nils-herrmann/clean_scirepeval huggingface dataset:
ConceptVector: Text Visual Analytics via Interactive Lexicon Building Using Word Embedding

Central to many text analysis methods is the notion of a concept: a set of semantically related keywords characterizing a specific object, phenomenon, or theme. Advances in word embedding allow building a concept from a small set of seed terms. However, naive application of such techniques may result in false positive errors because of the polysemy of natural language. To mitigate this problem, we present a visual analytics system called ConceptVector that guides a user in building such concepts and then using them to analyze documents. Document-analysis case studies with real-world datasets demonstrate the fine-grained analysis provided by ConceptVector. To support the elaborate modeling of concepts, we introduce a bipolar concept model and support for specifying irrelevant words. We validate the interactive lexicon building interface by a user study and expert reviews. Quantitative evaluation shows that the bipolar lexicon generated with our methods is comparable to human-generated ones.
High-speed visible light communication systems

This article presents recent achievements and trends in high-speed indoor visible light communication (VLC) research. We address potential applications and future visions for the VLC technology, where transport of information is “piggybacked” on the original lighting function of LED-based lamps. To mature this technology and transfer it into practice, our recent research is focused on real-time implementation and trials. For the first time, a bidirectional real-time VLC prototype achieving data rates of up to 500 Mb/s is presented. This system paves the way for future real world applications. Finally, we discuss the remaining technical challenges as well as the research outlook in the field of high-speed VLC systems.
Dr. AI, where did you get your degree?

Federal health agencies are currently developing regulatory strategies for Artificial Intelligence based medical products. Regulatory regimes need to account for the new risks and benefits that come with modern AI, along with safety concerns and potential for continual autonomous learning that makes AI non-static and dramatically different than the drugs and products that agencies are used to regulating. Currently, the U.S. Food and Drug Administration (FDA) and other regulatory agencies treat AI-enabled products as medical devices. Alternatively, we propose that AI regulation in the medical domain can analogously adopt aspects of the models used to regulate medical providers.
A 13.56MHz CMOS active diode full-wave rectifier achieving ZVS with voltage-time-conversion delay-locked loop for wireless power transmission

A CMOS active diode rectifier for wireless power transmission with proposed voltage-time-conversion (VTC) delay-locked loop (DLL) control suppresses reverse current by realizing zero-voltage switching (ZVS), regardless of AC input and process variations. The proposed circuit is implemented in a standard 0.18μm CMOS process using I/O MOSFETs, which corresponds to 0.35μm technology. The maximum power conversion efficiency of 78% is obtained at 231Ω load resistance.
Conversion disorder: the modern hysteria

All doctors have encountered patients whose symptoms they cannot explain. These individuals frequently provoke despair and disillusionment. Many doctors make a link between inexplicable physical symptoms and assumed psychiatric ill­ ness. An array of adjectives in medicine apply to symptoms without established organic basis – ‘supratentorial’, ‘psychosomatic’, ‘functional’ – and these are sometimes used without reference to their real meaning. In psychiatry, such symptoms fall under the umbrella of the somatoform disorders, which includes a broad range of diagnoses. Conversion disorder is just one of these. Its meaning is not always well understood and it is often confused with somatisation disorder.† Our aim here is to clarify the notion of a conversion disorder (and the differences between conversion and other somatoform disorders) and to discuss prevalence, aetiology, management and prognosis.
Reference models supporting enterprise networks and virtual enterprises

This article analyses different types of reference models applicable to support the set up and (re)configuration of Virtual Enterprises (VEs). Reference models are models capturing concepts common to VEs aiming to convert the task of setting up a VE into a configuration task, and hence reducing the time needed for VE creation. The reference models are analysed through a mapping onto the Virtual Enterprise Reference Architecture (VERA) based upon GERAM and created in the IMS GLOBEMEN project.
Fitting the mind to the world: face adaptation and attractiveness aftereffects.

Average faces are attractive, but what is average depends on experience. We examined the effect of brief exposure to consistent facial distortions on what looks normal (average) and what looks attractive. Adaptation to a consistent distortion shifted what looked most normal, and what looked most attractive, toward that distortion. These normality and attractiveness aftereffects occurred when the adapting and test faces differed in orientation by 90 degrees (+45 degrees vs. -45 degrees ), suggesting adaptation of high-level neurons whose coding is not strictly retino- topic. Our results suggest that perceptual adaptation can rapidly recalibrate people's preferences to fit the faces they see. The results also suggest that average faces are attractive because of their central location in a distribution of faces (i.e., prototypicality), rather than because of any intrinsic appeal of particular physical characteristics. Recalibration of preferences may have important consequences, given the powerful effects of perceived attractiveness on person perception, mate choice, social interactions, and social outcomes for individuals.
Convolutional Neural Network for Universal Sentence Embeddings

This paper proposes a simple CNN model for creating general-purpose sentence embeddings that can transfer easily across domains and can also act as effective initialization for downstream tasks. Recently, averaging the embeddings of words in a sentence has proven to be a surprisingly successful and efficient way of obtaining sentence embeddings. However, these models represent a sentence, only in terms of features of words or uni-grams in it. In contrast, our model (CSE) utilizes both features of words and n-grams to encode sentences, which is actually a generalization of these bag-of-words models. The extensive experiments demonstrate that CSE performs better than average models in transfer learning setting and exceeds the state of the art in supervised learning setting by initializing the parameters with the pre-trained sentence embeddings.
Multiple object identification with passive RFID tags

We investigate the applicability of passive RFID systems to the task of identifying multiple tagged objects simultaneously, assuming that the number of tags is not known in advance. We present a combinatorial model of the communication mechanism between the reader device and the tags, and use this model to derive the optimal parameter setting for the reading process, based on estimates for the number of tags. Some results on the performance of an implementation are presented.  RFID, collision-resolution, tagging, combinatorics.
Towards a Consumer Cloud Computing Maturity Model - Proposition of Development Guidelines, Maturity Domains and Maturity Levels

In recent years, Cloud Computing (CC) has transformed from a new trend to IT management reality. Its potential promises to significantly change computing and benefit many organisations but at the same time uncertainty and the need for managerial guidance prevail. To benefit from the opportunities that CC promises, organisations need to adapt to the new circumstances that this phenomenon triggers and develop new capabilities. Maturity models have shown to be an excellent and easily applicable tool for the assessment and improvement of capabilities. However, there is no fully developed and universally accepted CC maturity model (CCMM) so far. Through the execution of a maturity model development process, this contribution is aiming at deriving development guidelines for the future development of a holistic consumer CCMM. Additionally, content and structure in the form of maturity domains and maturity levels are proposed throughout the development process, the combination of which represents the first steps towards a holistic consumer CCMM.
A Fault Ride-Through Technique of DFIG Wind Turbine Systems Using Dynamic Voltage Restorers

This paper proposes a low-voltage ride-through technique of a doubly fed induction generator (DFIG) wind turbine system using a dynamic voltage restorer (DVR). For effective control of the DVR, digital all-pass filters are used for extracting the positive-sequence component from the unbalanced grid voltage since they have the advantages of giving a desired phase shift and no magnitude reduction over conventional low- or high-pass filters. Using the positive-sequence component, the phase angles for the positive- and negative-sequence components of the grid voltage are derived. A control algorithm for the DVR that is dual voltage controllers only is implemented for the two sequence components in the dq synchronous reference frame. In order to achieve the power rating reduction of the DVR, the stator power reference for the DFIG is reduced during faults. In addition, a control scheme of pitch angle system is applied to stabilize the operation of the wind turbine system in the event of grid faults. PSCAD/EMTDC simulations show the effectiveness of the proposed technique and a feasibility of reducing the power rating of DVR for the fault ride-through capability of DFIG. The validity of the proposed control scheme for the DVR has also been verified by experimental results.
Sensing the Structural Differences in Cellulose from Apple and Bacterial Cell Wall Materials by Raman and FT-IR Spectroscopy

Raman and Fourier Transform Infrared (FT-IR) spectroscopy was used for assessment of structural differences of celluloses of various origins. Investigated celluloses were: bacterial celluloses cultured in presence of pectin and/or xyloglucan, as well as commercial celluloses and cellulose extracted from apple parenchyma. FT-IR spectra were used to estimate of the I(β) content, whereas Raman spectra were used to evaluate the degree of crystallinity of the cellulose. The crystallinity index (X(C)(RAMAN)%) varied from -25% for apple cellulose to 53% for microcrystalline commercial cellulose. Considering bacterial cellulose, addition of xyloglucan has an impact on the percentage content of cellulose I(β). However, addition of only xyloglucan or only pectins to pure bacterial cellulose both resulted in a slight decrease of crystallinity. However, culturing bacterial cellulose in the presence of mixtures of xyloglucan and pectins results in an increase of crystallinity. The results confirmed that the higher degree of crystallinity, the broader the peak around 913 cm(-1). Among all bacterial celluloses the bacterial cellulose cultured in presence of xyloglucan and pectin (BCPX) has the most similar structure to those observed in natural primary cell walls.
Eraser: Your Data Won't Be Back

Secure deletion of data from non-volatile storage is a well-recognized problem. While numerous solutions have been proposed, advances in storage technologies have stymied efforts to solve the problem. For instance, SSDs make use of techniques such as wear leveling that involve replication of data; this is in direct opposition to efforts to securely delete sensitive data from storage. We present a technique to provide secure deletion guarantees at file granularity, independent of the characteristics of the underlying storage medium. The approach builds on prior seminal work on cryptographic erasure, encrypting every file on an insecure medium with a unique key that can later be discarded to cryptographically render the data irrecoverable. To make the approach scalable and, therefore, usable on commodity systems, keys are organized in an efficient tree structure where a single master key is confined to a secure store. We describe an implementation of this scheme as a fileaware stackable block device, deployed as a standalone Linux kernel module that does not require modifications to the operating system. Our prototype demonstrates that secure deletion independent of the underlying storage medium can be achieved with comparable overhead to existing full disk encryption implementations.
Multimodal Machine Translation with Reinforcement Learning

Multimodal machine translation is one of the applications that integrates computer vision and language processing. It is a unique task givent that in the field of machine translation, many state-of-the-arts algorithms still only employ textual information. In this work, we explore the effectiveness of reinforcement learning in multimodal machine translation. We present a novel algorithm based on the Advantage ActorCritic (A2C) algorithm that specifically cater to the multimodal machine translation task of the EMNLP 2018 Third Conference on Machine Translation (WMT18). We experiment our proposed algorithm on the Multi30K multilingual English-German image description dataset and the Flickr30K image entity dataset. Our model takes two channels of inputs, image and text, uses translation evaluation metrics as training rewards, and achieves better results than supervised learning MLE baseline models. Furthermore, we discuss the prospects and limitations of using reinforcement learning for machine translation. Our experiment results suggest a promising reinforcement learning solution to the general task of multimodal sequence to sequence learning.
SDLC Models-A Survey Sukhdev Singh Ghuman

Software Development Life Cycle (SDLC) is a model which provides us the basic information about the methods/techniques to develop software. It is concerned with the software management processes that examine the area of software development through the development models, which are known as software development life cycle. There are many development models namely Waterfall model, Iterative model, V-shaped model, Spiral model, Extreme programming, Iterative and Incremental Method, Rapid prototyping model and Big Bang Model. This is paper is concerned with the study of these different software development models and to compare their advantages and disadvantages.
Onychomatricoma: an often misdiagnosed tumor of the nails.

Onychomatricoma is a subungual tumor that is clinically characterized by banded or diffuse thickening, yellowish discoloration, splinter hemorrhages, and transverse overcurvature of the nail plate. It is often and easily misdiagnosed because the condition is not well known and rarely has been described. We report the case of a 45-year-old man with a subungual tumor on the right index finger that fulfills the criteria of onychomatricoma.
A programmable analog delay line for Micro-beamforming in a transesophageal ultrasound probe

Our research project is to design a readout IC for an ultrasonic transducer consisting of a matrix of more than 2000 elements. The IC and the matrix transducer will be put into the tip of a transesophageal probe for 3D echocardiography. A key building block of the readout IC, a programmable analog delay line, is presented in this paper. It is based on the time-interleaved sample-and-hold (S/H) principle. Compared with conventional analog delay lines, this design is simple, accurate and flexible. A prototype has been fabricated in a standard 0.35µm CMOS technology. Measurement results showing its functionality are presented.
Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers

Type-2 fuzzy sets, which are characterized by membership functions (MFs) that are themselves fuzzy, have been attracting interest. This paper focuses on advancing the understanding of interval type-2 fuzzy logic controllers (FLCs). First, a type-2 FLC is evolved using Genetic Algorithms (GAs). The type-2 FLC is then compared with another three GA evolved type-1 FLCs that have different design parameters. The objective is to examine the amount by which the extra degrees of freedom provided by antecedent type-2 fuzzy sets is able to improve the control performance. Experimental results show that better control can be achieved using a type-2 FLC with fewer fuzzy sets/rules so one benefit of type-2 FLC is a lower trade-off between modeling accuracy and interpretability.
Electrical characteristics of conductive yarns and textile electrodes for medical applications

Clothing with conductive textiles for health care applications has in the last decade been of an upcoming research interest. An advantage with the technique is its suitability in distributed and home health care. The present study investigates the electrical properties of conductive yarns and textile electrodes in contact with human skin, thus representing a real ECG-registration situation. The yarn measurements showed a pure resistive characteristic proportional to the length. The electrodes made of pure stainless steel (electrode A) and 20% stainless steel/80% polyester (electrode B) showed acceptable stability of electrode potentials, the stability of A was better than that of B. The electrode made of silver plated copper (electrode C) was less stable. The electrode impedance was lower for electrodes A and B than that for electrode C. From an electrical properties point of view we recommend to use electrodes of type A to be used in intelligent textile medical applications.
Fingerprint Recognition with Monitoring on Remote Whats App

-Finger print recognition is more popular attending system mostly used in many offices as it provides more accuracy. Machinery also system software based finger print recognition systems are mostly used. But its real time monitoring and remote intimation is not performed until now if wrong person is entering. Instant reporting to officer is necessary for maintaining absence/presence of staff members. This automatic reporting is necessary as officer may be remotely available. So, fingerprint identification based attendance system is proposed with real time remote monitoring. Proposed system requires Finger print sensor, data acquisition system for it, Processor (ARM 11), Ethernet/Wi-Fi Interface for Internet access and Smart phone for monitoring. WhatsApp is generally used by most of peoples and is easily accessible to all so generally preferred in this work. ARM 11 is necessary as it requires the Internet connection for What’ s App data transfer.
A renaissance in RNA synthetic biology: new mechanisms, applications and tools for the future.

Since our ability to engineer biological systems is directly related to our ability to control gene expression, a central focus of synthetic biology has been to develop programmable genetic regulatory systems. Researchers are increasingly turning to RNA regulators for this task because of their versatility, and the emergence of new powerful RNA design principles. Here we review advances that are transforming the way we use RNAs to engineer biological systems. First, we examine new designable RNA mechanisms that are enabling large libraries of regulators with protein-like dynamic ranges. Next, we review emerging applications, from RNA genetic circuits to molecular diagnostics. Finally, we describe new experimental and computational tools that promise to accelerate our understanding of RNA folding, function and design.
Review on Electric Vehicle , Battery Charger , Charging Station and Standards

Electric vehicles are a new and upcoming technology in the transportation and power sector that have many benefits in terms of economic and environmental. This study presents a comprehensive review and evaluation of various types of electric vehicles and its associated equipment in particular battery charger and charging station. A comparison is made on the commercial and prototype electric vehicles in terms of electric range, battery size, charger power and charging time. The various types of charging stations and standards used for charging electric vehicles have been outlined and the impact of electric vehicle charging on utility distribution system is also discussed.
Nutrition for swimming.

Swimming is a sport that requires considerable training commitment to reach individual performance goals. Nutrition requirements are specific to the macrocycle, microcycle, and individual session. Swimmers should ensure suitable energy availability to support training while maintaining long term health. Carbohydrate intake, both over the day and in relation to a workout, should be manipulated (3-10 g/kg of body mass/day) according to the fuel demands of training and the varying importance of undertaking these sessions with high carbohydrate availability. Swimmers should aim to consume 0.3 g of high-biological-value protein per kilogram of body mass immediately after key sessions and at regular intervals throughout the day to promote tissue adaptation. A mixed diet consisting of a variety of nutrient-dense food choices should be sufficient to meet the micronutrient requirements of most swimmers. Specific dietary supplements may prove beneficial to swimmers in unique situations, but should be tried only with the support of trained professionals. All swimmers, particularly adolescent and youth swimmers, are encouraged to focus on a well-planned diet to maximize training performance, which ensures sufficient energy availability especially during periods of growth and development. Swimmers are encouraged to avoid rapid weight fluctuations; rather, optimal body composition should be achieved over longer periods by modest dietary modifications that improve their food choices. During periods of reduced energy expenditure (taper, injury, off season) swimmers are encouraged to match energy intake to requirement. Swimmers undertaking demanding competition programs should ensure suitable recovery practices are used to maintain adequate glycogen stores over the entirety of the competition period.
A molecular approach to Cu doped ZnO nanorods with tunable dopant content.

A novel molecular approach to the synthesis of polycrystalline Cu-doped ZnO rod-like nanostructures with variable concentrations of introduced copper ions in ZnO host matrix is presented. Spectroscopic (PLS, variable temperature XRD, XPS, ELNES, HERFD) and microscopic (HRTEM) analysis methods reveal the +II oxidation state of the lattice incorporated Cu ions. Photoluminescence spectra show a systematic narrowing (tuning) of the band gap depending on the amount of Cu(II) doping. The advantage of the template assembly of doped ZnO nanorods is that it offers general access to doped oxide structures under moderate thermal conditions. The doping content of the host structure can be individually tuned by the stoichiometric ratio of the molecular precursor complex of the host metal oxide and the molecular precursor complex of the dopant, Di-aquo-bis[2-(methoxyimino)-propanoato]zinc(II) 1 and -copper(II) 2. Moreover, these keto-dioximato complexes are accessible for a number of transition metal and lanthanide elements, thus allowing this synthetic approach to be expanded into a variety of doped 1D metal oxide structures.