nils-herrmann/clean_scirepeval huggingface dataset:
CFTL : A Convertible Flash Translation Layer with Consideration of Data Access Patterns

NAND flash memory-based storage devices are increasingly adopted as one of the main alternatives for magnetic disk drives. The flash translation layer (FTL) is a software/hardware interface inside NAND flash memory, which allows existing disk-based applications to use it without any significant modifications. Since FTL has a critical impact on the performance of NAND flash-based devices, a variety of FTL schemes have been proposed to improve their performance. However, existing FTLs perform well for either a read intensive workload or a write intensive workload, not for both of them due to their fixed and static address mapping schemes. To overcome this limitation, in this paper, we propose a novel FTL addressing scheme named as Convertible Flash Translation Layer (CFTL, for short). CFTL is adaptive to data access patterns so that it can dynamically switch the mapping of a data block to either read-optimized or write-optimized mapping scheme in order to fully exploit the benefits of both schemes. By judiciously taking advantage of both schemes, CFTL resolves the intrinsic problems of the existing FTLs. In addition to this convertible scheme, we propose an efficient caching strategy so as to considerably improve the CFTL performance further with only a simple hint. Consequently, both of the convertible feature and caching strategy empower CFTL to achieve good read performance as well as good write performance. Our experimental evaluation with a variety of realistic workloads demonstrates that the proposed CFTL scheme outperforms other FTL schemes.
ISeeCube: visual analysis of gaze data for video

We introduce a new design for the visual analysis of eye tracking data recorded from dynamic stimuli such as video. ISeeCube includes multiple coordinated views to support different aspects of various analysis tasks. It combines methods for the spatiotemporal analysis of gaze data recorded from unlabeled videos as well as the possibility to annotate and investigate dynamic Areas of Interest (AOIs). A static overview of the complete data set is provided by a space-time cube visualization that shows gaze points with density-based color mapping and spatiotemporal clustering of the data. A timeline visualization supports the analysis of dynamic AOIs and the viewers' attention on them. AOI-based scanpaths of different viewers can be clustered by their Levenshtein distance, an attention map, or the transitions between AOIs. With the provided visual analytics techniques, the exploration of eye tracking data recorded from several viewers is supported for a wide range of analysis tasks.
Broadcast-based distributed alternating direction method of multipliers

We consider a multi agent optimization problem where a network of agents collectively solves a global optimization problem with the objective function given by the sum of locally known convex functions. We propose a fully distributed broadcast-based Alternating Direction Method of Multipliers (ADMM), in which each agent broadcasts the outcome of his local processing to all his neighbors. We show that both the objective function values and the feasibility violation converge with rate O(1/T), where T is the number of iterations. This improves upon the O(1/√T) convergence rate of subgradient-based methods. We also characterize the effect of network structure and the choice of communication matrix on the convergence speed. Because of its broadcast nature, the storage requirements of our algorithm are much more modest compared to the distributed algorithms that use pairwise communication between agents.
The cobas® 6800/8800 System: a new era of automation in molecular diagnostics.

Molecular diagnostics is a key component of laboratory medicine. Here, the authors review key triggers of ever-increasing automation in nucleic acid amplification testing (NAAT) with a focus on specific automated Polymerase Chain Reaction (PCR) testing and platforms such as the recently launched cobas® 6800 and cobas® 8800 Systems. The benefits of such automation for different stakeholders including patients, clinicians, laboratory personnel, hospital administrators, payers, and manufacturers are described.  The authors describe how molecular diagnostics has achieved total laboratory automation over time, rivaling clinical chemistry to significantly improve testing efficiency. Finally, the authors discuss how advances in automation decrease the development time for new tests enabling clinicians to more readily provide test results.  The advancements described enable complete diagnostic solutions whereby specific test results can be combined with relevant patient data sets to allow healthcare providers to deliver comprehensive clinical recommendations in multiple fields ranging from infectious disease to outbreak management and blood safety solutions.
Design of Highly Efficient Broadband Class-E Power Amplifier Using Synthesized Low-Pass Matching Networks

A new methodology for designing and implementing high-efficiency broadband Class-E power amplifiers (PAs) using high-order low-pass filter-prototype is proposed in this paper. A GaN transistor is used in this work, which is carefully modeled and characterized to prescribe the optimal output impedance for the broadband Class-E operation. A sixth-order low-pass filter-matching network is designed and implemented for the output matching, which provides optimized fundamental and harmonic impedances within an octave bandwidth (L-band). Simulation and experimental results show that an optimal Class-E PA is realized from 1.2 to 2 GHz (50%) with a measured efficiency of 80%-89%, which is the highest reported today for such a bandwidth. An overall PA bandwidth of 0.9-2.2 GHz (84%) is measured with 10-20-W output power, 10-13-dB gain, and 63%-89% efficiency throughout the band. Furthermore, the Class-E PA is characterized through measurements using constant-envelop global system for mobile communications signals, indicating a favorable adjacent channel power ratio from -40 to -50 dBc within the entire bandwidth.
WYSIWYG NPR: drawing strokes directly on 3D models

We present a system that lets a designer directly annotate a 3D model with strokes, imparting a personal aesthetic to the non-photorealistic rendering of the object. The artist chooses a "brush" style, then draws strokes over the model from one or more viewpoints. When the system renders the scene from any new viewpoint, it adapts the number and placement of the strokes appropriately to maintain the original look.
B2VDM: Blockchain Based Vehicular Data Management

Smart interconnected vehicles generate a huge amount of data to be used by a wide range of applications. Although cloud based data management is currently in practice, for many applications serving road safety or traffic regulation, it is utmost important that applications access these data at the site itself for improved quality of service. Road side units (RSUs) play a crucial role in handling these vast amount of vehicular data and serving the running applications in turn. In this current era of edge computing, in-place data access is also proven to be advantageous from cost point of view. As multiple applications from different service providers are interested to access different fragments of these data, a robust access control mechanism is needed to ensure desired level of security as well as reliability for these data. In this paper, we introduce B2VDM, a novel architecture for vehicular data management at RSUs, that provides a seamless access control using Blockchain technology. The proposed B2VDM framework also implements a simple load distribution module, which maintains the reliability by minimizing the number of packet drops at a heavily loaded RSU during peak hours. An extensive evaluation using Etherium Blockchain validates the effectiveness of the proposed architecture.
An RSS-feed auditory aggregator using earcons

In this work we present a data sonification framework based on parallel/concurrent sonic earcons' representations for monitoring in real-time information related to stock market. The information under consideration is conveyed through the well-known Really Simple Syndication (RSS) feed Internet mechanism and includes both text and numeric values, converted to speech and earcons using existing speech synthesis techniques and sonic design guidelines. Due to the considered application characteristics, particular emphasis is provided on information representation concurrency, mainly achieved using sound source spatialization techniques and different timbre characteristics. Spatial positioning of sound sources is performed through typical binaural processing and reproduction. A number of systematic, subjective assessments performed have shown that the overall perceptual efficiency and sonic representation accuracy fulfills the overall application requirements, provided that the users are appropriately trained prior to using the proposed RSS-feed auditory aggregator.
Design of PID Controller for Plant Control and Comparison with ZN PID Controller

Proportional-integral-derivative (PID) controllers are widely used in industrial control systems because of the reduced number of parameters to be tuned. The most popular design technique is the Ziegler–Nichols method. This paper presents the design of PID controller to realize governor action in power generation plant. The conventional PID controller is replaced by Ziegler Nichols tuning PID controller to make them more general and to achieve the minimum steady state error, also to improve the other dynamic behaviour. The performance and design for automatic selection of the PID constants are also discussed. Proportional-Integral-Derivative controls, PID hardware, Ziegler-Nichols Tuning, PID controllers design.
Intelligent heart disease prediction system using data mining techniques

The healthcare industry collects huge amounts of healthcare data which, unfortunately, are not ";mined"; to discover hidden information for effective decision making. Discovery of hidden patterns and relationships often goes unexploited. Advanced data mining techniques can help remedy this situation. This research has developed a prototype Intelligent Heart Disease Prediction System (IHDPS) using data mining techniques, namely, Decision Trees, Naive Bayes and Neural Network. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. IHDPS can answer complex ";what if"; queries which traditional decision support systems cannot. Using medical profiles such as age, sex, blood pressure and blood sugar it can predict the likelihood of patients getting a heart disease. It enables significant knowledge, e.g. patterns, relationships between medical factors related to heart disease, to be established. IHDPS is Web-based, user-friendly, scalable, reliable and expandable. It is implemented on the .NET platform.
Challenges in Applying Control Theory to Software Performance Engineering for Adaptive Systems

Control theory has recently started to be applied to software engineering domain, mostly for managing the behavior of adaptive software systems under external disturbances. In general terms, the main advantage of control theory is that it can be formally proven that controllers achieve their goals (with certain characteristics), whereas the price to pay is that controllers and system-to-be-controlled have to be modeled by equations. The investigation of how suited are control theory techniques to address performance problems is, however, still at the beginning. In this paper we devise the main challenges behind the adoption of control theory in the context of Software Performance Engineering applied to adaptive software systems.
Biogeography based optimization for Traveling Salesman Problem

Biogeography-based optimization algorithm(BBO) is a new kind of optimization algorithm based on Biogeography. It mimics the migration strategy of animals to solve the problem of optimization. A new algorithm for Traveling Salesman Problem(TSPBBO) based on BBO is presented in this paper. It is tested on classical TSP problem. The comparison results with the other kinds of optimization algorithm show that TSPBBO is a very effective algorithm for TSP combination optimization. It provides a new method for this kind of problem.
A time and space complexity analysis of model integration

The computational study of complex systems increasingly requires model integration. The drivers include a growing interest in leveraging accepted legacy models, an intensifying pressure to reduce development costs by reusing models, and expanding user requirements that are best met by combining different modeling methods. There have been many published successes including supporting theory, conceptual frameworks, software tools, and case studies. Nonetheless, on an empirical basis, the published work suggests that correctly specifying model integration strategies remains challenging. This naturally raises a question that has not yet been answered in the literature, namely 'what is the computational difficulty of model integration?' This paper's contribution is to address this question with a time and space complexity analysis that concludes that deep model integration with proven correctness is both NP-complete and PSPACE-complete and that reducing this complexity requires sacrificing correctness proofs in favor of guidance from both subject matter experts and modeling specialists.
AppGuard - Enforcing User Requirements on Android Apps

The success of Android phones makes them a prominent target for malicious software, in particular since the Android permission system turned out to be inadequate to protect the user against security and privacy threats. This work presents AppGuard, a powerful and flexible system for the enforcement of user-customizable security policies on untrusted Android applications. AppGuard does not require any changes to a smartphone’s firmware or root access. Our system offers complete mediation of security-relevant methods based on callee-site inline reference monitoring. We demonstrate the general applicability of AppGuard by several case studies, e.g., removing permissions from overly curious apps as well as defending against several recent real-world attacks on Android phones. Our technique exhibits very little space and runtime overhead. AppGuard is publicly available, has been invited to the Samsung Apps market, and has had more than 500,000 downloads so far.
Weak semantic context helps phonetic learning in a model of infant language acquisition

Learning phonetic categories is one of the first steps to learning a language, yet is hard to do using only distributional phonetic information. Semantics could potentially be useful, since words with different meanings have distinct phonetics, but it is unclear how many word meanings are known to infants learning phonetic categories. We show that attending to a weaker source of semantics, in the form of a distribution over topics in the current context, can lead to improvements in phonetic category learning. In our model, an extension of a previous model of joint word-form and phonetic category inference, the probability of word-forms is topic-dependent, enabling the model to find significantly better phonetic vowel categories and word-forms than a model with no semantic knowledge.
Origami axioms and circle extension

Origami, i.e. paper folding, is a powerful tool for geometrical constructions. In 1989, Humiaki Huzita introduced six folding operations based on aligning one or more combinations of points and lines . Jacques Justin, in his paper of the same proceedings, also presented a list of seven distinct operations . His list included, without literal description, one extra operation not in Huzita's paper. Justin's work was written in French, and was somehow unknown among researchers. This led Hatori  to 'discover' the same seventh operation in 2001. Alperin and Lang in 2006  showed, by exhaustive enumeration of combinations of superpositions of points and lines involved, that the seven operations are complete combinations of the alignments. Huzita did not call his list of operations axioms. However, over years, the term Huzita axioms, or Huzita-Justin or Huzita-Hatori axioms, has been widely used in origami community. From logical point of view, it is not accurate to call Huzita's original statements of folding operations as axioms, because they are not always true in plane Euclidean geometry. In this paper, we present precise statements of the folding operations, by which naming them 'axioms' is logically valid, and we make some notes about the work of Huzita and Justin.
Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning

The encoder-decoder models for unsupervised sentence representation learning tend to discard the decoder after being trained on a large unlabelled corpus, since only the encoder is needed to map the input sentence into a vector representation. However, parameters learnt in the decoder also contain useful information about language. In order to utilise the decoder after learning, we present two types of decoding functions whose inverse can be easily derived without expensive inverse calculation. Therefore, the inverse of the decoding function serves as another encoder that produces sentence representations. We show that, with careful design of the decoding functions, the model learns good sentence representations, and the ensemble of the representations produced from the encoder and the inverse of the decoder demonstrate even better generalisation ability and solid transferability.
Distributed Intelligent MEMS: A Survey and a Real-Time Programming Framework

In recent years, distributed intelligent microelectromechanical systems (DiMEMSs) have appeared as a new form of distributed embedded systems. DiMEMSs contain thousands or millions of removable autonomous devices, which will collaborate with each other to achieve the final target of the whole system. Programming such systems is becoming an extremely difficult problem. The difficulty is due not only to their inherent nature of distributed collaboration, mobility, large scale, and limited resources of their devices (e.g., in terms of energy, memory, communication, and computation) but also to the requirements of real-time control and tolerance for uncertainties such as inaccurate actuation and unreliable communications. As a result, existing programming languages for traditional distributed and embedded systems are not suitable for DiMEMSs. In this article, we first introduce the origin and characteristics of DiMEMSs and then survey typical implementations of DiMEMSs and related research hotspots. Finally, we propose a real-time programming framework that can be used to design new real-time programming languages for DiMEMSs. The framework is composed of three layers: a real-time programming model layer, a compilation layer, and a runtime system layer. The design challenges and requirements of these layers are investigated. The framework is then discussed in further detail and suggestions for future research are given.
An Architecture For Opportunistic Text Generation

We describe the architecture of the ILEX system, • which supports opportunistic text generation. In • web-based text generation, the SYstem cannot plan the entire multi-page discourse because the user's browsing path is unpredictable. For this reason, • the system must be ready opportunistically to take • advantage of whatever path the user chooses. We describe both the nature of opportunism in ILEX's museum domain, and then show how ILEX has been designed to function in this environment. The architecture presented addresses opportunism in both content determination and sentenceplanning. 1 E x p l o i t i n g o p p o r t u n i t i e s in t e x t g e n e r a t i o n • Many models of text generation make use of standard patterns (whether expressed as schemas (e.g. [McKeown 85]) or plan operators (e.g. [Moore and Paris 93])) to break down communicative goals in such a way as to produce extended texts. Such models are making two basic assumptions: 1. Text generation is goal directed, in the sense that spans and subspans of text are designed to achieve unitary communicative goals [Grosz and Sidner 86]. 2. Although the details Of the structUre of a text may have to be tuned to particulars of the communicative situation, generally the structure is determined by the goals and their decomposition. That is, a generator •needs strategies for decomposing the achievement of complex • goals into sequences of utterances, rather than ways of combining sequences of utterances into more complex structures. Generation is "top-down", rather than"bottom-up" [Marcu 97]. Our belief is that there is an important class of NLG problems for which these basic assumptions• are not helpful. These problems all involve situations where semi-fixed explanation strategies are less useful than the ability to exploit opportunities. WordNet gives the following definition of 0pportunity': O p p o r t u n i t y : "A possibility due to a favorable combination of circumstances" Because • opportunities involve •combinations of circumstances, they are often unexpected and hard to predict. It may be too expensive or impossible to have complete knowledge about them. Topdown generation strategies may not be able •to exploit opportunities (except at the cost of looking for all opportunities at all• points) because it is difficult to associate classes of opportunities with fixed stages in the explanation •process. We are investigating opportunistic text generation in the Intelligent Labelling Explorer (ILEX) project, which seeks automatically to generate a sequence of commentaries for items in an electronic 180 South Bridge, Edinburgh EH1 1HN,  Email: {alik, jon}@cogsci.ed, ac.uk
Food allergy: epidemiology and natural history.

The prevalence of food allergy is rising for unclear reasons, with prevalence estimates in the developed world approaching 10%. Knowledge regarding the natural course of food allergies is important because it can aid the clinician in diagnosing food allergies and in determining when to consider evaluation for food allergy resolution. Many food allergies with onset in early childhood are outgrown later in childhood, although a minority of food allergy persists into adolescence and even adulthood. More research is needed to improve food allergy diagnosis, treatment, and prevention.
Judgment of natural perspective projections in head-mounted display environments

The display units integrated in todays head-mounted displays (HMDs) provide only a limited field of view (FOV) to the virtual world. In order to present an undistorted view to the virtual environment (VE), the perspective projection used to render the VE has to be adjusted to the limitations caused by the HMD characteristics. In particular, the geometric field of view (GFOV), which defines the virtual aperture angle used for rendering of the 3D scene, is set up according to the display's field of view. A discrepancy between these two fields of view distorts the geometry of the VE in a way that either minifies or magnifies the imagery displayed to the user. Discrepancies between the geometric and physical FOV causes the imagery to be minified or magnified. This distortion has the potential to negatively or positively affect a user's perception of the virtual space, sense of presence, and performance on visual search tasks.
 In this paper we analyze if a user is consciously aware of perspective distortions of the VE displayed in the HMD. We introduce a psychophysical calibration method to determine the HMD's actual field of view, which may vary from the nominal values specified by the manufacturer. Furthermore, we conducted an experiment to identify perspective projections for HMDs which are identified as natural by subjects---even if these perspectives deviate from the perspectives that are inherently defined by the display's field of view. We found that subjects evaluate a field of view as natural when it is larger than the actual field of view of the HMD---in some cases up to 50%.