nils-herrmann/clean_scirepeval huggingface dataset:
Supernumerary nostril with congenital cataract.

Supernumerary nostril is a very rare congenital anomaly. It can be unilateral or bilateral, and it sometimes occurs in the presence of other congenital deformities. Behind the external opening of a supernumerary nostril is a small accessory nasal cavity, which may or may not communicate with the normal nasal cavity on the same side. We describe a new case in which the supernumerary nostril with a small accessory nasal cavity, which did not communicate with the normal nasal cavity on the same side, appeared in a young girl who also had microcornea and congenital cataract. The accessory nasal cavity was successfully removed surgically. We believe that this case may represent the first reported case of a supernumerary nostril with a congenital cataract on the same side. We also discuss the hypotheses that have been proposed to explain supernumerary nostrils.
Socializing by Gaming: Revealing Social Relationships in Multiplayer Online Games

Multiplayer Online Games (MOGs) like Defense of the Ancients and StarCraft II have attracted hundreds of millions of users who communicate, interact, and socialize with each other through gaming. In MOGs, rich social relationships emerge and can be used to improve gaming services such as match recommendation and game population retention, which are important for the user experience and the commercial value of the companies who run these MOGs. In this work, we focus on understanding social relationships in MOGs. We propose a graph model that is able to capture social relationships of a variety of types and strengths. We apply our model to real-world data collected from three MOGs that contain in total over ten years of behavioral history for millions of players and matches. We compare social relationships in MOGs across different game genres and with regular online social networks like Facebook. Taking match recommendation as an example application of our model, we propose SAMRA, a Socially Aware Match Recommendation Algorithm that takes social relationships into account. We show that our model not only improves the precision of traditional link prediction approaches, but also potentially helps players enjoy games to a higher extent.
Wide-band CMOS low-noise amplifier exploiting thermal noise canceling

Known elementary wide-band amplifiers suffer from a fundamental tradeoff between noise figure (NF) and source impedance matching, which limits the NF to values typically above 3 dB. Global negative feedback can be used to break this tradeoff, however, at the price of potential instability. In contrast, this paper presents a feedforward noise-canceling technique, which allows for simultaneous noise and impedance matching, while canceling the noise and distortion contributions of the matching device. This allows for designing wide-band impedance-matching amplifiers with NF well below 3 dB, without suffering from instability issues. An amplifier realized in 0.25-/spl mu/m standard CMOS shows NF values below 2.4 dB over more than one decade of bandwidth (i.e., 150-2000 MHz) and below 2 dB over more than two octaves (i.e., 250-1100 MHz). Furthermore, the total voltage gain is 13.7 dB, the -3-dB bandwidth is from 2 MHz to 1.6 GHz, the IIP2 is +12 dBm, and the IIP3 is 0 dBm. The LNA drains 14 mA from a 2.5-V supply and the die area is 0.3/spl times/0.25 mm/sup 2/.
Incremental tessellation of trimmed parametric surfaces

This paper presents an incremental approach for tessellating trimmed parametric surfaces. A database is built to keep the tessellation of a CAD model. With the topological information provided, the database is efficiently updated when the model is modified. This enhances the tessellation process as only a slight change of the existing tessellation is required. The tessellation which involves the insertion and removal of trimlines is performed completely in the parametric space. The topological information also facilitates the triangles classification and the merging of boundaries between surfaces. The algorithm is particularly suitable for the generation of a valid triangulation of a complex CAD model for many downstream applications, e.g. in rapid prototyping (RP). q 2000 Elsevier Science Ltd. All rights reserved.
Communicating neuronal ensembles between neuromorphic chips

I describe an interchip communication system that reads out pulse trains from a 64 64 array of neurons on one chip, and transmits them to corresponding locations in a 64 64 array of neurons on a second chip. It uses a random-access, time-multiplexed, asynchronous digital bus to transmit log2N -bit addresses that uniquely identify each of theN neurons in the sending population. A peak transmission rate of 2.5MSpikes/s is achieved by pipelining the operation of the channel. I discuss how the communication channel design is optimized for sporadic stimulus-triggered activity which causes some small subpopulation to re in synchrony, by adopting an arbitered, event-driven architecture. I derive the bandwidth required to transmit this neuronal ensemble, without temporal dispersion, in terms of the number of neurons, the probability that a neuron is part of the ensemble, and the degree of synchrony.
Making digital characters: creation, deformation, and animation

Digital characters have been taken an very important role for filmmaking and video games over the last decade. Now we are at the border that the difference between digital characters and real ones are vanishing. In this course we will introduce the fundamental knowledge of how to create digital characters. A state-of-the-art workflow consists of three stages: creating of the facial and body puppet, applying the right deformation techniques to the puppet, and driving the puppet with keyframe animation or motion capture data through retargeting. Our goal is to present the best practice guide in terms of making digital humans for visual production.
 We start with an general overview of the process on how to make digital characters. It then focuses on the details about production of facial and body puppets through 3D acquisition of geometry and texture, template registration techniques that are based on generic deformation or morphable models, using deformation transfer to automatically create believable poses, and how to use motion capture data to enhance the current poses. The second part of the course will introduce various important deformation techniques such as skinning, pose space deformation, and how to do volumetric deformation based on real body medical imaging data. Finally several animation techniques will be presented to show how to make puppets perform.
Relationship between color and emotion : a study of college students

Ninety-eight college students were asked to indicate their emotional responses to five principle hues (i.e., red, yellow, green, blue, purple), five intermediate hues (i.e., yellow-red, greenyellow, blue-green, purple-blue, and red-purple), and three achromatic colors (white, gray, and black) and the reasons for their choices. The color stimuli were referenced from the Munsell Color System. The results revealed that the principle hues comprised the highest number of positive emotional responses, followed by the intermediate hues and the achromatic colors. The color green evoked mainly positive emotions such as relaxation and comfort because it reminded most of the respondents of nature. The color green-yellow had the lowest number of positive responses because it was associated with vomit and elicited the feelings of sickness and disgust. For the achromatic colors, white attained a large number of positive responses, followed by the colors black and gray. The reasons for the color-emotion associations are discussed and future research areas are suggested.
Stacked Patch Antenna With Dual-Polarization and Low Mutual Coupling for Massive MIMO

Massive multiple input and multiple output (MIMO) has attracted significant interests in both academia and industry. It has been considered as one of most promising technologies for 5G wireless systems. The large-scale antenna array for base stations naturally becomes the key to deploy the Massive MIMO technologies. In this communication, we present a dual-polarized antenna array with 144 ports for Massive MIMO operating at 3.7 GHz. The proposed array consists of 18 low profile subarrays. Each subarray consists of four single units. Each single antenna unit consists of one vertically polarized port and one horizontally polarized port connected to power splitters, which serve as a feeding network. A stacked patch design is used to construct the single unit with the feeding network, which gives higher gain and lower mutual coupling within the size of a conversional dual-port patch antenna. Simulation results of the proposed single antenna unit, sub-array, and Massive MIMO array are verified by measurement.
SVM-Based Comments Classification and Mining of Virtual Community : For Case of Sentiment Classification of Hotel Reviews

Comments of virtual communities are very import to the operation and development of an enterprise, through analysis the sentiment of the comments, we can mine the user's semantic orientation and preferences or hates, it is very helpful for enterprises to improve their products and services and for individuals to use these information rationally. This paper takes hotel review of the virtual community for example, to use key technologies of support vector machine (SVM) and sentiment classification to build a small domain sentiment corpus, and to propose a sentiment classification model based on the corpus to reach the purpose of feature dimension reduction. We choose a hotel reviews corpus as instance to validate the method we proposed in this paper, the results of the experiment shows that the accuracy of support vector machine algorithm has been enhanced by adding a user’s sentiment corpus. This method can be fatherly extended to apply to other comments of the virtual communities.
Optimal Tuning of PID controller by Cuckoo Search via Lévy flights

Nature has been a main source of inspiration for many optimization algorithms. Such algorithms are increasingly becoming popular among control engineers for the optimal tuning of PID controller. In this paper, a very recent nature inspired metaheuristic technique known as Cuckoo Search Algorithm is presented for the optimal tuning of PID controller. This controller is required to achieve the desired specification of the closed loop response of the DC motor plant, that here is taken as a third order plant system. Though several conventional techniques have been proposed to sufficiently optimize linear plant systems but the desired performance indices i.e. settling time, overshoot, rise time etc. are comparatively higher than the response attained by heuristic algorithms. Here, a study is done on PID controller optimized by Cuckoo Search Algorithm for different fitness functions i.e. IAE, ISE, ITAE and ITSE and their responses are compared with one such conventional method.
Comparison study of non-orthogonal multiple access schemes for 5G

With the development of mobile Internet and Internet of things (IoT), the 5th generation (5G) wireless communications will foresee explosive increase in mobile traffic. To address challenges in 5G such as higher spectral efficiency, massive connectivity, and lower latency, some non-orthogonal multiple access (NOMA) schemes have been recently actively investigated, including power-domain NOMA, multiple access with low-density spreading (LDS), sparse code multiple access (SCMA), multiuser shared access (MUSA), pattern division multiple access (PDMA), etc. Different from conventional orthogonal multiple access (OMA) schemes, NOMA can realize overloading by introducing some controllable interferences at the cost of slightly increased receiver complexity, which can achieve significant gains in spectral efficiency and accommodate much more users. In this paper, we will discuss basic principles and key features of three typical NOMA schemes, i.e., SCMA, MUSA, and PDMA. What's more, their performance in terms of uplink bit error rate (BER) will be compared. Simulation results show that in typical Rayleigh fading channels, SCMA has the best performance, while the BER performance of MUSA and PDMA are very close to each other. In addition, we also analyze the performance of PDMA using the same factor graph as SCMA, which indicates that the performance gain of SCMA over PDMA comes from both the difference of factor graph and the codebook optimization.
A Compact S-Box Design for SMS4 Block Cipher

This paper proposes a compact design of SMS4 S-box using combinational logic which is suitable for the implementation in area constraint environments like smart cards. The inversion algorithm of the proposed S-box is based on composite field GF(((2))) using normal basis at all levels. In our approach, we examined all possible normal basis combinations having trace equal to one at each subfield level. There are 16 such possible combinations with normal basis and we have compared the S-box designs based on each case in terms of logic gates it uses for implementation. The isomorphism mapping and inverse mapping bit matrices are fully optimized using greedy algorithm. We prove that our best case reduces the complexity upon the SMS4 S-box design with existing inversion algorithm based on polynomial basis by 15% XOR and 42% AND gates.
MarrNet: 3D Shape Reconstruction via 2.5D Sketches

3D object reconstruction from a single image is a highly under-determined problem, requiring strong prior knowledge of plausible 3D shapes. This introduces challenges for learning-based approaches, as 3D object annotations are scarce in real images. Previous work chose to train on synthetic data with ground truth 3D information, but suffered from domain adaptation when tested on real data. In this work, we propose MarrNet, an end-to-end trainable model that sequentially estimates 2.5D sketches and 3D object shape. Our disentangled, two-step formulation has three advantages. First, compared to full 3D shape, 2.5D sketches are much easier to be recovered from a 2D image; models that recover 2.5D sketches are also more likely to transfer from synthetic to real data. Second, for 3D reconstruction from 2.5D sketches, systems can learn purely from synthetic data. This is because we can easily render realistic 2.5D sketches without modeling object appearance variations in real images, including lighting, texture, etc. This further relieves the domain adaptation problem. Third, we derive differentiable projective functions from 3D shape to 2.5D sketches; the framework is therefore end-to-end trainable on real images, requiring no human annotations. Our model achieves state-of-the-art performance on 3D shape reconstruction.
The burden of allergic contact dermatitis caused by acrylates.

Acrylates and methacrylates are esters of acrylic acid and methacrylic acid, respectively, that polymerize either spontaneously or on ultraviolet (UV) light exposure to form products that are commonly used in adhesives in healthcare settings, and in plastics and textiles (1). They were commonly considered to be occupational contact allergens, particularly in dentists and orthopaedic surgeons, owing to the use of (meth)acrylates in dental materials and bone cement (2). However, more recently, the demand for long-lasting cosmetic nails has led to the widespread use of gel nails and acrylic nails. Gel nails are methacrylate-based gel varnishes that rely on UV curing to form a hard nail-coating colour that lasts for up to 2 weeks. This has led to an occupational shift in (metha)crylate allergy, with a rise in incidence among beauticians and nail technicians using these products (1, 3–5). In addition, with home use UV-curing kits now readily available, there is a further shift of contact allergy to consumers. Our aim was to characterize the cases of allergic contact dermatitis caused by meth(acrylates) and cyanoacrylates in our large regional patch testing centre. Because of its significant occupational and health-related sequelae, we highlight the current burden of the serious allergy to these compounds.
Robotic Single-Site Surgery for Female-to-Male Transsexuals: Preliminary Experience

Hysterectomy with bilateral salpingo-oophorectomy is a part of gender reassignment surgery for the treatment of female-to-male transsexualism. Over the last years many efforts were made in order to reduce invasiveness of laparoscopic and robotic surgery such as the introduction of single-site approach. We report our preliminary experience on single-site robotic hysterectomy for cross-sex reassignment surgery. Our data suggest that single-site robotic hysterectomy is feasible and safe in female-to-male transsexualism with some benefits in terms of postoperative pain and aesthetic results.
Artificial Intelligence Approaches To UCAV Autonomy

This paper covers a number of approaches that leverage Artificial Intelligence algorithms and techniques to aid Unmanned Combat Aerial Vehicle (UCAV) autonomy. An analysis of current approaches to autonomous control is provided followed by an exploration of how these techniques can be extended and enriched with AI techniques including Artificial Neural Networks (ANN), Ensembling and Reinforcement Learning (RL) to evolve control strategies for UCAVs.
ControlChain: Blockchain as a Central Enabler for Access Control Authorizations in the IoT

The IoT is pervading our daily activities and lives with devices scattered all over our cities, transport systems, buildings, homes and bodies. This invasion of devices with sensors and communication capabilities brings big concerns, mainly about the privacy and confidentiality of the collected information. These concerns hinder the wide adoption of the IoT. To overcome them, in this work, we present an Blockchain-based architecture for IoT access authorizations. Following the IoT tendency requirements, our architecture is user transparent, user friendly, fully decentralized, scalable, fault tolerant and compatible with a wide range of today's access control models used in the IoT. Finally, our architecture also has a secure way to establish relationships between users, devices and group of both, allowing the assignment of attributes for these relationships and their use in the access control authorization.
Automatic detection of motion artifacts in MR images using CNNS

Considerable practical interest exists in being able to automatically determine whether a recorded magnetic resonance image is affected by motion artifacts caused by patient movements during scanning. Existing approaches usually rely on the use of navigators or external sensors to detect and track patient motion during image acquisition. In this work, we present an algorithm based on convolutional neural networks that enables fully automated detection of motion artifacts in MR scans without special hardware requirements. The approach is data driven and uses the magnitude of MR images in the spatial domain as input. We evaluate the performance of our algorithm on both synthetic and real data and observe adequate performance in terms of accuracy and generalization to different types of data. Our proposed approach could potentially be used in clinical practice to tag an MR image as motion-free or motion-corrupted immediately after a scan is finished. This process would facilitate the acquisition of high-quality MR images that are often indispensable for accurate medical diagnosis.
Flexible a-IGZO TFT amplifier fabricated on a free standing polyimide foil operating at 1.2 MHz while bent to a radius of 5 mm

We present flexible common source and cascode amplifiers fabricated on a free-standing plastic foil, using amorphous-Indium-Gallium-Zinc-Oxide (a-IGZO) TFTs with minimum channel lengths of 2.5 μm. Amplifiers are operated at a supply voltage VDD of 5 V, and exhibit maximum cutoff frequencies fC of 1.2 MHz. The circuits stay fully operational while bent to a tensile radius of 5 mm, and after 1000 cycles of repeated bending and re-flattening. To our knowledge, these are the fastest flexible oxide semiconductor based amplifiers.
High aspect-ratio 3D microstructures via near-field electrospinning for energy storage applications

High-aspect-ratio, three dimensional (3D) microstructures have been constructed by a direct-write method via self-aligned near-field electrospinning process. Using papers as the collectors, the process enables both design and fabrication of a variety of 3D structures, such as walls, grids and other configurations based on layer-by-layer deposition of electrospun micro/nano fibers. Afterwards, these fabricated polymeric structures can be mechanically separated from the paper substrate for various applications. In this work, we have successfully fabricated 20-layer, ca. 100 μm in thickness, 2 × 2 cm2 3D grid-structures made of PVDF (Polyvinylidene fluoride) electrospun fibers. After a coating process using the dip-and-dry process in the CNT (carbon nanotube) ink, conductive and flexible electrodes made of CNT coated polymer grid-structures have been demonstrated and assembled as a micro-supercapacitor.
Chapter 2 INTRUSION DETECTION : A SURVEY

This chapter provides the overview of the state of the art in intrusion detection research. Intrusion detection systems are software and/or hardware components that monitor computer systems and analyze events occurring in them for signs of intrusions. Due to widespread diversity and complexity of computer infrastructures, it is difficult to provide a completely secure computer system. Therefore, there are numerous security systems and intrusion detection systems that address different aspects of computer security. This chapter first provides taxonomy of computer intrusions, along with brief descriptions of major computer attack categories. Second, a common architecture of intrusion detection systems and their basic characteristics are presented. Third, taxonomy of intrusion detection systems based on five criteria (information source, analysis strategy, time aspects, architecture, response) is given. Finally, intrusion detection systems are classified according to each of these categories and the most representative research prototypes are briefly described.
Human-comfortable navigation for an autonomous robotic wheelchair

Reliable autonomous navigation is an active research topic that has drawn the attention for decades, however, human factors such as navigational comfort has not received the same level of attention. This work proposes the concept of “comfortable map” and presents a navigation approach for autonomous passenger vehicles which in top of being safe and reliable is comfortable. In our approach we first extract information from users preference related to comfort while sitting on a robotic wheelchair under different conditions in an indoor corridor environment. Human-comfort factors are integrated to a geometric map generated by SLAM framework. Then a global planner computes a safe and comfortable path which is followed by the robotic wheelchair. Finally, an evaluation with 29 participants using a fully autonomous robotic wheelchair, showed that more than 90% of them found the proposed approach more comfortable than a shortest-path state of the art approach.