nils-herrmann/clean_scirepeval huggingface dataset:
Warm Glow or Extra Charge? The Ambivalent Effect of Corporate Social Responsibility Activities on Customers' Perceived Price Fairness

Prior research has firmly established that consumers draw benefits from a firm's engagement in corporate social responsibility (CSR) especially the feeling of a "warm glow." These benefits positively affect several desirable outcomes, such as willingness to pay and customer loyalty. The authors propose that consumers do not blindly perceive benefits from a firm's CSR engagement but tend to suspect that a firm's prices include a markup to finance the CSR engagement. Taking customers' benefit perceptions and price markup inferences into account, the authors suggest that CSR engagement has mixed effects on consumers' evaluation of price fairness and, thus, on subsequent outcomes such as customer loyalty. The authors conduct one qualitative study and four quantitative studies leveraging longitudinal field and experimental data from more than 4,000 customers and show that customers indeed infer CSR price markups, entailing mixed effects of firms' CSR engagement on price fairness. The authors find that perception critically depends on customers' CSR attributions, and they explore the underlying psychological mechanisms. They propose communication strategies to optimize the effect of CSR engagement on perceived price fairness.
Antifouling pseudo zwitterionic poly(vinylidene fluoride) membranes with efficient mixed charge surface grafting via glow dielectric barrier discharge plasma induced copolymerization

This work reports on the glow dielectric barrier discharge (GDBD) plasma induced surface grafting of poly(vinylidene fluoride) (PVDF) membranes with mixed charge copolymers of [2 (methacryloyloxy)ethyl] trimethylammonium (TMA) and sulfopropyl methacrylate (SA) The aim is to investigate the antifouling properties and the hemocompatibility of this system. We first characterize the physico chemical properties of the membranes. With SA alone in the coating solution, efficient grafting cannot be achieved as monomer is blown away during grafting. Membranes grafted with a mixture of SA and TMA, or TMA alone do not meet this problem and grafting density ranged between 0.29 and 0.41 mg/cm2. Bovine serum albumin and lysozyme adsorption tests (70% reduction) and Escherichia coli attachment test (annihilation of adhesion) unveil that pseudo zwitterionic PVDF membranes are very efficient to reduce biofouling in static condition. Different fouling resistance behaviors are observed in dynamic conditions. Permeability of virgin membranes progressively decreases over the cycles, arising from a gradual pore blockage and irreversible fouling. All potential adsorption sites of pseudo zwitterionic membrane and membrane with positive charge bias are fouled after the first cycle, and flux recovery is maximal in the following cycles. This behavior is ascribed to the lack of homogeneity of the surface grafting. Finally, pseudo zwitterionic membranes are hemocompatible (resistance to blood cells, low hemolysis activity) Provided a better tuning of surface uniformity, the method and system presented in this work are a promising approach to the new generation of antifouling mixed charge membranes for water treatment or blood contacting devices.
An Overview of Various Improvements of DBSCAN Algorithm in Clustering Spatial Databases

2  Clustering is an important data mining method for knowledge discovery in large databases. It is an exploratory data analysis tool which aims at categorizing different objects into groups (clusters) in such a way that the degree of association between two objects is high if they belong to the same group and low otherwise. Discovering clusters in spatial data is a challenging one because of its complexity nature. The clusters in spatial data are of different sizes, shapes and densities, and also contain noise and outliers. Different clustering techniques have been proposed for knowledge discovery from spatial databases. DBSCAN (Density Based Spatial Clustering of Applications with Noise) algorithm is a traditional and well known density based clustering method. It defines a cluster as a maximal set of density connected points. It can detect clusters of arbitrary shapes and filter out noise effectively. The clusters which are formed based on density are easy understandable and it does not limit the shapes. Besides its popularity, DBSCAN needs some improvements for better results. In this paper, we have analyzed and presented various significant enhancements of DBSCAN algorithm for our evaluation.
A non parametric k nearest neighbour entropy estimator
Venue: Physical review. E

A nonparametric k nearest neighbor based entropy estimator is proposed. It improves on the classical Kozachenko Leonenko estimator by considering nonuniform probability densities in the region of k nearest neighbors around each sample point. It aims to improve the classical estimators in three situations: first, when the dimensionality of the random variable is large; second, when near functional relationships leading to high correlation between components of the random variable are present; and third, when the marginal variances of random variable components vary significantly with respect to each other. Heuristics on the error of the proposed and classical estimators are presented. Finally, the proposed estimator is tested for a variety of distributions in successively increasing dimensions and in the presence of a near functional relationship. Its performance is compared with a classical estimator, and a significant improvement is demonstrated.
A robust method for elevator operation in semi outdoor environment for mobile robot transportation system in life science laboratories
Venue: 2016 IEEE 20th Jubilee International Conference on Intelligent Engineering Systems (INES)

A new robust method is developed for elevator operation in semi outdoor environment for mobile robot transportation systems in life science laboratories. Elevator operation includes the entry button detection, floor button recognition, and reading of current floor information. Different techniques have been employed for the elevator operation including HSL color representation, adaptive binary threshold filter, and optical character recognition. In addition to these techniques an enhancement function has been developed to combat the direct sunlight effect in the Kinect vision sensor. Button panel landmarks were adopted to minimize the false positive measurements in internal button detection. The implemented system approves an efficient performance with a high success rate under different light conditions.
ANALISA TEKNIS PENGGUNAAN SERAT DAUN NANAS SEBAGAI ALTERNATIF BAHAN KOMPOSIT PEMBUATAN KULIT KAPAL DITINJAU DARI KEKUATAN TARIK, BENDING DAN IMPACT

Serat daun nanas saat ini banyak digunakan dalam industri industri mebel dan kerajinan rumah tangga (UKM) karena selain mudah didapat, murah, tidak membahayakan kesehatan, dapat mengurangi polusi lingkungan sehingga nantinya dengan pemanfaatan sebagai serat penguat komposit mampu mengatasi permasalahan lingkungan. Dari pertimbangan diatas maka penelitian ini dilakukan untuk mendapatkan analisa teknis berupa kekuatan tarik, bending dan impak dari komposit berpenguat serat daun nanas dengan perlakuan pola anyaman variasi arah serat sudut bersilangan 0deg, 11.25deg, 22.50deg dan 45deg. Sebagai matrik resin polyester Dari hasil pengujian spesimen dilakukan analisa kekuatan tarik, bending dan impak kemudian dibandingkan dengan nilai yang di ijinkan oleh Biro Klasifikasi Indonesia sebagai tolak ukur standar ujinya. Pengujian komposit berpenguat serat daun nanas membandingkan arah serat sudut 0deg, 11.25deg, 22.50deg dan 45deg, perlakuan serat pola anyaman, fraksi volume 70% matriks polyester dan 30% serat daun nanas, dengan metode hand lay up hasil pengujian didapat nilai kekuatan tarik tertinggi dimiliki oleh komposit dengan arah sudut 45deg rata rata kuat tariknya 34.8 Mpa dan rata rata modulus elastisitasnya 6088.16 Mpa, sedangkan nilai kekuatan uji bending tertinggi pada sudut 22.50deg dengan nilai rata rata 144.08 Mpa dan nilai uji impact tertinggi pada sudut 45deg dengan nilai 0.0375 joule/mm 2 Hasil pengujian menunjukan bahwa kekuatan tarik, modulus elastisitas dan kekuatan uji bending tertinggi dari komposit berpenguat serat daun nanas belum dapat memenuhi ketentuan peraturan kekuatan tarik dan modulus elastisitas dari BKI yang mempunyai nilai standar kekuatan tarik 100 Mpa, modulus elastisitas 7000 Mpa dan kekuatan bending 150 Mpa.
Triangle Based Representative Possible Worlds of Uncertain Graphs
Venue: DASFAA

Uncertain graph data has been collected, processed and analyzed in a wide range of applications. Under the possible world model, an uncertain graph represents a probability distribution over all its possible worlds. Each possible world is a deterministic graph in which the uncertain graph may be present in practice. To deal with the hardness of computations on uncertain graphs, Parchas et al. first proposed the concept of a degree based representative possible world. This approach is distinguished from the sampling approach in that it computes on one representative possible world instead of on a large number of possible worlds sampled at random. However, the degree based representative possible world only tries to preserve vertex degrees. In this paper, we are motivated by the fact that motif structures such as triangles can affect the structural properties of graphs and propose the concept of a triangle based representative possible world. We also develop an algorithm for finding the triangle based representative possible world of an uncertain graph. We conducted extensive experimental evaluations and show that the triangle based representative possible world outperforms the degree based representative possible world in preserving the structural characteristics of an uncertain graph in expectation.
On the Conjecture of Lehmer, Limit Mahler Measure of Trinomials and Asymptotic Expansions

Let n 2 be an integer and denote by thn the real root in (0, 1) of the trinomial Gn(X) 1 X Xn. The sequence of Perron numbers (thn 1)n>=2 \theta _n^ 1} )_{n \ge 2} tends to 1. We prove that the Conjecture of Lehmer is true for {thn 1|n>=2} \theta _n^ 1} |n \ge 2\ by the direct method of Poincare asymptotic expansions (divergent formal series of functions) of the roots thn, zj,n, of Gn(X) lying in |z| 1, as a function of n, j only. This method, not yet applied to Lehmer's problem up to the knowledge of the author, is successfully introduced here. It first gives the asymptotic expansion of the Mahler measures M(Gn)=M(thn)=M(thn 1) \rm{M}(G_n \rm{M}\theta _n \rm{M}\theta _n^ 1} of the trinomials Gn as a function of n only, without invoking Smyth's Theorem, and their unique limit point above the smallest Pisot number. Comparison is made with Smyth's, Boyd's and Flammang's previous results. By this method we obtain a direct proof that the conjecture of Schinzel Zassenhaus is true for {thn 1|n>=2} \theta _n^ 1} |n \ge 2\ with a minoration of the house and a minoration of the Mahler measure M(Gn) better than Dobrowolski's one. The angular regularity of the roots of Gn, near the unit circle, and limit equidistribution of the conjugates, for n tending to infinity (in the sense of Bilu, Petsche, Pritsker) towards the Haar measure on the unit circle, are described in the context of the Erdos Turan Amoroso Mignotte theory, with uniformly bounded discrepancy functions.
Battery Energy Storage System Applied to Wind Power System Based On Z Source Inverter Connected to Grid

This paper presents a wind power generation system (WPGS) with battery energy storage system (BESS) based on the Z source inverter (ZSI) with simple boost control. Wind turbines using the squirrel cage induction generator (SCIG) are widely accepted due to their robustness, simplicity, light weight and low cost. The SCIG is connected to the power grid through voltage source converters VSC, and the WPGS is reinforced by the BESS in order to keep grid power balance. The BESS has a battery bank, which is integrated with the system through a bidirectional DC DC converter (buck boost) Moreover, the ZSI is an alternative power conversion topology that can both (buck boost) the input voltage using passive components. The operation of ZSI is analyzed, and the active and reactive power decoupling method is proposed for a double closed loop control system, which ensures the stability in voltage capacitor of ZSI. Also, the traditional sine pulse width modulation technique is modified to achieve the shoot through characteristic of ZSI. The proposed system has high performance, minimal component count, increased efficiency and reduced cost. Simulation results verify the efficacy of the proposed control strategies.
Battery Energy Storage System Applied to Wind Power System Based On Z Source Inverter Connected to Grid
Venue: IEEE Latin America Transactions

This paper presents a wind power generation system (WPGS) with battery energy storage system (BESS) based on the Z source inverter (ZSI) with simple boost control. Wind turbines using the squirrel cage induction generator (SCIG) are widely accepted due to their robustness, simplicity, light weight and low cost. The SCIG is connected to the power grid through voltage source converters VSC, and the WPGS is reinforced by the BESS in order to keep grid power balance. The BESS has a battery bank, which is integrated with the system through a bidirectional DC DC converter (buck boost) Moreover, the ZSI is an alternative power conversion topology that can both (buck boost) the input voltage using passive components. The operation of ZSI is analyzed, and the active and reactive power decoupling method is proposed for a double closed loop control system, which ensures the stability in voltage capacitor of ZSI. Also, the traditional sine pulse width modulation technique is modified to achieve the shoot through characteristic of ZSI. The proposed system has high performance, minimal component count, increased efficiency and reduced cost. Simulation results verify the efficacy of the proposed control strategies.
Multifunctional coatings to simultaneously promote osseointegration and prevent infection of orthopaedic implants.
Venue: Biomaterials

The two leading causes of failure for joint arthroplasty prostheses are aseptic loosening and periprosthetic joint infection. With the number of primary and revision joint replacement surgeries on the rise, strategies to mitigate these failure modes have become increasingly important. Much of the recent work in this field has focused on the design of coatings either to prevent infection while ignoring bone mineralization or vice versa, to promote osseointegration while ignoring microbial susceptibility. However, both coating functions are required to achieve long term success of the implant; therefore, these two modalities must be evaluated in parallel during the development of new orthopaedic coating strategies. In this review, we discuss recent progress and future directions for the design of multifunctional orthopaedic coatings that can inhibit microbial cells while still promoting osseointegration.
Privacy Preserving Probabilistic Record Linkage Using Locality Sensitive Hashes
Venue: DBSec

As part of increased efforts to provide precision medicine to patients, large clinical research networks (CRNs) are building regional and national collections of electronic health records (EHRs) and patient reported outcomes (PROs) To protect patient privacy, each data contributor to the CRN (for example, a health care provider) uses anonymizing and encryption technology before publishing the data. An important problem in such CRNs involves linking records of the same patient across multiple source databases. Unfortunately, in practice, the records to be matched often contain typographic errors and inconsistencies arising out of formatting and pronunciation incompatibilities, as well as incomplete information. When encryption is applied on these records, similarity search for record linkage is rendered impossible. The central idea behind our work is to create characterizing signatures for the linkage of attributes of each record using minhashes and locality sensitive hash functions before encrypting those attributes. Then, using a privacy preserving record linkage protocol we perform probabilistic matching based on Jaccard similarity measure. We have developed a proof of concept for this protocol and we show some experimental results based on synthetic, but realistic, data.
Energy management method for photovoltaic DC micro grid system based on power tracking control
Venue: IECON 2016 42nd Annual Conference of the IEEE Industrial Electronics Society

In order to reduce the impact of high penetration of renewable energy on the utility grid and suppress the influence of micro grid power fluctuation on power quality, a power tracking control strategy for DC micro grid has been studied. And a novel energy management method based on this control strategy has been designed. The DC micro grid, which contains renewable energy and hybrid energy storage unit, is used to build a complete control system model according to the DPS and its control system model. The power tracking control strategy has been analyzed and designed based on frequency domain method. With the designed control strategy, the system can realize coordinated operation of the hybrid energy storage unit by absorbing the load power fluctuation within different frequency range. Furthermore, the system is controlled to absorb/deliver predefined amount of power from/to the utility grid under the grid connected mode and zero power under the islanding mode. In this way, smooth switching between different modes and the stable operation of the micro grid are realized. Finally, the function of the system is verified with an emulated DC micro grid system.
Constrained creation of poetic forms during theme driven exploration of a domain defined by an N gram model
Venue: Connect. Sci.

Most poetry generation systems apply opportunistic approaches where algorithmic procedures are applied to explore the conceptual space defined by a given knowledge resource in search of solutions that might be aesthetically valuable. Aesthetical value is assumed to arise from compliance to a given poetic form such as rhyme or metrical regularity or from evidence of semantic relations between the words in the resulting poems that can be interpreted as rhetorical tropes such as similes, analogies, or metaphors. This approach tends to fix a priori the aesthetic parameters of the results, and imposes no constraints on the message to be conveyed. The present paper describes an attempt to initiate a shift in this balance, introducing means for constraining the output to certain topics and allowing a looser mechanism for constraining form. This goal arose as a result of the need to produce poems for a themed collection commissioned to be included in a book. The solution adopted explores an approach to creativity where the goals are not solely aesthetic and where the results may be surprising in their poetic form. An existing computer poet, originally developed to produce poems in a given form but with no specific constraints on their content, is put to the task of producing a set of poems with explicit restrictions on content, and allowing for an exploration of poetic form. Alternative generation methods are devised to overcome the difficulties, and the various insights arising from these new methods and the impact they have on the set of resulting poems are discussed in terms of their potential contribution to better poetry generation systems.
A CNN Regression Approach for Real Time 2D/3D Registration
Venue: IEEE Transactions on Medical Imaging

In this paper, we present a Convolutional Neural Network (CNN) regression approach to address the two major limitations of existing intensity based 2 D/3 D registration technology: 1) slow computation and 2) small capture range. Different from optimization based methods, which iteratively optimize the transformation parameters over a scalar valued metric function representing the quality of the registration, the proposed method exploits the information embedded in the appearances of the digitally reconstructed radiograph and X ray images, and employs CNN regressors to directly estimate the transformation parameters. An automatic feature extraction step is introduced to calculate 3 D pose indexed features that are sensitive to the variables to be regressed while robust to other factors. The CNN regressors are then trained for local zones and applied in a hierarchical manner to break down the complex regression task into multiple simpler sub tasks that can be learned separately. Weight sharing is furthermore employed in the CNN regression model to reduce the memory footprint. The proposed approach has been quantitatively evaluated on 3 potential clinical applications, demonstrating its significant advantage in providing highly accurate real time 2 D/3 D registration with a significantly enlarged capture range when compared to intensity based methods.
Real time 2D/3D registration via CNN regression
Venue: 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)

In this paper, we present a Convolutional Neural Network (CNN) regression approach for real time 2 D/3 D registration. Different from optimization based methods, which iteratively optimize the transformation parameters over a scalar valued metric function representing the quality of the registration, the proposed method exploits the information embedded in the appearances of the Digitally Reconstructed Radiograph and X ray images, and employs CNN regressors to directly estimate the transformation parameters. The CNN regressors are trained for local zones and applied in a hierarchical manner to break down the complex regression task into simpler sub tasks that can be learned separately. Our experiment results demonstrate the advantage of the proposed method in computational efficiency with negligible degradation of registration accuracy compared to intensity based methods.