nils-herrmann/clean_scirepeval huggingface dataset:
Real Estate Market Dynamics in the City of Naples: An Integration of a Multi Criteria Decision Analysis and Geographical Information System
Year: 2020

Urban development and regeneration projects produce multidimensional impacts on the city, on its environmental, economic, and social systems. An aspect that can be considerably affected by urban dynamics is linked to the real estate market. So, analysing real estate dynamics is useful to support decision makers in the elaboration of urban regeneration plans and projects, and thus orient their choices. Focusing attention on the city of Naples (Italy) the purpose of this paper is to analyse in detail the real estate dynamics in this city through the integration of a Multi Criteria Decision Analysis (MCDA) method and Geographical Information System (GIS) This integration allowed us to map and analyse the territory, linking a specific issue (the real estate dynamics) to the territory itself, and to analyse it according to specific criteria. This aims for a better understanding and interpretation of real estate dynamics, representing a useful tool for orienting and supporting urban planning strategies.
What Counts and What Gets Counted (2nd Edition)
Year: 2017

Management reporting systems are like power tools. They help you improve performance quickly and effectively, but one careless moment can cause irreparable damage and serious injury. For years, my students have been asking permission to send this book of best practices and safety tips to colleagues, friends and family. This revision provides a comprehensive introduction to management reporting systems, complete with links to nearly 100 videos, written to be appropriate for students and practitioners of any background, across all areas where people organize their efforts to improve performance. Examples include business, charities, governmental agencies, education, sports, and family life. Each of its 28 essays can be read separately, making the book well suited to use as supplemental reading.Drawing extensively from current research and classical philosophy, the book encourages both deep skepticism about performance measures and pragmatic recognition of how useful they can be. Thoughtless adherence to performance measures leads many to decry "bean counters," and emphasize that "Not everything that counts can be counted, and not everything that can be counted counts." Yet something gets counted whenever we need to make critical decisions throughout the workplace, politics and daily life.This book will help readers interpret the performance measures generated by the managerial reporting systems most pervasive in modern organizations, design systems that generate more useful measures, and make better use those measures even though what gets counted often paints a misleading picture of what counts.
Testing the predictive strength of the comparative method: An ongoing experiment on unattested words in Western Kho Bwa languages
Year: 2019

Although it is well known tomost historical linguists that the comparative method could in principle be used to predict hitherto unobserved words in genetically related languages, the task of word prediction is rarely discussed in the linguistic literature. Here, we introduce "relex retrodiction" as a new task for historical linguistics and report an ongoing experiment in which we use a computer assisted worklow to retrodict relexes for so far unobserved words in eight varieties of Western Kho Bwa (a subgroup of Sino Tibetan) Since, at the time of writing this report, the experiment is still ongoing, we do not report concrete results, but instead provide an estimate of our expectations by testing the performance of the computational part of our worklow on existing language data. Our results suggest that relex retrodiction has the potential of becoming a useful tool for historically oriented ieldwork.
Current progress achieved in novel materials for supercapacitor electrodes: mini review
Year: 2019

Supercapacitors are highly attractive for a large number of emerging mobile devices for addressing energy storage and harvesting issues. This mini review presents a summary of recent developments in supercapacitor research and technology, including all kinds of supercapacitor design techniques using various electrode materials and production methods. It also covers the current progress achieved in novel materials for supercapacitor electrodes. The latest produced EDLC/hybrid/pseudo supercapacitors have also been described. In particular, metal oxides, specifically ZnO, used as electrode materials are in focus here. Eventually, future developments, prospects, and challenges in supercapacitor research have been elaborated on.
Lexical Semantics for Terminology
Year: 2020

An introduction explores the interconnections between lexical semantics and terminology. More specifically, it shows how principles borrowed from lexico semantic frameworks and methodologies derived from them can help understand terms and describe them in resources. It also explains how lexical analysis complements perspectives primarily focused on knowledge. Topics such as term identification, meaning, polysemy, relations between terms, and equivalence are discussed thoroughly and illustrated with examples taken from various fields of knowledge. This book is an indispensable companion for those who are interested in words and work with specialized terms, e.g. terminologists, translators, lexicographers, corpus linguists. A background in terminology or lexical semantics is not required since all notions are defined and explained. This book complements other textbooks on terminology that do not focus on lexical semantics per se.
Engineering Ethics Case Study of Hydroelectric Sayano Sheshenkaya Accident: Lesson Learned for Malaysian Engineer
Year: 2014

Sayano Shushenskaya hydroelectric power station can be categorized as the biggest hydro power plant in Russia. The power plant full capacity is 6500MW. It is made up of 10 turbines which is each turbine rated power is 650MW. The accident that happened in the power station have been claimed many lives and high cost of damage. All people are keeping asking about the main causes of this tragedy. In order to know the causes of this tragedy, a study case needs to be conducted in order to relate the study with the engineering ethical theory. The goal of this case study is to study about the main causes of the accident that is related with the code of ethics and find the lessons that can be taken from the accident toward Malaysian engineer. This case study shows most of the causes of the accidents are related to the engineering ethical theory. The results of the findings really indicate the important of following the code of ethics in the working environment. The safety of the hydro plant resources is depending on the people who are conducting the plant in a proper manner.
A STUDY ON APPLICATION OF MACHINE LEARNING AND COMPUTER VISION FOR RETAIL PROJECTS
Year: 2017

The motivation for developing computer vision is the human vision system which is the richest sense that we have. To us, vision seems an easy task of just seeing objects in daily life and identifying them, but in reality, our eyes along with the brain are processing information of around 50 images every second with millions of pixels in each image. Most of these images obtained are currently just looked at by people. The challenging task is to process images from all these cameras and allow automation of tasks never before considered. Neural networks help us in making cameras intelligent enough to understand the images it captures. Convolutional neural networks (CNN) are trained to give image classification results of good accuracy, with the challenge to improve utilization of computing resources. Google Net is in its essence a deep CNN that uses inception architecture to attain leading edge results for classification and detection problems. In this paper, a study was made on applications of computer vision techniques in retail and customer strategic projects. Further, it was analyzed that if cameras trained with CNN can work well enough to be deployed in retail market scenarios to automate sales and stock supervision.
A New Deep Transfer Learning Method for Bearing Fault Diagnosis Under Different Working Conditions
Venue: IEEE Sensors Journal
Year: 2020

Fault diagnosis is very important for condition based maintenance. Recently, deep learning models are introduced to learn hierarchical representations from raw data instead of using hand crafted features, which exhibit excellent performance. The success of current deep learning lies in: 1) the training (source domain) and testing (target domain) datasets are from the same feature distribution; 2) Enough labeled data with fault information exist. However, because the machine operates under a non stationary working condition, the trained model built on the source domain can not be directly applied on the target domain. Moreover, since no sufficient labeled or even unlabeled data are available in target domain, collecting the labeled data and building the model from scratch is time consuming and expensive. Motivated by transfer learning (TL) we present a new fault diagnosis method, which generalizes convolutional neural network (CNN) to TL scenario. Two layers with regard to task specific features are adapted in a layer wise way to regularize the parameters of CNN. What's more, the domain loss is calculated by a linear combination of multiple Gaussian kernels so that the ability of adaptation is enhanced compared to single kernel. Through these two means, the distribution discrepancy is reduced and the transferable features are learned. The proposed method is validated by transfer fault diagnosis experiments. Compared to CNN without domain adaptation and shallow transfer learning methods, the proposed method gets the best performance for fault classification.
ANTESEDEN EMPLOYEE TURNOVER
Year: 2018

This research is concerning the effect of workplace environment, job satisfaction, and job performance on employee turnover, and the background is to get the convenience of employees condition, the satisfaction of job results, maximum performance, and keep and reduce in and out employees. The purpose of this research is to see how far the influence of workplace environment, job satisfaction, and job performance on employee turnover. Planning of this research uses primary data that is got by handing over questioners to 200 employees in Telecommunication company in East Jakarta. The analysis method which is used is double regresi. Results of this research give conclusion that there's a positive and significant influence of workplace environment, job satisfaction, and job performance on employee turnover.
Designing a PCA based Collaborative Visual Analytics System
Year: 2009

In visual analytics, collaboration is viewed as a knowledge sharing process that helps people perform analytical reasoning tasks effectively. In this paper, we present a collaborative visual analytics tool, iPCA CE, that supports interactive data analysis using principal component analysis (PCA) on a tabletop display. We define three data analysis scenarios that are addressed when designing the collaborative data analysis system. With the system, users are able to collaboratively analyze data, share ideas or knowledge, and divide their work load.
Perceptual Metric Guided Deep Attention Network for Single Image Super Resolution
Year: 2020

Deep learning has been widely applied to image super resolution (SR) tasks and has achieved superior performance over traditional methods due to its excellent feature learning capabilities. However, most of these deep learning based methods require training image sets to pre train SR network parameters. In this paper, we propose a new single image SR network without the need of any pre training. The proposed network is optimized to achieve the SR reconstruction only from a low resolution observation rather than training image sets, and it focuses on improving the visual quality of reconstructed images. Specifically, we designed an attention based decoder encoder network for predicting the SR reconstruction, in which a residual spatial attention (RSA) unit is deployed in each layer of decoder to capture key information. Moreover, we adopt the perceptual metric consisting of L1 metric and multi scale structural similarity (MSSSIM) metric to learn the network parameters. Different than the conventional MSE (mean squared error) metric, the perceptual metric coincides well with perceptual characteristics of the human visual system. Under the guidance of the perceptual metric, the RSA units are capable of predicting the visually sensitive areas at different scales. The proposed network can thus pay more attention to these areas for preserving visual informative structures at multiple scales. The experimental results on the Set5 and Set14 image set demonstrate that the combination of Perceptual metric and RSA units can significantly improve the reconstruction quality. In terms of PSNR and structural similarity (SSIM) values, the proposed method achieves better reconstruction results than the related works, and it is even comparable to some pre trained networks.
Subjective well being, consumption comparisons, and optimal income taxation
Year: 2018

We introduce reference consumption into the standard utility function from optimal tax analysis. Individuals compare their consumption "narrowly" with those of the same productivity, or "broadly" with the average consumption across society. In both narrow and broad equilibria reference consumption is an increasing function of the tax parameters, so generating new theoretical results. Individual well being decreases with the net wage (net of tax) rate for low productivity workers under narrow (broad) comparisons, thus adjusting redistributive taxation considerations. Further, in both cases reference consumption distorts labor supply away from the social optimum level, giving a distortion correcting role for taxation.
Ricardian Heckscher Ohlin Comparative Advantage: Theory and Evidence
Year: 2010

This paper derives and estimates a unified and tractable model of comparative advantage due to differences in both factor abundance and relative productivity differences across industries. It derives conditions under which ignoring one force for comparative advantage biases empirical tests of the other. I emphasize two empirical results: First, factor abundance and relative productivity based models each possesses explanatory power when nesting the other as an alternate hypothesis. Second, productivity differences across industries do not bias tests of the HO model in my sample. However, I find weak and mixed evidence that Heckscher Ohlin forces can potentially bias tests of the Ricardian model.
STUDIES ON BIOLOGICAL CONTROL OF FUSARIUM OXYSPORUM IN TOMATO (SOLANUM
Year: 2018

Biological control is a method of controlling plant diseases using other organisms. In this study the bio control of Fusarium oxysporum in Tomato (Solanum lycopersicum L. under nursery experiments. The soil samples were collected from isolate fungal pathogens and antagonistic fungi. The various type of fungal colonies were identified from collected soil. Among the isolate the dominant fungal pathogen (F. oxysporum) and antagonistic fungi (Trichoderma viride) was selected based on antagonistic activity. The biocontrol agent resulted in increase in soil fertility, control of minor pathogens and increase in general health of plants, ultimately leading to an increase in plant metabolism. If enhanced the growth and development of the plant.
Fast and Highly Selective Continuous Flow Catalytic Hydrogenation of a Cafestol Kahweol Mixture Obtained from Green Coffee Beans
Venue: ACS omega
Year: 2020

This work investigates batch and continuous flow heterogeneous catalytic hydrogenation of a mixture of cafestol and kahweol (C&K) to obtain pure cafestol. These diterpenes were extracted from green coffee beans, and hydrogenation was performed using well established palladium catalysts (Pd/C, Pd/CaCO3, Pd/BaSO4, and Pd/Al2O3) and a carbon black supported Pd catalyst coated by a covalently tethered SiO2 shell with mesoporous texture (Pd/CB@SiO2) all partially deactivated with quinoline. Pd/C 10% poisoned with 1 wt quinoline gave the best result for batch reaction, producing cafestol from kahweol with high selectivity >99% after 10 min. Excellent selectivity was also obtained with the catalyst Pd/CB@SiO2 with only 1% Pd. In addition, Pd/C quinoline adapted for continuous flow experiments exhibited the best catalytic activity, also providing cafestol with excellent selectivity >99% after 9.8 s.
Voxelnet An Agent Based System for Spatial Data Analytics
Year: 2016

Voxelnet is a proposed voxel based spatialised framework built upon internet communication and associated geospatial data standards. Each Voxelnet block has an individual IP address and functions as a computational agent. The internet of things (IoT) is also based upon objects having individual IP addresses on the internet so they can communicate using an individual unique identifier. IP addresses can roughly reveal where things are via geo locations. The internet, though, is a document based repository with 3D plug ins that is not effective for sharing a unified world of interconnections from a volumetric point of view. The Voxelnet provides volumetric semantics on top of the current internet, within which measurements can be located, shared, interrelated and spatially analysed, supporting smart informed decisions in real and virtual worlds that account for spatial structure. It can also be used to interact with IoT systems using an integrated spatial representation.  Geospatial Data Systems; Block Models; Internet of Things; Data Sharing; Multi Agent Systems.
On the 1 switch conjecture in the Hypercube and other graphs
Year: 2015

Feder and Subi conjectured that for any $2$ coloring of the edges of the $n$ dimensional cube, we can find an antipodal pair of vertices connected by a path that changes color at most once. We discuss the case of random colorings, and we prove the conjecture for a wide class of colorings. Our method can be applied to a more general problem, where $Q_n$ can be replaced by any graph $G$ the notion of antipodality by a fixed automorphism \phi \in Aut(G) Thus for any $2$ coloring of $E(G) we are looking for a pair of vertices $u,v$ such that $u= \phi(v) and there is a path between them with as few color changes as possible. We solve this problem for the toroidal grid $G=C_{2a} \square c_{2b} with the automorphism that takes every vertex to its unique farthest pair. Our results point towards a more general conjecture which turns out to be supported by a previous theorem of Feder and Subi.
Information Aggregation in a Dynamic Stochastic General Equilibrium Model
Venue: NBER Macroeconomics Annual
Year: 2015

We introduce the information microstructure of a canonical noisy rational expectations model (Hellwig 1980) into the framework of a conventional real businesscycle model. Each household receives a private signal about future productivity. In equilibrium, the stock price serves to aggregate and transmit this information. We find that dispersed information about future productivity affects the quantitative properties of our real businesscycle model in three dimensions. First, households' ability to learn about the future affects their consumptionsavings decision. The equity premium falls and the riskfree interest rate rises when the stock price perfectly reveals innovations to future productivity. Second, when noise trader demand shocks limit the stock market's capacity to aggregate information, households hold heterogeneous expectations in equilibrium. However, for a reasonable size of noise trader demand shocks the model cannot generate the kind of disagreement observed in the data. Third, even moderate heterogeneity in the equilibrium expectations held by households has a sizable effect on the level of all economic aggregates and on the correlations and standard deviations produced by the model. For example, the correlation between consumption and investment growth is 0.29 when households have no information about the future, but 0.41 when information is dispersed.
Detection of nutrition deficiencies in plants using proximal images and machine learning: A review
Venue: Comput. Electron. Agric.
Year: 2019

During the last decade, the combination of digital images and machine learning techniques for tackling agricultural problems has been one of the most explored elements of digital farming. In the specific case of proximal images, most efforts have been directed to the detection and classification of plant diseases and crop damaging pests. Important progress has also been made on the use of close range images to determine vegetal nutrient status, but because such studies are fewer and more scattered, it is difficult to draw a complete picture on the state of art of this type of research. In this context, a thorough literature search was carried out in order to identify as many relevant investigations on the subject as possible. Every kind of imaging sensor was considered (visible range, multispectral, hyperspectral, chlorophyll fluorescence, etc. provided that images were captured at close range, thus excluding research using Unmanned Aerial Vehicles (UAVs) airplanes and satellites. A careful analysis of the techniques for detection and classification was carried out and used as basis for an in depth discussion on the main challenges yet to be overcome. Some directions for future research are also suggested, having as target to increase the practical adoption of this kind of technology.
Review of museums' indoor environment conditions studies and guidelines and their impact on the museums' artifacts and energy consumption
Year: 2018

Museums are the main link between the past, the present and the future. The presence of ancient historical artifacts is the main factor differentiating museums' environment from the environments of other types of buildings. This review paper, is focused on the indoor environment quality of the exhibition halls in the museums. The information presented is based on three main aspects. Gathering the required indoor environmental parameters related to the indoor exhibition spaces in the museums then discuss in terms of temperature, relative humidity, lighting, and indoor air quality (air pollutants and ventilations) this is done while considering the museum's artifacts, visitors and personnel. The second aspect focuses on the different researches carried out within the museum indoor environment focusing on temperature (T) relative humidity (RH) lighting (artificial lighting and daylight) as well as the studies conducted within the subject of indoor environment quality of museums (IEQ) The third aspect focuses on studies and guidelines designed for upgrading existing museums into more sustainable projects by focusing on energy efficiency part of museums. This review paper provides a rich guide of all the needed information in terms of museums indoor environments parameters for the museum officials to implement strategies and enhance the current conditions of the museums. It also highlights some of the remaining issues that researchers can look at in the future.