nils-herrmann/clean_scirepeval huggingface dataset:
Construction of 3D Volumetric Objects for a 3D Cadastral System

This article presents a new method to illustrate the feasibility of 3D topology creation. We base the 3D construction process on testing real cases of implementation of 3D parcels construction in a 3D cadastral system. With the utilization and development of dense urban space, true 3D geometric volume primitives are needed to represent 3D parcels with the adjacency and incidence relationship. We present an effective straightforward approach to identifying and constructing the valid volumetric cadastral object from the given faces, and build the topological relationships among 3D cadastral objects on-thefly, based on input consisting of loose boundary 3D faces made by surveyors. This is drastically different from most existing methods, which focus on the validation of single volumetric objects after the assumption of the object’s creation. Existing methods do not support the needed types of geometry/ topology (e.g. non 2-manifold, singularities) and how to create and maintain valid 3D parcels is still a challenge in practice. We will show that the method does not change the faces themselves and faces in a given input are independently specified. Various volumetric objects, including non-manifold 3D cadastral objects (legal spaces), can be constructed correctly by this method, as will be shown from the
High-frequency (50–100MHz) medical ultrasound transducer arrays produced by micromachining bulk PZT materials

This paper describes the development and characterization of a high frequency (65 MHz) ultrasound transducer array. The array was built using bulk PZT that was etched using an optimized chlorine-based plasma process. The median etch rate of 6 mum/hr yielded a good profile (sidewall) angle (>830) and a reasonable processing time for etch depths up to 40 mum. A backing layer having an acoustic impedance of 6 MRayl together with a front-end matching layer of parylene yielded a transducer bandwidth of 40%. The impedance of the backing material will be increased to 20 MRayls in the near future, and this will increase the bandwidth to 70%. The two-way insertion loss and cross talk between adjacent channels at the center frequency are 26.5 dB and -25 dB, respectively.
Developing a corpus of strategic conversation in The Settlers of Catan

We describe a dialogue model and an implemented annotation scheme for a pilot corpus of annotated online chats concerning bargaining negotiations in the game The Settlers of Catan. We will use this model and data to analyze how conversations proceed in the absence of strong forms of cooperativity, where agents have diverging motives. Here we concentrate on the description of our annotation scheme for negotiation dialogues, illustrated with our pilot data, and some perspectives for future research on the issue.
Validity and reliability of body composition analysers in children and adults.

We tested the validity and reliability of the BioSpace InBody 320, Omron and Bod-eComm body composition devices in men and women (n 254; 21-80 years) and boys and girls (n 117; 10-17 years). We analysed percentage body fat (%BF) and compared the results with dual-energy X-ray absorptiometry (DEXA) in adults and compared the results of the InBody with underwater weighing (UW) in children. All body composition devices were correlated (r 0.54-0.97; P< or =0.010) to DEXA except the Bod-eComm in women aged 71-80 years (r 0.54; P=0.106). In girls, the InBody %BF was correlated with UW (r 0.79; P< or =0.010); however, a more moderate correlation (r 0.69; P< or =0.010) existed in boys. Bland-Altman plots indicated that all body composition devices underestimated %BF in adults (1.0-4.8 %) and overestimated %BF in children (0.3-2.3 %). Lastly, independent t tests revealed that the mean %BF assessed by the Bod-eComm in women (aged 51-60 and 71-80 years) and in the Omron (age 18-35 years) were significantly different compared with DEXA (P< or =0.010). In men, the Omron (aged 18-35 years), and the InBody (aged 36-50 years) were significantly different compared with DEXA (P=0.025; P=0.040 respectively). In addition, independent t tests indicated that the InBody mean %BF in girls aged 10-17 years was significantly different from UW (P=0.001). Pearson's correlation analyses demonstrated that the Bod-eComm (men and women) and Omron (women) had significant mean differences compared with the reference criterion; therefore, the %BF output from these two devices should be interpreted with caution. The repeatability of each body composition device was supported by small CV (<3.0 %).
Comprehensive analysis of distance and similarity measures for Wi-Fi fingerprinting indoor positioning systems

9 Recent advances in Indoor Positioning Systems led to a business interest in those applications and services where a precise localization is crucial. Wi-Fi fingerprinting based on Machine Learning and Expert Systems are commonly used in the literature. They compare a current fingerprint to a database of fingerprints, and then return the most similar one/ones according to: 1) a distance function, 2) a data representation method for Received Signal Strength values, and 3) a thresholding strategy. However, most of the previous works simply use the Euclidean distance with the raw unprocessed data. There is not any previous work that studies which is the best distance function, which is the best way of representing the data and which is the effect of applying thresholding. In this paper, we present a comprehensive study using 51 distance metrics, 4 alternatives to represent the raw data (2 of them proposed by us), a thresholding based on the RSS values and the public UJIIndoorLoc database. The results shown in this paper demonstrates that researchers and developers should take into account the conclusions arisen in this work in order to improve the accuracy of their systems. The IPSs based on k-NN are improved by just selecting the appropriate configuration (mainly distance function and data representation). In the best case, 13-NN with Sørensen distance and the powed data representation, the error in determining the place (building and floor) Preprint submitted to Experts Systems with Applications August 22, 2015
How to get pavement distress detection ready for deep learning? A systematic approach

Road condition acquisition and assessment are the key to guarantee their permanent availability. In order to maintain a country's whole road network, millions of high-resolution images have to be analyzed annually. Currently, this requires cost and time excessive manual labor. We aim to automate this process to a high degree by applying deep neural networks. Such networks need a lot of data to be trained successfully, which are not publicly available at the moment. In this paper, we present the GAPs dataset, which is the first freely available pavement distress dataset of a size, large enough to train high-performing deep neural networks. It provides high quality images, recorded by a standardized process fulfilling German federal regulations, and detailed distress annotations. For the first time, this enables a fair comparison of research in this field. Furthermore, we present a first evaluation of the state of the art in pavement distress detection and an analysis of the effectiveness of state of the art regularization techniques on this dataset.
Strigolactone Signaling and Evolution.

Strigolactones are a structurally diverse class of plant hormones that control many aspects of shoot and root growth. Strigolactones are also exuded by plants into the rhizosphere, where they promote symbiotic interactions with arbuscular mycorrhizal fungi and germination of root parasitic plants in the Orobanchaceae family. Therefore, understanding how strigolactones are made, transported, and perceived may lead to agricultural innovations as well as a deeper knowledge of how plants function. Substantial progress has been made in these areas over the past decade. In this review, we focus on the molecular mechanisms, core developmental roles, and evolutionary history of strigolactone signaling. We also propose potential translational applications of strigolactone research to agriculture.
A Neuromorphic Event-Based Neural Recording System for Smart Brain-Machine-Interfaces

Neural recording systems are a central component of Brain-Machince Interfaces (BMIs). In most of these systems the emphasis is on faithful reproduction and transmission of the recorded signal to remote systems for further processing or data analysis. Here we follow an alternative approach: we propose a neural recording system that can be directly interfaced locally to neuromorphic spiking neural processing circuits for compressing the large amounts of data recorded, carrying out signal processing and neural computation to extract relevant information, and transmitting only the low-bandwidth outcome of the processing to remote computing or actuating modules. The fabricated system includes a low-noise amplifier, a delta-modulator analog-to-digital converter, and a low-power band-pass filter. The bio-amplifier has a programmable gain of 45-54 dB, with a Root Mean Squared (RMS) input-referred noise level of 2.1 μV, and consumes 90 μW . The band-pass filter and delta-modulator circuits include asynchronous handshaking interface logic compatible with event-based communication protocols. We describe the properties of the neural recording circuits, validating them with experimental measurements, and present system-level application examples, by interfacing these circuits to a reconfigurable neuromorphic processor comprising an array of spiking neurons with plastic and dynamic synapses. The pool of neurons within the neuromorphic processor was configured to implement a recurrent neural network, and to process the events generated by the neural recording system in order to carry out pattern recognition.
Metagenomic Identification of Bacterioplankton Taxa and Pathways Involved in Microcystin Degradation in Lake Erie

Cyanobacterial harmful blooms (CyanoHABs) that produce microcystins are appearing in an increasing number of freshwater ecosystems worldwide, damaging quality of water for use by human and aquatic life. Heterotrophic bacteria assemblages are thought to be important in transforming and detoxifying microcystins in natural environments. However, little is known about their taxonomic composition or pathways involved in the process. To address this knowledge gap, we compared the metagenomes of Lake Erie free-living bacterioplankton assemblages in laboratory microcosms amended with microcystins relative to unamended controls. A diverse array of bacterial phyla were responsive to elevated supply of microcystins, including Acidobacteria, Actinobacteria, Bacteroidetes, Planctomycetes, Proteobacteria of the alpha, beta, gamma, delta and epsilon subdivisions and Verrucomicrobia. At more detailed taxonomic levels, Methylophilales (mainly in genus Methylotenera) and Burkholderiales (mainly in genera Bordetella, Burkholderia, Cupriavidus, Polaromonas, Ralstonia, Polynucleobacter and Variovorax) of Betaproteobacteria were suggested to be more important in microcystin degradation than Sphingomonadales of Alphaproteobacteria. The latter taxa were previously thought to be major microcystin degraders. Homologs to known microcystin-degrading genes (mlr) were not overrepresented in microcystin-amended metagenomes, indicating that Lake Erie bacterioplankton might employ alternative genes and/or pathways in microcystin degradation. Genes for xenobiotic metabolism were overrepresented in microcystin-amended microcosms, suggesting they are important in bacterial degradation of microcystin, a phenomenon that has been identified previously only in eukaryotic systems.
Local Free-Style Perforator Flaps in Head and Neck Reconstruction: An Update and a Useful Classification.

Any standard skin flap of the body including a detectable or identified perforator at its axis can be safely designed and harvested in a free-style fashion.



Fifty-six local free-style perforator flaps in the head and neck region, 33 primary and 23 recycle flaps, were performed in 53 patients. The authors introduced the term "recycle" to describe a perforator flap harvested within the borders of a previously transferred flap. A Doppler device was routinely used preoperatively for locating perforators in the area adjacent to a given defect. The final flap design and degree of mobilization were decided intraoperatively, depending on the location of the most suitable perforator and the ability to achieve primary closure of the donor site. Based on clinical experience, the authors suggest a useful classification of local free-style perforator flaps.



All primary and 20 of 23 recycle free-style perforator flaps survived completely, providing tension-free coverage and a pleasing final contour for patients. In the remaining three recycle cases, the skeletonization of the pedicle resulted in pedicle damage, because of surrounding postradiotherapy scarring and flap failure. All donor sites except one were closed primarily, and all of them healed without any complications.



The free-style concept has significantly increased the potential and versatility of the standard local and recycled head and neck flap alternatives for moderate to large defects, providing a more robust, custom-made, tissue-sparing, and cosmetically superior outcome in a one-stage procedure, with minimal donor-site morbidity.



Therapeutic, V.
Re-thinking water scarcity : Can science and technology solve the global water crisis ?

This paper provides examples from the last fifty years of scientific and technological innovations that provide relatively easy, quick and affordable means of addressing key water management issues. Scientific knowledge and technological innovation can help open up previously closed decision-making systems. Four of these tools are discussed in this paper: a) the opportunities afforded by virtual water trade; b) the silent revolution for beneficial use of groundwater; c) salt water desalination; and finally, d) the use of remote sensing and geographic information systems (GIS). Together these advances are changing the options available to address water and food security that have been predominant for centuries in the minds of most water decision-makers.
Demonstration of a 50 kW and 100 kHz SiC high power density converter for aerospace application

The high power density converter is required due to the strict demands of volume and weight in more electric aircraft, which makes SiC extremely attractive for this application. In this work, a prototype of 50 kW SiC high power density converter with the topology of two-level three-phase voltage source inverter is demonstrated. This converter is driven at high switching speed based on the optimization in switching characterization. It operates at a switching frequency up to 100 kHz and a low dead time of 250 ns. And the converter efficiency is measured to be 99% at 40 kHz and 97.8% at 100 kHz.
A Novel, Gradient Boosting Framework for Sentiment Analysis in Languages where NLP Resources Are Not Plentiful: A Case Study for Modern Greek

Sentiment analysis has played a primary role in text classification. It is an undoubted fact that some years ago, textual information was spreading in manageable rates; however, nowadays, such information has overcome even the most ambiguous expectations and constantly grows within seconds. It is therefore quite complex to cope with the vast amount of textual data particularly if we also take the incremental production speed into account. Social media, e-commerce, news articles, comments and opinions are broadcasted on a daily basis. A rational solution, in order to handle the abundance of data, would be to build automated information processing systems, for analyzing and extracting meaningful patterns from text. The present paper focuses on sentiment analysis applied in Greek texts. Thus far, there is no wide availability of natural language processing tools for Modern Greek. Hence, a thorough analysis of Greek, from the lexical to the syntactical level, is difficult to perform. This paper attempts a different approach, based on the proven capabilities of gradient boosting, a well-known technique for dealing with high-dimensional data. The main rationale is that since English has dominated the area of preprocessing tools and there are also quite reliable translation services, we could exploit them to transform Greek tokens into English, thus assuring the precision of the translation, since the translation of large texts is not always reliable and meaningful. The new feature set of English tokens is augmented with the original set of Greek, consequently producing a high dimensional dataset that poses certain difficulties for any traditional classifier. Accordingly, we apply gradient boosting machines, an ensemble algorithm that can learn with different loss functions providing the ability to work efficiently with high dimensional data. Moreover, for the task at hand, we deal with a class imbalance issues since the distribution of sentiments in real-world applications often displays issues of inequality. For example, in political forums or electronic discussions about immigration or religion, negative comments overwhelm the positive ones. The class imbalance problem was confronted using a hybrid technique that performs a variation of under-sampling the majority class and over-sampling the minority class, respectively. Experimental results, considering different settings, such as translation of tokens against translation of sentences, consideration of limited Greek text preprocessing and omission of the translation phase, demonstrated that the proposed gradient boosting framework can effectively cope with both high-dimensional and imbalanced datasets and performs significantly better than a plethora of traditional machine learning classification approaches in terms of precision and recall measures.
A legal cross-references taxonomy for reasoning about compliance requirements

Companies must ensure their software complies with relevant laws and regulations to avoid the risk of costly penalties, lost reputation, and brand damage resulting from non-compliance. Laws and regulations contain internal cross-references to portions of the same legal text, as well as cross-references to external legal texts. These cross-references introduce ambiguities, exceptions, as well as other challenges to regulatory compliance. Requirements engineers need guidance as to how to address cross-references in order to comply with the requirements of the law. Herein, we analyze each external cross-reference within the U.S. Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule, the Gramm–Leach–Bliley Act (GLBA), and the GLBA Financial Privacy Rule to determine whether a cross-reference either introduces a conflicting requirement, a conflicting definition, or refines an existing requirement. Herein, we propose a legal cross-reference taxonomy to aid requirements engineers in classifying cross-references as they specify compliance requirements. Analyzing cross-references enables us to address conflicting requirements that may otherwise thwart legal compliance. We identify five sets of conflicting compliance requirements and recommend strategies for resolving these conflicts.
DEFENSE MECHANISM FOR DDoS ATTACK THROUGH MACHINE LEARNING

There is a huge advancement in Computer networking in the past decade. But with the advancement, the threats to the computer networks are also increased. Today one of the biggest threats to the computer networks is the Distributed Denial of Service (DDoS) flooding attack. This paper emphasizes the application layer DDoS flooding attacks because these (layer seven) attacks are growing rapidly and becoming more severe problem. Many researchers used machine-learning techniques for intrusion detection, but some shows poor detection and some methods take more training time. From a survey, it is found that Naïve Bayes (NB) algorithm provides faster learning/training speed than other machine learning algorithms. Also it has more accuracy in classification and detection of attack. So we are proposing a network intrusion detection system (IDS) which uses a machine learning approach with the help of NB algorithm.
You Are Known by How You Vlog: Personality Impressions and Nonverbal Behavior in YouTube

An increasing interest in understanding human perception in social media has led to the study of the processes of personality self-presentation and impression formation based on user profiles and text blogs. However, despite the popularity of online video, we do not know of any attempt to study personality impressions that go beyond the use of text and still photos. In this paper, we analyze one facet of YouTube as a repository of brief behavioral slices in the form of personal conversational vlogs, which are a unique medium for selfpresentation and interpersonal perception. We investigate the use of nonverbal cues as descriptors of vloggers’ behavior and find significant associations between automatically extracted nonverbal cues for several personality judgments. As one notable result, audio and visual cues together can be used to predict 34% of the variance of the Extraversion trait of the Big Five model. In addition, we explore the associations between vloggers’ personality scores and the level of social attention that their videos received in YouTube. Our study is conducted on a dataset of 442 YouTube vlogs and 2,210 annotations collected using Amazon’s Mechanical Turk.
A Survey of Beacon-Enabled IEEE 802.15.4 MAC Protocols in Wireless Sensor Networks

IEEE 802.15.4 is the de facto standard for Wireless Sensor Networks (WSNs) that outlines the specifications of the PHY layer and MAC sub-layer in these networks. The MAC protocol is needed to orchestrate sensor nodes access to the wireless communication medium. Although distinguished by a set of strengths that contributed to its popularity in various WSNs, IEEE 802.15.4 MAC suffers from several limitations that play a role in deteriorating its performance. Also, from a practical perspective, 80.15.4-based networks are usually deployed in the vicinity of other wireless networks that operate in the same ISM band. This means that 802.15.4 MAC should be ready to cope with interference from other networks. These facts have motivated efforts to devise improved IEEE 802.15.4 MAC protocols for WSNs. In this paper we provide a survey for these protocols and highlight the methodologies they follow to enhance the performance of the IEEE 802.15.4 MAC protocol.
Using linux device drivers for static verification tools benchmarking

The Linux Driver Verification system is designed for static analysis of the source code of Linux kernel space device drivers. In this paper, we describe the architecture of the verification system, including the integration of third-party tools for static verification of C programs. We consider characteristics of the Linux drivers source code that are important from the viewpoint of verification algorithms and give examples of comparative analysis of different verification tools, as well as different versions and configurations of a given tool.