nils-herrmann/clean_scirepeval huggingface dataset:
PEMBUATAN GAME ROLE PLAYING TURN BASED DENGAN SISTEM ROCK PAPER SCISSORS "GAVANGEN"
Year: 2018

Game "Gevangen" adalah game dengan genre Role Playing Game turn based dengan sistem Rock Paper Scissors. Game ini dirancang dengan menggunakan game engine Unity dengan C# sebagai bahasa pemrogramannya. Game ini memiliki tujuan untuk mengisi waktu luang dengan melawan monster dan menyelesaikan cerita dalam game ini. Pengujian dilakukan dengan metode blackbox testing, alpha testing oleh dosen pembimbing, dan beta testing dengan melalui survei pada 30 responden. Hasil pengujian menunjukkan bahwa masih banyak pemain yang tidak pernah memainkan game Role Playing Game turn based dengan system Rock Paper Scissors. Game "Gevangen" memiliki desain tampilan permainan dan gameplay yang menarik namun masih memiliki kekurangan yaitu cerita dalam game yang disuguhkan biasa saja.
Wideband (22 30GHz) mm Wave Substrate Integrated Waveguide (SIW) Antenna for 5G Applications
Venue: 2019 IEEE Conference on Antenna Measurements Applications (CAMA)
Year: 2019

In this paper, the SIW cavity slots antenna wideband millimeter wave is proposed for fifth generation (5G) communication. The antenna also shows an average gain of 8,574 dBi, 20 x 20 mm2 compact. The proposed antenna applies to 5G application at 28 GHz operating frequency. The simulated results show that the SIW antenna resonates throughout the 22 GHz to 30 GHz bands to cover all applications within this range. The coefficients of reflection in all ranges from 22 GHz to 30 GHz are below 10 dB. At 28 Ghz, high efficiency and outstanding gain of the antenna is achieved.
Efficient or Fair? Operationalizing Ethical Principles in Flood Risk Management: A Case Study on the Dutch German Rhine
Venue: Risk analysis an official publication of the Society for Risk Analysis
Year: 2020

Flood risk management decisions in many countries are based on decision support frameworks which rely on cost benefit analyses. Such frameworks are seldom informative about the geographical distribution of risk, raising questions on the fairness of the proposed policies. In the present work, we propose a new decision criterion that accounts for the distribution of risk reduction and apply it to support flood risk management decisions on a transboundary stretch of the Rhine River. Three types of interventions are considered: embankment heightening, making Room for the River, and changing the discharge distribution of the river branches. The analysis involves solving a flood risk management problem according to four alternative formulations, based on different ethical principles. Formulations based on cost optimization lead to very poor performances in some areas for the sake of reducing the overall aggregated costs. Formulations that also include equity criteria have different results depending on how these are defined. When risk reduction is distributed equally, very poor economic performance is achieved. When risk is distributed equally, results are in line with formulations based on cost optimization, while a fairer risk distribution is achieved. Risk reduction measures also differ, with the cost optimization approach strongly favoring the leverage of changing the discharge distribution and the alternative formulations spending more on embankment heightening and Room for the River, to rebalance inequalities in risk levels. The proposed method advances risk based decision making by allowing to consider risk distribution aspects and their impacts on the choice of risk reduction measures.
Data Protection Conflicts between the United States and the European Union in the War on Terror: Lessons Learned from the Existing System of Financial Information Exchange
Year: 2008

In the middle of 2006, two significant issues, both involving privacy and specifically data protection, came to the forefront of U.S. efforts in the War on Terror. First, in May 2006, the European Court of Justice (ECJ) annulled an agreement between the United States and the European Union regarding the transfer of airline passenger information or passenger name records (PNR) from the European Union to the United States. The annulment of the PNR data transfer agreement by the ECJ reignited the debate as to whether the transfers violated E.U. data protection laws. The second major issue arose on June 24, 2006 when the New York Times uncovered a secret U.S. government financial record surveillance program called the Terrorist Finance Tracking Program (TFTP) Details of the secret TFTP immediately raised concerns of data protection violations both in the United States and in the European Union. Because terrorists reveal themselves to the international community only (1) when they travel abroad; or (2) when they transact abroad, both the PNR transfer and the TFTP represent noteworthy counter terrorism efforts by the United States. Clearly, however, the annulment of the PNR data transfer agreement and disclosure of the TFTP to the international community have strained relations between the European Union and the United States. The European Union and the United States will be hard pressed to improve relations unless the two governments can find common ground regarding the impact of their data protection policies on these two distinct problems. In order to find that common ground, this note recommends (1) that the United States terminate the TFTP and improve the existing system
Analysis of Techniques for Credit Card Fraud Detection: A Data Mining Perspective
Venue: Advances in Intelligent Systems and Computing
Year: 2019

The expeditious development of World Wide Web tradition has derived the situation where online shopping and other payment services become most popular among people. They always buy goods and services online or off line and use their credit or debit card for payment. With the swipe card employment, the fraud rate is also swelling day by day. Hence, the credit card has evolved as the standardized method of payment and the fraud associated with credit card is also expanding exponentially. As we know, many modern data mining techniques have been deployed for the detection of fraud in the domain of credit cards, such as Hidden Markov model, fuzzy logic, K nearest neighbor, genetic algorithm, Bayesian network, artificial immune system, neural network, decision tree, support vector machine, hybridized method, and ensemble classification. The purpose addressed in this paper is to consolidate various data mining approaches used for finding credit card frauds by researchers to carry out research in the domain and has a state of the art view of the financial domain.
COVID Net US: A Tailored, Highly Efficient, Self Attention Deep Convolutional Neural Network Design for Detection of COVID 19 Patient Cases from Point of care Ultrasound Imaging
Venue: DART/FAIR@MICCAI
Year: 2021

The Coronavirus Disease 2019 (COVID 19) pandemic has impacted many aspects of life globally, and a critical factor in mitigating its effects is screening individuals for infections, thereby allowing for both proper treatment for those individuals as well as action to be taken to prevent further spread of the virus. Point of care ultrasound (POCUS) imaging has been proposed as a screening tool as it is a much cheaper and easier to apply imaging modality than others that are traditionally used for pulmonary examinations, namely chest x ray and computed tomography. Given the scarcity of expert radiologists for interpreting POCUS examinations in many highly affected regions around the world, lowcost deep learning driven clinical decision support solutions can have a large impact during the on going pandemic. Motivated by this, we introduce COVID Net US, a highly efficient, self attention deep convolutional neural network design tailored for COVID 19 screening from lung POCUS images. Experimental results show that the proposed COVIDNet US can achieve an AUC of over 0.98 while achieving 353x lower architectural complexity, 62x lower computational complexity, and 14.3x faster inference times on a Raspberry Pi. Clinical validation was also conducted, where select cases were reviewed and reported on by a practicing clinician (20 years of clinical practice) specializing in intensive care (ICU) and 15 years of expertise in POCUS interpretation. To advocate affordable healthcare and artificial intelligence for resource constrained environments, we have made COVID Net US open source and publicly available as part of the COVID Net open source initiative. 6 https:/github.com/maclean alexander/COVID Net US/ ar X iv :2 10 8. 03 13 1v 1 ee ss .I V 5 A ug 2 02 1
Great Expectations? Relation of Previous Experiences With Social Robots in Real Life or in the Media and Expectancies Based on Qualitative and Quantitative Assessment
Venue: Front. Psychol.
Year: 2019

Social robots, which mostly look and behave like humans, are often perceived as somehow alive and treated similar to humans, despite the fact that they are non living electronic devices. Based on considerations of the uncertainty reduction theory, the question arises what expectancies regarding social robots people have and what sources they use to achieve these expectancies. To receive an in depth understanding of people's expectancies regarding social robots and particularly how these expectancies are influenced by people's experiences with real robots but also with fictional robots from media, thirteen semi structured interviews and a quantitative online study (n 433) were conducted. Results indicate that people's experiences with robots in the media lead to high expectations regarding the skills of robots, which in turn increase people's general expectancies regarding social robots being part of the society as well as their personal lives. Furthermore, knowledge of negatively perceived fictional robots increases negative expectancies of robots becoming a threat to humans, while technical affinity reduces general robot anxiety.
The Promise of Fintech Financial Inclusion in the Post COVID 19 Era
Year: 2020

Technology is changing the landscape of the financial sector, increasing access to financial services in profound ways. These changes have been in motion for several years, affecting nearly all countries in the world. During the COVID 19 pandemic, technology has created new opportunities for digital financial services to accelerate and enhance financial inclusion, amid social distancing and containment measures. At the same time, the risks emerging prior to COVID 19, as digital financial services developed, are becoming even more relevant.
Revision de las estrategias para la prevencion de lesiones en el deporte desde la actividad fisica
Year: 2008

Injuries are a serious problem in the training competition process, since their occurrence leads to modification or interruption of activity. Any lesion alters training plans and is an important factor in monitoring of training. Within the sports community, the most common intervention focuses on recovery from injuries in order to return to previous performance levels, this process being expensive from both the economic and sporting points of view. However, in many sports, strategies aimed at injury prevention have not been systematically implemented, despite their proven effectiveness. The present article reviews some of preventive programs that can be incorporated into training schedules to minimize the impact of injuries.
Les "techniques du corps" dans l'apprentissage du football professionnel
Year: 2009

L'acces au marche du travail footballistique exige un long et intensif apprentissage que dispense des institutions specifiques, les centres de formation des clubs professionnels. Le travail sociologique presente ici s'appuie sur une enquete socio ethnographique, melant entretiens (n=58) et observation de longue duree, a l'interieur de l'une de ces structures. Celle ci forme environ cent vingt jeunes ages de 12 a 19 ans. Grace a la methodologie employee, l'etude analyse la maniere dont ces apprentis footballeurs s'approprient une gestualite specifique et souligne comment, en depassant un point de vue strictement technique, cet apprentissage participe de leur interiorisation d'une culture professionnelle et des dispositions sociales qui la composent. Deux points meritent alors d'etre soulignes. D'une part, l'apprentissage dans le centre de formation se caracterise par le poids d'une mise en exercice du jeu qui, en reposant sur une planification rationalisee de l'enseignement, implique une importante mise en ordre spatio temporelle. La logique de l'exercice et l'usage regle du temps et de l'espace qui en decoule, la discipline des comportements qui affecte le jeu sont constitutifs de ce mode d'enseignement qui proscrit la debauche spontanee d'energie. D'autre part, les techniques elle memes vehiculent un rapport a l'activite et a soi marque par la discipline et la valorisation de l'effort. Parce que les gestes sont dotes d'une valeur symbolique qui en font des " techniques du corps " (Marcel Mauss) l'acquisition d'habiletes et d'un style de jeu participe de cette socialisation. Le desir d'entrer dans le duel et le drible en exprimant une virtuosite technique est ainsi reprime au profit d'une mise en ordre individuelle et collective et de l'initiation a un jeu que les formateurs nomment " propre " et " simple " C'est ainsi que l'apprentissage de ces competences constitue une education corporelle qui contribue a la production de l'ethos de footballeur professionnel.
Financial Modelling and Memory: Mathematical System
Year: 2015

Data based search for patterns are of concern to almost all fields of studies and research. To do so, parametric mathematical models are constructed to explain observed data sets, forecast future prices, etc. The models we use are extremely varied, seeking to be reliable, robust and explanatory. Financial models for example have for the most part assumed models that are based on drift and randomness to construct models of asset prices. Typical examples include random walks and stochastic (Brownian motion) differential equations (such as a lognormal process) as well as Poisson and Jump stochastic processes. These latter models are based on events that occur at random and independent times. They assume also a number of simplifying assumptions, all of which are either explicit or implicit. For example, stochastic differential equations assume that data can be expressed in terms of two statistical properties: the data drift and its volatility, both of which are defined in terms of underlying (Brownian motion) normally and statistically distributed events. By the same token, Poisson like jump processes are defined in terms of a memory less process (with independent inter events time distributions) To circumvent some of their assumptions, more complex and multi variable models are used to account for observations that such models fail to explain. For the most part these models are based on both a rationality and an experience acquired based on theoretical constructs and on data analyses. These models are extremely useful, and provide an ex ante interpretation for the behavior of data sets as well define the statistical properties of observed financial variables. Ex post, however, these models may default since all models are merely an educated hypothesis of underlying processes. Modeling financial processes is therefore a work in process, in search for coherent and complete mathematical systems that can on the one hand be justified theoretically and on the other account far more precisely for observed data sets.
SUPERVISI AKADEMIK DALAM UPAYA PEMBINAAN KOMPETENSI PROFESIONAL GURU PENDIDIKAN ANAK USIA DINI (PAUD)
Year: 2019

Artikel ini bertujuan untuk memberikan gambaran tentang bagaimana supervisi akademik dilakukan sebagai upaya pembinaan kompetensi profesional guru pendidikan anak usia dini(PAUD).Keberhasilan proses pembelajaran yang berkualitas sangat bergantung pada peran guru sebagai unsur tenaga pendidik tanpa terkecuali bagi guru PAUD.Guru PAUD dituntut untuk memiliki kemampuan atau kompetensi dalam menjalankan profesinya sebagai guru yang profesional.Kompetensi yang dimaksud meliputi kompetensi pedagogik, kompetensi kepribadian, kompetensi profesional dan kompetensi social.Kegiatan supervisi akademik digunakan sebagai suatu pendekatan yang paling tepat dalam melakukan upaya pembinaan untuk membantu guru PAUD dalam mengembangkan kompetensi profesionalnya.Fungsi dari kegiatan supervisi akademik ini sebagai alat untuk mengelola pembelajaran di PAUD secara efektif.Pada kegiatan supervisi akademik, Kepala sekolah bertindak sebagai supervisor yang secara berkelanjutan memberikan pembinaan berupa pengamatan, penilaian, arahan, bimbingan dan bantuan kepada guru PAUD. profesi guru, kompetensi profesional, supervisi akademik Abstract This article aims to provide an overview of how academic supervision is carried out as an effort to foster the professional competence of early childhood education teachers (PAUD) The success of a quality learning process relies heavily on the role of the teacher as an element of the teaching staff without the exception of PAUD teachers. PAUD teachers are required to have the ability or competence in carrying out their profession as professional teachers. The competencies in question include pedagogic competence, personality competence, professional competence and social competence. Academic supervision activities are used as the most appropriate approach in conducting coaching efforts to assist PAUD teachers in developing their professional competencies. The function of academic supervision activities is a tool to effectively manage PAUD learning. In academic supervision activities, the Principal acts as a supervisor who continuously provides guidance in the form of observations, assessments, directives, guidance and assistance to PAUD teachers Keywords professional teacher, professional competence, academic supervision
PDKSAP Perfected Double Key Stealth Address Protocol without Temporary Key Leakage in Blockchain
Venue: 2020 IEEE/CIC International Conference on Communications in China (ICCC Workshops)
Year: 2020

The stealth address protocol is to create a one time temporary output address of a transaction, hide its real output address, destroy the association between the input address and the real output address to achieve privacy protection for user identities in the transaction. However, the widely used double key stealth address protocol (DKSAP) requires the sender to transmit the temporary public key along with the transaction, which enables attackers to easily identify stealth and non stealth transactions and can lead to the loss of some private information. We propose a double key stealth address protocol without temporary key leakage PDKSAP by which senders and receivers maintain local transaction record databases to record the number of transactions with other users. Senders and receivers generate a temporary key pair for a transaction based on the number of transactions between them, which prevent leaking the transaction temporary key. Finally, we verify the protocol through experiments.
Positive and Negative Politeness: A Cross Cultural Study of Responding to Apologies by British and Pakistani Speakers
Year: 2018

Speech etiquette is an essential part of culture, behavior and human communication. Based upon a theoretical framework of politeness and face threatening acts (FTAs) this study investigates cultural differences in apology responses (ARs) moderated by the threatened face type and the relationship between participants. A discourse completion test, consists of twelve situations is used for data collection. The data was collected from 150 Pakistani Urdu speakers (teachers, doctors, army personals, lawyers, journalists and academicians) working in different institutions and 30 British English speakers (faculty members of English Department, Coventry University, UK, Leeds University, UK and British Association of Applied Linguistics members) The findings reveal that Pakistanis are found using more positive face threatening apology responses (Acceptance and Acknowledgment) including Absolution, Dismissal, Intensifiers, and Acknowledgement with Thanking, Advice, and Suggestion, than British speakers who tend to use both positive FTAs (Acceptance) based on Absolution "That's Okay" and Dismissal "no worries at all but be careful next time" and negative FTAs based on Evasion with Deflection and Evasion with Thanking. The findings further illustrate that the understanding and demonstration of politeness and face in conversation functions are susceptible to cultural and sociolinguistic variations.
BioConceptVec: Creating and evaluating literature based biomedical concept embeddings on a large scale
Venue: PLoS Comput. Biol.
Year: 2020

A massive number of biological entities, such as genes and mutations, are mentioned in the biomedical literature. The capturing of the semantic relatedness of biological entities is vital to many biological applications, such as protein protein interaction prediction and literature based discovery. Concept embeddings which involve the learning of vector representations of concepts using machine learning models have been employed to capture the semantics of concepts. To develop concept embeddings, named entity recognition (NER) tools are first used to identify and normalize concepts from the literature, and then different machine learning models are used to train the embeddings. Despite multiple attempts, existing biomedical concept embeddings generally suffer from suboptimal NER tools, small scale evaluation, and limited availability. In response, we employed high performance machine learning based NER tools for concept recognition and trained our concept embeddings, BioConceptVec, via four different machine learning models on ~30 million PubMed abstracts. BioConceptVec covers over 400,000 biomedical concepts mentioned in the literature and is of the largest among the publicly available biomedical concept embeddings to date. To evaluate the validity and utility of BioConceptVec, we respectively performed two intrinsic evaluations (identifying related concepts based on drug gene and gene gene interactions) and two extrinsic evaluations (protein protein interaction prediction and drug drug interaction extraction) collectively using over 25 million instances from nine independent datasets (17 million instances from six intrinsic evaluation tasks and 8 million instances from three extrinsic evaluation tasks) which is, by far, the most comprehensive to our best knowledge. The intrinsic evaluation results demonstrate that BioConceptVec consistently has, by a large margin, better performance than existing concept embeddings in identifying similar and related concepts. More importantly, the extrinsic evaluation results demonstrate that using BioConceptVec with advanced deep learning models can significantly improve performance in downstream bioinformatics studies and biomedical text mining applications. Our BioConceptVec embeddings and benchmarking datasets are publicly available at https:/github.com/ncbi nlp/BioConceptVec.