nils-herrmann/clean_scirepeval huggingface dataset:
An Incremental Type-2 Meta-Cognitive Extreme Learning Machine

Existing extreme learning algorithm have not taken into account four issues: 1) complexity; 2) uncertainty; 3) concept drift; and 4) high dimensionality. A novel incremental type-2 meta-cognitive extreme learning machine (ELM) called evolving type-2 ELM (eT2ELM) is proposed to cope with the four issues in this paper. The eT2ELM presents three main pillars of human meta-cognition: 1) what-to-learn; 2) how-to-learn; and 3) when-to-learn. The what-to-learn component selects important training samples for model updates by virtue of the online certainty-based active learning method, which renders eT2ELM as a semi-supervised classifier. The how-to-learn element develops a synergy between extreme learning theory and the evolving concept, whereby the hidden nodes can be generated and pruned automatically from data streams with no tuning of hidden nodes. The when-to-learn constituent makes use of the standard sample reserved strategy. A generalized interval type-2 fuzzy neural network is also put forward as a cognitive component, in which a hidden node is built upon the interval type-2 multivariate Gaussian function while exploiting a subset of Chebyshev series in the output node. The efficacy of the proposed eT2ELM is numerically validated in 12 data streams containing various concept drifts. The numerical results are confirmed by thorough statistical tests, where the eT2ELM demonstrates the most encouraging numerical results in delivering reliable prediction, while sustaining low complexity.
Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm

Learning to learn is a powerful paradigm for enabling models to learn from data more effectively and efficiently. A popular approach to meta-learning is to train a recurrent model to read in a training dataset as input and output the parameters of a learned model, or output predictions for new test inputs. Alternatively, a more recent approach to meta-learning aims to acquire deep representations that can be effectively fine-tuned, via standard gradient descent, to new tasks. In this paper, we consider the meta-learning problem from the perspective of universality, formalizing the notion of learning algorithm approximation and comparing the expressive power of the aforementioned recurrent models to the more recent approaches that embed gradient descent into the meta-learner. In particular, we seek to answer the following question: does deep representation combined with standard gradient descent have sufficient capacity to approximate any learning algorithm? We find that this is indeed true, and further find, in our experiments, that gradient-based meta-learning consistently leads to learning strategies that generalize more widely compared to those represented by recurrent models.
BER estimation from EVM for QPSK and 16-QAM coherent optical systems

BER estimation from measured EVM values is shown experimentally for QPSK and 16QAM optical signals with 28 GBd. Various impairments, such as gain imbalance, quadrature error and timing skew, are introduced into the transmitted signal in order to evaluate the robustness of the method. The EVM was measured using two different real-time sampling systems and the EVM measurement accuracy is discussed.
Chinese Spelling Errors Detection Based on CSLM

Spelling errors are very common in various electronic documents and it leads to serious influence sometimes. To solve this problem, methods based on the n-gram language model are the most commonly used. CSLM (continuous space language model) which represents a word as a vector is different from traditional models. In this paper, we experimented with a specific CSLM, namely, the CBOW (Continuous Bag-of-Words) model, to detect spelling errors. Since spelling errors are usually considered as wrong characters rather than words in Chinese language, we trained character vectors with a large Chinese corpus, and then judged a Chinese character is right or not by its probability of the occurrence in a given context. Experimental results show that the method based on CSLM outperforms the n-gram language model.
Educational Game and Intelligent Tutoring System: A Classroom Study and Comparative Design Analysis

Educational games and intelligent tutoring systems (ITS) both support learning by doing, although often in different ways. The current classroom experiment compared a popular commercial game for equation solving, DragonBox and a research-based ITS, Lynnette with respect to desirable educational outcomes. The 190 participating 7th and 8th grade students were randomly assigned to work with either system for 5 class periods. We measured out-of-system transfer of learning with a paper and pencil pre- and post-test of students’ equation-solving skill. We measured enjoyment and accuracy of self-assessment with a questionnaire. The students who used DragonBox solved many more problems and enjoyed the experience more, but the students who used Lynnette performed significantly better on the post-test. Our analysis of the design features of both systems suggests possible explanations and spurs ideas for how the strengths of the two systems might be combined. The study shows that intuitions about what works, educationally, can be fallible. Therefore, there is no substitute for rigorous empirical evaluation of educational technologies.
Mobile outdoor parking space detection application

Finding a vacant parking space in outdoor parking lots is a daily concern of most vehicle drivers during rush hours, especially in the urban context. In this paper, an outdoor parking space vacancy detection system is proposed, using mobile devices to improve parking space searching experience for vehicle drivers by providing them with the location and occupancy information of parking spaces. The system uses state-of-the-art image recognition algorithm, namely Convolutional Neural Network with a Raspberry Pi to identify vacant parking spaces from a parking lot image retrieved in real time via an IP camera. A university parking lot has been chosen as the test bed to deploy the proposed system for real time parking space vacancy detection. An Android smartphone application called Driver App is developed to enable ubiquitous visualization of real time outdoor parking spaces occupancy information for vehicle drivers. Evaluation outcomes based on the responses to System Usability Scale (SUS) questionnaire revealed high usability of the Driver App as a tool that provides smart parking service to assist vehicle drivers in searching for a vacant parking space.
Nasal reconstruction with a forehead flap.

The tint of forehead skin so exactly matches that of the face and nose that a forehead flap must be the first choice for reconstruction of a nasal defect. The forehead flap makes by far the best nose. With some plastic surgery juggling, the forehead defect can be camouflaged effectively. This article describes the author's technique in two-stage and three-stage forehead flap procedures.
Technology Adoption among Small and Medium Enterprises ( SME ' s ) : A Research Agenda

This paper presents the research agenda that has been proposed to develop an integrated model to explain technology adoption of SMEs in Malaysia. SMEs form over 90% of all business entities in Malaysia and they have been contributing to the development of the nation. Technology adoption has been a thorn issue among SMEs as they require big outlay which might not be available to the SMEs. Although resource has been an issue among SMEs they cannot lie low and ignore the technological advancements that are taking place at a rapid pace. With that in mind this paper proposes a model to explain the technology adoption issue among SMEs. Technology adoption, integrated model, Small and Medium Enterprises (SME), Malaysia
New dissimilarity measures for image phylogeny reconstruction

Image phylogeny is the problem of reconstructing the structure that represents the history of generation of semantically similar images (e.g., near-duplicate images). Typical image phylogeny approaches break the problem into two steps: (1) estimating the dissimilarity between each pair of images and (2) reconstructing the phylogeny structure. Given that the dissimilarity calculation directly impacts the phylogeny reconstruction, in this paper, we propose new approaches to the standard formulation of the dissimilarity measure employed in image phylogeny, aiming at improving the reconstruction of the tree structure that represents the generational relationships between semantically similar images. These new formulations exploit a different method of color adjustment, local gradients to estimate pixel differences and mutual information as a similarity measure. The results obtained with the proposed formulation remarkably outperform the existing counterparts in the literature, allowing a much better analysis of the kinship relationships in a set of images, allowing for more accurate deployment of phylogeny solutions to tackle traitor tracing, copyright enforcement and digital forensics problems.
Fingerprint-based Similarity Search and its Applications

This paper introduces a new technology and tools from the field of text-based information retrieval. The authors have developed – a fingerprint-based method for a highly efficient near similarity search, and – an application of this method to identify plagiarized passages in large document collections. The contribution of our work is twofold. Firstly, it is a search technology that enables a new quality for the comparative analysis of complex and large scientific texts. Secondly, this technology gives rise to a new class of tools for plagiarism analysis, since the comparison of entire books becomes computationally feasible. The paper is organized as follows. Section 1 gives an introduction to plagiarism delicts and related detection methods, Section 2 outlines the method of fuzzy-fingerprints as a means for near similarity search, and Section 3 shows our methods in action: It gives examples for near similarity search as well as plagiarism detection and discusses results from a comprehensive performance analyses. 1 Plagiarism Analysis Plagiarism is the act of claiming to be the author of material that someone else actually wrote (Encyclopædia Britannica 2005), and, with the ubiquitousness
Association of Enterococcus faecalis with different forms of periradicular diseases.

Data from culture studies have revealed that Enterococcus faecalis is occasionally isolated from primary endodontic infections but frequently recovered from treatment failures. This molecular study was undertaken to investigate the prevalence of E. faecalis in endodontic infections and to determine whether this species is associated with particular forms of periradicular diseases. Samples were taken from cases of untreated teeth with asymptomatic chronic periradicular lesions, acute apical periodontitis, or acute periradicular abscesses, and from root-filled teeth associated with asymptomatic chronic periradicular lesions. DNA was extracted from the samples, and a 16S rDNA-based nested polymerase chain reaction assay was used to identify E. faecalis. This species occurred in seven of 21 root canals associated with asymptomatic chronic periradicular lesions, in one of 10 root canals associated with acute apical periodontitis, and in one of 19 pus samples aspirated from acute periradicular abscesses. Statistical analysis showed that E. faecalis was significantly more associated with asymptomatic cases than with symptomatic ones. E. faecalis was detected in 20 of 30 cases of persistent endodontic infections associated with root-filled teeth. When comparing the frequencies of this species in 30 cases of persistent infections with 50 cases of primary infections, statistical analysis demonstrated that E. faecalis was strongly associated with persistent infections. The average odds of detecting E. faecalis in cases of persistent infections associated with treatment failure were 9.1. The results of this study indicated that E. faecalis is significantly more associated with asymptomatic cases of primary endodontic infections than with symptomatic ones. Furthermore, E. faecalis was much more likely to be found in cases of failed endodontic therapy than in primary infections.
ELECTRICAL DISTRIBUTION POWER SYSTEMS OF MODERN CIVIL AIRCRAFTS

As the aircraft industry is moving towards the all electric and More Electric Aircraft (MEA), there is increase demand for electrical power in the aircraft. The trend in the aircraft industry is to replace hydraulic and pneumatic systems with electrical systems achieving more comfort and monitoring features. Moreover, the structure of MEA distribution system improves aircraft maintainability, reliability, flight safety and efficiency. Detailed descriptions of the modern MEA generation and distribution systems as well as the power converters and load types are explained and outlined. MEA electrical distribution systems are mainly in the form of multi-converter power electronic system.
D2D-Based Grouped Random Access to Mitigate Radio Access Network Congestion in Massive Machine-Type Communications

Massive Machine-Type Communications (mMTC) presents significant challenges in terms of the number of devices accessing the shared resource, and coordination among those devices. This paper overviews work on RAN congestion control in order to better manage resources in the context of device-to-device (D2D) interaction among the MTCDs. It then proceeds to introduce a novel grouping-assisted random access protocol for mMTC, showing beneficial performance of the concept against parameters such as group size, number of MTCDs in the overall scenario, and reliability of D2D links. Finally, the association is made with a Geolocation Database (GDB) capability to assist the grouping decisions, drawing parallels with recent regulatory-driven initiatives around GDBs, and arguing benefits of the concept.
Cogniculture: Towards a Better Human-Machine Co-evolution

Research in Artificial Intelligence is breaking technology barriers every day. New algorithms and high performance computing are making things possible which we could only have imagined earlier. Though the enhancements in AI are making life easier for human beings day by day, there is constant fear that AI based systems will pose a threat to humanity. People in AI community have diverse set of opinions regarding the pros and cons of AI mimicking human behavior. Instead of worrying about AI advancements, we propose a novel idea of cognitive agents, including both human and machines, living together in a complex adaptive ecosystem, collaborating on human computation for producing essential social goods while promoting sustenance, survival and evolution of the agents’ life cycle. We highlight several research challenges and technology barriers in achieving this goal. We propose a governance mechanism around this ecosystem to ensure ethical behaviors of all cognitive agents. Along with a novel set of use-cases of Cogniculture , we discuss the road map ahead
The Rate and Risk Factors for Anemia among Pregnant Mothers in Jerteh Terengganu, Malaysia

Antenatal mothers with anemia are high risk to varieties of health implications as well as to their off springs. Many studies show a high mortality and morbidity related to anemia in pregnancy.  This cross-sectional study was designed to determine factors associated with anemia amongst forty seven antenatal mothers attending Antenatal Clinic at Klinik Kesihatan Kuala Besut, Terengganu in November 2009. Systematic random sampling was applied and information gathered based on patients’ medical records and through face-to-face interviewed by using a structured questionnaire.  The mean age of respondents was 28.3 year-old. More than half of mothers were multigravidas. Of 47 respondents, 57.4% (95% CI: 43.0, 72.0) was anemic. The proportion of anemia was high for grand multigravidas mother (66.7%), those at third trimester of pregnancy (70.4%), did antenatal booking at first trimester (65.4%), poor haematinic compliance (76.5%), not taking any medication (60.5%), those with no co-morbid illnesses (60.0%), mothers with high education level (71.4%) and those with satisfactory monthly income (61.5%). The proportion of anemia was 58.3% and 57.1% for mothers with last child birth spacing of two years or less and more than two years accordingly. There was a significant association of haematinic compliance with the anemia (OR: 4.571; 95% CI: 1.068, 19.573).  Antenatal mothers in this area have a substantial proportion of anemia despite of freely and routinely prescription of haematinic at primary health care centers. Poor haematinic compliance was a significant risk factor. Health education programs regarding haematinic compliance and adequate intake of iron rich diet during pregnancy need to be strengthened to curb this problem. Corresponding author: NH Nik Rosmawati, Environmental Health Unit, Department of Community Medicine, School of Medical Science, Health Campus, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia, E-mail: rosmawati@kk.usm.my Received May 03, 2012;  2012;   Nik Rosmawati NH, Mohd Nazri S, Mohd Ismail I (2012) The Rate and Risk Factors for Anemia among Pregnant Mothers in Jerteh Terengganu, Malaysia. J Community Med Health Educ 2:150. doi:10.4172/2161-0711.1000150
Dyna-C: A Minimal Topology for Bidirectional Solid-State Transformers

This paper presents a topology for bidirectional solid-state transformers with a minimal device count. The topology, referenced as dynamic-current or Dyna-C, has two current-source inverter stages with a high-frequency galvanic isolation, requiring 12 switches for four-quadrant three-phase ac/ac power conversion. The topology has voltage step-up/down capability, and the input and output can have arbitrary power factors and frequencies. Further, the Dyna-C can be configured as isolated power converters for single- or multiterminal dc, and single- or multiphase ac systems. The modular nature of the Dyna-C lends itself to be connected in series and/or parallel for high-voltage high-power applications. The proposed converter topology can find a broad range of applications such as isolated battery chargers, uninterruptible power supplies, renewable energy integration, smart grid, and power conversion for space-critical applications including aviation, locomotives, and ships. This paper outlines various configurations of the Dyna-C, as well as the relative operation and controls. The converter functionality is validated through simulations and experimental measurements of a 50-kVA prototype.
Development of a spectroscopic technique for continuous online monitoring of oxygen and site-specific nitrogen isotopic composition of atmospheric nitrous oxide.

Nitrous oxide is an important greenhouse gas and ozone-depleting-substance. Its sources are diffuse and poorly characterized, complicating efforts to understand anthropogenic impacts and develop mitigation policies. Online, spectroscopic analysis of N2O isotopic composition can provide continuous measurements at high time resolution, giving new insight into N2O sources, sinks, and chemistry. We present a new preconcentration unit, "Stheno II", coupled to a tunable infrared laser direct absorption spectroscopy (TILDAS) instrument, to measure ambient-level variations in (18)O and site-specific (15)N N2O isotopic composition at remote sites with a temporal resolution of <1 h. Trapping of N2O is quantitative up to a sample size of ∼4 L, with an optimal sample size of 1200-1800 mL at a sampling frequency of 28 min. Line shape variations with the partial pressure of the major matrix gases N2/O2 and CO2 are measured, and show that characterization of both pressure broadening and Dicke narrowing is necessary for an optimal spectral fit. Partial pressure variations of CO2 and bath gas result in a linear isotopic measurement offset of 2.6-6.0 ‰ mbar(-1). Comparison of IR MS and TILDAS measurements shows that the TILDAS technique is accurate and precise, and less susceptible to interferences than IR MS measurements. Two weeks of measurements of N2O isotopic composition from Cambridge, MA, in May 2013 are presented. The measurements show significant short-term variability in N2O isotopic composition larger than the measurement precision, in response to meteorological parameters such as atmospheric pressure and temperature.
3D Printing and 3D Bioprinting in Pediatrics

Additive manufacturing, commonly referred to as 3D printing, is a technology that builds three-dimensional structures and components layer by layer. Bioprinting is the use of 3D printing technology to fabricate tissue constructs for regenerative medicine from cell-laden bio-inks. 3D printing and bioprinting have huge potential in revolutionizing the field of tissue engineering and regenerative medicine. This paper reviews the application of 3D printing and bioprinting in the field of pediatrics.
Electroporation: a general phenomenon for manipulating cells and tissues.

Electroporation is a fascinating cell membrane phenomenon with several existing biological applications and others likely. Although DNA introduction is the most common use, electroporation of isolated cells has also been used for: (1) introduction of enzymes, antibodies, and other biochemical reagents for intracellular assays; (2) selective biochemical loading of one size cell in the presence of many smaller cells; (3) introduction of virus and other particles; (4) cell killing under nontoxic conditions; and (5) insertion of membrane macromolecules into the cell membrane. More recently, tissue electroporation has begun to be explored, with potential applications including: (1) enhanced cancer tumor chemotherapy, (2) gene therapy, (3) transdermal drug delivery, and (4) noninvasive sampling for biochemical measurement. As presently understood, electroporation is an essentially universal membrane phenomenon that occurs in cell and artificial planar bilayer membranes. For short pulses (microsecond to ms), electroporation occurs if the transmembrane voltage, U(t), reaches 0.5-1.5 V. In the case of isolated cells, the pulse magnitude is 10(3)-10(4) V/cm. These pulses cause reversible electrical breakdown (REB), accompanied by a tremendous increase molecular transport across the membrane. REB results in a rapid membrane discharge, with the elevated U(t) returning to low values within a few microseconds of the pulse. However, membrane recovery can be orders of magnitude slower. An associated cell stress commonly occurs, probably because of chemical influxes and effluxes leading to chemical imbalances, which also contribute to eventual survival or death. Basic phenomena, present understanding of mechanism, and the existing and potential applications are briefly reviewed.