nils-herrmann/clean_scirepeval huggingface dataset:
Dengue viremia titer, antibody response pattern, and virus serotype correlate with disease severity.

Viremia titers in serial plasma samples from 168 children with acute dengue virus infection who were enrolled in a prospective study at 2 hospitals in Thailand were examined to determine the role of virus load in the pathogenesis of dengue hemorrhagic fever (DHF). The infecting virus serotype was identified for 165 patients (DEN-1, 46 patients; DEN-2, 47 patients; DEN-3, 47 patients, DEN-4, 25 patients). Patients with DEN-2 infections experienced more severe disease than those infected with other serotypes. Eighty-one percent of patients experienced a secondary dengue virus infection that was associated with more severe disease. Viremia titers were determined for 41 DEN-1 and 46 DEN-2 patients. Higher peak titers were associated with increased disease severity for the 31 patients with a peak titer identified (mean titer of 107.6 for those with dengue fever vs. 108.5 for patients with DHF, P=.01). Increased dengue disease severity correlated with high viremia titer, secondary dengue virus infection, and DEN-2 virus type.
On the journey to continuous deployment: Technical and social challenges along the way

Continuous deployment (CD) is an emerging software development process with organisations such as Facebook, Microsoft, and IBM successfully implementing and using the process. The CD process aims to immediately deploy software to customers as soon as new code is developed, and can result in a number of benefits for organizations, such as: new business opportunities, reduced risk for each release, and prevent development of wasted software. There is little academic literature on the challenges organisations face when adopting the CD process, however there are many anecdotal challenges that organisations have voiced on their online blogs.  The aim of this research is to examine the challenges faced by organisations when adopting CD as well as the strategies to mitigate these challenges.  An explorative case study technique that involves in-depth interviews with software practitioners in an organisation that has adopted CD was conducted to identify these challenges.  This study found a total of 20 technical and social adoption challenges that organisations may face when adopting the CD process. The results are discussed to gain a deeper understanding of the strategies employed by organisations to mitigate the impacts of these challenges.  While a number of individual technical and social adoption challenges were uncovered by the case study in this research, most challenges were not faced in isolation. The severity of these challenges were reduced by a number of mitigation strategies employed by the case study organization. It is concluded that organisations need to be well prepared to handle technical and social adoption challenges with their existing expertise, processes and tools before adopting the CD
High-Resistivity SOI CMOS Cellular Antenna Switches

Results for cellular antenna switches using highresistivity silicon-on-insulator (SOI) CMOS technology are presented. The performance of SOI RF switch FETs is presented and compared to a production GaAs pHEMT technology. Data from prototype high-resistivity SOI RF switch designs is presented and compared to pHEMT based designs. Index Terms — RF CMOS, SOI, silicon-on-insulator, RF SOI, cellular switch, signal isolation
A CMOS Time-to-Digital Converter (TDC) Based On a Cyclic Time Domain Successive Approximation Interpolation Method

This paper describes a time-to-digital converter (TDC) with ~1.2 ps resolution and ~327 mus dynamic range suitable for laser range-finding application for example. The resolution of ~1.2 ps is achieved with interpolation based on a cyclic time domain successive approximation (CTDSA) method that resolves the time difference between two non-repetitive signals using binary search. The method utilizes a pair of digital-to-time converters (DTC), the propagation delay difference between which is implemented by digitally controlling the unit load capacitors of their delay cells, thus enabling sub-gate delay timing resolution. The rms single-shot precision, i.e., standard deviation sigma-value of the TDC is 3.2 ps, which is achieved by using an external integral nonlinearity look-up table (INL-LUT) for the interpolators. The power consumption is 33 mW at 100 MHz with a 3.3 V operating voltage. The prototypes were fabricated in a 0.35 mum CMOS process.
WebChild: harvesting and organizing commonsense knowledge from the web

This paper presents a method for automatically constructing a large commonsense knowledge base, called WebChild, from Web contents. WebChild contains triples that connect nouns with adjectives via fine-grained relations like hasShape, hasTaste, evokesEmotion, etc. The arguments of these assertions, nouns and adjectives, are disambiguated by mapping them onto their proper WordNet senses. Our method is based on semi-supervised Label Propagation over graphs of noisy candidate assertions. We automatically derive seeds from WordNet and by pattern matching from Web text collections. The Label Propagation algorithm provides us with domain sets and range sets for 19 different relations, and with confidence-ranked assertions between WordNet senses. Large-scale experiments demonstrate the high accuracy (more than 80 percent) and coverage (more than four million fine grained disambiguated assertions) of WebChild.
From e-commerce to social commerce: A close look at design features

E-commerce is undergoing an evolution through the adoption of Web 2.0 capabilities to enhance customer participation and achieve greater economic value. This new phenomenon is commonly referred to as social commerce, however it has not yet been fully understood. In addition to the lack of a stable and agreed-upon definition, there is little research on social commerce and no significant research dedicated to the design of social commerce platforms. This study offers literature review to explain the concept of social commerce, tracks its nascent state-of-the-art, and discusses relevant design features as they relate to e-commerce and Web 2.0. We propose a new model and a set of principles for guiding social commerce design. We also apply the model and guidelines to two leading social commerce platforms, Amazon and Starbucks on Facebook. The findings indicate that, for any social commerce website, it is critical to achieve a minimum set of social commerce design features. These design features must cover all the layers of the proposed model, including the individual, conversation, community and commerce levels.
Multi-session PLDA scoring of i-vector for partially open-set speaker detection

This paper advocates the use of probabilistic linear discriminant analysis (PLDA) for partially open-set detection task with multiple i-vectors enrollment condition. Also referred to as speaker verification, the speaker detection task has always been considered under an open-set scenario. In this paper, a more general partially open-set speaker detection problem in considered, where the imposters might be one of the known speakers previously enrolled to the system. We show how this could be coped with by modifying the definition of the alternative hypothesis in the PLDA scoring function. We also look into the impact of the conditionalindependent assumption as it was used to derive the PLDA scoring function with multiple training i-vectors. Experiments were conducted using the NIST 2012 Speaker Recognition Evaluation (SRE’12) datasets to validate various points discussed in the paper.
A systemic and cognitive view on collaborative knowledge building with wikis

Wikis provide new opportunities for learning and for collaborative knowledge building as well as for understanding these processes. This article presents a theoretical framework for describing how learning and collaborative knowledge building take place. In order to understand these processes, three aspects need to be considered: the social processes facilitated by a wiki, the cognitive processes of the users, and how both processes influence each other mutually. For this purpose, the model presented in this article borrows from the systemic approach of Luhmann as well as from Piaget’s theory of equilibration and combines these approaches. The model analyzes processes which take place in the social system of a wiki as well as in the cognitive systems of the users. The model also describes learning activities as processes of externalization and internalization. Individual learning happens through internal processes of assimilation and accommodation, whereas changes in a wiki are due to activities of external assimilation and accommodation which in turn lead to collaborative knowledge building. This article provides empirical examples for these equilibration activities by analyzing Wikipedia articles. Equilibration activities are described as being caused by subjectively perceived incongruities between an individuals’ knowledge and the information provided by a wiki. Incongruities of medium level cause cognitive conflicts which in turn activate the described processes of equilibration and facilitate individual learning and collaborative knowledge building.
Formal specification, verification and evaluation of the MQTT protocol in the Internet of Things

This paper presents the formal modeling and performance analysis of one of Internet of Things (IoT) protocols. The Internet of Things is among the subjects best financed in the industry and studied in the academic world. The rapid evolution of mobile Internet, the manufacture of mini hardware, microcomputer, and machine-to-machine (M2M) enabled IoT technologies to be at the top of media subjects. These technologies allow things or devices that are not computers to act intelligently and to make collaborative decisions that are beneficial for certain applications. Hence, the intelligent decision making, the self configuration and the ad hoc networking are from the main characteristics of IoT. Therefore, the implementation of protocols for IoT must comply the standards and satisfy the good properties. Using formal methods in the study of developed protocols ensure these conditions. In this paper, we use probabilistic timed automata for the formal modeling of Message Queue Telemetry Transport (MQTT) and we use further statistical model checking of UPPAAL SMC tool-set for the performance evaluation of the protocol.
Characterizing and Predicting Viral-and-Popular Video Content

The proliferation of online video content has triggered numerous works on its evolution and popularity, as well as on the effect of social sharing on content propagation. In this paper, we focus on the observable dependencies between the virality of video content on a micro-blogging social network (in this case, Twitter) and the popularity of such content on a video distribution service (YouTube). To this end, we collected and analysed a corpus of Twitter posts containing links to YouTube clips and the corresponding video meta-data from YouTube. Our analysis highlights the unique properties of content that is both popular and viral, which allows such content to attract high number of views on YouTube and achieve fast propagation on Twitter. With this in mind, we proceed to the predictions of popular-and-viral clips and propose a framework that can, with high degree of accuracy and low amount of training data, predict videos that are likely to be popular, viral, and both. The key contribution of our work is the focus on cross-system dynamics between YouTube and Twitter. We conjecture and validate that cross-system prediction of both popularity and virality of videos is feasible, and can be performed with a reasonably high degree of accuracy. One of our key findings is that YouTube features capturing user engagement, have strong virality prediction capabilities. This findings allows to solely rely on data extracted from a video sharing service to predict popularity and virality aspects of videos.
A View Of Cloud Computing

Today’s IT infrastructure is under tremendous pressure and is finding it difficult to keep up. In distributed computing environments, up to 85 percent of computing capacity sits idle. 66 percent of every dollar on IT is spent on maintaining current IT infrastructures versus adding new capabilities. In history, operations have industrialized to become smarter. Cloud Computing is positioned to industrialize the IT delivery of the future. It is a natural evolution of the widespread adoption of multiple technical advances in the distributed computing area including virtualization, grid computing, autonomic computing, utility computing and software-as-a-service. It provides a new paradigm for consumption and delivery of IT based services – It provides an enhanced user experience with a self-service user interface for IT management. It abstracts the technical details from end-users so that they no longer need expertise in, or control over, the technology infrastructure “in the cloud” that supports them. It provides flexible pricing based on pay per usage. It enables flexible delivery and sourcing models including private, public and hybrid clouds. Finally, it provides automated provisioning and elastic scaling of IT infrastructure. This paper presents several views on different perspectives of Cloud Computing, including technical advancement, IT delivery and deployment modes, and economics.
A review on soccer player tracking techniques based on extracted features

Playing games specially soccer is one of the most likable activities which performed by a large mass base in most countries. All the broadcasted videos of these games are taken as an extensive challenging by researchers in computer vision field. The topics which get the big chance of importance in industry are the tracking of both player and field. This can be used to describe the match for people who are visually impaired. In this review, we summarize some of the recent researcher's work related to different player tracking techniques according to specific features extracted from the scene to build a robust object (player and/or ball) tracking, such as motion, color, edges, etc., which considered as the most commonly used in object tracking. Also, we compare some of these techniques according to two groups of publicly available data sets in order to study the effect of selecting these features on the tracking accuracy.
Original Loop-Closure Detection Algorithm for Monocular vSLAM

Vision-based simultaneous localization and mapping (vSLAM) is a well-established problem in mobile robotics and monocular vSLAM is one of the most challenging variations of that problem nowadays. In this work we study one of the core post-processing optimization mechanisms in vSLAM, e.g. loop-closure detection. We analyze the existing methods and propose original algorithm for loop-closure detection, which is suitable for dense, semi-dense and feature-based vSLAM methods. We evaluate the algorithm experimentally and show that it contribute to more accurate mapping while speeding up the monocular vSLAM pipeline to the extent the latter can be used in real-time for controlling small multirotor vehicle (drone).
A Stable and Accurate Marker-Less Augmented Reality Registration Method

Markerless Augmented Reality (AR) registration using the standard Homography matrix is unstable, and for image-based registration it has very low accuracy. In this paper, we present a new method to improve the stability and the accuracy of marker-less registration in AR. Based on the Visual Simultaneous Localization and Mapping (V-SLAM) framework, our method adds a three-dimensional dense cloud processing step to the state-of-the-art ORB-SLAM in order to deal with mainly the point cloud fusion and the object recognition. Our algorithm for the object recognition process acts as a stabilizer to improve the registration accuracy during the model to the scene transformation process. This has been achieved by integrating the Hough voting algorithm with the Iterative Closest Points(ICP) method. Our proposed AR framework also further increases the registration accuracy with the use of integrated camera poses on the registration of virtual objects. Our experiments show that the proposed method not only accelerates the speed of camera tracking with a standard SLAM system, but also effectively identifies objects and improves the stability of markerless augmented reality applications.
Chapter 2 Challenges to the Adoption of E-commerce Technology for Supply Chain Management in a Developing Economy : A Focus on Nigerian SMEs

The evolution of Information Technology has enhanced consumers’ and organisations’ ability to gather information along with purchasing goods and services. Information Technology offers businesses increased competition, lower prices of goods and services, the choice of comparing products from different vendors and easy access to various vendors anywhere, anytime. Therefore, Information Technology facilitates the global nature of commerce. In developing countries, e-commerce dominates their economic activities. E-commerce is one of the leading non-oil sectors in Nigeria, 18.9 % GDP. In contrast with developed nations, e-commerce has not been as successfully adopted in developing countries. This chapter addresses the challenges and benefits of e-commerce technology in relation to SMEs in Nigeria. It presents quantitative evidence of SMEs perceptions of e-commerce technology, benefits, and barriers. A number of hypotheses are presented and assessed. Recommendations to mitigate barriers are suggested.
Three Types of Chief Digital Officers and the Reasons Organizations Adopt the Role

Digital innovation impacts every industry, and in response many organizations have introduced a new leadership role—the chief digital officer (CDO). Based on interviews with CDOs from various sectors, we have identified three types of CDOs—digital accelerators, digital marketers and digital harmonizers—and three domains where successful CDOs build digital capabilities (digital innovation, data analytics and customer engagement). As shown below, each type of CDO focuses specifically on one of the digital capabilities. The table also shows the primary objective of each type of CDO and the reasons for establishing that role. Digital Accelerator CDOs. The common characteristic of digital accelerator CDOs is that they drive digital innovation—typically complementing existing IT leaders who are predominantly involved with supporting operational and missioncritical activities, with a strong emphasis on reliability, performance and security. The scope of the CDO is different from that of IT executives in their organizations—less focused on operational reliability and more focused on experimenting with new capabilities in novel areas. Digital accelerator CDOs complement more conservative IT organizations by focusing on rapid development and evaluation of digital technologies. The role of digital accelerator CDOs is to achieve fast results by facilitating continual experimentation with minimal viable products of digital innovations. Digital Marketer CDOs. This type of CDO guides the organization’s digital marketing efforts with an emphasis on customer intimacy through technologies like social media and mobile computing, as well as intensive analysis of customer data. Digital marketer CDO roles have been established to streamline online and offline marketing channels for engaging with customers. These CDOs complement marketing efforts by deploying digital technologies that can enhance products, customer relationships and competitive position. Digital Harmonizer CDOs. In addition to complementing the IT or the marketing functions, some CDOs (digital harmonizers) are brought in to take an aggregate view of all ongoing digital initiatives. These CDOs are charged with linking together a wide variety of digital initiatives in many different areas of their organizations. The digital harmonizer role is a way of bringing these initiatives under a single, typically more strategic, umbrella. Digital harmonizers aggregate the disparate digital efforts distributed across the organization into a single unit and coordinate them. They emphasize governance and the need for transparency in digital projects.
A 6-Gbit/s Hybrid Voltage-Mode Transmitter With Current-Mode Equalization in 90-nm CMOS

Low-power (LP) high-speed serial I/O transmitters which include equalization to compensate for channel frequency-dependent loss are required to meet the aggressive link energy-efficiency targets of future systems. This brief presents an LP serial-link-transmitter design that utilizes an output stage which combines a voltage-mode driver, which offers low static-power dissipation, and current-mode equalization, which offers low complexity and dynamic-power dissipation. The utilization of current-mode equalization decouples the equalization settings and termination impedance, allowing for a significant reduction in predriver complexity relative to segmented voltage-mode drivers. Proper transmitter series termination is set with an impedance control loop which adjusts the on-resistance of the output transistors in the driver voltage-mode portion. Further reductions in dynamic-power dissipation are achieved through scaling the serializer and local clock distribution supply with data rate. Fabricated in a 1.2-V 90-nm LP CMOS process, the transmitter supports an output swing range of 100–400 $\hbox{mV}_{{\rm ppd}}$ and up to 6 dB of equalization and includes output-duty-cycle control. The transmitter achieves 6-Gbit/s operation at 1.26-pJ/bit energy efficiency with 300-$\hbox{mV}_{{\rm ppd}}$ output swing and 3.72-dB equalization.
Citation Recommendation Using Distributed Representation of Discourse Facets in Scientific Articles

Scientific articles usually follow a common pattern of discourse, and their contents can be divided into several facets, such as objective, method, and result. We examine the efficacy of using these discourse facets for citation recommendation. A method for learning multi-vector representations of scientific articles is proposed, in which each vector encodes a discourse facet present in an article. With each facet represented as a separate vector, the similarity of articles can be measured not in their entirety, but facet by facet. The proposed representation method is tested on a new citation recommendation task called context-based co-citation recommendation. This task calls for the evaluation of article similarity in terms of citation contexts, wherein facets help to abstract and generalize the diversity of contexts. The experimental results show that the facet-based representation outperforms the standard monolithic representation of articles.
Convolutional Neural Networks for Font Classification

Classifying pages or text lines into font categories aids transcription because single font Optical Character Recognition (OCR) is generally more accurate than omni-font OCR. We present a simple framework based on Convolutional Neural Networks (CNNs), where a CNN is trained to classify small patches of text into predefined font classes. To classify page or line images, we average the CNN predictions over densely extracted patches. We show that this method achieves state-of-the-art performance on a challenging dataset of 40 Arabic computer fonts with 98.8% line level accuracy. This same method also achieves the highest reported accuracy of 86.6% in predicting paleographic scribal script classes at the page level on medieval Latin manuscripts. Finally, we analyze what features are learned by the CNN on Latin manuscripts and find evidence that the CNN is learning both the defining morphological differences between scribal script classes as well as overfitting to class-correlated nuisance factors. We propose a novel form of data augmentation that improves robustness to text darkness, further increasing classification performance.