nils-herrmann/clean_scirepeval huggingface dataset:
OpenAIRE fur Repository ManagerInnen wie Repository ManagerInnen Open Science unterstutzen konnen
Venue: Mitteilungen der Vereinigung Osterreichischer Bibliothekarinnen und Bibliothekare
Year: 2019

Das EU Projekt OpenAIRE unterstutzt seit 2009 nun bereits im vierten Projektzyklus die Anstrengungen der Europaischen Kommission, wissenschaftliche Ergebnisse zuganglich, wiederverwendbar und offen zu gestalten. Mit der European Open Science Cloud (EOSC) strebt die EU bis 2022 die Schaffung einer Forschungsdatenplattform an, die WissenschafterInnen und Studierenden sowie der Offentlichkeit zur Verfugung stehen soll. OpenAIRE Advance (2018 2020) ist in den Vorbereitungen zur EOSC mit anderen Projekten involviert und setzt sich hier zum Ziel, den Gedanken von Open Science einerseits zu verankern und andererseits die Infrastruktur zu verstetigen. Die Anbindung von institutionellen oder themenspezifischen Repositorien aus ganz Europa an das OpenAIRE Portal stellt hierfur eine der Kernaufgaben dar. Schliesslich ermoglicht diese eine leichterte Auffindbarkeit von Forschungsoutput und erhoht damit die Sichtbarkeit wissenschaftlicher Leistungen. Im vorliegenden Beitrag werden die Vorteile der Compliancy von institutionellen und disziplinspezifischen Repositorien im Kontext von Open Science diskutiert, es wird auf die technischen Voraussetzungen fur eine solche eingegangen und zukunftige sich noch in Planung befindliche Services vorgestellt.
KONTROL DIRI DAN DUKUNGAN SOSIAL TEMAN SEBAYA DENGAN KEPATUHAN SANTRI DALAMMELAKSANAKAN TATA TERTIB
Year: 2020

Penelitian ini bertujuan untuk mengetahui hubungan kontrol diri dan dukungan sosialteman sebaya dengan kepatuhan santri dalam melaksankan tata tertib di PondokPesantren Sirnarasa, Ciamis Jawa Barat. Penelitian menggunakan metode kuantitatif,teknik pengambilan sampel menggunakan random sampling dengan sampel sebanyak92 santri. Pengambilan data menggunakan skala likert terdiri dari skala kepatuhan,skala kontrol diri, dan skala dukungan sosial teman sebaya, analisis datamenggunakan bivariate correlation dan multivariate correlation dengan bantuanprogram SPSS 24.00 for windows. Hasil analisis teknik bivariate correlationmenunjukkan ada hubungan yang signifikan dengan arah positif antara kontrol diridengan kepatuhan di mana koefisien korelasi rxy1 sebesar 0,436 dan p< 0,05 sertaadanya hubungan yang signifikan dengan arah positif antara dukungan sosial temansebaya dengan kepatuhan di mana koefisien korelasi rxy2 sebesar 0,433 dan p< 0,05.Selanjutnya uji hipotesis teknik multivariate correlation menunjukkan ada hubunganyang signifikan dengan arah positif antara kontrol diri dan dukungan sosial temansebaya dengan kepatuhan R 0,515 dan p< 0,05. Sumbangan efektif antara kontrol diridan dukungan sosial teman sebaya dengan kepatuhan sebesar 26,5% sedangkan 73,5%merupakan sumbangan dari faktor lain yang tidak di teliti
A Review on Evolution of 3GPP Systems Interworking with WLAN
Venue: J. ICT Stand.
Year: 2015

is succeeding on its fifth generation (5G) Over the past decade, interworking between heterogeneous RATs has undergone remarkable growth, as there is explosive growth in mobile devices such as smartphones supporting multiple RATs, especially Global System for Mobile communications (GSM) Code division multiple access (CDMA) Universal Mobile Telecommunications System (UMTS) High Speed Packet Access (HSPA) Long Term Evolution (LTE) Wireless Local Area Network (WLAN) WLAN is complementary options available to mobile operators when they consider expanding the user data traffic capacity further from the unlicensed spectrum. Since 2004 (Release 6) the Third Generation Partnership Project (3GPP)  has initiated to develop a 3GPPWLAN interworking architecture to allow 3GPP service providers to offload data traffic from wide area wireless spectrum to WLANs in indoor locations, hotspots, and other areas with high user density. The initial work in 3GPP specified loose integration (at the core network) and progressively introduced potential enhancements for tighter integration (at the radio access network) based on market trends and demands. This paper provides an insight on the evolution of 3GPP systems interworking with WLAN from 3GPP Release 6 to Release 13. Journal of ICT, Vol. 3, 133 156.
Canadian diplomacy and the Offshore Islands Crisis, 1954 1955: A limited national interest
Year: 2013

In September 1954 forces from the People's Republic of China began shelling Chinese Nationalist positions on the tiny offshore islands that lay between the mainland and Formosa (present day Taiwan) The outsized US response to this routine harassment sparked a Cold War confrontation that soon threatened to escalate out of control. This paper explores Canada's stake in that crisis. It follows Ottawa's early reaction to the events in the straits and traces foreign minister Lester B. Pearson's mediatory efforts to promote negotiations and a peaceful settlement. Pearson's liberal internationalist impulses, the paper argues, were always balanced and shaped by a realist calculation of where Canada's national interest lay. His doubts about the wisdom of US policy and his commitment to allied unity ensured that he beat a dignified retreat when the circumstances for peacemaking proved unpropitious.
The Relationship between Listening Anxiety Listening Comprehension Strategies and Listening Performance among Iranian EFL University Students
Year: 2016

The present study was conducted to explore the relationship between listening anxiety, listening strategies, and listening proficiency among Iranian EFL university students. A total number of 110 EFL language learners participated in this study. Three instruments were used in this study. The instruments were comprised of: (a) Foreign Language Listening Anxiety Scale (FLLAS) (b) Listening Strategy Questionnaire, and (C) an original TOEFL iBT test by ETS. Based on the results, it was found out that EFL language learners use Meta cognitive listening strategies the most followed by affective strategies, memory strategies, compensation strategies and cognitive strategies. Moreover, it was found out that all listening strategies were negatively correlated with listening anxiety, which means that as the anxiety level of the participants increases they use listening strategies less and vice versa. In addition, it was found out that compensation and meta cognitive category of listening strategies positively correlated with listening proficiency, while cognitive category negatively correlated with listening proficiency, suggesting that more proficient participants use more compensation and meta cognitive strategies but less cognitive listening strategies. In other words, as listening proficiency increases, compensation and meta cognitive listening strategy use increases and cognitive strategy use decreases. Finally, it was found out that listening is an anxiety inducing skill and listening proficiency plays a key role in determining the level of anxiety. In other words, as listening proficiency increases, the listening anxiety decreases and vice versa.
Digital technologies for language learning and teaching
Year: 2013

Digital Technologies for Language Learning and Teaching provides a state of the art overview of many of the recent trends in digital education and learning applied to a language learning context. In opposition to much of the literature on learning technologies, Thomas argues against both the techno optimist and techno skeptical positions that have dichotomized debates about digital technologies in education. The book adopts a refreshingly critical and historical perspective and examines a number of key areas of technology use, combining both theoretical perspectives and illustrative case studies. It argues that the use of digital technologies in education has to be grounded in sound pedagogy rather than a fashionable anti school discourse. Instructors have explored how new digital tools and virtual learning environments could solve many of the problems they face in the language classroom, from lack of student engagement and motivation, to the absence of creativity and learner participation. Digital Technologies for Language Learning and Teaching addresses the myths, realities, potential and implications of these digital transformations and their specific impact on language learning. By examining a number of areas that have been closely linked with these transformative claims, including digital literacies, social media, digital gaming, virtual worlds, and mobile learning, the book outlines the importance of a task based approach utilizing digital technologies.
Learning to Teach Science Using English as the Medium of Instruction
Year: 2009

Malaysia is currently reforming its education system in line with the government's Vision 2020. Key areas such as science and mathematics education are high on the agenda. However, as considerable world knowledge is written in English, Malaysian preservice teachers are being educated to teach these areas using English as the Medium of Instruction (EMI) This study describes Malaysian preservice teachers' perceptions about their preparation for learning to teach science using EMI at the conclusion of their first year of a new Bachelor of Education Studies (Primary Science) degree. An open ended questionnaire collected data from 50 Malaysian preservice teachers from a Malaysian institute. These preservice teachers indicated that English vocabulary, grammar, and pronunciation were paramount for their concept development in science education. Self assessments after one year of education also indicated an increase in English language proficiency towards teaching primary science education (Pre course: M=4.68, SD=1.20; after one year: M=6.38, SD=1.12) Emailing, Internet chatting, short service messaging, and allocating English only days were considered other ways for increasing such proficiencies. These and other findings are discussed in this paper to provide an understanding on practices that may be incorporated into coursework for enhancing both science education and English language skills.
Augmented Behavioral Cloning from Observation
Venue: 2020 International Joint Conference on Neural Networks (IJCNN)
Year: 2020

Imitation from observation is a computational technique that teaches an agent on how to mimic the behavior of an expert by observing only the sequence of states from the expert demonstrations. Recent approaches learn the inverse dynamics of the environment and an imitation policy by interleaving epochs of both models while changing the demonstration data. However, such approaches often get stuck into sub optimal solutions that are distant from the expert, limiting their imitation effectiveness. We address this problem with a novel approach that overcomes the problem of reaching bad local minima by exploring: (i) a self attention mechanism that better captures global features of the states; and (ii) a sampling strategy that regulates the observations that are used for learning. We show empirically that our approach outperforms the state of the art approaches in four different environments by a large margin.
Perancangan sistem manajemen energi pada industri manufaktur berdasarkan ISO 50001:2011
Year: 2020

As one manufacturing industry with a large level of energy consumption makes energy management mandatory applied at PT. XYZ, the purpose of this research is to design energy management system implementation strategy in PT. XYZ based on ISO 50001. Started by self assessment and by collecting data on the use of primary energy sources in the company, followed by processing and analyzing using simple linear regression. The self assessment results show 38% of the total value' s completeness of existing program in the clause of ISO 50001. From the processing and analyzing' s energy usage showed energy base line and energy performance indicators (EnPI) of the company. The result of research is identifies and proposes the potential of energy savings in air compressor distribution system, steam boiler distribution, and electrical distribution system with good housekeeping, control system, and modification, proposes the energy management system implementation based on Deming 's PDCA cycle, and continued by recommending roadmap towards the implementation of energy management systems.
Conformable and scalable tactile sensor skin for curved surfaces
Venue: Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006.
Year: 2006

We present the design and realization of a conformable tactile sensor skin (patent pending) The skin is organized as a network of self contained modules consisting of tiny pressure sensitive elements which communicate through a serial bus. By adding or removing modules it is possible to adjust the area covered by the skin as well as the number (and density) of tactile elements. The skin is therefore highly modular and thus intrinsically scalable. Moreover, because the substrate on which the modules are mounted is sufficiently pliable to be folded and stiff enough to be cut, it is possible to freely distribute the individual tactile elements. A tactile skin composed of multiple modules can also be installed on curved surfaces. Due to their easy configurability we call our sensors "cut and paste tactile sensors." We describe a prototype implementation of the skin on a humanoid robot
Major League Baseball Anti Trust Immunity: Examining the Legal and Financial Implications of Relocation Rules
Year: 2006

Major League Baseball (MLB) rules restrict the movement of any franchise into another's territory. These territorial rules are designed to protect each team's potential local revenue sources as well as to provide stability throughout the league. Recently, Major League Baseball approved financial compensation for the Washington Nationals move into the Baltimore Orioles' territory primarily because it was in the best interest of MLB even though it hurt the Orioles. However, the Oakland Athletics were unable to even negotiate a potential compensation plan for a move into the San Francisco Giants territory, despite the apparent financial benefit the move could have provided for every other league franchise. The Athletics are already located within 15 miles of the Giants, and their potential 40 mile move to San Jose, California would not add a new team to the San Francisco Bay Area; rather, it would simply be a move of a current team to a different location within the metropolitan area. The refusal of the Giants or MLB to negotiate a potential compromise has kept the Oakland Athletics in a substandard facility and has led to their potential move to Fremont, CA a less desirable location than San Jose.This paper investigates the legal, policy, and financial considerations concerning Major League Baseball's territorial rules. Specifically, it addresses antitrust law as it pertains to American professional sport, relative sport franchise relocation cases, financial arguments why leagues desire to control relocation, financial components of MLB's current Collective Bargaining Agreement, and the legal and financial impact of a challenge to MLB's territorial rules an option the Oakland Athletic initially investigated prior to their decision to pursue a potential move to Fremont.
Multi Camera Vehicle Tracking with Powerful Visual Features and Spatial Temporal Cue
Venue: CVPR Workshops
Year: 2019

Vehicle re identification and multi camera multi object vehicle tracking are important components in the field of intelligent traffic, which is attracting more and more attention. In the NVIDIA AI City Challenge, we propose our solutions to solve these issues. In Track1 task, clustering loss and trajectory consistent loss are introduced into the vehicle re identification training framework to train more suitable trajectory based features for the clustering task. Besides, spatial temporal cue is fully excavated to make up the deficiency of appearance feature and constrained hierarchical clustering is introduced into the pipeline to get the final cluster results. In Track2 task, we propose an effective vehicle training framework and trajectory based weighted ranking method, which greatly improve the performance. Furthermore, an efficient way to mining the additional data to train more robust features is proposed to enlarge the training data. Finally, our algorithm achieves the state of theart performance in the competition.
Understanding advanced DRAM edge placement error budget and opportunities for control
Venue: Advanced Lithography
Year: 2020

In leading edge patterning processes, overlay is now entangled with CD including OPC residuals and stochastics. This combined effect is a serious challenge for continued shrink and can be characterized with an Edge Placement Error (EPE) budget containing multi domain components: global and local CD, local placement errors, overlay errors, etch biases and OPC. EPE defines process capability and ultimately relates to device yield. Understanding the EPE budget leads to efficient ways to monitor process capability and optimize it using EPE based process control applications. We examine a critical EPE use case on a leading edge DRAM node. We start by constructing and verifying the EPE Budget via densely sampled on product in device local, global CD and Overlay metrology after the etch process step. EPE budget contributors are ranked according to their impact to overall EPE performance and later with simulated EPE performance improvements per component. A cost/benefit analysis is shown to help choose the most HVM friendly solutions.
Prognostic Assessment of COVID 19 in ICU by Machine Learning Methods: A Retrospective Study.
Venue: Journal of medical Internet research
Year: 2020

Patients with coronavirus disease (COVID 19) in ICU have a high mortality rate, and how to early assess the prognosis and carry out precise treatment is of great significance.  To use machine learning to construct a model for the analysis of risk factors and prediction of death among ICU patients with COVID 19.  In this retrospective study, 123 COVID 19 patients inthe ICU of Vulcan Hill Hospital were selected from the database, and data were randomly divided into a training data set (n 98) and test data set (n 25) with a 4:1 ratio. Significance tests, analysis of correlation and factor analysis were used to screen the 100 potential risk factors individually. Conventional logistic regression methods and four machine learning algorithms were used to construct the risk prediction model for the prognosis of COVID 19 patients in ICU. Performance of these machine learning models was measured by the area under the receiver operating characteristic curve (AUC) Model interpretation and model evaluation of the risk prediction model, such as calibration curve, SHAP, LIME, etc. were performed to ensure its stability and reliability.The outcome is based on the ICU death recorded from the database.  Layer by layer screening of 100 potential risk factors finallyrevealed 8 important risk factors that were included in the risk prediction model: lymphocyte percentage (LYM% prothrombin time (PT) lactate dehydrogenase (LDH) total bilirubin (T Bil) percentage of eosinophils (EOS% creatinine(Cr) neutrophil percentage (NEUT% albumin (ALB) level. Finally, eXtreme Gradient Boosting (XGBoost) established by 8 important risk factors showed the best recognition ability in the training set of 5 fold cross validation (AUC=0.86) and the verification queue (AUC=0.92) The calibration curve showed that the risk predicted by the model was in good agreement with the actual risk. In addition, using SHapley Additive exPlanations (SHAP) and Local Interpretable Model Agnostic Explanations (LIME) algorithms, feature interpretation and sample prediction interpretation algorithms of the XGBoost black box model were implemented. Additionally, the model has been translated into an online risk calculator that is freely available for the public usage http:/114.251.235.51:1226/index)  The 8 factors XGBoost model predicts risk of death in ICU patients with COVID 19 well,which initially demonstrates stability and can be used effectively to predict COVID 19 prognosis in ICU patients.
The Ideal Gas in Slow Time
Year: 2020

We continue our exploration of thermodynamics at long observational timescales, "slow time," by including turbulent dynamics leading to a condition of fluctuating local equilibrium. Averaging these fluctuations in wind speed and temperature results in a velocity distribution with heavy tails which, however, are necessarily truncated at some large molecular speed preserving all moments of the velocity distribution including the energy. This leads to an expression for the ideal gas law in slow time which as its core has the superficially familiar term 3 2 N k th\frac{3}{2}Nk\theta in addition to a term accounting for the large scale fluctuations, which is also proportional to the particle number N; th is a new temperature including thermalization of wind. The traditional temperature T no longer exists. Likewise, the additional energy term necessitates a new quantity that parallels entropy in the sense that it captures hidden degrees of freedom. Like entropy, it captures physical properties manifesting indirectly, but on scales larger than the familiar laboratory scales. We call this quantity epitropy.
Multiple sclerosis identification by convolutional neural network with dropout and parametric ReLU
Venue: J. Comput. Sci.
Year: 2018

Multiple sclerosis is a condition affecting brain and/or spinal cord. Based on deep learning, this study aims to develop an improved convolutional neural network system. We collected 676 multiple sclerosis brain slices and 681 healthy control brain slices. Data augmentation was used to increase the size of training set. Our improved convolutional neural network combined the parametric rectified linear unit (PReLU) and dropout techniques. Finally, a 10 layer deep convolutional neural network was established, with 7 convolution layer and 3 fully connected layers. The retention probabilities of three dropout layers are set as 0.4, 0.5, and 0.5, respectively. Our method achieved a sensitivity of 98.22% a specificity of 98.24% and an accuracy of 98.23% The dropout helped increase the accuracy by 0.88% compared to not using dropout. PReLU helped increase the accuracy by 1.92% compared to using ordinary ReLU, and by 1.48% compared to using leaky ReLU. This proposed method is superior to four state of the art approaches.