nils-herrmann/clean_scirepeval huggingface dataset:
Grey wolf optimizer: a review of recent variants and applications

Grey wolf optimizer (GWO) is one of recent metaheuristics swarm intelligence methods. It has been widely tailored for a wide variety of optimization problems due to its impressive characteristics over other swarm intelligence methods: it has very few parameters, and no derivation information is required in the initial search. Also it is simple, easy to use, flexible, scalable, and has a special capability to strike the right balance between the exploration and exploitation during the search which leads to favourable convergence. Therefore, the GWO has recently gained a very big research interest with tremendous audiences from several domains in a very short time. Thus, in this review paper, several research publications using GWO have been overviewed and summarized. Initially, an introductory information about GWO is provided which illustrates the natural foundation context and its related optimization conceptual framework. The main operations of GWO are procedurally discussed, and the theoretical foundation is described. Furthermore, the recent versions of GWO are discussed in detail which are categorized into modified, hybridized and paralleled versions. The main applications of GWO are also thoroughly described. The applications belong to the domains of global optimization, power engineering, bioinformatics, environmental applications, machine learning, networking and image processing, etc. The open source software of GWO is also provided. The review paper is ended by providing a summary conclusion of the main foundation of GWO and suggests several possible future directions that can be further investigated.
Stride directed prefetching in scalar processors

The execution of numerically intensive programs presents a challenge to memory system designers. Numerical program execution can be accelerated by pipelined arithmetic units, but to be effective, must be supported by high speed memory access. A cache memory is a well known hardware mechanism used to reduce the average memory access latency. Numerical programs, however, often have poor cache performance. Stride directed prefetching has been proposed to improve the cache performance of numerical programs executing on a vector processor, This paper shows how this approach can be extended to a scalar processor by using a simple hardware mechanism, called a stride prediction table (SPT), to calculate the stride distances of array accesses made from within the loop body of a program. The results using selected programs from the PERFECT and SPEC benchmarks show that stride directed prefetching on a scalar processor can significantly reduce the cache miss rate of particular programs and a SPT need only a small number of entries to be effective. the cache miss ratio for the scalar execution of the matrix multiply for matrix sizes of 100 x 100. For comparison purposes the corresponding vector execution is also shown. The results were obtained using trace driven simulation of 2 4 Kbyte cache with block sizes of 8, 16,32 and 64 bytes. The traces are from executions on an Alliant FX/80. Each trace is for single processor execution where the scalar and vector versions are generated using compiler optimizations. Two miss ratios are shown for each execution; ALL means that all memory data references am simulated and MATRIX means that only references to matrix data (data size of 8 bytes) are simulated. There are 19 and 2.2 million references for scalar and vector executions respectively but only 4 and 2 million of these references are to matrix data. Note that the vector miss ratios are computed relative to the number of vector accesses and not the number of vector referencing instructions. For example, a vector instruction may load 32 elements but this is counted as 32 vector accesses.
WebVRGIS: WebGIS Based Interactive Online 3D Virtual Community

In this paper we present a WebVRGIS based Interactive On line 3D Virtual Community which is achieved based on WebGIS technology and web VR technology. It is Multi-Dimensional(MD) web geographic information system (WebGIS) based 3D interactive on line virtual community which is a virtual real-time 3D communication systems and web systems development platform. It is capable of running on a variety of browsers. In this work, four key issues are studied: (1) Multi-source MD geographical data fusion of the WebGIS, (2) scene combination with 3D avatar, (3) massive data network dispatch, and (4) multi-user avatar real-time interactive. Our system is divided into three modules: data preprocessing, background management and front end user interaction. The core of the front interaction module is packaged in the MD map expression engine 3GWebMapper and the free plug-in network 3D rendering engine WebFlashVR. We have evaluated the robustness of our system on three campus of Ocean University of China(OUC) as a testing base. The results shows high efficiency, easy to use and robustness of our system.
MHz GaN-based interleaved CRM bi-directional buck/boost converter with coupled inductor

This paper presents a high frequency high efficiency GaN device based interleaved critical current mode (CRM) bi-directional buck/boost converter with a coupled inductor. The switching frequency is continually driven to MHz range with GaN devices due to their small switching loss and driving loss, which greatly reduce the size of the passive components. The coupled inductor further reduces the core volume due to certain DC flux reductions. The equivalent inductance and the impact of the coupled inductor on the CRM buck-boost converter are analyzed in detail. The resonant period at CRM is less with a coupled inductor than with a non-coupled inductor, which is beneficial for high frequency operation. The soft-switching range and the circulating energy are both improved using a coupled inductor at CRM. Experimental results validate the theoretical analysis, and the coupled inductor prototype efficiency is 98.5% at 1MHz, which is 0.3% higher than a prototype with a non-coupled inductor.
Dermoscopy of poikilodermatous mycosis fungoides (MF).

the First Clinical College, Nanjing University of Chinese edicine, and Department of Dermatology, Affiliated Hospital Nanjing University of Chinese Medicine. orted in part by the National Natural Science Foundation of hina (Grant No. 81173400). licts of interest: None declared. int requests: Cheng Tan, MD, Department of Dermatology, ffiliated Hospital of Nanjing University of Chinese Medicine, 155 Hanzhong Road, Nanjing, China 210029.   0190-9622/$36.00 a 2015 by the American Academy of Dermatology, Inc.
Performance evaluation of Latent Dirichlet Allocation in text mining

This paper introduces three classic models of statistical topic models: Latent Semantic Indexing (LSI), Probabilistic Latent Semantic Indexing (PLSI) and Latent Dirichlet Allocation (LDA). Then a method of text classification based on LDA model is briefly described, which uses LDA model as a text representation method. Each document means a probability distribution of fixed latent topic sets. Next, Support Vector Machine (SVM) is chose as classification algorithm. Finally, the evaluation parameters in classification system of LDA with SVM are higher than other two methods which are LSI with SVM and VSM with SVM, showing a better classification performance.
High-Accuracy and Fast-Speed MPPT Methods for PV String Under Partially Shaded Conditions

The photovoltaic (PV) string under partially shaded conditions exhibits complex output characteristics, i.e., the current–voltage <inline-formula> <tex-math notation="LaTeX">$(I\mbox{--}V)$</tex-math></inline-formula> curve presents multiple current stairs, whereas the power–voltage <inline-formula> <tex-math notation="LaTeX">$(P\mbox{--}V)$</tex-math></inline-formula> curve shows multiple power peaks. Thus, the conventional maximum power point tracking (MPPT) method is not acceptable either on tracking accuracy or on tracking speed. In this paper, two global MPPT methods, namely, the search–skip–judge global MPPT (SSJ-GMPPT) and rapid global MPPT (R-GMPPT) methods are proposed in terms of reducing the searching voltage range based on comprehensive study of <inline-formula> <tex-math notation="LaTeX">$I\mbox{--}V$</tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$P\mbox{--}V$</tex-math></inline-formula> characteristics of PV string. The SSJ-GMPPT method can track the real maximum power point under any shading conditions and achieve high accuracy and fast tracking speed without additional circuits and sensors. The R-GMPPT method aims to enhance the tracking speed of long string with vast PV modules and reduces more than 90% of the tracking time that is consumed by the conventional global searching method. The improved performance of the two proposed methods has been validated by experimental results on a PV string. The comparison with other methods highlights the two proposed methods more powerful.
The Coach-Athlete Relationship Questionnaire (CART-Q): development and initial validation.

The purpose of the present study was to develop and validate a self-report instrument that measures the nature of the coach-athlete relationship. Jowett et al.'s (Jowett & Meek, 2000; Jowett, in press) qualitative case studies and relevant literature were used to generate items for an instrument that measures affective, cognitive, and behavioral aspects of the coach-athlete relationship. Two studies were carried out in an attempt to assess content, predictive, and construct validity, as well as internal consistency, of the Coach-Athlete Relationship Questionnaire (CART-Q), using two independent British samples. Principal component analysis and confirmatory factor analysis were used to reduce the number of items, identify principal components, and confirm the latent structure of the CART-Q. Results supported the multidimensional nature of the coach-athlete relationship. The latent structure of the CART-Q was underlined by the latent variables of coaches' and athletes' Closeness (emotions), Commitment (cognitions), and Complementarity (behaviors).
Opinion Mining on Social Media Data

Microblogging (Twitter or Facebook) has become a very popular communication tool among Internet users in recent years. Information is generated and managed through either computer or mobile devices by one person and is consumed by many other persons, with most of this user-generated content being textual information. As there are a lot of raw data of people posting real time messages about their opinions on a variety of topics in daily life, it is a worthwhile research endeavor to collect and analyze these data, which may be useful for users or managers to make informed decisions, for example. However this problem is challenging because a micro-blog post is usually very short and colloquial, and traditional opinion mining algorithms do not work well in such type of text. Therefore, in this paper, we propose a new system architecture that can automatically analyze the sentiments of these messages. We combine this system with manually annotated data from Twitter, one of the most popular microblogging platforms, for the task of sentiment analysis. In this system, machines can learn how to automatically extract the set of messages which contain opinions, filter out nonopinion messages and determine their sentiment directions (i.e. positive, negative). Experimental results verify the effectiveness of our system on sentiment analysis in real microblogging applications.
G.fast: evolving the copper access network

Continuous improvements in communication technologies over copper pair access networks have enabled hybrid fiber/copper access networks that provide ever increasing broadband data rates. Most recently, field trials have demonstrated that crosstalk cancellation, also referred to as vectoring, and bonding two pairs to push data rates of very high speed DSL above 100 Mb/s on a single copper pair and above 200 Mb/s on two copper pairs. Looking ahead, the G.fast project group of the ITU-T is currently defining a new copper access technology to provide aggregate (upstream and downstream) data rates of up to 1 Gb/s over distances up to 250 m. This article provides an overview of some key challenges that need to be addressed for G.fast.
Discourse-Aware Neural Rewards for Coherent Text Generation

In this paper, we investigate the use of discourse-aware rewards with reinforcement learning to guide a model to generate long, coherent text. In particular, we propose to learn neural rewards to model cross-sentence ordering as a means to approximate desired discourse structure. Empirical results demonstrate that a generator trained with the learned reward produces more coherent and less repetitive text than models trained with crossentropy or with reinforcement learning with commonly used scores as rewards.
Weakly Supervised Learning of Part Selection Model with Spatial Constraints for Fine-Grained Image Classification

Fine-grained image classification is challenging due to the large intra-class variance and small inter-class variance, aiming at recognizing hundreds of sub-categories belonging to the same basic-level category. Since two different subcategories is distinguished only by the subtle differences in some specific parts, semantic part localization is crucial for fine-grained image classification. Most previous works improve the accuracy by looking for the semantic parts, but rely heavily upon the use of the object or part annotations of images whose labeling are costly. Recently, some researchers begin to focus on recognizing sub-categories via weakly supervised part detection instead of using the expensive annotations. However, these works ignore the spatial relationship between the object and its parts as well as the interaction of the parts, both of them are helpful to promote part selection. Therefore, this paper proposes a weakly supervised part selection method with spatial constraints for fine-grained image classification, which is free of using any bounding box or part annotations. We first learn a whole-object detector automatically to localize the object through jointly using saliency extraction and co-segmentation. Then two spatial constraints are proposed to select the distinguished parts. The first spatial constraint, called box constraint, defines the relationship between the object and its parts, and aims to ensure that the selected parts are definitely located in the object region, and have the largest overlap with the object region. The second spatial constraint, called parts constraint, defines the relationship of the object’s parts, is to reduce the parts’ overlap with each other to avoid the information redundancy and ensure the selected parts are the most distinguishing parts from other categories. Combining two spatial constraints promotes parts selection significantly as well as achieves a notable improvement on fine-grained image classification. Experimental results on CUB-200-2011 dataset demonstrate the superiority of our method even compared with those methods using expensive annotations.
Dual Band-Notched Small Monopole Antenna With Novel Coupled Inverted U-Ring Strip and Novel Fork-Shaped Slit for UWB Applications

This letter proposes a novel, small, printed monopole antenna for ultrawideband (UWB) applications with dual band-notch function. By cutting an inverted fork-shaped slit in the ground plane, additional resonance is excited, and hence much wider impedance bandwidth can be produced. To generate dual band-notch characteristics, we use a coupled inverted U-ring strip in the radiating patch. The measured results reveal that the presented dual band-notch monopole antenna offers a wide bandwidth with two notched bands, covering all the 5.2/5.8-GHz WLAN, 3.5/5.5-GHz WiMAX, and 4-GHz C-bands. The proposed antenna has a small size of 12<formula formulatype="inline"><tex Notation="TeX">$\,\times\,$</tex> </formula>18 mm<formula formulatype="inline"><tex Notation="TeX">$^{2}$</tex> </formula> or about <formula formulatype="inline"><tex Notation="TeX">$0.15 \lambda \times 0.25 \lambda$</tex></formula> at 4.2 GHz (first resonance frequency), which has a size reduction of 28% with respect to the previous similar antenna. Simulated and measured results are presented to validate the usefulness of the proposed antenna structure UWB applications.
Capture-replay vs. programmable web testing: An empirical assessment during test case evolution

There are several approaches for automated functional web testing and the choice among them depends on a number of factors, including the tools used for web testing and the costs associated with their adoption. In this paper, we present an empirical cost/benefit analysis of two different categories of automated functional web testing approaches: (1) capture-replay web testing (in particular, using Selenium IDE); and, (2) programmable web testing (using Selenium WebDriver). On a set of six web applications, we evaluated the costs of applying these testing approaches both when developing the initial test suites from scratch and when the test suites are maintained, upon the release of a new software version. Results indicate that, on the one hand, the development of the test suites is more expensive in terms of time required (between 32% and 112%) when the programmable web testing approach is adopted, but on the other hand, test suite maintenance is less expensive when this approach is used (with a saving between 16% and 51%). We found that, in the majority of the cases, after a small number of releases (from one to three), the cumulative cost of programmable web testing becomes lower than the cost involved with capture-replay web testing and the cost saving gets amplified over the successive releases.
Impact of enterprise resource planning systems on management control systems and firm performance

October 2008 Received in revised form 12 February 2010 Accepted 24 February 2010 In this study, we extend existing research on enterprise resource planning systems by exploring the effects of enterprise system adoption on subsequent non-financial and financial performance of a firm. Specifically, we investigate the role of formal and informalmanagement control systems as mechanisms which mediate the effect of enterprise resource planning systems adoption onfirmperformance.Our empirical analyses are based on survey data drawn from70 Finnish business units. Overall, our findings demonstrate that formal types of management control systems act as intervening variables mediating the positive lagged effect between enterprise systems adoption and non-financial performance. Informal types of management control systems, however, do not show similar mediating effects. We also predict and find a significant relationship between non-financial and financial firm performance. These results are important because the evidence on the joint roles of enterprise systems and management control system on improving the firm performance is very limited in prior literature. Our results show that the use of enterprise systems results in improved firm performance in the long run, and that more formal than informal types of management controls help firms achieve future performance goals.
Real-time geometric deformation displacement maps using programmable hardware

Striving for photorealism, texture mapping, and its more advanced variations, bump and displacement mapping, have all become fundamental tools in computer graphics. Recently, the introduction of programmable graphics hardware has enabled the employment of displacement mapping in real-time applications. While displacement mapping facilitates the actual modification of the underlying geometry, it is constrained by being an injective mapping. Further, it is also limited because it usually maps the geometry of the (low-resolution) smooth base surfaces, typically by displacing their vertices. Drawing from recent work on deformation displacement mapping (DDM) , in this paper we offer real-time solutions to both these limitations. Our solutions make it possible to employ the DDM paradigm on programmable graphics hardware. By reversing the roles of the base surfaces and their geometric details, both the one-to-one constraint and the base surface resolution limitation are resolved. Furthermore, this role reversal also paves the way for other benefits such as a tremendous decrease in the memory consumption of geometric detail information in the DDM and the ability to animate the details over the base surface. We show that the presented scheme can be used effectively to generate highly complex renderings and animations, in real time, on modern graphics hardware. The capabilities of the proposed method are demonstrated for both rational parametric base surfaces and polygonal base surfaces.
Using Sampling and Queries to Extract Rules from Trained Neural Networks

Concepts learned by neural networks are dif-cult to understand because they are represented using large assemblages of real-valued parameters. One approach to understanding trained neural networks is to extract symbolic rules that describe their classiica-tion behavior. There are several existing rule-extraction approaches that operate by searching for such rules. We present a novel method that casts rule extraction not as a search problem, but instead as a learning problem. In addition to learning from training examples, our method exploits the property that networks can be eeciently queried. We describe algorithms for extracting both conjunctive and M-of-N rules, and present experiments that show that our method is more eecient than conventional search-based approaches.
A New Visual Speech Recognition Approach for RGB-D Cameras

Visual speech recognition remains a challenging topic due to various speaking characteristics. This paper proposes a new approach for lipreading to recognize isolated speech segments (words, digits, phrases, etc.) using both of 2D image and depth data. The process of the proposed system is divided into three consecutive steps, namely, mouth region tracking and extraction, motion and appearance descriptors (HOG and MBH) computing, and classification using the Support Vector Machine (SVM) method. To evaluate the proposed approach, three public databases (MIRACL-VC, Ouluvs, and CUAVE) were used. Speaker dependent and speaker independent settings were considered in the evaluation experiments. The obtained recognition results demonstrate that lipreading can be performed effectively, and the proposed approach outperforms recent works in the literature for the speaker dependent setting while being competitive for the speaker independent setting.
A circular polarizer designed with a dielectric septum loading

This paper presents a simple method to realize a circular polarizer by inserting a dielectric septum in the middle of the cylindrical waveguide. Since fixing slots are built to precisely locate the septum, dual-compensation slots are made in the orthogonal plane to balance the effects of the fixing slots. The measured axial ratio is smaller than 0.5 dB and the phase difference is flat in the frequency range from 60 to 62.25 GHz. In addition, the return losses are better than -13 dB for both E/sub x/ and E/sub y/ polarizations in the same frequency range. This design has the added advantage that poor phase differences resulting from fabrication error or an inaccurate dielectric constant can easily be improved by adjusting the length of the inserted dielectric septum.