nils-herrmann/clean_scirepeval huggingface dataset:
Using simulation to develop entrepreneurial skills and mind set: an exploratory case study
Year: 2018

Entrepreneurs need to develop a range of skills to be successful, including skills in decision making, risk management, problem solving, communication, and teamwork. Games and simulations are increasingly being used in both academia and business to encourage such skills development. This paper describes a business simulation module whereby postgraduate students use a game to simulate managing and operating a business. The game replicates real world scenarios, thereby providing an innovative and contextualized learning environment. This paper presents extracts from students' reflective essays, which describe various learning outcomes. The paper concludes with some guidelines for teachers considering integrating game based learning into their curricula to facilitate skills development, as well as recommendations for future research.
Chapter 6 Optimal Budget Allocation Across Search Markets
Year: 2014

How to effectively allocate the limited advertising budget is a critical issue for an advertiser in sponsored search auctions. However, due to the heterogeneity of major search markets in terms of auction mechanisms, ranking algorithms, and advertising structures, it is becoming increasingly difficult for an advertiser to manipulate advertising budget simultaneously across several search markets. In this chapter, we establish a novel optimal budget allocation model across search advertising markets, under a finite time horizon. Considering distinctive features of search auctions, we introduce the quality score qq and the dynamic advertising effort uu to extend the advertising response function to fit budget decision scenarios. We also provide a feasible solution to our model and study some desirable properties: (a) the marginal return is non increasing with respect to the advertising budget; (b) the optimal budget solution satisfies the condition that the advertising effort uu is positively proportional to the product of the change of accumulated revenue in a market VV, the change of market share thth, and the advertising elasticity aa. Computational experiments are made to evaluate our model and identified properties. Experimental results show that the advertiser with increasing advertising elasticity is recommended to invest more budget in the late stages, but the advertiser with decreasing advertising elasticity should invest more budget in the initial stage, in order to maximize net profits.
Joint Rate Distortion Optimization for Simultaneous Texture and Deep Feature Compression of Facial Images
Venue: 2018 IEEE Fourth International Conference on Multimedia Big Data (BigMM)
Year: 2018

The explosion of surveillance cameras in smart cites and the increasing demand of low latency visual analysis have pushed the horizon from the traditional image/video compression to feature compression. Due to the recent advances of face recognition, we investigate the simultaneous compression of facial images and deep features, which is demonstrated to be beneficial in terms of the whole system performance including visual quality and recognition accuracy. Herein, we propose the Texture Feature Quality Index (TFQI) to measure the ultimate utility of the facial images based on automatic visual analysis and monitoring. Furthermore, based on TFQI, a bit allocation scheme is proposed to optimally allocate the given bits for images and features, such that the overall coding performance can be optimized. The proposed scheme is validated using the standard face verification benchmark, Labeled Faces in the Wild (LFW) Better rate TFQI and rate Accuracy performance compared to the traditional texture coding can be achieved, especially in the scenario of low bit rate coding.
Study of Vortex Generator Effect on Airfoil Aerodynamics Using the Computational Fluids Dynamics Method
Year: 2020

The lift force is one of the important factors in supporting the aircraft flying capabilities. The airplane has a section called the aircraft wing. In particular, the wing section of aircraft is called the airfoil. One of the efforts to increase the lift force is to make the flow of air fluid at the top of the airfoil more turbulent. Turbulent flow can attract momentum from the boundary layer, the result of this momentum transfer has energy that is more resistant to the adverse pressure gradient which can trigger the flow separation. Efforts that can be made to reduce separation flow and increase lift force are the addition of a turbulent generator on the upper surface of the airfoil, one type of turbulent generator is a vortex generator, a vortex generator can accelerate the transition from the laminar boundary layer to the turbulent boundary layer. This study was conducted with the aim of knowing the effect of the vortex generator on the aerodynamics of NACA 4412 using the computational fluid dynamics method. The main thing that will be investigated is the effect of the straight type vortex generator application on the lift coefficient, by comparing the plain airfoil and airfoil that has been applied to the vortex generator to vary the angle of attack. The variation of the angles of attack are 0o, 5o, 10o, 15o and the placement of the vortex generator is 24% of the leading edge. The results obtained that the lift coefficient changes with increasing angle of attack and the application of a vortex generator to an airfoil can increase the lift coefficient than a plain airfoil. The optimum increase in lift coefficient is at the angle of attack of 5o as much as 13%
Sensitivity Analyses for Incorporating Machine Learning Predictions into Causal Estimates
Year: 2020

Causal inference methods can yield insights into causation from observational datasets. When some necessary variables are unavailable for a causal analysis, machine learning systems may be able to infer those variables based on unstructured data such as images and text. However, if these inferred variables are to be incorporated into causal analyses, the error rate of the underlying classifier should affect the uncertainty in the causal conclusions. Past work has framed classifier accuracy as measurement error to incorporate predictions into consistently estimated causal effects. However, this estimator is sensitive to small errors in its estimation of the classifier's error rate, leading to erratic outputs that are uninterpretable for any given analysis. In this paper we introduce three sensitivity analyses that capture the uncertainty from using a machine learning classifier in causal estimation, and show that our methods enable more robust analyses.
Big Data Meaning in the Architecture of IoT for Smart Cities
Venue: DMBD
Year: 2016

Internet of Things (IoT) is the technology that allows making interconnections between devices and internet; its applications have been developed to give answer to society's needs and requirements. In the last years, communities have gotten interested into incorporate this and some other Information Technologies to the cities, to make of those Smart Cities. Currently, applications just reply to particular necessities but general structures of IoT are being developed to improve the Smart City functioning and there is where Big Data (Classification and analysis of information) takes an important place inside the architecture, because this area manages the complexity, quantity and the variety of data for the right working of systems and the acquisition of classified useful data in real time. This paper aims to explain the importance of Big Data as Information Technology (IT) to organize and direct correctly the information in complex systems as the involved in the development of the Smart Cities.
THE MARINE ICHTHYOFAUNA OF THE EASTERN LEVANT HISTORY, INVENTORY, AND CHARACTERIZATION
Year: 2013

A general study of the marine ichthyofauna of the eastern Levant is presented. A historical survey of the ichthyofaunistic literature on the area reveals a constant rate of increase in the number of new recorded species, resulting from increased collection effort and the continuous influx of species of Red Sea origin. An annotated list of 30 newly recorded species and two first substantiated records is given. A checklist of eastern Levantine marine ichthyofauna including 405 species within 125 families is presented. A database of eastern Levantine marine ichthyofauna was compiled with respect to local conditions of abundance, habitat type, depth, feeding habits, size, and geographic distribution. The database allows characterization of species composition within each of the above categories, in addition to a further breakdown of each category with respect to the other categories.
How do performance feedback characteristics influence recipients' reactions? A state of the art review on feedback source, timing, and valence effects
Year: 2018

One of the most important measures to stimulate individual performance is feedback, whose effectiveness highly depends on underlying feedback characteristics. Although an extensive body of research has stressed its importance, a conclusive overall picture on feedback characteristics effects is missing. However, synthesized knowledge is important when one is willing to implement feedback systems to effectively influence recipients' reactions. To address this issue, we organize and summarize the findings regarding the main effects of feedback source, feedback timing, and feedback valence as well as regarding their interactions with the source, message, task, and recipients' individual characteristics from different disciplines. Based on an analysis of 64 empirical articles, we show that main effects have been considered very context specific and are often inconsistent, while the occurrence of certain source, message, task, and individual characteristics even inverts the generally assumed main relationships. Based on an extract of our findings, we provide specific research propositions and offer avenues for future research, which will be of value for researchers and feedback providing practitioners.
Ouroboros Praos: An Adaptively Secure, Semi synchronous Proof of Stake Blockchain
Venue: EUROCRYPT
Year: 2018

We present "Ouroboros Praos" a proof of stake blockchain protocol that, for the first time, provides security against fully adaptive corruption in the semi synchronous setting: Specifically, the adversary can corrupt any participant of a dynamically evolving population of stakeholders at any moment as long the stakeholder distribution maintains an honest majority of stake; furthermore, the protocol tolerates an adversarially controlled message delivery delay unknown to protocol participants.
Teknik Budidaya Kelapa Organik The Organic Coconut Cultivation Technique
Year: 2018

The awareness of the impact of agricultural development to the quality of environment has leaded the coconut cultivation technique to produce organic coconut products. There is no use of anorganic fertilizer and chemical pesticide in organic farming system. As a result, the uses of coconut product that free from any chemical substance, such as botanical pesticide, and wasted coconut parts have been intensified. Agricultural products using organic label have certain markets and consumers and high price as well. Some countries such as Pantai Gading Sri Lanka have intensively used wasted coconut parts as organic fertilizer. Organic coconut products can be obtained by applying organic coconut cultivation technique.  Menyadari dampak pembangunan pertanian terhadap mutu lingkungan maka pengusahaan kelapa harus berorientasi terhadap mutu lingkungan dengan mendorong terciptannya produkproduk kelapa organik melalui teknik budidaya kelapa organik. Pertanian organik tidak menggunakan input luar berupa pupuk buatan (anorganik) dan pestisida kimia. Teknologi tersebut meliputi penggunaan produk kelapa yang berasal dari tanaman yang bebas pengaruh bahan kimia, seperti penggunaan pupuk organik, penggunanan pestisida nabati dan pengolahan limbah dari tanaman kelapa sebagai bahan organik yang nantinya akan digunakan sebagai pupuk pada tanaman kelapa. Produk pertanian yang memiliki label organik memiliki nilai jual yang tinggi serta mempunyai pasar dan konsumen tersendiri. Di beberapa negara seperti Pantai Gading dan Sri Langka pemanfaatan bagian dari limbah tanaman kelapa sudah dilaksanakan sebagai pupuk organik. Dengan menerapkan teknik budidaya kelapa organik dapat menghasilkan produk kelapa organik.
SU F T 455: Is Contouring the Whole Breast Necessary for Two Field 3D Breast Planning?
Venue: Medical physics
Year: 2016

To investigate the effect of contouring the whole breast on reducing the radiation dose to the heart and affected lung in tangential field in field 3D breast planning. We hypothesize that contouring the whole breast will simplify the plan normalization process, reduce dose to critical structures, while maintaining treatment plan quality and consistency.  Twenty previously treated breast cancer patients using tangential field in field 3D planning technique were randomly selected. The affected breast was contoured following the RTOG breast atlas guideline. Breast PTV was created by shrinking 5 mm from the breast contour. The same plan has been pasted to the new contour and normalized to 95% of the Breast PTV receiving the prescribed isodose line. Lung V20 Gy% and Heart V25 Gy% were the primary study endpoints. Homogeneity Index (HI) and Conformity Index (CI) were calculated based on the following equations. HI= Dmax/ D95 and Nakamura's Conformity Index= PIV/TVPIV x TV/TVPIV.  The average CI for previous plans was 1.68 vs. 1.66 for the new hybrid plan: both plans were conformal to the breast with similar quality. The HI for both the previous and the new hybrid plan was 1.24. Lung V 20% slightly increased from 4.27% to 4.82% Heart V 25% for LT breast patients slightly decreased from 0.38% to 0.29% Heart V 25% for RT breast patients was close to zero in both cases.  With similar conformal and homogeneity indices for the plan quality, by contouring the whole breast following RTOG breast atlas guideline will simplify the planning process. The study showed that contouring the whole breast for patients with left sided breast cancer reduced the heart V 25% although not significantly, while maintaining the CI and HI. There was no measurable gain seen with whole breast contour for right sided breast cancer patients.
3D Point Cloud Analysis and Classification in Large Scale Scene Based on Deep Learning
Venue: IEEE Access
Year: 2019

We present a deep learning framework for efficient large scale 3D point cloud analysis and classification using the designed feature description matrix (FDM) As the 3D points are unordered in the large scale scene, and no topology structure can be employed directly for classification and recognition, it is difficult to apply deep neural network directly on 3D point clouds as points cannot be arranged in a fixed order as 2D image pixels. We design a new pipeline for 3D data processing by combining the traditional features extraction method and deep learning method. Our FDM encapsulates the 3D features of the point and can be used as the input of the deep neural network for training and testing. The experiments demonstrate that our method can acquire higher classification accuracy compared with our previous work and other state of art works.
Crowd counting via scale adaptive convolutional neural network in extremely dense crowd images
Year: 2019

Crowd counting, a high accuracy and high speed technology, has been applied in new retail, shopping mall, underground, rail station and vehicle surveillance systems. However, due to the inconsistent sizes of human heads, there are a lot of counting errors and instability of the crowd density estimation in extremely dense crowd images. Therefore, a scale adaptive Convolutional Neural Network (CNN) architecture is proposed by introducing residual network on the basis of multi column CNN. In the process of model training, joint learning is proposed in this paper. Through alternating training for residual network and multi column CNN, network parameters with the best accuracy are selected after iteration. Joint learning helps to enhance the modelling ability for massive scale transformation and the scale self adaptability of the network. The proposed method is experimented on public dense crowd data sets. Experimental results prove that scale adaptive CNN shows higher counting capability than the current state of the art method.
Evaluation de la qualite de prise en charge nutritionnelle chez les patients hemodialyses chroniques d'un centre lourd
Year: 2015

Le patient hemodialyse chronique constitue un groupe a risque de denutrition avec une prevalence elevee et une mortalite multipliee par 2. Les recommandations actuelles concernant le diagnostic et la prise en charge de la denutrition dans cette population sont nombreuses et difficilement applicables en pratique clinique. C'est pourquoi, nous avons souhaite evaluer la qualite de la prise en charge nutritionnelle dans un centre lourd d'hemodialyse. Patients et methodes Une etude retrospective observationnelle a ete realisee sur une population de patients hemodialyses chroniques en janvier 2014. Deux sous groupes de patients ont ete distingues ceux avec et ceux sans support nutritionnel en janvier 2014, defini par un complement nutritionnel oral (CNO) une nutrition parenterale per dialytique (NPPD) une nutrition enterale (NE) et/ou une nutrition parenterale (NP) Resultats Parmi les 108 patients, 60 ont une prise en charge nutritionnelle jugee suffisante soit parce que le statut nutritionnel est correct, soit parce que l'intervention nutritionnelle est efficace. Environ 30 d'entre eux ont une prise en charge jugee insuffisante il s'agit de patients presentant une denutrition moderee a severe ou de patients dont l'etat nutritionnel s'est aggrave malgre la mise en place d'un support. Les supports nutritionnels utilises en majorite sont le CNO (seul dans 67,4 puis la NPPD (28  Les causes identifiees du defaut de prise en charge sont un sous depistage de la denutrition, un manque de tracabilite dans le dossier medical et dietetique, un manque d'evaluation des ingesta et un manque de recours a des therapies jugees invasives.  La prise en charge nutritionnelle a ete jugee insuffisante pour 30 des patients, cependant l'impact des pathologies intercurrentes evolutives n'a pas ete evalue (cancer, hospitalisation. Afin d'optimiser celle ci, un renforcement du depistage de la denutrition avec l'utilisation d'un nouveau score simple et complet elabore par Moreau Gaudry et al. a ete mis en place depuis janvier 2015, ainsi qu'une alerte systematique des patients en denutrition moderee a severe aupres des nephrologues et dieteticiens.
Recycling A Contemporary Identity of The Past
Year: 2012

When postmodernism decreed that art has lost originality and can only be repetitious as well as that it should change perspective from the external reality to the text, writers began focusing on previously written texts as the core subject matter of their work. From this point of view, focus is placed on recycling, seen as a postmodern technique used to construct a new identity for the past under its different forms as history, as writers and as text(s) Thus, the past is integrated into contemporaneity while constantly being reshaped by the many contemporary novels that look back on writers, novels and literary movements belonging to the past. Moreover, this dynamic and multifaceted dialogue between contemporary novels and past ones is also considered a means of providing the latter with historical continuity (by bringing them into the attention of contemporaneity) and the former with perspectives of canonical inclusion.
Les conduites a risques et le Trouble Deficitaire de l'Attention/Hyperactivite (TDAH) chez l'enfant et l'adolescent l'exemple des jeux dangereux
Year: 2009

Ce present travail porte sur l'etude des conduites a risques et le Trouble Deficitaire de l'Attention/Hyperactivite chez l'enfant et l'adolescent. Les relations entre les conduites a risques, plus specifiquement la consommation de substances psycho actives, et le TDAH constituent un objet d'etude important. Parmi les conduites risques nous avons voulu nous centrer particulierement sur les jeux dangereux (jeux de non oxygenation et jeux violents) ces conduites sont encore peu documentees au niveau de la litterature. Toutefois, certaines etudes mettent en evidence un lien entre ces pratiques et les troubles externalises. L'objectif de ce travail etait d'identifier les facteurs associes voire de vulnerabilite aux conduites a risques, les jeux dangereux, chez les enfants et les adolescents. Nous avons etudie les liens entre les jeux dangereux et le TDAH, puis nous avons mis en evidence l'implication de variables psychologiques et psychopathologiques. Dans notre premiere etude, notre echantillon est constitue de 746 collegiens. Nous avons utilise une methodologie quantitative visant a evaluer les conduites a risques, la symptomatologie anxieuse, depressive et hyperactive, les styles motivationnels ainsi que la personnalite en reference au modele de Cloninger. Notre deuxieme etude, realisee en milieu clinique aupres de 215 enfants presentant un TDAH, nous a permis d'etudier les variables psychologiques et psychopathologiques dans le TDAH. Puis, dans notre troisieme etude, nous avons evalue chez les enfants TDAH les conduites a risques et nous avons mis en evidence l'implication de facteurs de vulnerabilite. Les resultats obtenus nous permettent de degager des profils psychologiques et psychopathologiques distincts selon le type de jeux dangereux. De plus, selon la severite du TDAH, les facteurs de vulnerabilite sont differents.
A Multiobjective Evolutionary Approach for Influence Maximization in Multilayer Networks
Venue: ICCAI
Year: 2020

Influence Maximization (IM) is one key algorithmic problems in information diffusion research; it aims to select a set of users from a social network and, by following a specific model, maximize the number of users influenced (the influence spread) Yet despite its immense potential, relatively little research is dedicated to IM for multilayer networks. Conversely, most existing IM studies that rely on a greedy algorithm strategy only obtain a single solution that provides limited insights on the target networks' core organization. With that in mind, we focus on studying the Influence Maximization Problem (IMP) in multilayer networks. Specifically, we define novel concepts, such as the pairwise reciprocal length and pairwise influence, with respect to the information diffusion process in multilayer networks. Then we formulate the IM in multilayer networks as a multiobjective optimization problem and employ the classic Nondominated Sorting Genetic Algorithm II (NSGA II) to find a set of Pareto optimal solutions that provide a wide range of options for decision makers. To maintain population diversity and accelerate the algorithm's convergence, we combine a heuristic population initialization strategy and an efficient two point crossover operation. Extensive experiments show that our approach has competitive performance when compared to off the shelf IM algorithms with regard to influence spread and running time.
Genome Sequence Resource for Nigrospora oryzae, an important pathogenic fungus threatening crop production.
Venue: Molecular plant microbe interactions MPMI
Year: 2021

Nigrospora oryzae is an important phytopathogenic fungus with a broad host range. Here, we report an annotated draft of the genome of N. oryzae field strain GZL1 collected from maize assembled from PacBio and Illumina sequencing reads. The assembly we obtained has 15 scaffolds with an N50 length of 4,037,616 bp. The resulting GZL1 draft genome is 43,214,190 bp, with GC content of 58.19% The completeness of GZL1 genome assembly is 99.30% This study is the first report of the genome sequence of N. oryzae, which can facilitate future study of the genetic variation and pathogenic mechanism of this important fungal pathogen.