nils-herrmann/clean_scirepeval huggingface dataset:
Extending feature usage: a study of the post-adoption of electronic medical records

In order to study the factors that influence how professionals use complex systems, we create a tentative research model that builds on PAM and TAM. Specifically we include PEOU and the construct ‘Professional Association Guidance’. We postulate that feature usage is enhanced when professional associations influence PU by highlighting additional benefits. We explore the theory in the context of post-adoption use of Electronic Medical Records (EMRs) by primary care physicians in Ontario. The methodology can be extended to other professional environments and we suggest directions for future research.
Mobile Security Catching Up? Revealing the Nuts and Bolts of the Security of Mobile Devices

We are currently moving from the Internet society to a mobile society where more and more access to information is done by previously dumb phones. For example, the number of mobile phones using a full blown OS has risen to nearly200% from Q3/2009 to Q3/2010. As a result, mobile security is no longer immanent, but imperative. This survey paper provides a concise overview of mobile network security, attack vectors using the back end system and the web browser, but also the hardware layer and the user as attack enabler. We show differences and similarities between "normal" security and mobile security, and draw conclusions for further research opportunities in this area.
Constructing a Hermitian Matrix from Its Diagonal Entries and Eigenvalues

Given two vectors a R the Schur Horn theorem states that a majorizes if and only if there exists a Hermitian matrix H with eigenvalues and diagonal entries a While the theory is regarded as classical by now the known proof is not constructive To construct a Hermitian matrix from its diagonal entries and eigenvalues therefore becomes an interesting and challenging inverse eigenvalue problem Two algorithms for determining the matrix numerically are proposed in this paper The lift and pro jection method is an iterative method which involves an interesting application of the Wielandt Ho man theorem The projected gradient method is a continuous method which besides its easy implementation o ers a new proof of existence because of its global convergence property
Dialogue-act-driven Conversation Model : An Experimental Study

The utility of additional semantic information for the task of next utterance selection in an automated dialogue system is the focus of study in this paper. In particular, we show that additional information available in the form of dialogue acts –when used along with context given in the form of dialogue history– improves the performance irrespective of the underlying model being generative or discriminative. In order to show the model agnostic behavior of dialogue acts, we experiment with several well-known models such as sequence-to-sequence encoder-decoder model, hierarchical encoder-decoder model, and Siamese-based models with and without hierarchy; and show that in all models, incorporating dialogue acts improves the performance by a significant margin. We, furthermore, propose a novel way of encoding dialogue act information, and use it along with hierarchical encoder to build a model that can use the sequential dialogue act information in a natural way. Our proposed model achieves an MRR of about 84.8% for the task of next utterance selection on a newly introduced DailyDialog dataset, and outperform the baseline models. We also provide a detailed analysis of results including key insights that explain the improvement in MRR because of dialogue act information.
The Fourth PASCAL Recognizing Textual Entailment Challenge

In 2008 the Recognizing Textual Entailment Challenge (RTE-4) was proposed for the first time as a track at the Text Analysis Conference (TAC). Another important innovation introduced in this campaign was a three-judgment task, which required the systems to make a further distinction between pairs where the entailment does not hold because the content of H is contradicted by the content of T, and pairs where the entailment cannot be determined because the truth of H cannot be verified on the basis of the content of T. A classic twoway task was also offered. RTE-4 attracted 26 teams, more than half of whom submitted runs for the new 3-way task. This paper describes the preparation of the dataset, and gives an overview of the results achieved by the participating systems.
Hybrid excited claw pole electric machine

The paper presents the concept and results of simulation and experimental research of a claw pole generator with hybrid excitation. Hybrid excitation is performed with a conventional coil located between two parts of the claw-shape rotor and additional permanent magnets which are placed on claw poles. Within the research first a simulation and next constructed experimental model has been developed on the basis of the mass-produced vehicle alternator. Experimental researches have shown that - at a suitable rotational speed - it is possible to self-excite of the generator without any additional source of electrical power.
Brain Areas Involved in Perception of Biological Motion

These experiments use functional magnetic resonance imaging (fMRI) to reveal neural activity uniquely associated with perception of biological motion. We isolated brain areas activated during the viewing of point-light figures, then compared those areas to regions known to be involved in coherent-motion perception and kinetic-boundary perception. Coherent motion activated a region matching previous reports of human MT/MST complex located on the temporo-parieto-occipital junction. Kinetic boundaries activated a region posterior and adjacent to human MT previously identified as the kinetic-occipital (KO) region or the lateral-occipital (LO) complex. The pattern of activation during viewing of biological motion was located within a small region on the ventral bank of the occipital extent of the superior-temporal sulcus (STS). This region is located lateral and anterior to human MT/MST, and anterior to KO. Among our observers, we localized this region more frequently in the right hemisphere than in the left. This was true regardless of whether the point-light figures were presented in the right or left hemifield. A small region in the medial cerebellum was also active when observers viewed biological-motion sequences. Consistent with earlier neuroimaging and single-unit studies, this pattern of results points to the existence of neural mechanisms specialized for analysis of the kinematics defining biological motion.
On Realistically Attacking Tor with Website Fingerprinting

Website fingerprinting allows a local, passive observer monitoring a web-browsing client’s encrypted channel to determine her web activity. Previous attacks have shown that website fingerprinting could be a threat to anonymity networks such as Tor under laboratory conditions. However, there are significant differences between laboratory conditions and realistic conditions. First, the training data set is very similar to the testing data set under laboratory conditions, but the attacker may not be able to guarantee similarity realistically. Second, laboratory packet sequences correspond to a single page each, but for realistic packet sequences the split between pages is not obvious. Third, packet sequences may include noise, which may adversely affect website fingerprinting, but this effect has not been studied. In this paper, we tackle these three problems to bridge the gap between laboratory and realistic conditions for website fingerprinting. We show that we can maintain a fresh training set with minimal resources. We demonstrate several classification-based techniques that allow us to split full packet sequences effectively into sequences corresponding to a single page each. Although we were not able to remove noise effectively, we will show that it is difficult for users to generate sufficient background noise to disrupt website fingerprinting on Tor. With our techniques, we are able to build the first website fingerprinting system that can operate on packet sequences collected in the wild.
Improved Performance of Serially Connected Li-Ion Batteries With Active Cell Balancing in Electric Vehicles

This paper presents an active cell balancing method for lithium-ion battery stacks using a flyback dc/dc converter topology. The method is described in detail, and a simulation is performed to estimate the energy gain for ten serially connected cells during one discharging cycle. The simulation is validated with measurements on a balancing prototype with ten cells. It is then shown how the active balancing method with respect to the cell voltages can be improved using the capacity and the state of charge rather than the voltage as the balancing criterion. For both charging and discharging, an improvement in performance is gained when having the state of charge and the capacity of the cells as information. A battery stack with three single cells is modeled, and a realistic driving cycle is applied to compare the difference between both methods in terms of usable energy. Simulations are also validated with measurements.
Presynaptic depression of glutamatergic synaptic transmission by D1-like dopamine receptor activation in the avian basal ganglia.

Vocal behavior in songbirds exemplifies a rich integration of motor, cognitive, and social functions that are shared among vertebrates. As a part of the underlying neural substrate, the song system, the anterior forebrain pathway (AFP) is required for song learning and maintenance. The AFP resembles the mammalian basal ganglia-thalamocortical loop in its macroscopic organization, neuronal intrinsic properties, and microcircuitry. Area X, the first station in the AFP, is a part of the basal ganglia essential for vocal learning. It receives glutamatergic inputs from pallial structures and sends GABAergic outputs to thalamic structures. It also receives dense dopaminergic innervation from the midbrain. The role of this innervation is essentially unknown. Here we provide evidence that dopamine (DA) can modulate the glutamatergic inputs to spiny neurons in area X. In whole-cell voltage-clamp recordings from neurons in brain slices of adult zebra finches, we found that activation of D1-like DA receptors depresses ionotropic glutamatergic synaptic current in area X spiny neurons. This effect is mediated by a presynaptic site of action, mimicked by activation of adenylyl cyclase, and blocked by protein kinase A inhibitor and an adenosine A1 receptor antagonist. These results suggest that, in addition to altering the input-output function of spiny neurons by modulating their excitability, as we have shown previously, DA can directly influence the excitatory inputs to these neurons as well. Thus, DA can exert fine control over information processing through spiny neurons in area X, the dynamics of the AFP output, and ultimately song learning and maintenance.
A low-friction passive fluid transmission and fluid-tendon soft actuator

We present a passive fluid transmission based on antagonist pairs of rolling diaphragm cylinders. The transmission fluid working volume is completely sealed, forming a closed, passive system, ensuring input-output symmetry and complete backdrivability. Rolling diaphragm-sealed cylinders provide leak-free operation without the stiction of a traditional sliding seal. Fluid pressure preloading allows for bidirectional operation and also serves to preload the gears or belts in the linear-to-rotary output coupler, eliminating system backlash end-to-end. A prototype transmission is built and tested for stiffness, bandwidth, and frictional properties using either air or water as working fluids. Torque transmission is smooth over the entire stroke and stiction is measured to be one percent of full-range torque or less. We also present a tendon-coupled design where the rolling diaphragm is inverted from its normal orientation; this design does not require shaft support bushings, tolerates misalignment, and can be made out of substantially soft materials. Actuator units and a passive transmission are demonstrated using this new soft cylinder design.
Representing Multilingual Data as Linked Data: the Case of BabelNet 2.0

Recent years have witnessed a surge in the amount of semantic information published on the Web. Indeed, the Web of Data, a subset of the Semantic Web, has been increasing steadily in both volume and variety, transforming the Web into a ‘global database’ in which resources are linked across sites. Linguistic fields – in a broad sense – have not been left behind, and we observe a similar trend with the growth of linguistic data collections on the so-called ‘Linguistic Linked Open Data (LLOD) cloud’. While both Semantic Web and Natural Language Processing communities can obviously take advantage of this growing and distributed linguistic knowledge base, they are today faced with a new challenge, i.e., that of facilitating multilingual access to the Web of data. In this paper we present the publication of BabelNet 2.0, a wide-coverage multilingual encyclopedic dictionary and ontology, as Linked Data. The conversion made use of lemon, a lexicon model for ontologies particularly well-suited for this enterprise. The result is an interlinked multilingual (lexical) resource which can not only be accessed on the LOD, but also be used to enrich existing datasets with linguistic information, or to support the process of mapping datasets across languages.
Geometric Approximation via Coresets

The paradigm of coresets has recently emerged as a powerful tool for efficiently approximating various extent measures of a point set P . Using this paradigm, one quickly computes a small subset Q of P , called a coreset, that approximates the original set P and and then solves the problem on Q using a relatively inefficient algorithm. The solution for Q is then translated to an approximate solution to the original point set P . This paper describes the ways in which this paradigm has been successfully applied to various optimization and extent measure problems.
Distantly Supervised POS Tagging of Low-Resource Languages under Extreme Data Sparsity: The Case of Hittite

This paper presents a statistical approach to automatic morphosyntactic annotation of Hittite transcripts. Hittite is an extinct Indo-European language using the cuneiform script. There are currently no morphosyntactic annotations available for Hittite, so we explored methods of distant supervision. The annotations were projected from parallel German translations of the Hittite texts. In order to reduce data sparsity, we applied stemming of German and Hittite texts. As there is no off-theshelf Hittite stemmer, a stemmer for Hittite was developed for this purpose. The resulting annotation projections were used to train a POS tagger, achieving an accuracy of 69% on a test sample. To our knowledge, this is the first attempt of statistical POS tagging of a cuneiform language.
Dual-band microstrip antenna for WiMAX applications using complementary split ring resonators

A new design of dual-band microstrip antenna is presented in this paper using metamaterial concept. By etching a metamaterial unit cells that have a resonance frequency of 5.3 GHz within the ground plane of a conventional patch resonates at 3.6 GHz, a dual resonance response is created to satisfy the requirement of covering the middle and upper bands of Wi-MAX.A detailed study of the placement of the unit cell is introduced and the most suitable one is chosen to be the place of our unit cell. Multi-unit cell concept is used for performance enhancement of the fabricated design to achieve a good matching with the simulated one.
Characterizing the Google Books Corpus: Strong Limits to Inferences of Socio-Cultural and Linguistic Evolution

It is tempting to treat frequency trends from the Google Books data sets as indicators of the "true" popularity of various words and phrases. Doing so allows us to draw quantitatively strong conclusions about the evolution of cultural perception of a given topic, such as time or gender. However, the Google Books corpus suffers from a number of limitations which make it an obscure mask of cultural popularity. A primary issue is that the corpus is in effect a library, containing one of each book. A single, prolific author is thereby able to noticeably insert new phrases into the Google Books lexicon, whether the author is widely read or not. With this understood, the Google Books corpus remains an important data set to be considered more lexicon-like than text-like. Here, we show that a distinct problematic feature arises from the inclusion of scientific texts, which have become an increasingly substantive portion of the corpus throughout the 1900 s. The result is a surge of phrases typical to academic articles but less common in general, such as references to time in the form of citations. We use information theoretic methods to highlight these dynamics by examining and comparing major contributions via a divergence measure of English data sets between decades in the period 1800-2000. We find that only the English Fiction data set from the second version of the corpus is not heavily affected by professional texts. Overall, our findings call into question the vast majority of existing claims drawn from the Google Books corpus, and point to the need to fully characterize the dynamics of the corpus before using these data sets to draw broad conclusions about cultural and linguistic evolution.
An experimental study of big spatial data systems

With the rise of location-aware IoT devices, there is an increased desire to process and manage the stationary and moving trajectory data generated by these real-time sensors. There has been a corresponding evolution of distributed database and compute technology to handle the increasing data load. Here we describe challenges in managing this kind of data and survey the technologies that address those challenges. We evaluate two distributed database technologies against a simulated high volume sensor data source and discuss the performance of predominant moving trajectory access patterns.
An introduction to millimeter-wave mobile broadband systems

Almost all mobile communication systems today use spectrum in the range of 300 MHz-3 GHz. In this article, we reason why the wireless community should start looking at the 3-300 GHz spectrum for mobile broadband applications. We discuss propagation and device technology challenges associated with this band as well as its unique advantages for mobile communication. We introduce a millimeter-wave mobile broadband (MMB) system as a candidate next generation mobile communication system. We demonstrate the feasibility for MMB to achieve gigabit-per-second data rates at a distance up to 1 km in an urban mobile environment. A few key concepts in MMB network architecture such as the MMB base station grid, MMB interBS backhaul link, and a hybrid MMB + 4G system are described. We also discuss beamforming techniques and the frame structure of the MMB air interface.
Visual Analysis of TED Talk Topic Trends

TED Talks are short, powerful talks given by some of the world's brightest minds - scientists, philanthropists, businessmen, artists, and many others. Funded by members and advertising, these talks are free to access by the public on the TED website and TED YouTube channel, and many videos have become viral phenomena. In this research project, we perform a visual analysis of TED Talk videos and playlists to gain a good understanding of the trends and relationships between TED Talk topics.
TwitterRank: finding topic-sensitive influential twitterers

This paper focuses on the problem of identifying influential users of micro-blogging services. Twitter, one of the most notable micro-blogging services, employs a social-networking model called "following", in which each user can choose who she wants to "follow" to receive tweets from without requiring the latter to give permission first. In a dataset prepared for this study, it is observed that (1) 72.4% of the users in Twitter follow more than 80% of their followers, and (2) 80.5% of the users have 80% of users they are following follow them back. Our study reveals that the presence of "reciprocity" can be explained by phenomenon of homophily. Based on this finding, TwitterRank, an extension of PageRank algorithm, is proposed to measure the influence of users in Twitter. TwitterRank measures the influence taking both the topical similarity between users and the link structure into account. Experimental results show that TwitterRank outperforms the one Twitter currently uses and other related algorithms, including the original PageRank and Topic-sensitive PageRank.
Shallow Networks for High-Accuracy Road Object-Detection

The ability to automatically detect other vehicles on the road is vital to the safety of partially-autonomous and fully-autonomous vehicles. Most of the high-accuracy techniques for this task are based on R-CNN or one of its faster variants. In the research community, much emphasis has been applied to using 3D vision or complex R-CNN variants to achieve higher accuracy. However, are there more straightforward modifications that could deliver higher accuracy? Yes. We show that increasing input image resolution (i.e. upsampling) offers up to 12 percentage-points higher accuracy compared to an off-the-shelf baseline. We also find situations where earlier/shallower layers of CNN provide higher accuracy than later/deeper layers. We further show that shallow models and upsampled images yield competitive accuracy. Our findings contrast with the current trend towards deeper and larger models to achieve high accuracy in domain specific detection tasks.
Natural Language Processing methods and systems for biomedical ontology learning

While the biomedical informatics community widely acknowledges the utility of domain ontologies, there remain many barriers to their effective use. One important requirement of domain ontologies is that they must achieve a high degree of coverage of the domain concepts and concept relationships. However, the development of these ontologies is typically a manual, time-consuming, and often error-prone process. Limited resources result in missing concepts and relationships as well as difficulty in updating the ontology as knowledge changes. Methodologies developed in the fields of Natural Language Processing, information extraction, information retrieval and machine learning provide techniques for automating the enrichment of an ontology from free-text documents. In this article, we review existing methodologies and developed systems, and discuss how existing methods can benefit the development of biomedical ontologies.
MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones

This paper presents MyExperience, a system for capturing both objective and subjective in situ data on mobile computing activities. MyExperience combines the following two techniques: 1) passive logging of device usage, user context, and environmental sensor readings, and 2) active context-triggered user experience sampling to collect in situ, subjective user feedback. MyExperience currently runs on mobile phones and supports logging of more than 140 event types, including: 1) device usage such as communication, application usage, and media capture, 2) user context such as calendar appointments, and 3) environmental sensing such as Bluetooth and GPS. In addition, user experience sampling can be targeted to moments of interest by triggering off sensor readings. We present several case studies of field deployments on people's personal phones to demonstrate how MyExperience can be used effectively to understand how people use and experience mobile technology.