nils-herrmann/clean_scirepeval huggingface dataset:
Emotional intelligence and transformational leadership behaviours of construction project managers
Year: 2018

Existing research has highlighted the need for influential leaders to respond to the evolving social, economic and environmental constraints on the construction industry. Studies on leadership in other sectors have shown that influential leaders tend to demonstrate a high level of emotional intelligence. Little or no research examining relationships between leadership style and emotional intelligence has been conducted specific to construction project managers. This study aims to identify the prevalent leadership style adopted by construction project managers and investigate potential correlations between leadership style and emotional intelligence.  An online questionnaire including a mix of open and closed questions was adopted to address the research objectives. The group studied comprised project managers currently working in the construction industry in New Zealand and the UK.  The research found that transformational leadership style is prevalent among project managers examined in this study. Significant positive relationships were found between project managers' emotional intelligence and their likelihood of adopting a transformational leadership style.  The research results provide the construction industry with a benchmark against which individuals with high emotional intelligence, and so most suited to the challenges of the project management role, can be identified and trained. Recommendations including suitable methods for identifying, recruiting and training project managers, as well as secondment and mentoring options, were suggested for improving leadership capabilities in the construction industry.
Analisis de motivos decorativos de tejidos y revestimientos ceramicos en el entorno de la vision artificial. Aplicacion a la reconstruccion de motivos historicos y al diseno
Year: 2011

El objetivo de esta tesis es la contribucion a la creacion, e implementacion en herramientas informaticas, de una metodologia aplicable para el analisis y edicion de imagenes procedentes del campo de los disenos ceramicos y textiles, y por extension, de todas aquellas imagenes que siguen un patron repetitivo y que, por tanto, se ajustan a la Teoria de Grupos de Simetria. Para ello, se ha definido una metodologia de analisis dividida en etapas, en la que se va aumentando gradualmente el nivel de la informacion manejada, desde los pixeles de la imagen inicial, pasando por los objetos (formas o unidades basicas perceptuales) y los motivos (agrupaciones de objetos realizadas con criterios perceptuales) hasta llegar a la estructura del patron, es decir, las distintas transformaciones geometricas que relacionan los elementos (objetos y motivos) que lo forman. La informacion estructural obtenida es utilizada con fines diversos: la clasificacion de las imagenes segun el Grupo de Simetria del Plano del patron, la reconstruccion de las imagenes aprovechando el conocimiento de que partes estan relacionadas por la estructura, y por ultimo, la edicion de patrones, tanto a nivel de formas y motivos, como de estructura, permitiendo realizar cambios estructurales con facilidad, con lo que se generan familias de patrones a partir de uno analizado. Las herramientas desarrolladas han sido probadas con un amplio conjunto de imagenes de patrones de procedencias muy diversas, destacando el estudio de los alicatados de la Alhambra de Granada y del Alcazar de Sevilla, asi como de textiles y, ampliando los objetivos iniciales, a diversos elementos del entorno urbano.
Object Tracking Using Maximum Colour Distance under Illumination Change
Year: 2012

This paper presents a new method for tracking moving objects that have colour variations due to illumination, which uses a maximum colour distance on the mean shift framework. Conventional colour based mean shift methods show good results when tracking non rigid moving objects. However, they do not provide accurate results when the initial colour distribution of the object disappears. Our method uses the maximum colour distance to represent the objects. If a colour distance can be defined as the geometric distance between two colour points in a colour space, then the maximum colour distance is defined as the maximum value among all of the colour distances. The physical illumination model, under assumptions, guarantees that the maximum colour distance is independent of ambient lighting and other illumination with an identical solid angle. The objective of our method is to provide robust real time object tracking with large colour variation in objects whose colour changes due to external illumination. The implementation of this new algorithm shows effective tracking results with a complete object colour change over time. The validation of our approach is illustrated by the comparison of experimental results obtained using the methods described above.
Wolfgang Iser's Critical Theory from the Perspective of Liminality
Year: 2010

By focusing on the theoretical statement of "liminality",this article gives a systematic mapping of Wolfgang Iser's critical theory. Intellectually indebted to Roman Ingarden,Hans Georg Gadamer and Walter Pater,Iser successively delineates the contour of liminal space between text and reader,literary fiction and imagination as well as intraculturally and interculturally to reveal the energizing potential disclosed in,generated from and promised by the liminal space. Iserian critical theory foregrounds a new continent and a new discourse full of creativity in Western humanities studies a discourse of knowledge with liminal phenomena as the object of critique.
Evolution of the Rho guanine nucleotide exchange factors Kalirin and Trio and their gene expression in Xenopus development.
Venue: Gene expression patterns GEP
Year: 2019

Guanine nucleotide exchange factors (GEFs) activate Rho GTPases by accelerating their GDP/GTP exchange. Trio and its paralog Kalirin (Kalrn) are unique members of the Rho GEFs that harbor three catalytic domains: two functional GEF domains and a serine/threonine kinase domain. The N terminal GEF domain activates Rac1 and RhoG GTPases, while the C terminal GEF domain acts specifically on RhoA. Trio and Kalrn have an evolutionary conserved function in morphogenetic processes including neuronal development. De novo mutations in TRIO have lately been identified in patients with intellectual disability, suggesting that this protein family plays an important role in development and disease. Phylogenetic and domain analysis revealed that a Kalrn/Trio ancestor originated in Prebilateria and duplicated in Urbilateria to yield Kalrn and Trio. Only few taxa outside the vertebrates retained both of these highly conserved proteins. To obtain first insights into their redundant or distinct functions in a vertebrate model system, we show for the first time a detailed comparative analysis of trio and kalrn expression in Xenopus laevis development. The mRNAs are maternally transcribed and expression increases starting with neurula stages. Trio and kalrn are detected in mesoderm/somites and different neuronal populations in the neural plate/tube and later also in the brain. However, only trio is expressed in migrating neural crest cells, while kalrn expression is detected in the cranial nerves, suggesting distinct functions. Thus, our expression analysis provides a good basis for further functional studies.
Image data analysis and classification in marketing
Venue: Adv. Data Anal. Classif.
Year: 2012

Nowadays, the diffusion of smartphones, tablet computers, and other multipurpose equipment with high speed Internet access makes new data types available for data analysis and classification in marketing. So, e.g. it is now possible to collect images/snaps, music, or videos instead of ratings. With appropriate algorithms and software at hand, a marketing researcher could simply group or classify respondents according to the content of uploaded images/snaps, music, or videos. However, appropriate algorithms and software are sparsely known in marketing research up to now. The paper tries to close this gap. Algorithms and software from computer science are presented, adapted and applied to data analysis and classification in marketing. The new SPSS like software package IMADAC is introduced.
The Design of CFM56 5B Engine Inlet Cowl Repair Platform
Year: 2014

In the reference of the repair platform of RSE1116 recommended by CMM, and according to the actual work requirements, the necessity of designing a more efficient engine inlet cowl repair platform exists, with which the disassembly, install, transport, storage, and repair of CFM56 5B engine would be much more convenient. This article gives the methods that abolish the original method of displaying CMM and that design a saddle bracket car and a maintenance shelf. These two methods cover all the need of engine inlet cowl disassemble, install, transport, storage, and overhaul.
Potassium Ion Storage: Direct Structure Performance Comparison of All Carbon Potassium and Sodium Ion Capacitors (Adv. Sci. 12/2019)
Venue: Advanced Science
Year: 2019

A hard carbon ion insertion anode gives much higher overpotential with K+ vs Na+ This significantly lowers the energy power of symmetric hybrid potassium ion capacitors (KICs) vs sodium ion capacitors (NICs) However, high surface area, ion adsorption carbon works well with both K and Na, opening the possibility for high performance symmetric KICs. In article number 1802272, Mengqiang Wu, David Mitlin, and co workers provide a direct performance comparison of potassium ion capacitors versus the better known sodium ion capacitors.
Topical and intravitreous administration of cationic nanoemulsions to deliver antisense oligonucleotides directed towards VEGF KDR receptors to the eye.
Venue: Journal of controlled release official journal of the Controlled Release Society
Year: 2010

Antisense oligonucleotides (ODNs) specific for VEGFR 2 (17 MER) and inhibiting HUVEC proliferation in vitro were screened. One efficient sequence was selected and incorporated in different types of nanoemulsions the potential toxicity of which was evaluated on HUVEC and ARPE19 cells. Our results showed that below 10 microl/ml, a 2.5% mid chain triglycerides cationic DOTAP nanoemulsion was non toxic on HUVEC and retinal cells. This formulation was therefore chosen for further experiments. In vitro transfection of FITC ODNs in ARPE cells using DOTAP nanoemulsions showed that nanodroplets do penetrate into the cells. Furthermore, ODNs are released from the nanoemulsion after 48 h and accumulate into the cell nuclei. In both ex vivo and in vivo ODN stability experiments in rabbit vitreous, it was noted that the nanoemulsion protected at least partially the ODN from degradation over 72 h. The kinetic results of fluorescent ODN (Hex) distribution in DOTAP nanoemulsion following intravitreal injection in the rat showed that the nanoemulsion penetrates all retinal cells. Pharmacokinetic and ocular tissue distribution of radioactive ODN following intravitreal injection in rabbits showed that the DOTAP nanoemulsion apparently enhanced the intraretinal penetration of the ODNs up to the inner nuclear layer (INL) and might yield potential therapeutic levels of ODN in the retina over 72 h post injection.
SpikE: spike based embeddings for multi relational graph data
Venue: 2021 International Joint Conference on Neural Networks (IJCNN)
Year: 2021

Despite the recent success of reconciling spike based coding with the error backpropagation algorithm, spiking neural networks are still mostly applied to tasks stemming from sensory processing, operating on traditional data structures like visual or auditory data. A rich data representation that finds wide application in industry and research is the so called knowledge graph a graph based structure where entities are depicted as nodes and relations between them as edges. Complex systems like molecules, social networks and industrial factory systems can be described using the common language of knowledge graphs, allowing the usage of graph embedding algorithms to make context aware predictions in these information packed environments. We propose a spike based algorithm where nodes in a graph are represented by single spike times of neuron populations and relations as spike time differences between populations. Learning such spike based embeddings only requires knowledge about spike times and spike time differences, compatible with recently proposed frameworks for training spiking neural networks. The presented model is easily mapped to current neuromorphic hardware systems and thereby moves inference on knowledge graphs into a domain where these architectures thrive, unlocking a promising industrial application area for this technology.
Robust Optimization Model for R&D Project Selection under Uncertainty in the Automobile Industry
Year: 2020

In a company, project management is responsible for project selection from candidates under some limited constraints to achieve the company's goal before the project begins as well as the project operations in progress. The development of new technologies and products can broaden a company's market share, and to do so, research and development (R&D) projects are significant. However, limited funds force a company to select projects that can best represent the company's interests. As projects may take a long time to develop, a number of uncertainties may occur, and the most concerning uncertainty is cost uncertainty. In this study, a robust optimization decision model for project selection considering cost uncertainty is proposed to assist the decision making process for companies that need to select projects from a number of candidates due to limited funds. The model considers project selection in view of the total cost of ownership, which is a key factor for customers and companies in the automobile industry. The proposed model is tested in the automobile industry environment with different conservatism levels about cost uncertainty, and an analysis of expected market changes and a company's income is performed with the solutions obtained from the proposed model. The result shows that the presented model reacts to cost uncertainty robustly for assisting the decision makers in the company.
Detection of Localised Muscle Fatigue by Using Wireless Surface Electromyogram sEMG and Heart Rate in Sports
Year: 2017

In sport, most of the muscle fatigue occurred on the upper limb is due to the arm movement in static and dynamic activities. Moreover, there are limited devices to measure muscle activity in real time monitoring when games ongoing. Therefore, the purpose of this study is to detect muscle fatigue by using the wireless surface Electromyogram (sEMG) in a different type of contraction activity. Two types of experiment were conducted in this paper, which is for isotonic and isometric contraction activities. In order to measure muscle activity, sEMG was used as an invasive technique with (Ag/AgCl) wet electrode placed on the skin. Furthermore, heart rate sensor was included to identify the relationship of muscle activity and heart beat. In prior, a prototype of sEMG with 10bit analogue digital converter (ADC) microcontroller was developed for the measurement. Then, it was transmitted the signal to the computer wirelessly for the further post processing analysis. Reducing the amplitude of signal during exercise indicates the muscle fatigue has occurred. The results reveal that biceps brachii is the most active muscle during forearm lifting movement. It was hugely differenced when compared to triceps brachii muscle during isotonic contraction in one sixth ratio. Also, increasing physical activity significantly accelerated fatigue in muscle and also raised the heart rate per minute. The results presented here may facilitate improvements in the prediction of fatigue that will lead to exhaustion for another muscle. _______________________________________________________________________________________
Nike, Colin Kaepernick, and the politicization of sports: Examining perceived organizational motives and public responses
Year: 2020

This study applies arguments from attribution theory to examine the role of perceived motives (values driven, egoistic driven, strategic driven, and stakeholder driven motives) in developing individuals' attitudes, positive word of mouth (PWOM) and negative word of mouth (NWOM) intentions in response to Nike's 30th Anniversary ad campaign featuring Colin Kaepernick. This study also examines how perceptions of the appropriateness of the politicization of sports moderate these relationships, as well as individual factors that predict people's assessments of sports as a politicized event. A survey (N 373) was conducted to examine how much people's perceptions of Nike's motives for engaging in Corporate Social Advocacy (CSA) guided their responses and the degree to which they were likely to engage in actions. Implications for theory and practice are discussed.
INTRODUCTION TO SYSTEM DYNAMIC MODELLING AND VENSIM SOFTWARE
Year: 2017

System dynamics simulation modelling technique is taught to students at undergraduate and graduate levels.The students are taught how to develop a system dynamics model of the system under study. This book is written to help students understand the concepts and fundamental elements of system dynamics simulation, and provide a step by step guide in conducting a system dynamics study. This book is suitable for students who are studying system dynamics simulation modelling at undergraduate and graduate levels.It offers the concepts and application of system dynamics as well as provides an approach for modelling effectively.Having read this book, the reader will be able to: *Learn the concept of system dynamics simulation and its application, Understand the important steps of modelling process, and*Conduct a system dynamics study successfully.
A hybrid dynamic berth allocation planning problem with fuel costs considerations for container terminal port using chemical reaction optimization approach
Venue: Ann. Oper. Res.
Year: 2020

This paper investigates the dynamic ship berth allocation problem for a container handling port, focusing on vessel waiting time at the anchorage due to the unavailability of the berth and quay cranes. A mixed integer linear programming model considering the fuel cost associated with waiting time and operational time of the docked vessel is developed. The hiring of the quay cranes to load/unload the containers from the ship and arrangement of the vessels in different berths is taken into account. Fuel consumed by the vessels while performing their respective port operations is incorporated in the model for addressing the sustainability aspects in berth allocation problem. A chemical reaction optimization algorithm is proposed to solve the problem in a large scale realistic environment and compared with the results with block based genetic algorithm, genetic algorithm and particle swarm optimization. The computational experiment illustrates and validates the proposed model on a real case scenario of the port located in India. The case shows that the developed model achieves better utilization of port resources and available berths.
Genre preferences in Reading Comprehension materials in first level English book of Senior High School
Year: 2019

This study aimed to know genre preferences in the reading comprehension material in first level English book of senior high school. This study, which is employed a qualitative narrative technique with no statistical analysis, described some material for reading comprehension material, such as descriptive text, narrative text, and recount text. This study revealed that the reading comprehension materials in first level English book of senior high school was presented into ten reading comprehension materials. Such as: self introduction, expression of compliment, plans and intention, descriptive text I and II, announcement, past and present prefect tense, recount text, narrative text, and song. It also revealed that genre preferences in the reading comprehension materials in first level English book senior high school was presented into three genre preferences: descriptive text, recount text, and narrative text. DOI:10.26905/enjourme.v4i2.3708
Discounted Cumulated Gain Based Evaluation of Multiple Query IR Sessions
Venue: ECIR
Year: 2008

IR research has a strong tradition of laboratory evaluation of systems. Such research is based on test collections, pre defined test topics, and standard evaluation metrics. While recent research has emphasized the user viewpoint by proposing user based metrics and non binary relevance assessments, the methods are insufficient for truly user based evaluation. The common assumption of a single query per topic and session poorly represents real life. On the other hand, one well known metric for multiple queries per session, instance recall, does not capture early (within session) retrieval of (highly) relevant documents. We propose an extension to the Discounted Cumulated Gain (DCG) metric, the Session based DCG (sDCG) metric for evaluation scenarios involving multiple query sessions, graded relevance assessments, and open ended user effort including decisions to stop searching. The sDCG metric discounts relevant results from later queries within a session. We exemplify the sDCG metric with data from an interactive experiment, we discuss how the metric might be applied, and we present research questions for which the metric is helpful.
Deep neural networks for small footprint text dependent speaker verification
Venue: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2014

In this paper we investigate the use of deep neural networks (DNNs) for a small footprint text dependent speaker verification task. At development stage, a DNN is trained to classify speakers at the frame level. During speaker enrollment, the trained DNN is used to extract speaker specific features from the last hidden layer. The average of these speaker features, or d vector, is taken as the speaker model. At evaluation stage, a d vector is extracted for each utterance and compared to the enrolled speaker model to make a verification decision. Experimental results show the DNN based speaker verification system achieves good performance compared to a popular i vector system on a small footprint text dependent speaker verification task. In addition, the DNN based system is more robust to additive noise and outperforms the i vector system at low False Rejection operating points. Finally the combined system outperforms the i vector system by 14% and 25% relative in equal error rate (EER) for clean and noisy conditions respectively.
Multi Stream Attention Based BLSTM with Feature Segmentation for Speech Emotion Recognition
Venue: INTERSPEECH
Year: 2020

This paper proposes a speech emotion recognition technique that considers the suprasegmental characteristics and temporal change of individual speech parameters. In recent years, speech emotion recognition using Bidirectional LSTM (BLSTM) has been studied actively because the model can focus on a particular temporal region that contains strong emotional characteristics. One of the model's weaknesses is that it cannot consider the statistics of speech features, which are known to be effective for speech emotion recognition. Besides, this method cannot train individual attention parameters for different descriptors because it handles the input sequence by a single BLSTM. In this paper, we introduce feature segmentation and multi stream processing into attention based BLSTM to solve these problems. In addition, we employed data augmentation based on emotional speech synthesis in a training step. The classification experiments between four emotions (i.e. anger, joy, neutral, and sadness) using the Japanese Twitter based Emotional Speech corpus (JTES) showed that the proposed method obtained a recognition accuracy of 73.4% which is comparable to human evaluation (75.5%