put-that-there": Voice and gesture at the graphics interface

Recent technological advances in connected-speech recognition and position sensing in space have encouraged the notion that voice and gesture inputs at the graphics interface can converge to provide a concerted, natural user modality.
 The work described herein involves the user commanding simple shapes about a large-screen graphics display surface. Because voice can be augmented with simultaneous pointing, the free usage of pronouns becomes possible, with a corresponding gain in naturalness and economy of expression. Conversely, gesture aided by voice gains precision in its power to reference.
The G-spot: an observational MRI pilot study.

To identify a G-spot complex (GSC) in vivo in MRI examinations at 1.5 Tesla field strength.



Observational study.



Single centre.



Twenty-one consecutive patients (January-March 2014).



Imaging analysis of routine imaging protocols for usual medical indications with and without concomitant opacification of the vaginal cavity with inert ultrasound gel. The gel distends the otherwise collapsed vaginal walls, allowing for an improved discrimination of anatomic features. The macroscopic and histological results recently derived from the dissections of fresh cadavers by Ostrzenski et al. were translated into imaging characteristics to be expected in the respective MRI sequences (e.g. T1- and T2-weighted) in search of an in vivo correlate of the GSC. Age, menopause status, medical indication and diagnosis were co-variables.



To analyse primarily whether MRI imaging is able to depict a distinct morphological entity in vivo matching the GSC, based on anatomical descriptions published recently. The elaboration of an appropriate MRI-imaging protocol was a secondary aim.



A total of 21 studies were obtained. A GSC was identified within the anterior vaginal wall in 13/21 patients (62%). In all, 10/21 (48%) had vaginal gel opacification. We identified a GSC in 10/10 patients (100%) with opacification in all three planes of the T2 images. This was only true for 3/11 cases (27%) without opacification.



There is evidence for an in vivo morphological correlate to the postmortem anatomical findings of a GSC described by Ostrzenski et al.; its visibility in MRI imaging can be significantly improved with vaginal opacification by ultrasound gel.



Identification of G-spot by MRI with vaginal gel-opacification in 13/21 patients.
Knowledge management and organizational culture: a theoretical integrative framework

Organizational culture is a critical factor in building and reinforcing knowledge management in organizations. However, there is no theoretical framework that comprehensively explains the effect of organizational culture on knowledge management in organizations. This paper endeavors to develop a theoretical integrative framework for organizational knowledge management and organizational culture.  This is a conceptual paper. It modifies the ‘‘competing value framework’’ by adding a new dimension representing ethical and trusting culture, and then integrates it with the SECI model of knowledge creation and conversion by identifying the conceptual parallels between the two frameworks and then analyzing the interaction effects among the dimensions.  Based on the congruity between the modified competing values framework and the knowledge creation and conversion framework, the paper formulates six propositions about the propensity of organizations of different dominant cultural styles to engage in the four processes of knowledge creation and conversion.  The dynamic nature of the framework presented in the paper points to the importance of longitudinal and comparative research in understanding the effects of organizational culture on organizational knowledge management systems in organizations.  The proposed integrative framework would facilitate organizational learning and lead to the improvement of knowledge management practices in organizations as it helps managers to understand the linkages between culture and knowledge management.  This paper presents a new framework linking organizational culture to knowledge management. It moves away from analyzing culture only in terms of its positive and negative influences on knowledge management. Instead, it suggests a typology of the kind of knowledge management processes that organizations are likely to focus on depending on the culture that prevails in an organization.
Big Data Cognitive Storage: An Optimum Way of handling the Educational Data in Indian Scenario

The concept of big data has been incorporated in majority of areas. The educational sector has plethora of data especially in online education which plays a vital in modern education. Moreover digital learning which comprises of data and analytics contributes significantly to enhance teaching and learning. The key challenge for handling such data can be a costly affair. IBM has introduced the technology "Cognitive Storage" which ensures that the most relevant information is always on hand. This technology governs the incoming data, stores the data in definite media, application of levels of data protection, policies for the lifecycle and retention of different classes of data. This technology can be very beneficial for online learning in Indian scenario. This technology will be very beneficial in Indian society so as to store more information for the upliftment of the students’ knowledge.
Automatic sperms counting using adaptive local threshold and ellipse detection

A male fertility is influenced by several factors. One of which is the quality of the sperm. Over the last 50 years, human sperm quality decreases. It became the driving force for a male to examine his sperm. It is therefore necessary to have a method to check the sperm quality which is not only accurate, but fast and cheap. Sperm quality can be measured by, one of which, sperm count. In some medical laboratories sperm count is still using manual assessment which makes it subjective, non repetitive, inaccurate, and time consuming. By using multimedia microscope that can record the sperm into a video, one can process it using image processing and computer vision method. In this paper, we propose a method to detect and count sperm in a video taken by a multimedia microscope using an adaptive local threshold and enhanced ellipse detection. The result is 90.97% accuracy compared to the manual assessment.
Intelligent Mobile Health Monitoring System (IMHMS)

Health monitoring is repeatedly mentioned as one of the main application areas for Pervasive computing. Mobile Health Care is the integration of mobile computing and health monitoring. It is the application of mobile computing technologies for improving communication among patients, physicians, and other health care workers. As mobile devices have become an inseparable part of our life it can integrate health care more seamlessly to our everyday life. It enables the delivery of accurate medical information anytime anywhere by means of mobile devices. Recent technological advances in sensors, low-power integrated circuits, and wireless communications have enabled the design of low-cost, miniature, lightweight and intelligent bio-sensor nodes. These nodes, capable of sensing, processing, and communicating one or more vital signs, can be seamlessly integrated into wireless personal or body area networks for mobile health monitoring. In this paper we present Intelligent Mobile Health Monitoring System (IMHMS), which can provide medical feedback to the patients through mobile devices based on the biomedical and environmental data collected by deployed sensors.
First-Order Theorem Proving and Vampire

In this tutorial we give a short introduction in first-order theorem proving and the use of the theorem prover Vampire. The first part of the tutorial is intended for the audience with little or no knowledge in theorem proving. We will discuss the the resolution and superposition calculus, introduce the saturation principle, present various algorithms implementing redundancy elimination, preprocessing and clause form transformation and demonstrate how these concepts are implemented in Vampire. The second part will cover more advanced topics and features. Some of these features are implemented only in Vampire. This includes reasoning with theories, such as arithmetic, answering queries to very large knowledge bases, interpolation, and an original technique of symbol elimination, which allows one to automatically discover invariants in programs with loops. All the introduced concepts will be illustrated by running the firstorder theorem prover Vampire.
vDNN: Virtualized deep neural networks for scalable, memory-efficient neural network design

The most widely used machine learning frameworks require users to carefully tune their memory usage so that the deep neural network (DNN) fits into the DRAM capacity of a GPU. This restriction hampers a researcher's flexibility to study different machine learning algorithms, forcing them to either use a less desirable network architecture or parallelize the processing across multiple GPUs. We propose a runtime memory manager that virtualizes the memory usage of DNNs such that both GPU and CPU memory can simultaneously be utilized for training larger DNNs. Our virtualized DNN (vDNN) reduces the average GPU memory usage of AlexNet by up to 89%, OverFeat by 91%, and GoogLeNet by 95%, a significant reduction in memory requirements of DNNs. Similar experiments on VGG-16, one of the deepest and memory hungry DNNs to date, demonstrate the memory-efficiency of our proposal. vDNN enables VGG-16 with batch size 256 (requiring 28 GB of memory) to be trained on a single NVIDIA Titan X GPU card containing 12 GB of memory, with 18% performance loss compared to a hypothetical, oracular GPU with enough memory to hold the entire DNN.
Could We Issue Driving Licenses to Autonomous Vehicles?

Many companies are studying autonomous vehicles. One trend in the development of control algorithms for autonomous vehicles is the use of deep-learning approaches. The general idea is to simulate a human driver’s decision-making and behavior in various scenarios without necessarily knowing why the decision is made. In this position paper, we first argue that traditional safety analysis methods need to be extended to verify deep-learning-based autonomous vehicles. Then, we propose borrowing ideas from the process of issuing driving licenses to human drivers to verify autonomous vehicles. Verification of autonomous vehicles could focus on sufficient training as well as mental and physical health checks. Based on this position, we list several challenges that need
Social fMRI: Investigating and shaping social mechanisms in the real world

We introduce the Friends and Family study, a longitudinal living laboratory in a residential community. In this study, we employ a ubiquitous computing approach, Social Functional Mechanism-design and Relationship Imaging, or Social fMRI, that combines extremely rich data collection with the ability to conduct targeted experimental interventions with study populations. We present our mobile-phone-based social and behavioral sensing system, deployed in thewild for over 15months. Finally,we present three investigations performed during the study, looking into the connection between individuals’ social behavior and their financial status, network effects in decision making, and a novel intervention aimed at increasing physical activity in the subject population. Results demonstrate the value of social factors for choice, motivation, and adherence, and enable quantifying the contribution of different incentive mechanisms.
Brain Training in Children and Adolescents: Is It Scientifically Valid?

Brain training products are becoming increasingly popular for children and adolescents. Despite the marketing aimed at their use in the general population, these products may provide more benefits for specific neurologically impaired populations. A review of Brain Training (BT) products analyzing their efficacy while considering the methodological limitations of supporting research is required for practical applications.  searches were made of the PubMed database (until March 2017) for studies including: (1) empirical data on the use of brain training for children or adolescents and any effects on near transfer (NT) and/or far transfer (FT) and/or neuroplasticity, (2) use of brain training for cognitive training purposes, (3) commercially available training applications, (4) computer-based programs for children developed since the 1990s, and (5) relevant printed and peer-reviewed material.  Database searches yielded a total of 16,402 references, of which 70 met the inclusion criteria for the review. We classified programs in terms of neuroplasticity, near and far transfer, and long-term effects and their applied methodology. Regarding efficacy, only 10 studies (14.2%) have been found that support neuroplasticity, and the majority of brain training platforms claimed to be based on such concepts without providing any supporting scientific data. Thirty-six studies (51.4%) have shown far transfer (7 of them are non-independent) and only 11 (15.7%) maintained far transfer at follow-up. Considering the methodology, 40 studies (68.2%) were not randomized and controlled; for those randomized, only 9 studies (12.9%) were double-blind, and only 13 studies (18.6%) included active controls in their trials.  Overall, few independent studies have found far transfer and long-term effects. The majority of independent results found only near transfer. There is a lack of double-blind randomized trials which include an active control group as well as a passive control to properly control for contaminant variables. Based on our results, Brain Training Programs as commercially available products are not as effective as first expected or as they promise in their advertisements.
Schedulability analysis of periodic fixed priority systems

Feasibility analysis of fixed priority systems has been widely studied in the real-time literature and several acceptance tests have been proposed to guarantee a set of periodic tasks. They can be divided in two main classes: polynomial time tests and exact tests. Polynomial time tests can efficiently be used for online guarantee of real-time applications, where tasks are activated at runtime. These tests introduce a negligible overhead, when executed upon a new task arrival, however provide only a sufficient schedulability condition, which may cause a poor processor utilization. On the other hand, exact tests, which are based on response time analysis, provide a necessary and sufficient schedulability condition, but are too complex to be executed on line for large task sets. As a consequence, for large task sets, they are often executed off line. This paper proposes a novel approach for analyzing the schedulability of periodic task sets on a single processor under an arbitrary fixed priority assignment: Using this approach, we derive a new schedulability test which can be tuned through a parameter to balance complexity versus acceptance ratio, so that it can be used on line to better exploit the processor, based on the available computational power. Extensive simulations show that our test, when used in its exact form, is significantly faster than the current response time analysis methods. Moreover the proposed approach, for its elegance and compactness, offers an explanation of some known phenomena of fixed priority scheduling and could be helpful for further work on schedulability analysis.
Comparison of orthodontic treatment outcomes in adults with skeletal open bite between conventional edgewise treatment and implant-anchored orthodontics.

Open bites are known to be difficult malocclusions to treat. Generally, with conventional edgewise treatment, incisor extrusion rather than molar intrusion is observed. Recently, the use of miniscrews as anchorage has markedly increased. In this study, orthodontic treatment outcomes after conventional edgewise treatment and implant-anchored treatment were investigated by cephalometric analysis and several occlusal indexes. In addition, the stability of these patients 2 years after the retention phase was also analyzed.



Thirty adults (15 for nonimplant treatment [non-IA group] and 15 for implant-anchored treatment [IA group]) were our subjects. Cephalometric analysis, peer assessment rating, discrepancy index, and objective grading system were used.



From the cephalometric values in the non-IA group, open-bite patients were generally treated by extrusion of the maxillary and mandibular incisors that resulted in clockwise rotation of the mandibular plane angle. In the IA group, intrusion of the maxillary and mandibular molars that resulted in counterclockwise rotation was noted. Furthermore, in the IA group, the soft-tissue analysis showed decreases in the facial convexity and the inferior labial sulcus angle that resulted in the disappearance of incompetent lips. In the retention phase, extrusion of the mandibular molars was observed in the IA group. From the objective grading system evaluation, significant reductions of overbite in canines and premolars were observed in both groups. Furthermore, less stability was observed in the IA group compared with the non-IA group according to the total objective grading system score.



Ideal occlusion can be achieved in adults with severe open bite with both conventional edgewise and implant-anchored orthodontic treatment. However, absolute intrusion of the molars and improvement in esthetics might be achieved more effectively by using miniscrews as an anchorage device. In addition, since a significant amount of tooth movement occurs with miniscrews, careful attention is required during the retention phase.
Twitter Data Analytics

Springer This e↵ort is dedicated to my family. Thank you for all your support and encouragement.-SK For my parents and Rio. Thank you for everything.-FM To my parents, wife, and sons.-HL Acknowledgments We would like to thank the following individuals for their help in realizing this book. We would like to thank Daniel Howe and Grant Marshall for helping to organize the examples in the book, Daria Bazzi and Luis Brown for their help in proofreading and suggestions in organizing the book, and Terry Wen for preparing the web site. We appreciate Dr. Ross Maciejewski's helpful suggestions and guidance as our data visualization mentor. We express our immense gratitude to Dr. Rebecca Goolsby for her vision and insight for using social media as a tool for Humanitarian Assistance and Disaster Relief. Finally, we thank all members of the Data Mining and Machine Learning lab for their encouragement and advice throughout this process. This book is the result of projects sponsored, in part, by the Oce of Naval Research. With their support, we developed TweetTracker and TweetXplorer, flagship projects that helped us gain the knowledge and experience needed to produce this book.
Midfield Wireless Power Transfer for Bioelectronics

Midfield wireless powering enables electronics to be designed at the millimeter-scale and operated at nearly any location in the body. Theoretical studies show a wireless power transfer paradigm with a maximum bound orders of magnitude higher than conventional near-field inductive coupling. Furthermore, higher frequency of operation for midfield coupling lends itself to miniaturization of the implant. Midfield powering experiments using an external patterned metal structure and a millimeter sized coil show significant power delivery within safe levels of tissue heating in the chest and the head of a porcine model, and will enable implantable bioelectronics to reach new levels of functionality and one day to become as ubiquitous as over-the-counter pharmaceuticals.
Analysis of waveguide slot-based structures using wide-band equivalent-circuit model

Analysis of geometrically complicated waveguide-based slotted arrays and filters is performed using a simple equivalent-circuit model. First, the circuit parameters (inductance and capacitance) of a simple waveguide slot-coupler problem are obtained through moment-method (MoM) analysis. The values of the lumped LC elements are virtually constant over the frequency range of interest (the X-band) for specific waveguide and slot dimensions. Based on the equivalent-circuit model of a single slot of two coupled waveguides, more complicated structures are then analyzed, such as slot coupler arrays and slot-based waveguide filters. The scattering parameters of these structures are obtained through circuit analysis, and are verified using the MoM and finite-difference time-domain method. Excellent agreement is observed over a wide band of frequencies and is confirmed by experimental results.