nils-herrmann/clean_scirepeval huggingface dataset:
Deep Learning in Medical Image Analysis.

This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.
Flexible design of a wearable lower limb exoskeleton robot

Wearable exoskeleton robot is a kind of humanoid service robot to help the elderly and the patients with walking dysfunction, it is also an effective medical rehabilitation method to help patients who have walking disorders due to central neural system damage. This paper focuses on the flexible mechanism design of wearable lower limb exoskeleton robot. A wearable exoskeleton robot prototype was developed which can assist human walking. This paper analyzes the role of the major joints of walking human by experimental studies based on bionic design methods from human anatomy and bone surgery. We first analyze parameters of joint movements in a gait cycle, then we design a preliminary bionic model, finally we proposed a control strategy including a pair of electric crutches for the exoskeleton robot.
Subjective Reality and Strong Artificial Intelligence

The main prospective aim of modern research related to Artificial Intelligence is the creation of technical systems that implement the idea of Strong Intelligence. According our point of view the path to the development of such systems comes through the research in the field related to perceptions. Here we formulate the model of the perception of external world which may be used for the description of perceptual activity of intelligent beings. We consider a number of issues related to the development of the set of patterns which will be used by the intelligent system when interacting with environment. The key idea of the presented perception model is the idea of subjective reality. The principle of the relativity of perceived world is formulated. It is shown that this principle is the immediate consequence of the idea of subjective reality. In this paper we show how the methodology of subjective reality may be used for the creation of different types of Strong AI systems.
A Network Model for Reddit Post Virality Prediction

In social networks, user connectivity plays an important role in the virality of content. Existing research has delved into predicting content virality within relationship-based networks such as Facebook. In this work, we explore virality prediction on Reddit, a content-driven network lacking a naturally-defined relationship between users, and whether properties of this user-network aid in predicting virality. We analyze the effects of network features on predictive ability of Reddit post score, a measure of how viral a posted piece of content on Reddit became. We first build a baseline model for virality prediction that accounts for temporal features (e.g. time of day/week content was posted), history of the content poster features, and linguistic features (of the title and any textual content). Then, we examine the impact of adding structural features of the Reddit user-user network on predictive ability. Results from our analysis suggests that features from a user interaction network of Reddit does not increase predictive power for how viral a post will become.
A Wearable Computing Prototype for supporting training activities in Automotive Production

This paper presents the results of the wearable computing prototype supporting trainingand qualification activities at the SKODA production facilities in Czech Republic. The emerged prototype is based upon the first of the 2 main “Variant Production Showcases” (training and assembly-line) which are to be implemented in the WearIT@work project (EC IP 004216). As an introduction, the authors of this paper investigate current training processes at Skoda, and derive the potential benefits and risks of applying wearable computing technology. Accordingly, the approach of creating the wearable prototypes, via usability experiments at the Skoda production site, is explained in detail. As a preliminary result, the first functional prototypes, including a task recognition prototype, based upon the components of the European Wearable Computing Platform, are described. The paper is rounded up by providing a short outlook regarding the second envisaged test case, which is focussed upon selected assembly line operations of blue collar workers.
The Effects of Profile Pictures and Friends' Comments on Social Network Site Users' Body Image and Adherence to the Norm

This study sought to explore the effects of exposure to Facebook body ideal profile pictures and norm conforming comments on users' body image. In addition, the social identity and self-categorization theoretical frameworks were used to explore users' endorsement of a body ideal norm. A mock Facebook page was used to conduct a pretest posttest 2 × 2 between-group web-based experiment that featured body ideal profile pictures (body ideal vs. no body) and body ideal comments (conforming vs. nonconforming). Five hundred and one participants completed the experiment and passed all manipulation checks. Participants viewed pictures and comments on the status page and were able to leave their own comment before exiting. Results demonstrated no significant main effects. However, predispositional body satisfaction significantly moderated the relationship between body ideal pictures and body satisfaction. Most comments supported the body ideal norm. However, in support of self-categorization theory, participants exposed to nonconforming comments made nonconforming comments themselves significantly more than those exposed to conforming comments. The findings demonstrated the importance of continued body image research in social network sites, as well as the potential for self-categorization theory to guide such research.
Performance comparison of adder architectures on 28nm FPGA

Adders are one of the most desirable entities in processor data path architecture. Since long, VLSI engineers are working towards optimization and miniaturization of adder architectures to ultimately improve the performance of processors. As the technology is scaling down, challenges towards optimization are also increasing. In this paper we present the implementation of various 16 bit adder architectures including parallel prefix adders and their comparative analysis based on ultimate performance parameters-area and power at 28nm technology. All designs have been synthesized and implemented on Xilinx Zynq-7000 FPGA board using Xilinx Vivado 14.4 design tool. Verilog HDL is used as programming HDL. Weinberger adder provides the best area solution.
Design and control of warehouse order picking: A literature review

Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the orderpicking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.
Encoded evidence: DNA in forensic analysis

Sherlock Holmes said “it has long been an axiom of mine that the little things are infinitely the most important”, but never imagined that such a little thing, the DNA molecule, could become perhaps the most powerful single tool in the multifaceted fight against crime. Twenty years after the development of DNA fingerprinting, forensic DNA analysis is key to the conviction or exoneration of suspects and the identification of victims of crimes, accidents and disasters, driving the development of innovative methods in molecular genetics, statistics and the use of massive intelligence databases.
Introduction to Space-Time Wireless Communications

published by the press syndicate of the university of cambridge A catalog record for this book is available from the British Library ISBN 0 521 82615 2 hardback Contents List of figures page xiv List of tables xxii Preface xxiii List of abbreviations xxvi List of symbols xxix vii viii Contents 2.6 Polarization and field diverse channels 27 2.7 Antenna array topology 28 2.8 Degenerate channels 29 2.9 Reciprocity and its implications 31 3 ST channel and signal models
On continuous deployment maturity in customer projects

The practice of making new software available to end users as soon as it gets implemented is becoming commonplace. This paper investigates a set of projects and their development practices in a mid-sized Finnish software company Solita Ltd. to understand how continuous deployment practices are applied in development teams. This was done by establishing a maturity scale and using it to survey the teams. In addition, we interviewed members of selected teams to understand why a particular level of maturity is desirable for a project, and to reveal the issues that impact team's ability to improve. We found that while the team, the customer, and the product all benefit from mature development practices associated with continuous deployment, some obstacles can be solved only by changing the organizational modus operandi.
Secret-Focus: A Practical Physical Layer Secret Communication System by Perturbing Focused Phases in Distributed Beamforming

Ensuring confidentiality of communication is fundamental to securing the operation of a wireless system, where eavesdropping is easily facilitated by the broadcast nature of the wireless medium. By applying distributed beamforming among a coalition, we show that a new approach for assuring physical layer secrecy, without requiring any knowledge about the eavesdropper or injecting any additional cover noise, is possible if the transmitters frequently perturb their phases around the proper alignment phase while transmitting messages. This approach is readily applied to amplitude-based modulation schemes, such as PAM or QAM. We present our secrecy mechanisms, prove several important secrecy properties, and develop a practical secret communication system design. We further implement and deploy a prototype that consists of 16 distributed transmitters using USRP N210s in a 20×20×3m3 area. By sending more than 160M bits over our system to the receiver, depending on system parameter settings, we measure that the eavesdroppers failed to decode 30%–60% of the bits cross multiple locations while the intended receiver has an estimated bit error ratio of 3×10−6.
Controlling Formations of Multiple Mobile Robots

In this paper we investigate feedback laws used to control multiple robots moving together in a formation. We propose a method for controlling formations that uses only local sensor-based information, in a leader-follower motion. We use methods of feedback linearization to exponentially stabilize the relative distance and orientation of the follower, and show that the zero dynamics of the system are also (asymptoti-cally) stable. We demonstrate in simulation the use of these algorithms to control six robots moving around an obstacle. These types of control laws can be used to control arbitrarily large numbers of robots moving in very general types of formations.
Adhesive restorations, centric relation, and the Dahl principle: minimally invasive approaches to localized anterior tooth erosion.

The purpose of this article is to review biomechanical and occlusal principles that could help optimize the conservative treatment of severely eroded and worn anterior dentition using adhesive restorations. It appears that enamel and dentin bonding, through the combined use of resin composites (on the palatal surface) and indirect porcelain veneers (on the facial/incisal surfaces) can lead to an optimal result from both esthetic and functional/biomechanical aspects. Cases of deep bite combined with palatal erosion and wear can be particularly challenging. A simplified approach is proposed through the use of an occlusal therapy combining centric relation and the Dahl principle to create anterior interocclusal space to reduce the need for more invasive palatal reduction. This approach allows the ultraconservative treatment of localized anterior tooth erosion and wear.
Generalized neural-network representation of high-dimensional potential-energy surfaces.

The accurate description of chemical processes often requires the use of computationally demanding methods like density-functional theory (DFT), making long simulations of large systems unfeasible. In this Letter we introduce a new kind of neural-network representation of DFT potential-energy surfaces, which provides the energy and forces as a function of all atomic positions in systems of arbitrary size and is several orders of magnitude faster than DFT. The high accuracy of the method is demonstrated for bulk silicon and compared with empirical potentials and DFT. The method is general and can be applied to all types of periodic and nonperiodic systems.
Laryngeal Tumor Detection and Classification in Endoscopic Video

The development of the narrow-band imaging (NBI) has been increasing the interest of medical specialists in the study of laryngeal microvascular network to establish diagnosis without biopsy and pathological examination. A possible solution to this challenging problem is presented in this paper, which proposes an automatic method based on anisotropic filtering and matched filter to extract the lesion area and segment blood vessels. Lesion classification is then performed based on a statistical analysis of the blood vessels' characteristics, such as thickness, tortuosity, and density. Here, the presented algorithm is applied to 50 NBI endoscopic images of laryngeal diseases and the segmentation and classification accuracies are investigated. The experimental results show the proposed algorithm provides reliable results, reaching an overall classification accuracy rating of 84.3%. This is a highly motivating preliminary result that proves the feasibility of the new method and supports the investment in further research and development to translate this study into clinical practice. Furthermore, to our best knowledge, this is the first time image processing is used to automatically classify laryngeal tumors in endoscopic videos based on tumor vascularization characteristics. Therefore, the introduced system represents an innovation in biomedical and health informatics.
A 10-Bit Column-Driver IC With Parasitic-Insensitive Iterative Charge-Sharing Based Capacitor-String Interpolation for Mobile Active-Matrix LCDs

This paper presents a 10-bit column driver IC for active-matrix LCDs, with a proposed iterative charge-sharing based (ICSB) capacitor-string that interpolates two output voltages from a resistor-string DAC. Iterative mode change between a capacitive voltage division mode and a charge sharing mode in the ICSB capacitor-string interpolation suppresses the effect of mismatches between capacitors and that of parasitic capacitances; thus, a highly linear capacitor sub-DAC is realized. In addition, the area-sharing layout technique, which stacks the interpolation capacitor-string on top of the R-DAC area, reduces the driver channel size and extends the bit resolution of the gamma-corrected nonlinear main R-DAC. Consequently, the proposed ICSB capacitor-string interpolation scheme provides highly uniform channel performance by passively dividing the coarse voltages from the global resistor-string DAC with high area efficiency, and more effective bit resolution for nonlinear gamma correction. The prototype column driver IC was implemented using a 0.11-μm CMOS process. The area occupation of the DAC and buffer amplifier per channel is only 188 × 15 μm2, and the static power consumption is 0.9 μA/channel with no additional static power dissipation for the interpolation. The measured maximum DNL and INL are 0.25 LSB and 0.43 LSB, respectively. The measured maximum inter-channel DVO is 5.6 mV. The proposed chip achieves state-of-the-art performance in terms of chip size and channel-to-channel uniformity.
Research and implementation of RSA algorithm for encryption and decryption

Cryptographic technique is one of the principal means to protect information security. Not only has it to ensure the information confidential, but also provides digital signature, authentication, secret sub-storage, system security and other functions. Therefore, the encryption and decryption solution can ensure the confidentiality of the information, as well as the integrity of information and certainty, to prevent information from tampering, forgery and counterfeiting. Encryption and decryption algorithm's security depends on the algorithm while the internal structure of the rigor of mathematics, it also depends on the key confidentiality. Key in the encryption algorithm has a pivotal position, once the key was leaked, it means that anyone can be in the encryption system to encrypt and decrypt information, it means the encryption algorithm is useless. Therefore, what kind of data you choose to be a key, how to distribute the private key, and how to save both data transmission keys are very important issues in the encryption and decryption algorithm. This paper proposed an implementation of a complete and practical RSA encrypt/decrypt solution based on the study of RSA public key algorithm. In addition, the encrypt procedure and code implementation is provided in details.
Continuous word embeddings for detecting local text reuses at the semantic level

Text reuse is a common phenomenon in a variety of user-generated content. Along with the quick expansion of social media, reuses of local text are occurring much more frequently than ever before. The task of detecting these local reuses serves as an essential step for many applications. It has attracted extensive attention in recent years. However, semantic level similarities have not received consideration in most previous works. In this paper, we introduce a novel method to efficiently detect local reuses at the semantic level for large scale problems. We propose to use continuous vector representations of words to capture the semantic level similarities between short text segments. In order to handle tens of billions of documents, methods based on information geometry and hashing methods are introduced to aggregate and map text segments presented by word embeddings to binary hash codes. Experimental results demonstrate that the proposed methods achieve significantly better performance than state-of-the-art approaches in all six document collections belonging to four different categories. At some recall levels, the precisions of the proposed method are even 10 times higher than previous methods. Moreover, the efficiency of the proposed method is comparable to or better than that of some other hashing methods.
Impact of Mg out-diffusion and activation on the p-GaN gate HEMT device performance

The p-GaN gate HEMT device architecture is a prime contender for normally-off GaN power transistors. In this work the growth parameters of the Mg doped p-type GaN layer are varied and the impact of Mg out-diffusion and Mg activation on the main HEMT device parameters is studied. The Mg chemical concentration is optimized together with the Mg active concentration to obtain improved device performance. Enhancement mode 36 mm p-GaN gate power transistors have been realized, featuring a threshold voltage of 2.1 V and a Ron of 150 ma.
Prevalence of Vitamin D Insufficiency in an Adult Normal Population

The vitamin D status of a general adult urban population was estimated between November and April in 1569 subjects selected from 20 French cities grouped in nine geographical regions (between latitude 43° and 51° N). Major differences in 25-hydroxyvitamin D (25(OH)D) concentration were found between regions, the lowest values being seen in the North and the greatest in the South, with a significant ‘sun’ effect (r = 0.72; p = 0.03) and latitude effect (r = -0.79; p = 0.01). In this healthy adult population, 14% of subjects exhibited 25(OH)D values ≤ 30 nmol/l (12 ng/ml), which represents the lower limit (< 2 SD) for a normal adult population measured in winter with the same method (RIA Incstar). A significant negative correlation was found between serum intact parathyroid hormone (iPTH) and serum 25(OH)D values (p < 0.01). Serum iPTH held a stable plateau level at 36 pg/ml as long as serum 25(OH)D values were higher than 78 nmol/l (31 ng/ml), but increased when the serum 25(OH)D value fell below this. When the 25(OH)D concentration became equal to or lower than 11.3 nmol/l (4.6 ng/ml), the PTH values reached the upper limit of normal values (55 pg/ml) found in vitamin D replete subjects. These results showed that in French normal adults living in an urban environment with a lack of direct exposure to sunshine, diet failed to provide an adequate amount of vitamin D. It is important to pay attention to this rather high prevalence of vitamin D insufficiency in the general adult population and to discuss the clinical utility of winter supplementation with low doses of vitamin D.
Semantic Interoperability via Category Theory

This paper aims to bring the benefits of the use of Category Theory to the field of Semantic Web, where the coexistence of intrinsically different models of local knowledge makes difficult the exchanging of information. The paper uses categorical limit and colimit to define operations of breaking and composing ontologies, formalizing usual concepts in ontologies (alignment, merge, integration, matching) and proposing a new operation (the hide operation). The presented set of operations form a useful framework that makes easier the manipulation and reuse of ontologies.
Fuzzy sets, advanced fuzzy sets and hybrids

Fuzzy Sets were proposed several years ago with various extensions in later years. Each extension has advantages over the fuzzy sets. Rough sets are used to handle incomplete information. Interval-valued fuzzy sets deal with uncertainty and vagueness. Intuitionistic fuzzy sets contain a sub-interval hesitation degree that lies between membership and non-membership degrees. Soft sets overcome the problem of insufficiency of parameterization. Advanced fuzzy sets have myriad number of advantages due to their applications in realistic examples. This paper briefly explains the abstract of fuzzy sets, advanced fuzzy sets and their hybrids. Advanced fuzzy sets include rough sets, intuitionistic fuzzy sets, interval-valued fuzzy sets and soft sets.