nils-herrmann/clean_scirepeval huggingface dataset:
A Comparative Analysis of Crowdsourced Natural Language Corpora for Spoken Dialog Systems

Recent spoken dialog systems have been able to recognize freely spoken user input in restricted domains thanks to statistical methods in the automatic speech recognition. These methods require a high number of natural language utterances to train the speech recognition engine and to assess the quality of the system. Since human speech offers many variants associated with a single intent, a high number of user utterances have to be elicited. Developers are therefore turning to crowdsourcing to collect this data. This paper compares three different methods to elicit multiple utterances for given semantics via crowd sourcing, namely with pictures, with text and with semantic entities. Specifically, we compare the methods with regard to the number of valid data and linguistic variance, whereby a quantitative and qualitative approach is proposed. In our study, the method with text led to a high variance in the utterances and a relatively low rate of invalid data.
Music, Intelligence and Artificiality

The discipline of Music-AI is defined as that activity which seeks to program computers to perform musical tasks in an intelligent, which possibly means humanlike way. A brief historical survey of different approaches within the discipline is presented. Two particular issues arise: the explicit representation of knowledge; and symbolic and subsymbolic representation and processing. When attempting to give a precise definition of Music-AI, it is argued that all musical processes must make some reference to human behaviour, and so Music-AI is a central rather than a peripheral discipline for musical computing. However, it turns out that the goals of Music-AI as first expressed, the mimicking of human behaviour, are impossible to achieve in full, and that it is impossible, in principle, for computers to pass a musical version of the Turing test. In practice, however, computers are used for their non-human-like behaviour just as much as their human-like behaviour, so the real goal of Music-AI must be reformulated. Furthermore, it is argued that the non-holistic analysis of human behaviour which this reformulation entails is actually informative for our understanding of human behaviour. Music-AI could also be fruitfully concerned with developing musical intelligences which were explicitly not human. Music-AI is then seen to be as much a creative enterprise as a scientific one.
A learner-centred approach to developing team skills through web-based learning and assessment

In traditional face-to-face classrooms, collaborative learning has been endorsed as an effective pedagogy that fosters skills of analysis, communication and higher order thinking. Increasingly, as online learning environments for tertiary learners make use of course support systems, there is greater recognition of the potential of communications technologies to foster dialogue, networking and team skills among learners. Such skills are now among the recognised core attributes that graduates are expected to develop. In face-toface classroom students learn the skills of collaboration and teamwork by engaging in tasks defined and supervised by a teacher. In online environments teacher presence is often limited to task definition, management and feedback functions. Team skills and collaboration therefore need to be supported though different pedagogies and processes such as establishing a climate of trust and openness, communication protocols, resolution of conflict and group processes that provide sanctions and support. In this paper we describe an innovative approach to building the skills of decision-making and conflict resolution, leadership and clarity in goal setting and communication. A case study of tertiary learners illustrates how the essential aspects of task definition, resources to support group learning and integrated online assessment foster team skills.  Traditional university education is quite different from professional learning, not only in the organisation of curricula, but also in its forms of delivery. According to Taylor, (1997) the curriculum addresses knowledge for and about practice, and is delivered both in formal institutional settings and in the field of professional practice. Often, students studying for the professions are mature age and are highly motivated as they 06_McL 15/10/02 12:40 pm Page 571
System Design of a 77 GHz Automotive Radar Sensor with Superresolution DOA Estimation

This paper introduces a novel 77 GHz FMCW automotive long range radar (LRR) system concept. High resolution direction of arrival (DOA) estimation is an important requirement for the application in automotive safety systems. The challenges in system design regarding low cost and superresolution signal processing are discussed. Dominant interferences to the MUSIC DOA estimator are amplitude and phase mismatches due to inhomogeneous antenna patterns. System simulation results deliver design guidelines for the required signal-to-noise ratio (SNR) and the antenna design. Road traffic measurements with a demonstrator system show superior DOA resolution and demonstrate the feasibility of the design goals.
Obstacle detection using U-disparity on quadratic road surfaces

This paper addresses the problem of detecting obstacles that protruding from the road. Traditionally, the road surface has been considered flat, and camera orientation is fixed. However, both assumptions are not strictly true in urban scenarios. The proposed algorithm employs a time-of-flight (ToF) camera. It allows dynamic pitch/roll angles, height variations and represents the ground as a quadratic surface. The range information given by the camera is represented in both Euclidean and disparity domains, so that their domain characteristics support each other to achieve accurate and efficient detection results. Gradient filtering of the disparity image presents Euclidean planner patches, with which outliers can be minimised during road fittings. Obstacle points are subsequently detected by the connect component labelling algorithm. Experimental results show that the proposed method can effectively segment and detect multiple obstacles and presents their bounding boxes in complex scenarios.
Efficient and robust pseudonymous authentication in VANET

Effective and robust operations, as well as security and privacy are critical for the deployment of vehicular ad hoc networks (VANETs). Efficient and easy-to-manage security and privacy-enhancing mechanisms are essential for the wide-spread adoption of the VANET technology. In this paper, we are concerned with this problem; and in particular, how to achieve efficient and robust pseudonym-based authentication. We design mechanisms that reduce the security overhead for safety beaconing, and retain robustness for transportation safety, even in adverse network settings. Moreover, we show how to enhance the availability and usability of privacy-enhancing VANET mechanisms: Our proposal enables vehicle on-board units to generate their own pseudonyms, without affecting the system security.
ERP in Higher Education : A Case Study of SAP and Campus Management

Enterprise Resource Planning (ERP) software has been applied to industries to support financial accounting, procurement, human resources, customer service management and supply change management. Recently, it is being promoted to new areas, for example, higher education. This case study examines the application of ERP software to the student information management in higher education at a Midwestern university that has replaced its legacy software with an ERP system. This paper also explores critical success factors (CSF) for a successful ERP implementation discussed in the literature. In addition, this paper investigates user acceptance of this new system specifically examining the staff attitudes, concerns expressed and comfort level for the average user.
Cyber security for home users: A new way of protection through awareness enforcement

We are currently living in an age, where the use of the Internet has become second nature to millions of people. Not only do businesses depend on the Internet for all types of electronic transactions, but more and more home users are experiencing the immense benefit of the Internet. However, this dependence and use of the Internet bring new and dangerous risks. This is due to increasing attempts from unauthorised third parties to compromise private information for their own benefit – the whole wide area of cyber crime. It is therefore essential that all users understand the risks of using the Internet, the importance of securing their personal information and the consequences if this is not done properly. It is well known that home users are specifically vulnerable, and that cyber criminals have such users squarely in their target. This vulnerability of home users are due to many factors, but one of the most important ones is the fact that such home users are in many cases not aware of the risks of using the Internet, and often venture into cyber space without any awareness preparation for this journey. This paper specifically investigates the position of the home user, and proposes a new model, The E-Awareness Model (E-AM), in which home users can be forced to acquaint themselves with the risks involved in venturing into cyber space. The E-AM consists of two components : the awareness component housed in the E-Awareness Portal, and the enforcement component. This model proposes a way to improve information security awareness amongst home users by presenting some information security content and enforcing the absorption of this content. The main difference between the presented model and other existing information security awareness models, is that in the presented model the acquiring/absorption of the awareness content is compulsory the user is forced to proceed via the E-Awareness Portal without the option of bypassing it.
Unlinkable Coin Mixing Scheme for Transaction Privacy Enhancement of Bitcoin

Bitcoin combines a peer-to-peer network and cryptographic algorithm to implement a distributed digital currency system, which keeps all transaction history on a public blockchain. Since all transactions recorded on the blockchain are public to everyone, Bitcoin users face a threat of leaking financial privacy. Many analysis and deanonymization approaches have been proposed to link transaction records to real identities. To eliminate this threat, we present an unlinkable coin mixing scheme that allows users to mix their bitcoins without trusting a third party. This mixing scheme employs a primitive known as ring signature with elliptic curve digital signature algorithm (ECDSA) to conceal the transfer of coins between addresses. The mixing server is only able to check whether the output addresses belong to its customers, but it cannot tell which address owned by which customer. Customers do not have to rely on the reputation of a third party to ensure his money will be returned, and his privacy will not be leaked. This scheme needs no modifications on current Bitcoin system and is convenient to deploy by any communities. We implemented a prototype of our scheme and tested it under the Bitcoin core’s regtest mode. Security and privacy of our mixing scheme are ensured through the standard ring signature and ECDSA unforgeability.
The crisis in antibiotic resistance.

The synthesis of large numbers of antibiotics over the past three decades has caused complacency about the threat of bacterial resistance. Bacteria have become resistant to antimicrobial agents as a result of chromosomal changes or the exchange of the exchange of genetic material via plasmids and transposons. Streptococcus pneumoniae, Streptococcus pyogenes, and staphylococci, organisms that cause respiratory and cutaneous infections, and members of the Enterobacteriaceae and Pseudomonas families, organisms that cause diarrhea, urinary infection, and sepsis, are now resistant to virtually all of the older antibiotics. The extensive use of antibiotics in the community and hospitals has fueled this crisis. Mechanisms such as antibiotic control programs, better hygiene, and synthesis of agents with improved antimicrobial activity need to be adopted in order to limit bacterial resistance.
Unified Perceptual Parsing for Scene Understanding

Humans recognize the visual world at multiple levels: we effortlessly categorize scenes and detect objects inside, while also identifying the textures and surfaces of the objects along with their different compositional parts. In this paper, we study a new task called Unified Perceptual Parsing, which requires the machine vision systems to recognize as many visual concepts as possible from a given image. A multi-task framework called UPerNet and a training strategy are developed to learn from heterogeneous image annotations. We benchmark our framework on Unified Perceptual Parsing and show that it is able to effectively segment a wide range of concepts from images. The trained networks are further applied to discover visual knowledge in natural scenes.
Comparisons between novel oral anticoagulants and vitamin K antagonists in patients with CKD.

Novel oral anticoagulants (NOACs) (rivaroxaban, dabigatran, apixaban) have been approved by international regulatory agencies to treat atrial fibrillation and venous thromboembolism in patients with kidney dysfunction. However, altered metabolism of these drugs in the setting of impaired kidney function may subject patients with CKD to alterations in their efficacy and a higher risk of bleeding. This article examined the efficacy and safety of the NOACs versus vitamin K antagonists (VKAs) for atrial fibrillation and venous thromboembolism in patients with CKD. A systematic review and meta-analyses of randomized controlled trials were conducted to estimate relative risk (RR) with 95% confidence interval (95% CIs) using a random-effects model. MEDLINE, Embase, and the Cochrane Library were searched to identify articles published up to March 2013. We selected published randomized controlled trials of NOACs compared with VKAs of at least 4 weeks' duration that enrolled patients with CKD (defined as creatinine clearance of 30-50 ml/min) and reported data on comparative efficacy and bleeding events. Eight randomized controlled trials were eligible. There was no significant difference in the primary efficacy outcomes of stroke and systemic thromboembolism (four trials, 9693 participants; RR, 0.64 [95% CI, 0.39 to 1.04]) and recurrent thromboembolism or thromboembolism-related death (four trials, 891 participants; RR, 0.97 [95% CI, 0.43 to 2.15]) with NOACs versus VKAs. The risk of major bleeding or the combined endpoint of major bleeding or clinically relevant nonmajor bleeding (primary safety outcome) (eight trials, 10,616 participants; RR 0.89 [95% CI, 0.68 to 1.16]) was similar between the groups. The use of NOACs in select patients with CKD demonstrates efficacy and safety similar to those with VKAs. Proactive postmarketing surveillance and further studies are pivotal to further define the rational use of these agents.
An AES Smart Card Implementation Resistant to Power Analysis Attacks

In this article we describe an efficient AES software implementation that is well suited for 8-bit smart cards and resistant against power analysis attacks. Our implementation masks the intermediate results and randomizes the sequence of operations at the beginning and the end of the AES execution. Because of the masking, it is secure against simple power analysis attacks, template attacks and first-order DPA attacks. Due to the combination of masking and randomization, it is resistant against higher-order DPA attacks. Resistant means that a large number of measurements is required for a successful attack. This expected number of measurements is tunable. The designer can choose the amount of randomization and thereby increase the number of measurements. This article also includes a practical evaluation of the countermeasures. The results prove the theoretical assessment of the countermeasures to be correct.
Optical based non invasive glucometer with IoT

Diabetes mellitus (DM) nicknamed as sugar is becoming one of incurable and critical challenge to medical field. Serious illness such as premature mortality even cause of death, which can be identified by continuous monitoring from a remote location. The traditional and conventional method such as finger pricking's demerits such as pain and damage to tissues that cause infection. Such type of infections can be overcome by non invasive technique. The objective of this paper is to monitor glucose level using non invasive technique by optical and IoT technology. The proposed sensor circuit consists of IR LED's of wavelength 650–2500nm for optical blood glucose measurement and NIR photodiodes (InGaAs) to receive the reflected light from body parts to determine the glucose level. The Beer-Lambert law is used for signal processing along with GSM based IoT real time information transmission. The project is implemented using Arduino IDE for finding the performance matrix of the system as well as various analytical studies.
Understanding the human parental brain: a critical role of the orbitofrontal cortex.

The bond between a parent and an infant often appears to form effortlessly and intuitively, and this relationship is fundamental to infant survival and development. Parenting is considered to depend on specific brain networks that are largely conserved across species and in place even before parenthood. Efforts to understand the neural basis of parenting in humans have focused on the overlapping networks implicated in reward and social cognition, within which the orbitofrontal cortex (OFC) is considered to be a crucial hub. This review examines emerging evidence that the OFC may be engaged in several phases of parent-infant interactions, from early, privileged orienting to infant cues, to ongoing monitoring of interactions and subsequent learning. Specifically, we review evidence suggesting that the OFC rapidly responds to a range of infant communicative cues, such as faces and voices, supporting their efficient processing. Crucially, this early orienting response may be fundamental in supporting adults to respond rapidly and appropriately to infant needs. We suggest a number of avenues for future research, including investigating neural activity in disrupted parenting, exploring multimodal cues, and consideration of neuroendocrine involvement in responsivity to infant cues. An increased understanding of the brain basis of caregiving will provide insight into our greatest challenge: parenting our young.
A Syntactic Resource for Thai: CG Treebank

This paper presents  Thai CG treebank, a categorial approach of language resources. Since there are very few Thai syntactic resources, we designed to create treebank based on CG formalism. Thai corpus was parsed with existing CG syntactic dictionary and LALR parser. The correct parsed trees were collected as preliminary CG treebank. It consists of 50,346 trees from 27,239 utterances. Trees can be split into three grammatical types. There are 12,876 sentential trees, 13,728 noun phrasal trees, and 18,342 verb phrasal trees. There are 17,847 utterances that obtain one tree, and an average tree per an utterance is 1.85.
Educational System for the Holy Quran and Its Sciences for Blind and Handicapped People Based on Google Speech API

There is a great need to provide educational environments for blind and handicapped people. There are many Islamic websites and applications dedicated to the educational services for the Holy Quran and Its Sciences (Quran Recitations, the interpretations, etc.) on the Internet. Unfortunately, blind and handicapped people could not use these services. These people cannot use the keyboard and the mouse. In addition, the ability to read and write is essential to benefit from these services. In this paper, we present an educational environment that allows these people to take full advantage of the scientific materials. This is done through the interaction with the system using voice commands by speaking directly without the need to write or to use the mouse. Google Speech API is used for the universal speech recognition after a preprocessing and post processing phases to improve the accuracy. For blind people, responses of these commands will be played back through the audio device instead of displaying the text to the screen. The text will be displayed on the screen to help other people make use of the system.
Using Smart City Technology to Make Healthcare Smarter

Smart cities use information and communication technologies (ICTs) to scale services include utilities and transportation to a growing population. In this paper, we discuss how smart city ICTs can also improve healthcare effectiveness and lower healthcare cost for smart city residents. We survey current literature and introduce original research to offer an overview of how smart city infrastructure supports strategic healthcare using both mobile and ambient sensors combined with machine learning. Finally, we consider challenges that will be faced as healthcare providers make use of these opportunities.
Culture, threat, and error: lessons from aviation

such as aviation and rail, have become increasingly safer over the past 20 years, accidents still occur. 1 Similarly, adverse outcomes occur in healthcare, despite numerous improvements in areas such as, for example, selection and training of personnel, design and maintenance of equipment, and greater availability and reduced side effects of many drugs. 2 However, the proportional gains in aviation have been larger than those in health-care, and, if for this reason alone, the Institute of Medicine Report, 'To Err is Human,' 3 recommended that medicine adopt aviation's approaches to safety and error management. 4 S Si im mi il la ar ri it ti ie es s b be et tw we ee en n a av vi ia at ti io on n a an nd d h he ea al lt th hc ca ar re e There are similarities in the ongoing struggle for safety in both healthcare and aviation. First, although safety is the primary goal, cost drives decisions. Second, both domains have, in part, become safer because of technological innovation. Third, there are multiple sources of threats to safety in both systems – technological , human, and environmental. Fourth, disasters are always followed by furious bouts of second-guessing. Fifth, teamwork is essential in reducing, trapping and mitigating or treating errors. 5–7 This last point demands further elaboration. Most endeavors in healthcare, science, and industry require groups to work together effectively – this is the essence of teamwork. Failures of teamwork in complex organizations can have deadly effects. More than two-thirds of air crashes involve human or pilot error as a primary factor, in contrast to the decreasing number of crashes related to primary mechanical failure. When human error is cited as a major contributor in an air crash, this occurs most often in the form of failures in teamwork, in such areas as communication and shared mental models. 8 Historically, however, professional training has focused on technical, rather than on interpersonal, skills. Aviation has mandated that the flight and cabin crews work together as a team, through the use of standard operating procedures (SOPs) and formal training in teamwork and communication. In contrast, it is said that getting the diverse groups in healthcare, such as surgeons, anesthesiologists, and nurses, to work as a team is like herding cats. Also of importance is the concept of 'context' or the 'whole situation relevant to a particular …