nils-herrmann/clean_scirepeval huggingface dataset:
Design of PI Controller for Automatic Generation Control of Multi Area Interconnected Power System using Bacterial Foraging Optimization

Naresh Kumari , Nitin Malik , A. N. Jha , Gaddam Mallesham #*4 # Department of Electrical, Electronics and Communication Engineering, The NorthCap University, Gurgaon, India 1 nareshkumari@ncuindia.edu 2 nitinmalik77@gmail.com * Ex-Professor, Electrical Engineering, Indian Institute of Technology, New Delhi, India 3 anjha@ee.iitd.ac.in #* Department of Electrical Engineering, Osmania University, Hyderabad, India 4 gm.eed.cs@gmail.com
XML - Based Schema Definition for Support of Interorganizational Workflow

Commerce on the Internet is still seriously hindered by the lack of a common language for collaborative commercial activities. Although XML (Extendible Markup Language) allows trading partners to exchange semantic information electronically, it does not provide support for document routing. In this paper, we propose the design for an eXchangeable routing language (XRL) using XML syntax. Since XML is becoming a major international standard, it is understood widely. The routing schema in XRL can be used to support flexible routing of documents in the Internet environment. The formal semantics of XRL are expressed in terms of Petri nets and examples are used to demonstrate how it can be used for implementing inter-organizational electronic commerce applications.
NEUTROSOPHIC INDEX NUMBERS . Neutrosophic logic applied in the statistical indicators theory

Neutrosophic numbers easily allow modeling uncertainties of prices universe, thus justifying the growing interest for theoretical and practical aspects of arithmetic generated by some special numbers in our work. At the beginning of this paper, we reconsider the importance in applied research of instrumental discernment, viewed as the main support of the final measurement validity. Theoretically, the need for discernment is revealed by decision logic, and more recently by the new neutrosophic logic and by constructing neutrosophic-type index numbers, exemplified in the context and applied to the world of prices, and, from a practical standpoint, by the possibility to use index numbers in characterization of some cyclical phenomena and economic processes, e.g. inflation rate. The neutrosophic index numbers or neutrosophic indexes are the key topic of this article. The next step is an interrogative and applicative one, drawing the coordinates of an optimized discernment centered on neutrosophic-type index numbers. The inevitable conclusions are optimistic in relation to the common future of the index method and neutrosophic logic, with statistical and economic meaning and utility.
Effects of genotype and environment on the content and composition of phytochemicals and dietary fiber components in rye in the HEALTHGRAIN diversity screen.

The effects of genotype and environment on the content of bioactive components in rye were determined with four varieties being grown on one site for three years and on three additional sites in the third year and a fourth variety being included in all trials except year 1. Clear differences were observed in the extent to which the contents of dietary fiber components (arabinoxylan, beta-glucan, total dietary fiber) and phytochemicals (folates, alkylresorcinols, sterols, tocols, phenolic acids) varied between varieties and between the same varieties grown in different sites (United Kingdom, France, Hungary, Poland) and years (2005-2007 in Hungary), with sterols being the most stable and phenolic acids the least. However, no single variety could be selected as having the highest overall level of bioactive components or as being more stable in comparison across environments.
Model-Based Development of Self-Adaptive Autonomous Vehicles using the SMARDT Methodology

Cyber-physical systems are deeply intertwined with their corresponding environment through sensors and actuators. To avoid severe accidents with surrounding objects, testing the the behavior of such systems is crucial. Therefore, this paper presents the novel SMARDT (Specification Methodology Applicable to Requirements, Design, and Testing) approach to enable automated test generation based on the requirement specification and design models formalized in SysML. This paper presents and applies the novel SMARDT methodology to develop a self-adaptive software architecture dealing with controlling, planning, environment understanding, and parameter tuning. To formalize our architecture we employ a recently introduced homogeneous model-driven approach for component and connector languages integrating features indispensable in the cyber-physical systems domain. In a compelling case study we show the model driven design of a self-adaptive vehicle robot based on a modular and extensible architecture.
Neural Voice Cloning with a Few Samples

Voice cloning is a highly desired feature for personalized speech interfaces. We introduce a neural voice cloning system that learns to synthesize a person’s voice from only a few audio samples. We study two approaches: speaker adaptation and speaker encoding. Speaker adaptation is based on fine-tuning a multi-speaker generative model. Speaker encoding is based on training a separate model to directly infer a new speaker embedding, which will be applied to a multi-speaker generative model. In terms of naturalness of the speech and similarity to the original speaker, both approaches can achieve good performance, even with a few cloning audios. 2 While speaker adaptation can achieve slightly better naturalness and similarity, cloning time and required memory for the speaker encoding approach are significantly less, making it more favorable for low-resource deployment.
Epidermolytic hyperkeratosis with rickets.

A 6-year-old child presented with generalized hyperkeratosis, most marked over the flexures; windswept deformity of the legs; and limping since 3 years. On the basis of the clinical, histopathologic and biochemical findings, he was diagnosed as a case of epidermolytic hyperkeratosis with rickets. He was treated with parenteral vitamin D3 and calcium supplements orally. Nutritional rickets has been reported in children with various types of ichthyosis like lamellar and X-linked types. We report this case of epidermolytic hyperkeratosis with rickets for its rarity.
Lane-Change Detection From Steering Signal Using Spectral Segmentation and Learning-Based Classification

In order to formulate a high-level understanding of driver behavior from massive naturalistic driving data, an effective approach is needed to automatically process or segregate data into low-level maneuvers. Besides traditional computer vision processing, this study addresses the lane-change detection problem by using vehicle dynamic signals (steering angle and vehicle speed) extracted from the CAN-bus, which is collected with 58 drivers around Dallas, TX area. After reviewing the literature, this study proposes a machine learning-based segmentation and classification algorithm, which is stratified into three stages. The first stage is preprocessing and prefiltering, which is intended to reduce noise and remove clear left and right turning events. Second, a spectral time-frequency analysis segmentation approach is employed to generalize all potential time-variant lane-change and lane-keeping candidates. The final stage compares two possible classification methods—1) dynamic time warping feature with k -nearest neighbor classifier and 2) hidden state sequence prediction with a combined hidden Markov model. The overall optimal classification accuracy can be obtained at 80.36% for lane-change-left and 83.22% for lane-change-right. The effectiveness and issues of failures are also discussed. With the availability of future large-scale naturalistic driving data, such as SHRP2, this proposed effective lane-change detection approach can further contribute to characterize both automatic route recognition as well as distracted driving state analysis.
DEM GENERATION FROM VERY HIGH RESOLUTION STEREO DATA IN URBAN AREAS

In this article an attempt for improving an existing method creating DEMs fully automatically from stereoscopic image pairs is presented. Results applying this method to very high resolution (VHR) satellite imagery is shown. The herein discussed “column” algorithm is illustrated in brief and compared to a conventional algorithm frequently used in generating DEMs from satellite line scanner data. The presented algorithm is producing DEMs with an improved matching of steep objects as can be found in urban satellite imagery but introduces also some blunders in the generated DEMs.
Application of CRISPR/Cas9 in plant biology

The CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated proteins) system was first identified in bacteria and archaea and can degrade exogenous substrates. It was developed as a gene editing technology in 2013. Over the subsequent years, it has received extensive attention owing to its easy manipulation, high efficiency, and wide application in gene mutation and transcriptional regulation in mammals and plants. The process of CRISPR/Cas is optimized constantly and its application has also expanded dramatically. Therefore, CRISPR/Cas is considered a revolutionary technology in plant biology. Here, we introduce the mechanism of the type II CRISPR/Cas called CRISPR/Cas9, update its recent advances in various applications in plants, and discuss its future prospects to provide an argument for its use in the study of medicinal plants.
Electrically conductive lines on cellulose nanopaper for flexible electrical devices.

Highly conductive circuits are fabricated on nanopapers composed of densely packed 15-60 nm wide cellulose nanofibers. Conductive materials are deposited on the nanopaper and mechanically sieved through the densely packed nanofiber networks. As a result, their conductivity is enhanced to the level of bulk silver and LED lights are successfully illuminated via these metallic conductive lines on the nanopaper. Under the same deposition conditions, traditional papers consisting of micro-sized pulp fibers produced very low conductivity lines with non-uniform boundaries because of their larger pore structures. These results indicate that advanced, lightweight and highly flexible devices can be realized on cellulose nanopaper using continuous deposition processes. Continuous deposition on nanopaper is a promising approach for a simple roll-to-roll manufacturing process.
A framework for cost based optimization of hybrid CPU/GPU query plans in database systems

Current database research identified the use of computational power of GPUs as a way to increase the performance of database systems. As GPU algorithms are not necessarily faster than their CPU counterparts, it is important to use the GPU only if it will be beneficial for query processing. In a general database context, only few research projects address hybrid query processing, i.e., using a mix of CPUand GPU-based processing to achieve optimal performance. In this paper, we extend our CPU/GPU scheduling framework to support hybrid query processing in database systems. We point out fundamental problems and propose an algorithm to create a hybrid query plan for a query using our scheduling framework. Additionally, we provide cost metrics, which consider the possible overlapping of data transfers and computation on the GPU. Furthermore, we present algorithms to create hybrid query plans for query sequences and query trees.
FurcaNet: An end-to-end deep gated convolutional, long short-term memory, deep neural networks for single channel speech separation

Deep gated convolutional networks have been proved to be very effective in single channel speech separation. However current state-of-the-art framework often considers training the gated convolutional networks in time-frequency (TF) domain. Such an approach will result in limited perceptual score, such as signal-to-distortion ratio (SDR) upper bound of separated utterances and also fail to exploit an end-to-end framework. In this paper we present an integrated simple and effective end-to-end approach to monaural speech separation, which consists of deep gated convolutional neural networks (GCNN) that takes the mixed utterance of two speakers and maps it to two separated utterances, where each utterance contains only one speaker’s voice. In addition long shortterm memory (LSTM) is employed for long term temporal modeling. For the objective, we propose to train the network by directly optimizing utterance level SDR in a permutation invariant training (PIT) style. Our experiments on the public WSJ0-2mix data corpus demonstrate that this new scheme can produce more discriminative separated utterances and leading to performance improvement on the speaker separation task.
Facial Expression Recognition

Facial expressions are the facial changes in response to a person’s internal emotional states, intentions, or social communications. Facial expression analysis has been an active research topic for behavioral scientists since the work of Darwin in 1872 [21, 26, 29, 83]. Suwa et al.  presented an early attempt to automatically analyze facial expressions by tracking the motion of 20 identified spots on an image sequence in 1978. After that, much progress has been made to build computer systems to help us understand and use this natural form of human communication [5, 7, 8, 17, 23, 32, 43, 45, 57, 64, 77, 92, 95, 106–108, 110]. In this chapter, facial expression analysis refers to computer systems that attempt to automatically analyze and recognize facial motions and facial feature changes from visual information. Sometimes the facial expression analysis has been confused with emotion analysis in the computer vision domain. For emotion analysis, higher level knowledge is required. For example, although facial expressions can convey emotion, they can also express intention, cognitive processes, physical effort, or other intraor interpersonal meanings. Interpretation is aided by context, body gesture, voice, individual differences, and cultural factors as well as by facial configuration and timing [11, 79, 80]. Computer facial expression analysis systems need to analyze the facial actions regardless of context, culture, gender, and so on.
Unexpected Effects of Activator Molecules' Polarity on the Electroreological Activity of Titanium Dioxide Nanopowders.

Titanium dioxide nanoparticles, obtained using the sol-gel method and modified with organic solvents, such as acetone, acetonitrile, benzene, diethyl ether, dimethyl sulfoxide, toluene, and chloroform, were used as the filler of polydimethylsiloxane-based electrorheological fluids. The effect of electric field strength on the shear stress and yield stress of electrorheological fluids was investigated, as well as the spectra of their dielectric relaxation in the frequency range from 25 to 106 Hz. Modification of titanium dioxide by polar molecules was found to enhance the electrorheological effect, as compared with unmodified TiO2, in accordance with the widely accepted concept of polar molecule dominated electrorheological effect (PM-ER). The most unexpected result of this study was an increase in the electrorheological effect during the application of nonpolar solvents with zero or near-zero dipole moments as the modifiers. It is suggested that nonpolar solvents, besides providing additional polarization effects at the filler particles interface, alter the internal pressure in the gaps between the particles. As a result, the filler particles are attracted to one another, leading to an increase in their aggregation and the formation of a network of bonds between the particles through liquid bridge contacts. Such changes in the electrorheological fluid structure result in a significant increase in the mechanical strength of the structures that arise when an electric field is applied, and an increase in the observed electrorheological effect in comparison with the unmodified titanium dioxide.
Automatic Detection Of Causal Relations For Question Answering

Causation relations are a pervasive feature of human language. Despite this, the automatic acquisition of causal information in text has proved to be a difficult task in NLP. This paper provides a method for the automatic detection and extraction of causal relations. We also present an inductive learning approach to the automatic discovery of lexical and semantic constraints necessary in the disambiguation of causal relations that are then used in question answering. We devised a classification of causal questions and tested the procedure on a QA system.
Mapping the complex topological organization of the human parietal face area

The macaque monkey ventral intraparietal area (VIP) contains neurons with aligned visual-tactile receptive fields anchored to the face and upper body. Our previous fMRI studies using standard head coils found a human parietal face area (VIP+ complex; putative macaque VIP homologue) containing superimposed topological maps of the face and near-face visual space. Here, we construct high signal-to-noise surface coils and used phase-encoded air puffs and looming stimuli to map topological organization of the parietal face area at higher resolution. This area is consistently identified as a region extending between the superior postcentral sulcus and the upper bank of the anterior intraparietal sulcus (IPS), avoiding the fundus of IPS. Using smaller voxel sizes, our surface coils picked up strong fMRI signals in response to tactile and visual stimuli. By analyzing tactile and visual maps in our current and previous studies, we constructed a set of topological models illustrating commonalities and differences in map organization across subjects. The most consistent topological feature of the VIP+ complex is a central-anterior upper face (and upper visual field) representation adjoined by lower face (and lower visual field) representations ventrally (laterally) and/or dorsally (medially), potentially forming two subdivisions VIPv (ventral) and VIPd (dorsal). The lower visual field representations typically extend laterally into the anterior IPS to adjoin human area AIP, and medially to overlap with the parietal body areas at the superior parietal ridge. Significant individual variations are then illustrated to provide an accurate and comprehensive view of the topological organization of the parietal face area.
Research on Combining Scrum with CMMI in Small and Medium Organizations

Agile method Scrum can effectively resolve numerous problems encountered when Capability Maturity Model Integration(CMMI) is implemented in small and medium software development organizations, but some special needs are hard to be satisfied. According to small and medium organizations' characteristic, the paper analyzes feasibility of combining Scrum and CMMI in depth. It is useful for organizations that build a new project management framework based on both CMMI and Scrum practices.
The future vision of simulation in healthcare.

Simulation is a technique-not a technology-to replace or amplify real experiences with guided experiences that evoke or replicate substantial aspects of the real world in a fully interactive manner. The diverse applications of simulation in healthcare can be categorized by 11 dimensions: aims and purposes of the simulation activity; unit of participation; experience level of participants; healthcare domain; professional discipline of participants; type of knowledge, skill, attitudes, or behaviors addressed; the simulated patient's age; technology applicable or required; site of simulation; extent of direct participation; and method of feedback used. Using simulation to improve safety will require full integration of its applications into the routine structures and practices of healthcare. The costs and benefits of simulation are difficult to determine, especially for the most challenging applications, where long-term use may be required. Various driving forces and implementation mechanisms can be expected to propel simulation forward, including professional societies, liability insurers, healthcare payers, and ultimately the public. The future of simulation in healthcare depends on the commitment and ingenuity of the healthcare simulation community to see that improved patient safety using this tool becomes a reality.
Fuzzy Neural Network PID Control for Electric Power Steering System

The automobile mathematical model is established on the analysis to the automobile electric power steering system (EPS) structural style and the performance. In order to solve the problem that the most automobile power steering is difficult to determine the PID controller parameter, the article uses the fuzzy neural network PID control in EPS. Through the simulation of PID control and the fuzzy neural network PID control computation, the test result indicated that, fuzzy neural network PID the control EPS system has a better robustness compared to traditional PID the control EPS, can improve EPS effectively the steering characteristic and the automobile changes characteristic well.
A Neural Network Approach to Missing Marker Reconstruction in Human Motion Capture

Optical motion capture systems have become a widely used technology in various fields, such as augmented reality, robotics, movie production, etc. Such systems use a large number of cameras to triangulate the position of optical markers. The marker positions are estimated with high accuracy. However, especially when tracking articulated bodies, a fraction of the markers in each timestep is missing from the reconstruction. In this paper, we propose to use a neural network approach to learn how human motion is temporally and spatially correlated, and reconstruct missing markers positions through this model. We experiment with two different models, one LSTM-based and one time-window-based. Both methods produce state-of-the-art results, while working online, as opposed to most of the alternative methods, which require the complete sequence to be known. The implementation is publicly available at https://github.com/Svitozar/NN-for-Missing-Marker-Reconstruction.
Euler number of the compactified Jacobian and multiplicity of rational curves

In this paper we show that the Euler number of the compactified Jacobian of a rational curve C with locally planar singularities is equal to the multiplicity of the δ-constant stratum in the base of a semi-universal deformation of C. In particular, the multiplicity assigned by Yau, Zaslow and Beauville to a rational curve on a K3 surface S coincides with the multiplicity of the normalisation map in the moduli space of stable maps to S.  Let C be a reduced and irreducible projective curve with singular set Σ ⊂ C and let n : C̃ −→ C be its normalisation. The generalised Jacobian JC of C is an extension of JC̃ by an affine commutative group of dimension δ := dimH0(n∗(OC̃)/OC) = ∑