nils-herrmann/clean_scirepeval huggingface dataset:
QoS computation and policing in dynamic web service selection

The emerging Service-Oriented Computing (SOC) paradigm promises to enable businesses and organizations to collaborate in an unprecedented way by means of standard web services. To support rapid and dynamic composition of services in this paradigm, web services that meet requesters' functional requirements must be able to be located and bounded dynamically from a large and constantly changing number of service providers based on their Quality of Service (QoS). In order to enable quality-driven web service selection, we need an open, fair, dynamic and secure framework to evaluate the QoS of a vast number of web services. The fair computation and enforcing of QoS of web services should have minimal overhead but yet able to achieve sufficient trust by both service requesters and providers. In this paper, we presented our open, fair and dynamic QoS computation model for web services selection through implementation of and experimentation with a QoS registry in a hypothetical phone service provisioning market place application.
Fruit and vegetable consumption and waste in Australia Recommendations towards a food supply system framework

Recommendations towards a food supply system framework that will deliver healthy food in a sustainable way. In 2007, Emily Morgan was one of fifteen Americans to be granted a Fulbright Postgraduate Scholarship to Australia. A Tufts University postgraduate student and former Mount Holyoke College graduate, Emily carried out her Fulbright research on the relationship between food, health and the environment. This project was completed at VicHealth, under the direction of nutrition promotion and food policy expert Dr Tony Worsley and in collaboration with the School of Exercise and Nutrition Sciences at Deakin University. Fruit and Vegetable Consumption and Waste in Australia iii Contents Executive Summary 1 Preamble 4 Introduction 5 The Australian Food System 7 How do we conceptualize the food system? 7 The sectors of the food system 8 Challenges to improving the system 9 Major forces on the food system 10 The role of government 11 Recommendations 11 Consumption and Waste in Australia 12 How much is enough? 12 Consumption data 13 International data 13 National nutrition survey 13 National children's nutrition and physical activity survey 13 National health survey 14 State-based consumption data 14 Waste data 15 Recommendations 18 Drivers for change 19 Health and the link with fruit and vegetable consumption 19 Cancer 20 Cardiovascular disease 21 Diabetes 22 Other conditions 22 Environment and its relationship with the food system 24 Climate change 24 Water usage 29 Biodiversity conservation and ecosystem health 31 Ethics and the food system 32 Environmental ethics 32 Human ethics 32 Animal ethics 34 Economics and the future of the food system 35 Current efforts to change the paradigm 36 Efforts to increase fruit and vegetable consumption 36 International 36 'Go for 2 and 5 ® ' campaign 36 'Go for your life' 37 Other efforts 37 Efforts to minimize and better manage food waste 39 Minimizing food losses along the supply system 39 Better managing food losses along the supply system 42 Minimizing food losses at the consumer level 44 Better managing food losses at the consumer level 44 Whole-of-system approaches to improving the food system 45 Recommendations 47  Culture change 49 Summary of recommendations 51 References 53 Fruit and Vegetable Consumption and Waste in Australia 1 Executive Summary Food is essential to human existence and healthy, nutritious food is vital for living life to its full potential. What we eat and how we dispose of it not only …
A clustering fuzzy approach for image segmentation

Segmentation is a fundamental step in image description or classi1cation. In recent years, several computational models have been used to implement segmentation methods but without establishing a single analytic solution. However, the intrinsic properties of neural networks make them an interesting approach, despite some measure of ine5ciency. This paper presents a clustering approach for image segmentation based on a modi1ed fuzzy approach for image segmentation (ART) model. The goal of the proposed approach is to 1nd a simple model able to instance a prototype for each cluster avoiding complex post-processing phases. Results and comparisons with other similar models presented in the literature (like self-organizing maps and original fuzzy ART) are also discussed. Qualitative and quantitative evaluations con1rm the validity of the approach proposed. ? 2004 Pattern Recognition Society.
Subcortical loops through the basal ganglia

Parallel, largely segregated, closed-loop projections are an important component of cortical-basal ganglia-cortical connectional architecture. Here, we present the hypothesis that such loops involving the neocortex are neither novel nor the first evolutionary example of closed-loop architecture involving the basal ganglia. Specifically, we propose that a phylogenetically older, closed-loop series of subcortical connections exists between the basal ganglia and brainstem sensorimotor structures, a good example of which is the midbrain superior colliculus. Insofar as this organization represents a general feature of brain architecture, cortical and subcortical inputs to the basal ganglia might act independently, co-operatively or competitively to influence the mechanisms of action selection.
Automated colon cancer detection using hybrid of novel geometric features and some traditional features

Automatic classification of colon into normal and malignant classes is complex due to numerous factors including similar colors in different biological constituents of histopathological imagery. Therefore, such techniques, which exploit the textural and geometric properties of constituents of colon tissues, are desired. In this paper, a novel feature extraction strategy that mathematically models the geometric characteristics of constituents of colon tissues is proposed. In this study, we also show that the hybrid feature space encompassing diverse knowledge about the tissues׳ characteristics is quite promising for classification of colon biopsy images. This paper thus presents a hybrid feature space based colon classification (HFS-CC) technique, which utilizes hybrid features for differentiating normal and malignant colon samples. The hybrid feature space is formed to provide the classifier different types of discriminative features such as features having rich information about geometric structure and image texture. Along with the proposed geometric features, a few conventional features such as morphological, texture, scale invariant feature transform (SIFT), and elliptic Fourier descriptors (EFDs) are also used to develop a hybrid feature set. The SIFT features are reduced using minimum redundancy and maximum relevancy (mRMR). Various kernels of support vector machines (SVM) are employed as classifiers, and their performance is analyzed on 174 colon biopsy images. The proposed geometric features have achieved an accuracy of 92.62%, thereby showing their effectiveness. Moreover, the proposed HFS-CC technique achieves 98.07% testing and 99.18% training accuracy. The better performance of HFS-CC is largely due to the discerning ability of the proposed geometric features and the developed hybrid feature space.
The Impact of Gamification - Recommending Education Scenarios

Many students play (computer) games in their leisure time, thus acquiring skills which can easily be utilized when it comes to teaching more sophisticated knowledge. Nevertheless many educators today are wasting this opportunity. Some have evaluated gaming scenarios and methods for teaching students and have created the term “gamification”. This paper describes the history of this new term and explains the possible impact on teaching. It will take well-researched facts into consideration to discuss the potential of games. Moreover, scenarios will be illustrated and evaluated for educators to adopt and use on their own.
A repetitive high voltage pulse adder based on solid state switches

A repetitive high voltage pulse adder based on solid state switches with isolated recharge is described. All capacitors in the modulator are recharged separately through a corresponding magnetic core transformer by a common high frequency power supply. This circuit configuration simplifies the insulation design and arrangement. This scheme is suitable for high frequency pulse discharge due to its high charge efficiency. At the same time it retains the inherent switch protection capability similar to a solid-state Marx modulator. In our present work, a 22-stage test modulator has been built and successfully operated at output voltage of 20 kV with repetitive rate of 20 kHz, rise time of 150 ns and pulse width of 3 ¿s. The primary experiments verified the system feasibility.
Design of GaN-Based MHz Totem-Pole PFC Rectifier

The totem-pole bridgeless power factor correction (PFC) rectifier has recently been recognized as a promising front-end candidate for applications like servers and telecommunication power supplies. This paper begins with a discussion of the advantages of using emerging high-voltage gallium-nitride (GaN) devices in totem-pole PFC rectifiers rather than traditional PFC rectifiers. The critical-mode operation is used in the totem-pole PFC rectifier in order to achieve both high frequency and high efficiency. Then, several high-frequency issues and detailed design considerations are introduced, including extending zero-voltage-switching operation for the entire line-cycle, a variable on-time strategy for zero-crossing distortion suppression, and interleaving control for ripple current cancellation. The volume reduction of differential-mode electromagnetic interference filters is also presented, which benefits greatly from MHz high-frequency operation and multiphase interleaving. Finally, a dual-phase interleaved GaN-based MHz totem-pole PFC rectifier is demonstrated with 99% peak efficiency and 220 W/in $^{\mathrm {{3}}}$  power density.
Stochastic Simulation of Benign Avascular Tumour Growth Using the Potts Model

We simulate the growth of a benign avascular tumour embedded in normal tissue, including cell sorting that occurs between tumour and normal cells, due to the variation of adhesion between diierent cell types. The simulation uses the Potts Model, an energy minimisation method. Trial random movements of cell walls are checked to see if they reduce the adhesion energy of the tissue. These trials are then accepted with Boltzmann weighted probability. The simulated tumour initially grows exponentially, then forms three concentric shells as the nutrient level supplied to the core by diiusion decreases: the outer shell consists of live proliferating cells, the middle of quiescent cells and the centre is a necrotic core, where the nutrient concentration is below the critical level that sustains life. The growth rate of the tumour decreases at the onset of shell formation in agreement with experimental observation. The tumour eventually approaches a steady state, where the increase in volume due to the growth of the proliferating cells equals the loss of volume due to the disintegration of cells in the necrotic core. The nal thickness of the shells also agrees with experiment.
Type IV Pili are required for virulence, twitching motility, and biofilm formation of acidovorax avenae subsp. Citrulli.

Acidovorax avenae subsp. citrulli is the causal agent of bacterial fruit blotch (BFB), a threatening disease of watermelon, melon, and other cucurbits. Despite the economic importance of BFB, relatively little is known about basic aspects of the pathogen's biology and the molecular basis of its interaction with host plants. To identify A. avenae subsp. citrulli genes associated with pathogenicity, we generated a transposon (Tn5) mutant library on the background of strain M6, a group I strain of A. avenae subsp. citrulli, and screened it for reduced virulence by seed-transmission assays with melon. Here, we report the identification of a Tn5 mutant with reduced virulence that is impaired in pilM, which encodes a protein involved in assembly of type IV pili (TFP). Further characterization of this mutant revealed that A. avenae subsp. citrulli requires TFP for twitching motility and wild-type levels of biofilm formation. Significant reductions in virulence and biofilm formation as well as abolishment of twitching were also observed in insertional mutants affected in other TFP genes. We also provide the first evidence that group I strains of A. avenae subsp. citrulli can colonize and move through host xylem vessels.
Code And Input Files For "Slope Limiting The Velocity Field In A Discontinuous Galerkin Divergence Free Two Phase Flow Solver"

Solving the Navier-Stokes equations when the density field contains a large sharp discontinuity—such as a water/air free surface—is numerically challenging. Convective instabilities cause Gibbs oscillations which quickly destroy the solution. We investigate the use of slope limiters for the velocity field to overcome this problem in a way that does not compromise on the mass conservation properties. The equations are discretised using the interior penalty discontinuous Galerkin finite element method that is divergence free to machine precision. A slope limiter made specifically for exactly divergence free (solenoidal) fields is presented and used to illustrated the difficulties in obtaining convectively stable fields that are also exactly solenoidal. The lessons learned from this are applied in constructing a simpler method based on the use of an existing scalar slope limiter applied to each velocity component. We show by numerical examples how both presented slope limiting methods are vastly superior to the naive non-limited method. The methods can solve difficult two-phase problems with high density ratios and high Reynolds numbers—typical for marine and offshore water/air simulations—in a way that conserves mass and stops unbounded energy growth caused by the Gibbs phenomenon.
A parallel hybrid banded system solver: the SPIKE algorithm

This paper describes an efficient and robust hybrid parallel solver ‘‘the SPIKE algorithm’’ for narrow-banded linear systems. Two versions of SPIKE with their built-in-options are described in detail: the Recursive SPIKE version for handling non-diagonally dominant systems and the Truncated SPIKE version for diagonally dominant ones. These SPIKE schemes can be used either as direct solvers, or as preconditioners for outer iterative schemes. Both versions are faster than the direct solvers in ScaLAPACK on parallel computing platforms, and quite competitive in terms of achieved accuracy for handling systems that are dense within the band.
[Practical guide to the examination and interpretation of genital lesions of minor female victims of sexual assault].

Through a comprehensive review of the literature on sexual assault, the authors propose to clarify the different stages of the exam and help the practitioner to the forensic interpretation of lesions. The authors describe the basic principles that make consensus in how to interview victims in order to increase the reliability of the information collected. The various medical data that must be collected allowing to guide diagnosis (urogenital symptoms, sexual behaviour disorder) or facilitate the interpretation of lesions (age of puberty, use of tampons…) are specified as well as the different positions of examination and their association to other complementary techniques (Foley catheter, colposcopy, toluidine blue). The authors present a simple decision tree that can help the practitioner to interpret the laceration of the hymen. They detail the description and forensic interpretation of all genital lesions that may be encountered as a result of sexual assault, and the pitfalls to avoid. Finally, two main problems in the interpretation of lesions are described, the absence of injury after penetration and the accidental genital lesions.
Virtual network functions orchestration in wireless networks

Network Function Virtualization (NFV) is emerging as one of the most innovative concepts in the networking landscape. By migrating network functions from dedicated mid-dleboxes to general purpose computing platforms, NFV can effectively reduce the cost to deploy and to operate large networks. However, in order to achieve its full potential, NFV needs to encompass also the radio access network allowing Mobile Virtual Network Operators to deploy custom resource allocation solutions within their virtual radio nodes. Such requirement raises several challenges in terms of performance isolation and resource provisioning. In this work we formalize the Virtual Network Function (VNF) placement problem for radio access networks as an integer linear programming problem and we propose a VNF placement heuristic. Moreover, we also present a proof-of-concept implementation of an NFV management and orchestration framework for Enterprise WLANs. The proposed architecture builds upon a programmable network fabric where pure forwarding nodes are mixed with radio and packet processing nodes leveraging on general computing platforms.
Virtual students' laboratories in the physics practicum of the Technical University

The author has organized the project activities of computer modeling in teaching physics for IT students at the Novosibirsk State Technical University. The students' teams develop soft-ware products that are virtual counterparts of experimental setups. The developed programs can be used as interactive virtual labs that enhance the physics laboratory practicum. Participation in the project activities of computer modeling contributes to formation of the students' professional competencies in the early stages of education.
Quadcopter – Obstacle Detection and Collision Avoidance

A simple approach for obstacle detection and collision avoidance of an autonomous flying quadcopter using low-cost ultrasonic sensors and simple data fusion is presented here. The approach has been implemented and tested in a self-developed quadcopter and its evaluation shows the general realizability as well as the drawbacks of this approach. In this paper, we propose a complete MICRO-UNMANNED AERIAL VEHICLE (MUAV) platform including hardware setup and processing pipeline-that is able to perceive obstacles in (almost) all directions in its surrounding. In this paper, we propose a complete micro aerial vehicle platform—including hardware setup and processing pipeline—that is able to perceive obstacles in (almost) all directions in its surrounding. Quadcopter is equipped with ultrasonic sensor. All signals from sensors are processed by Arduino microcontroller board.  Output from Arduino microcontroller board used to control Quadcopter propellers.  Obstacle Detection, Collision Avoidance, PID controller programming, components.
The immunological life cycle of tuberculosis

Immune responses to Mycobacterium tuberculosis are only partially effective; they drive the bacteria into a latent state, but rarely eliminate them. Unfortunately, the latent state of M. tuberculosis is reversible, and reactivation tuberculosis is the source of most transmission. Studies in animal models and in humans have not yet yielded a comprehensive picture of the mechanisms or correlates of immunity to M. tuberculosis infection, or of why immunity fails to eradicate the pathogen. This Review proposes that there are distinct stages in the immune response to M. tuberculosis that form an 'immunological life cycle'. It is hoped that this thesis will provide a framework for investigation to understand immunity to M. tuberculosis and to guide tuberculosis vaccine discovery and development.
Robotic monitoring of power systems

Monitoring of electric power systems in real time for reliability, aging status, and presence of incipient faults requires distributed and centralized processing of large amounts of data from distributed sensor networks. To solve this task, cohesive multidisciplinary efforts are needed from such fields as sensing, signal processing, control, communications, optimization theory, and, more recently, robotics. This review paper focuses on one trend of power system monitoring, namely, mobile monitoring. The developments in robotic maintenance for power systems indicate significant potential of this technological approach. Authors discuss integration of several important relevant sensor technologies that are used to monitor power systems, including acoustic sensing, fringing electric field sensing, and infrared sensing.
Riemannian approach to batch normalization

Batch Normalization (BN) has proven to be an effective algorithm for deep neural network training by normalizing the input to each neuron and reducing the internal covariate shift. The space of weight vectors in the BN layer can be naturally interpreted as a Riemannian manifold, which is invariant to linear scaling of weights. Following the intrinsic geometry of this manifold provides a new learning rule that is more efficient and easier to analyze. We also propose intuitive and effective gradient clipping and regularization methods for the proposed algorithm by utilizing the geometry of the manifold. The resulting algorithm consistently outperforms the original BN on various types of network architectures and datasets.
Combined Holistic and Local Patches for Recovering 6D Object Pose

We present a novel method for recovering 6D object pose in RGB-D images. By contrast with recent holistic or local patch-based method, we combine holistic patches and local patches together to fulfil this task. Our method has three stages, including holistic patch classification, local patch regression and fine 6D pose estimation. In the first stage, we apply a simple Convolutional Neural Network (CNN) to classify all the sampled holistic patches from the scene image. After that, the candidate region of target object can be segmented. In the second stage, as proposed in Doumanoglou et al.  and Kehl et al. , a Convolutional Autoencoder (CAE) is employed to extract condensed local patch feature, and coarse 6D object pose can be estimated by the regression of feature voting. Finally, we apply Particle Swarm Optimization (PSO) to refine 6D object pose. Our method is evaluated on the LINEMOD dataset  and the Occlusion dataset [10, 5], and compared with the state-of-the-art on the same sequences. Experimental results show that our method has high precision and good performance under foreground occlusion and background clutter conditions.
Executing SPARQL queries over Mapped Document Store with SparqlMap-M

With the increasing adoption of NoSQL data base systems like MongoDB or CouchDB more and more applications store structured data according to a non-relational, document oriented model. Exposing this structured data as Linked Data is currently inhibited by a lack of standards as well as tools and requires the implementation of custom solutions. While recent efforts aim at expressing transformations of such data models into RDF in a standardized manner, there is a lack of approaches which facilitate SPARQL execution over mapped non-relational data sources. With SparqlMap-M we show how dynamic SPARQL access to non-relational data can be achieved. SparqlMap-M is an extension to our SPARQL-to-SQL rewriter SparqlMap that performs a (partial) transformation of SPARQL queries by using a relational abstraction over a document store. Further, duplicate data in the document store is used to reduce the number of joins and custom optimizations are introduced. Our showcase scenario employs the Berlin SPARQL Benchmark (BSBM) with different adaptions to a document data model. We use this scenario to demonstrate the viability of our approach and compare it to different MongoDB setups and native SQL.