nils-herrmann/clean_scirepeval huggingface dataset:
A novel broadband AMC surface for lowering the height of planar antennas

A novel broadband artificial magnetic conductor (AMC) surface is proposed for lowering the height of planar antennas. By replacing the conventional perfect electric conductor (PEC) ground plane with the AMC surface, the height of planar antenna can be significantly reduced. Three planar antennas for LTE700/GSM900 base stations are investigated. The antenna height is lowered from 0.263λ0.83GHz to 0.083λ0.83GHz, (where λ0.83GHz is the wavelength in free space at the frequency 0.83 GHz). The height-lowered planar antennas maintain a wide bandwidth of, e.g., 38% for a linearly polarized antenna, 35% for a dual-polarized antenna, and 46% for a circularly polarized antenna. All these planar antennas above the AMC surface have a gain of higher than 7 dBi.
Reflections on SOA and Microservices

Today's Enterprises are facing many challenges in the service oriented, customer experience centric and customer demand driven global environment where ICT is becoming the leading enabler and partner of the modern enterprise. In the last decade, many enterprises have invested heavily in SOA-aligned IT transformations, but not harvested what SOA promised to provide. Now the API and Microservice paradigm has emerged as the "next big thing" for delivering IT outcomes to support the modern enterprise, with many technology vendors and service jumping on the bandwagon. This paper undertakes a critical investigation of the key concepts around SOA, API and Microservices, identifying similarities and differences between them and dispelling the confusion and hype around them. Based on our discussion and analysis, this paper presents a set of recommendations and best practices on the effective use and management of enterprise software components, drawing upon the best of SOA, API and Microservice concepts and practice.
Lightweight Hardware Architectures for the Present Cipher in FPGA

In recent years, the study of lightweight symmetric ciphers has gained interest due to the increasing demand for security services in constrained computing environments, such as in the Internet of Things. However, when there are several algorithms to choose from and different implementation criteria and conditions, it becomes hard to select the most adequate security primitive for a specific application. This paper discusses the hardware implementations of Present, a standardized lightweight cipher called to overcome part of the security issues in extremely constrained environments. The most representative realizations of this cipher are reviewed and two novel designs are presented. Using the same implementation conditions, the two new proposals and three state-of-the-art designs are evaluated and compared, using area, performance, energy, and efficiency as metrics. From this wide experimental evaluation, to the best of our knowledge, new records are obtained in terms of implementation size and energy consumption. In particular, our designs result to be adequate in regards to energy-per-bit and throughput-per-slice.
Supervised autonomous robotic soft tissue surgery

The current paradigm of robot-assisted surgeries (RASs) depends entirely on an individual surgeon’s manual capability. Autonomous robotic surgery—removing the surgeon’s hands—promises enhanced efficacy, safety, and improved access to optimized surgical techniques. Surgeries involving soft tissue have not been performed autonomously because of technological limitations, including lack of vision systems that can distinguish and track the target tissues in dynamic surgical environments and lack of intelligent algorithms that can execute complex surgical tasks. We demonstrate in vivo supervised autonomous soft tissue surgery in an open surgical setting, enabled by a plenoptic three-dimensional and near-infrared fluorescent (NIRF) imaging system and an autonomous suturing algorithm. Inspired by the best human surgical practices, a computer program generates a plan to complete complex surgical tasks on deformable soft tissue, such as suturing and intestinal anastomosis. We compared metrics of anastomosis—including the consistency of suturing informed by the average suture spacing, the pressure at which the anastomosis leaked, the number of mistakes that required removing the needle from the tissue, completion time, and lumen reduction in intestinal anastomoses—between our supervised autonomous system, manual laparoscopic surgery, and clinically used RAS approaches. Despite dynamic scene changes and tissue movement during surgery, we demonstrate that the outcome of supervised autonomous procedures is superior to surgery performed by expert surgeons and RAS techniques in ex vivo porcine tissues and in living pigs. These results demonstrate the potential for autonomous robots to improve the efficacy, consistency, functional outcome, and accessibility of surgical techniques.
Stacked PMOS clamps for high voltage power supply protection

Large PMOS FETs with multiple gates can be arranged to provide ESD protection to high voltage on-chip power supplies in submicron CMOS integrated circuits. These clamps divide the supply voltage among several gate oxides; the circuitry accompanying the large series FETs provides near-maximum gate drive during ESD for high pulsed current. Layouts are densely packed because minimum dimensions can be used and because no contact is needed between the stacked gates. The high voltage designs are extensions of the large PMOS FET ESD clamps and timed drive circuitry that are used to clamp ordinary on-chip power supply lines.
An Eigendecomposition Approach to Weighted Graph Matching Problems

This paper discusses an approximate solution to the weighted graph matching prohlem (WGMP) for both undirected and directed graphs. The WGMP is the problem of finding the optimum matching between two weighted graphs, which are graphs with weights at each arc. The proposed method employs an analytic, instead of a combinatorial or iterative, approach to the optimum matching problem of such graphs. By using the eigendecompoyitions of the adjacency matrices (in the case of the undirected graph matching problem) or some Hermitian matrices derived from the adjacency matrices (in the case of the directed graph matching problem), a matching close to the optimum one can be found efficiently when the graphs are sufficiently close to each other. Simulation experiments are also given to evaluate the performance of the proposed method. Index Termy-Eigendecomposition, inexact matching, structural description, structural pattern recognition, weighted graph matching.
A 24-GHz low power and high isolation active quasi-circulator

A 24-GHz novel active quasi-circulator is developed in TSMC 0.18-µm CMOS. We proposed a new architecture by using the canceling mechanism to achieve high isolations and reduce the circuit area. The measured insertion losses |S<inf>32</inf>| and |S<inf>21</inf>| are 9 and 8.5 dB, respectively. The isolation |S<inf>31</inf>| is greater than 30 dB. The dc power consumption is only 9.12 mW with a chip size of 0.35 mm<sup>2</sup>.
A Simple and Efficient Connected Components Labeling Algorithm

We describe a two-scan algorithm for labeling connected components in binary images in raster format. Unlike the classical two-scan approach, our algorithm processes equivalences during the first scan by merging equivalence classes as soon as a new equivalence is found. We show that this significantly improves the efficiency of the labeling process with respect to the classical approach. The datastructure used to support the handling of equivalences is a 1D-array. This renders the more frequent operation of finding class identifiers very fast, while the less-frequent classmerging operation has a relatively high computational cost. Nonetheless, it is possible to reduce significantly the mergings cost by two slight modifications to algorithm’s basic structure. The ideas of merging equivalence classes is present also in Samet’s general labeling algorithm. However, when considering the case of binary images in raster format this algorithm is much more complex than the one we describe in this paper.
Self-Imitation Learning

This paper proposes Self-Imitation Learning (SIL), a simple off-policy actor-critic algorithm that learns to reproduce the agent’s past good decisions. This algorithm is designed to verify our hypothesis that exploiting past good experiences can indirectly drive deep exploration. Our empirical results show that SIL significantly improves advantage actor-critic (A2C) on several hard exploration Atari games and is competitive to the state-of-the-art count-based exploration methods. We also show that SIL improves proximal policy optimization (PPO) on MuJoCo tasks.
FlowChecker: configuration analysis and verification of federated openflow infrastructures

It is difficult to build a real network to test novel experiments. OpenFlow makes it easier for researchers to run their own experiments by providing a virtual slice and configuration on real networks. Multiple users can share the same network by assigning a different slice for each one. Users are given the responsibility to maintain and use their own slice by writing rules in a FlowTable. Misconfiguration problems can arise when a user writes conflicting rules for single FlowTable or even within a path of multiple OpenFlow switches that need multiple FlowTables to be maintained at the same time.
 In this work, we describe a tool, FlowChecker, to identify any intra-switch misconfiguration within a single FlowTable. We also describe the inter-switch or inter-federated inconsistencies in a path of OpenFlow switches across the same or different OpenFlow infrastructures. FlowChecker encodes FlowTables configuration using Binary Decision Diagrams and then uses the model checker technique to model the inter-connected network of OpenFlow switches.
Proportionality in Asian and North American Caucasian Faces Using Neoclassical Facial Canons as Criteria

Nine projective linear measurements were taken to determine morphometric differences of the face among healthy young adult Chinese, Vietnamese, and Thais (60 in each group) and to assess the validity of six neoclassical facial canons in these populations. In addition, the findings in the Asian ethnic groups were compared to the data of 60 North American Caucasians. The canons served as criteria for determining the differences between the Asians and Caucasians. In neither Asian nor Caucasian subjects were the three sections of the facial profile equal. The validity of the five other facial canons was more frequent in Caucasians (range: 16.7–36.7%) than in Asians (range: 1.7–26.7%). Horizontal measurement results were significantly greater in the faces of the Asians (en–en, al–al, zy–zy) than in their white counterparts; as a result, the variation between the classical proportions and the actual measurements was significantly higher among Asians (range: 90–100%) than Caucasians (range: 13.3–48%). The dominant characteristics of the Asian face were a wider intercanthal distance in relation to a shorter palpebral fissure, a much wider soft nose within wide facial contours, a smaller mouth width, and a lower face smaller than the forehead height. In the absence of valid anthropometric norms of craniofacial measurements and proportion indices, our results, based on quantitative analysis of the main vertical and horizontal measurements of the face, offers surgeons guidance in judging the faces of Asian patients in preparation for corrective surgery.
Modeling and Design Considerations for Substrate Integrated Waveguide Circuits and Components

This paper presents an overview of the recent achievements in the held of substrate integrated waveguides (SIW) technology, with particular emphasis on the modeling strategy and design considerations of millimeter-wave integrated circuits as well as the physical interpretation of the operation principles and loss mechanisms of these structures. The most common numerical methods for modeling both SIW interconnects and circuits are presented. Some considerations and guidelines for designing SIW structures, interconnects and circuits are discussed, along with the physical interpretation of the major issues related to radiation leakage and losses. Examples of SIW circuits and components operating in the microwave and millimeter wave bands are also reported, with numerical and experimental results.
Fashion Shopping in Multichannel Retail: The Role of Technology in Enhancing the Customer Experience

The difficulty of translating the in-store experience to the online environment is one of the main reasons why the fashion industry has been slower than other sectors to adopt e-commerce. Recently, however, new information technologies (ITs) have enabled consumers to evaluate fashion online, creating an interactive and exciting shopping experience. As a result, clothing has become the fastest-growing online category of goods bought in the United Kingdom. This trend could have serious consequences for brick-andmortar stores. The aim of this quantitative research is to gain a better understanding of multichannel fashion-shopping experiences, focusing on the role of IT and the crossover effects between channels. In particular, I explore the influence of the level of online experience on the perceptions and motivations of fashion consumers when they buy across multiple channels. The theoretical framework of hedonic and utilitarian shopping values is applied to measure consumers’ shopping experiences and shopping motivations to buy in different channels. The results from a quantitative survey of 439 consumers in the United Kingdom suggest the need to redefine the in-store shopping experience, promoting the use of technology as a way to create an engaging and integrated experience among channels. Retailers must think in all channels holistically, boosting interactive and new technologies for the Internet and taking advantage of all touchpoints with the consumer, including mobile devices and social networks.
Modeling and identification for high-performance robot control: an RRR-robotic arm case study

This paper explains a procedure for getting models of robot kinematics and dynamics that are appropriate for robot control design. The procedure consists of the following steps: 1) derivation of robot kinematic and dynamic models and establishing correctness of their structures; 2) experimental estimation of the model parameters; 3) model validation; and 4) identification of the remaining robot dynamics, not covered with the derived model. We give particular attention to the design of identification experiments and to online reconstruction of state coordinates, as these strongly influence the quality of the estimation process. The importance of correct friction modeling and the estimation of friction parameters are illuminated. The models of robot kinematics and dynamics can be used in model-based nonlinear control. The remaining dynamics cannot be ignored if high-performance robot operation with adequate robustness is required. The complete procedure is demonstrated for a direct-drive robotic arm with three rotational joints.
Evaluating word embeddings and a revised corpus for part-of-speech tagging in Portuguese

Part-of-speech tagging is an important preprocessing step in many natural language processing applications. Despite much work already carried out in this field, there is still room for improvement, especially in Portuguese. We experiment here with an architecture based on neural networks and word embeddings, and that has achieved promising results in English. We tested our classifier in different corpora: a new revision of the Mac-Morpho corpus, in which we merged some tags and performed corrections and two previous versions of it. We evaluate the impact of using different types of word embeddings and explicit features as input. We compare our tagger’s performance with other systems and achieve state-of-the-art results in the new corpus. We show how different methods for generating word embeddings and additional features differ in accuracy. The work reported here contributes with a new revision of the Mac-Morpho corpus and a state-of-the-art new tagger available for use out-of-the-box.
Selective increases of bifidobacteria in gut microflora improve high-fat-diet-induced diabetes in mice through a mechanism associated with endotoxaemia

Recent evidence suggests that a particular gut microbial community may favour occurrence of the metabolic diseases. Recently, we reported that high-fat (HF) feeding was associated with higher endotoxaemia and lower Bifidobacterium species (spp.) caecal content in mice. We therefore tested whether restoration of the quantity of caecal Bifidobacterium spp. could modulate metabolic endotoxaemia, the inflammatory tone and the development of diabetes. Since bifidobacteria have been reported to reduce intestinal endotoxin levels and improve mucosal barrier function, we specifically increased the gut bifidobacterial content of HF-diet-fed mice through the use of a prebiotic (oligofructose [OFS]). Compared with normal chow-fed control mice, HF feeding significantly reduced intestinal Gram-negative and Gram-positive bacteria including levels of bifidobacteria, a dominant member of the intestinal microbiota, which is seen as physiologically positive. As expected, HF-OFS-fed mice had totally restored quantities of bifidobacteria. HF-feeding significantly increased endotoxaemia, which was normalised to control levels in HF-OFS-treated mice. Multiple-correlation analyses showed that endotoxaemia significantly and negatively correlated with Bifidobacterium spp., but no relationship was seen between endotoxaemia and any other bacterial group. Finally, in HF-OFS-treated-mice, Bifidobacterium spp. significantly and positively correlated with improved glucose tolerance, glucose-induced insulin secretion and normalised inflammatory tone (decreased endotoxaemia, plasma and adipose tissue proinflammatory cytokines). Together, these findings suggest that the gut microbiota contribute towards the pathophysiological regulation of endotoxaemia and set the tone of inflammation for occurrence of diabetes and/or obesity. Thus, it would be useful to develop specific strategies for modifying gut microbiota in favour of bifidobacteria to prevent the deleterious effect of HF-diet-induced metabolic diseases.
2.4/5.2/5.8 GHz WLAN antenna for the ultrabook computer with metal housing

A promising small-size WLAN antenna suitable to be mounted along the hinge of the ultrabook computer with metal housing is presented. The antenna is formed by a two-branch structure of a monopole strip and a loop strip. The antenna has attractive features of low profile and wideband operation. In addition, by using the closed resonant path provided by the loop strip, possible coupling of the proposed antenna with nearby conducting elements for frequencies over the 2.4 GHz band can be expected to be decreased. Also, when the antenna is operated in the 5.2/5.8 GHz band, the loop strip is not at resonance and can serve as a shielding element for the monopole strip. This can also lead to decreased possible coupling of the proposed antenna with nearby conducting elements over the 5.2/5.8 GHz bands.
Automatic batch-invariant color segmentation of histological cancer images

We propose an automatic color segmentation system that (1) incorporates domain knowledge to guide histological image segmentation and (2) normalizes images to reduce sensitivity to batch effects. Color segmentation is an important, yet difficult, component of image-based diagnostic systems. User-interactive guidance by domain experts—i.e., pathologistsߞoften leads to the best color segmentation or “ground truth” regardless of stain color variations in different batches. However, such guidance limits the objectivity, reproducibility and speed of diagnostic systems. Our system uses knowledge from pre-segmented reference images to normalize and classify pixels in patient images. The system then refines the segmentation by re-classifying pixels in the original color space. We test our system on four batches of H&E stained images and, in comparison to a system with no normalization (39% average accuracy), we obtain an average segmentation accuracy of 85%.
Advanced data preprocessing for intersites Web usage mining

Web usage mining applies data mining procedures to analyze user access of Web sites. As with any KDD (knowledge discovery and data mining) process, WUM contains three main steps: preprocessing, knowledge extraction, and results analysis. We focus on data preprocessing, a fastidious, complex process. Analysts aim to determine the exact list of users who accessed the Web site and to reconstitute user sessions-the sequence of actions each user performed on the Web site. Intersites WUM deals with Web server logs from several Web sites, generally belonging to the same organization. Thus, analysts must reassemble the users' path through all the different Web servers that they visited. Our solution is to join all the log files and reconstitute the visit. Classical data preprocessing involves three steps: data fusion, data cleaning, and data structuration. Our solution for WUM adds what we call advanced data preprocessing. This consists of a data summarization step, which will allow the analyst to select only the information of interest. We've successfully tested our solution in an experiment with log files from INRIA Web sites.
Design technology co-optimization of back end of line design rules for a 7 nm predictive process design kit

This paper discusses the back-end-of-line (BEOL) layers for a 7 nm predictive process design kit (PDK). The rationale behind choosing a particular lithographic process—EUV lithography, self-aligned double patterning (SADP), and litho-etch litho-etch (LELE)—for different layers, in addition to some design rule values, is described. The rules are based on the literature and on design technology co-optimization (DTCO) evaluation of standard cell based designs and automated place-and-route experiments. Decomposition criteria and design rules to ensure conflict-free coloring of SADP metal topologies and manufacturable SADP photolithography masks are discussed in detail. Their efficacy is demonstrated through successful coloring and photolithography mask derivation for target metal shape layouts, which represent corner cases, by using the Mentor Graphics Calibre and multi-patterning tools. Edge placement errors, misalignment, and critical dimension uniformity are included in the analysis.
Efficient Distributed Linear Classification Algorithms via the Alternating Direction Method of Multipliers

Linear classification has demonstrated success in many areas of applications. Modern algorithms for linear classification can train reasonably good models while going through the data in only tens of rounds. However, large data often does not fit in the memory of a single machine, which makes the bottleneck in large-scale learning the disk I/O, not the CPU. Following this observation, Yu et al. (2010) made significant progress in reducing disk usage, and their algorithms now outperform LIBLINEAR. In this paper, rather than optimizing algorithms on a single machine, we propose and implement distributed algorithms that achieve parallel disk loading and access the disk only once. Our large-scale learning algorithms are based on the framework of alternating direction methods of multipliers. The framework derives a subproblem that remains to be solved efficiently for which we propose using dual coordinate descent and trust region Newton method. Our experimental evaluations on large datasets demonstrate that the proposed algorithms achieve significant speedup over the classifier proposed by Yu et al. running on a single machine. Our algorithms are faster than existing distributed solvers, such as Zinkevich et al. (2010)’s parallel stochastic gradient descent and Vowpal Wabbit.