nils-herrmann/clean_scirepeval huggingface dataset:
Pattern specification and application in metamodels in ecore

The increased use of domain-specific languages (DSLs) and the absence of adequate tooling to take advantage of commonalities among DSLs has led to a situation where the same structure is duplicated in multiple DSLs. This observation has lead to the work described in this paper: an investigation of methods and tools for pattern specification and application and two extensions of a state-of-the-art tool for patterns in DSLs, DSL-tao. The extensions make patterns more understandable and they also make the tool suitable for more complex pattern applications. The first extension introduces a literal specification for patterns and the second extension introduces a merge function for the application of patterns. These two extensions are demonstrated on an often-occurring pattern in DSLs.
Overlapping Sound Event Recognition using Local Spectrogram Features with the Generalised Hough Transform

In this paper, we address the challenging task of simultaneous recognition of overlapping sound events from single channel audio. Conventional frame-based methods aren’t well suited to the problem, as each time frame contains a mixture of information from multiple sources. Missing feature masks are able to improve the recognition in such cases, but are limited by the accuracy of the mask, which is a non-trivial problem. In this paper, we propose an approach based on Local Spectrogram Features (LSFs) which represent local spectral information that is extracted from the two-dimensional region surrounding “keypoints” detected in the spectrogram. The keypoints are designed to locate the sparse, discriminative peaks in the spectrogram, such that we can model sound events through a set of representative LSF clusters and their occurrences in the spectrogram. To recognise overlapping sound events, we use a Generalised Hough Transform (GHT) voting system, which sums the information over many independent keypoints to produce onset hypotheses, that can detect any arbitrary combination of sound events in the spectrogram. Each hypothesis is then scored against the class distribution models to recognise the existence of the sound in the spectrogram. Experiments on a set of five overlapping sound events, in the presence of non-stationary background noise, demonstrates the potential of our approach.
Quantum-inspired evolutionary algorithms with a new termination criterion, H/sub /spl epsi// gate, and two-phase scheme

From recent research on combinatorial optimization of the knapsack problem, quantum-inspired evolutionary algorithm (QEA) was proved to be better than conventional genetic algorithms. To improve the performance of the QEA, this paper proposes research issues on QEA such as a termination criterion, a Q-gate, and a two-phase scheme, for a class of numerical and combinatorial optimization problems. A new termination criterion is proposed which gives a clearer meaning on the convergence of Q-bit individuals. A novel variation operator H/sub /spl epsi// gate, which is a modified version of the rotation gate, is proposed along with a two-phase QEA scheme based on the analysis of the effect of changing the initial conditions of Q-bits of the Q-bit individual in the first phase. To demonstrate the effectiveness and applicability of the updated QEA, several experiments are carried out on a class of numerical and combinatorial optimization problems. The results show that the updated QEA makes QEA more powerful than the previous QEA in terms of convergence speed, fitness, and robustness.
Nursing informatics competencies required of nurses in Taiwan

In today's workplace, nurses are highly skilled professionals possessing expertise in both information technology and nursing. Nursing informatics competencies are recognized as an important capability of nurses. No established guidelines existed for nurses in Asia. This study focused on identifying the nursing informatics competencies required of nurses in Taiwan.



A modified Web-based Delphi method was used for two expert groups in nursing, educators and administrators. Experts responded to 323 items on the Nursing Informatics Competencies Questionnaire, modified from the initial work of Staggers, Gassert and Curran to include 45 additional items. Three Web-based Delphi rounds were conducted. Analysis included detailed item analysis. Competencies that met 60% or greater agreement of item importance and appropriate level of nursing practice were included.



N=32 experts agreed to participate in Round 1, 23 nursing educators and 9 administrators. The participation rates for Rounds 2 and 3=68.8%.  A high degree of agreement existed for specific nursing informatics competencies required for nurses in Taiwan (97.8%).



This study provides a current master list of nursing informatics competency requirements for nurses at four levels in the U.S. and Taiwan. The results are very similar to the original work of Staggers et al. The results have international relevance because of the global importance of information technology for the nursing profession.
Operational IT Business Alignment as the Missing Link from IT Strategy to Firm Success

Strategic IT business alignment deals with the capability of IT to both shape and support business strategy. It can be interpreted as an organizational learning process that combines business and IT knowledge to support business objectives and can positively affect organizational profitability by creating superior strategies that achieve a competitive advantage. These strategies have to be implemented because strategies are only effective when they are translated into actions readily. Therefore, we introduce the concept of operational IT business alignment, reflecting the functional integration at the structural level and representing the link between business and IT structure. Using structural equation modeling and data from 136 banks, we show that operational IT business alignment positively impacts dynamic IT and business capabilities and in turn strategic alignment and firm performance.
Synchronous mucinous metaplasia and neoplasia of the female genital tract with external urethral meatus neoplasm: A case report

•We present a case of multiple mucinous metaplasia and neoplasia of cervix, endometrium, fallopian tube, ovary, and mesenterium with external urethral meatus neoplasm.•Immunohistochemistry showed almost same pattern in each neoplasms.•PCR-direct sequencing showed no existence of both KRAS and GNAS mutations.•This report suggests a possibility of synchronous mucinous metaplasia and neoplasia "beyond" female genital tract.
The Expressive Power of Neural Networks: A View from the Width

The expressive power of neural networks is important for understanding deep learning. Most existing works consider this problem from the view of the depth of a network. In this paper, we study how width affects the expressiveness of neural networks. Classical results state that depth-bounded (e.g. depth-2) networks with suitable activation functions are universal approximators. We show a universal approximation theorem for width-bounded ReLU networks: width-(n+ 4) ReLU networks, where n is the input dimension, are universal approximators. Moreover, except for a measure zero set, all functions cannot be approximated by width-n ReLU networks, which exhibits a phase transition. Several recent works demonstrate the benefits of depth by proving the depth-efficiency of neural networks. That is, there are classes of deep networks which cannot be realized by any shallow network whose size is no more than an exponential bound. Here we pose the dual question on the width-efficiency of ReLU networks: Are there wide networks that cannot be realized by narrow networks whose size is not substantially larger? We show that there exist classes of wide networks which cannot be realized by any narrow network whose depth is no more than a polynomial bound. On the other hand, we demonstrate by extensive experiments that narrow networks whose size exceed the polynomial bound by a constant factor can approximate wide and shallow network with high accuracy. Our results provide more comprehensive evidence that depth may be more effective than width for the expressiveness of ReLU networks.
Video Frame's Background Modeling: Reviewing the Techniques

Background modeling is a technique for extracting moving objects in video frames. This technique can be used in machine vision applications, such as video frame compression and monitoring. To model the background in video frames, initially, a model of scene background is constructed, then the current frame is subtracted from the background. Eventually, the difference determines the moving objects. This paper evaluates a number of existing background modeling techniques in terms of accuracy, speed and memory requirement.
Deep Learning for Hand Gesture Recognition on Skeletal Data

In this paper, we introduce a new 3D hand gesture recognition approach based on a deep learning model. We propose a new Convolutional Neural Network (CNN) where sequences of hand-skeletal joints' positions are processed by parallel convolutions; we then investigate the performance of this model on hand gesture sequence classification tasks. Our model only uses hand-skeletal data and no depth image. Experimental results show that our approach achieves a state-of-the-art performance on a challenging dataset (DHG dataset from the SHREC 2017 3D Shape Retrieval Contest), when compared to other published approaches. Our model achieves a 91.28% classification accuracy for the 14 gesture classes case and an 84.35% classification accuracy for the 28 gesture classes case.
A design method with iron powder core for a claw pole type half-wave rectified variable field flux motor

We have proposed a claw pole type half-wave rectified variable field flux motor (CP-HVFM) with special self-excitation method. The claw pole rotor needs the 3D magnetic path core. This paper reports an analysis method with experimental BH and loss data of the iron powder core for FEM. And it shows a designed analysis model and characteristics such as torque, efficiency and loss calculation results.
Retrograde amnesia: neither partial nor complete hippocampal lesions in rats result in preferential sparing of remote spatial memory, even after reminding

Many lesion experiments have provided evidence that the hippocampus plays a time-limited role in memory, consistent with the operation of a systems-level memory consolidation process during which lasting neocortical memory traces become established [see Squire, L. R., Clark, R. E., & Knowlton, B. J. (2001). Retrograde amnesia. Hippocampus 11, 50]. However, large lesions of the hippocampus at different time intervals after acquisition of a watermaze spatial reference memory task have consistently resulted in temporally ungraded retrograde amnesia [Bolhuis,  (1994). Retrograde amnesia and memory reactivation in rats with ibotenate lesions to the hippocampus or subiculum.  (1999). Retrograde amnesia and selective damage to the hippocampal formation: memory for places and object discriminations. Behavioural Brain Research 106, 97; Sutherland, R. J., Weisend, M. P., Mumby, D., Astur, R. S., Hanlon, F. M., et al. (2001). Retrograde amnesia after hippocampal damage: recent vs. remote memories in two tasks. Hippocampus 11, 27]. It is possible that spatial memories acquired during such a task remain permanently dependent on the hippocampus, that chance performance may reflect a failure to access memory traces that are initially unexpressed but still present, or that graded retrograde amnesia for spatial information might only be observed following partial hippocampal lesions. This study examined the retrograde memory impairments of rats that received either partial or complete lesions of the hippocampus either 1-2 days, or 6 weeks after training in a watermaze reference memory task. Memory retention was assessed using a novel 'reminding' procedure consisting of a series of rewarded probe trials, allowing the measurement of both free recall and memory reactivation. Rats with complete hippocampal lesions exhibited stable, temporally ungraded retrograde amnesia, and could not be reminded of the correct location. Partially lesioned rats could be reminded of a recently learned platform location, but no recovery of remote memory was observed. These results offer no support for hippocampus-dependent consolidation of allocentric spatial information, and suggest that the hippocampus can play a long-lasting role in spatial memory. The nature of this role--in the storage, retrieval, or expression of memory--is discussed.
Efficient Trapdoor Hash Functions for Digital Signatures

By appending some bits to the original signature, a trapdoor hash function converts any signature scheme into secure signature scheme with very efficient online computation. Many of them have been proposed. The paper presents three new trapdoor hash functions with promotion in offline computation, online computation, appended bits, and the size of trapdoor key (but with longer public key). While the appended bits is shortened half (or more), the efficiency of online computation is doubled or more. These features make it suitable for mobile environment and real-time application.
Full Duplex Networking: Mission Impossible?

Mobile traffic is projected to increase 1000 times from 2010 to 2020. This poses significant challenges on the 5t h generation (5G) wireless communication system design, inc luding network structure, air interface, key transmission schemes, multiple access, and duplexing schemes. In this paper, full duplex networking issues are discussed, aiming to provide some ins ights on the design and possible future deployment for 5G. Particu larly, the interference scenarios in full duplex are analyzed, fol lowed by discussions on several candidate interference mitigati on approaches, interference proof frame structures, transceiv er structures for channel reciprocity recovery, and super full duplex base station where each sector operates in time division duplex ( TDD) mode. The extension of TDD and frequency division duplex (FDD) to full duplex is also examined. It is anticipated thatwith future standardization and deployment of full duplex systems, TDD and FDD will be harmoniously integrated, supporting all the existing half duplex mobile phones efficiently, and lead ing to a substantially enhanced 5G system performance.
A survey on named data networking

Named Data Networking (NDN) is an entirely new internet architecture inspired by years of empirical research into network usage. NDN is related to Content Centric Networking. Unique feature of NDN is its adaptive forwarding plane. In NDN, the packets carry the data name instead of the source and destination address. In NDN, communication takes place by the exchange of Interest and Data packets. Data consumers send Interest packets in the form of names. Routers forward the Interest packet based on the data name and also maintain the state information of pending Interests that enable NDN routers to detect loops, measure performance of different path, quickly detect failures and retry alternative path. The producer replies with data packet that takes the reverse path of Interests. In this paper the motivation and the vision of NDN architecture, and basic components and operations of NDN are described. Also the strength and weakness of NDN are reviewed. The final discussion aims to identify challenges and some future directions for NDN deployment.
A Study on Formal Methods to Generalize Heterogeneous Mobile Malware Propagation and Their Impacts

Mobile personal devices, such as smartphones, USB thumb drives, and sensors, are becoming essential elements of our modern lives. Their large-scale pervasive deployment within the population has already attracted many malware authors, cybercriminals, and even governments. Since the first demonstration of mobile malware by Marcos Velasco, millions of these have been developed with very sophisticated capabilities. They infiltrate highly secure networks using air-gap jumping capability (e.g., “Hammer Drill” and “Brutal Kangaroo”) and spread through heterogeneous computing and communication platforms. Some of these cross-platform malware attacks are capable of infiltrating isolated control systems which might be running a variety of operating systems, such as Windows, Mac OS X, Solaris, and Linux. This paper investigates cross-platform/heterogeneous mobile malware that uses removable media, such as USB connection, to spread between incompatible computing platforms and operating systems. Deep analysis and modeling of cross-platform mobile malware are conducted at the micro (infection) and macro (spread) levels. The micro-level analysis aims to understand the cross-platform malware states and transitions between these states during node-to-node infection. The micro-level analysis helps derive the parameters essential for macro-level analysis, which are also crucial for the elaboration of suitable detection and prevention solutions. The macro-level analysis aims to identify the most important factors affecting cross-platform mobile malware spread within a digitized population. Through simulation, we show that identifying these factors helps to mitigate any outbreaks.
Comparison of scapular posterior tilting exercise alone and scapular posterior tilting exercise after pectoralis minor stretching on scapular alignment and scapular upward rotators activity in subjects with short pectoralis minor.

To compare scapular posterior tilting exercise alone and scapular posterior tilting exercise after pectoralis minor (PM) stretching on the PM index (PMI), scapular anterior tilting index, scapular upward rotation angle, and scapular upward rotators' activity in subjects with a short PM.



Fifteen subjects with a short PM participated in this study.



The PMI, scapular anterior tilting index, and scapular upward rotation angle were measured after scapular posterior tilting exercise alone and scapular posterior tilting exercise after PM stretches. Scapular upward rotators' activities were collected during scapular posterior tilting exercise alone and scapular posterior tilting exercise after PM stretches.



The PMI and scapular upward rotation angle, as well as the activity of the upper trapezius, lower trapezius, and serratus anterior muscles, were significantly greater for scapular posterior tilting exercise after PM stretching and the scapular anterior tilting index was significantly lower for scapular posterior tilting exercise after PM stretching than the scapular posterior tilting exercise alone.



Scapular posterior tilting exercise after PM stretching in subjects with a short PM could be an effective method of modifying scapular alignment and scapular upward rotator activity.
Context-aware Recommendation of Visualization Components

Although many valuable visualizations have been developed to gain insights from large data sets, selecting an appropriate visualization for a specific data set and goal remains challenging for non-experts. In this paper, we propose a novel approach for knowledge-assisted, context-aware visualization recommendation. Both semantic web data and visualization components are annotated with formalized visualization knowledge from an ontology. We present a recommendation algorithm that leverages those annotations to provide visualization components that support the users’ data and task. We successfully proved the practicability of our approach by integrating it into two research prototypes. Keywords-recommendation, visualization, ontology, mashup
How to evaluate the microcirculation: report of a round table conference

Microvascular alterations may play an important role in the development of organ failure in critically ill patients and especially in sepsis. Recent advances in technology have allowed visualization of the microcirculation, but several scoring systems have been used so it is sometimes difficult to compare studies. This paper reports the results of a round table conference that was organized in Amsterdam in November 2006 in order to achieve consensus on image acquisition and analysis.



The participants convened to discuss the various aspects of image acquisition and the different scores, and a consensus statement was drafted using the Delphi methodology.



The participants identified the following five key points for optimal image acquisition: five sites per organ, avoidance of pressure artifacts, elimination of secretions, adequate focus and contrast adjustment, and recording quality. The scores that can be used to describe numerically the microcirculatory images consist of the following: a measure of vessel density (total and perfused vessel density; two indices of perfusion of the vessels (proportion of perfused vessels and microcirculatory flow index); and a heterogeneity index. In addition, this information should be provided for all vessels and for small vessels (mostly capillaries) identified as smaller than 20 microm. Venular perfusion should be reported as a quality control index, because venules should always be perfused in the absence of pressure artifact. It is anticipated that although this information is currently obtained manually, it is likely that image analysis software will ease analysis in the future.



We proposed that scoring of the microcirculation should include an index of vascular density, assessment of capillary perfusion and a heterogeneity index.
Self-Protection against Attacks in an Autonomic Computing Environment

Computing systems have steadily evolved into more complex, interconnected, heterogeneous entities. Ad-hoc techniques are most often used in designing them. Furthermore, researchers and designers from both academia and industry have focused on vertical approaches to emphasizing the advantages of one specific feature such as fault tolerance, security or performance. Such approaches led to very specialized computing systems and applications. Autonomic systems, as an alternative approach, can control and manage themselves automatically with minimal intervention by users or system administrators. This paper presents an autonomic framework in developing and implementing autonomic computing services and applications. Firstly, it shows how to apply this framework to autonomically manage the security of networks. Then an approach is presented to develop autonomic components from existing legacy components such as software modules/applications or hardware resources (router, processor, server, etc.). Experimental evaluation of the prototype shows that the system can be programmed dynamically to enable the components to operate autonomously.
Framework for Validation, Test and Analysis of Real-Time Scheduling Algorithms and Scheduler Implementations

This paper describes our work towards a rapid prototyping system for hard real-time systems focusing on scheduling algorithms and scheduler implementations. The framework aims at speeding up the decision making process during selection of a suitable scheduling algorithm for a real-time application. The framework supports various kinds of realtime scheduling algorithms, which can be simulated for evaluation purposes. Furthermore, implementations of these algorithms can be tested in a real-time operating system (RTOS) with real or synthetic workloads. The algorithms are implemented as software routines, which are part of the operating system (OS), or realized within a coprocessor to free the operating system kernel from time consuming scheduling operations. Both kinds of implementations have to provide an application programmers interface that hides the algorithm from implementation issues. The target operating system of our framework is mainly RTLinux, eventhough development for those systems is possible under Linux as well as Windows-NT. The framework proposed in this paper is new in that it supports the selection of the right algorithm and the right implementation for the target platform based on real-time scheduling analy-