nils-herrmann/clean_scirepeval huggingface dataset:
Key importance of compression properties in the biophysical characteristics of hyaluronic acid soft-tissue fillers.

Hyaluronic acid (HA) soft-tissue fillers are the most popular degradable injectable products used for correcting skin depressions and restoring facial volume loss. From a rheological perspective, HA fillers are commonly characterised through their viscoelastic properties under shear-stress. However, despite the continuous mechanical pressure that the skin applies on the fillers, compression properties in static and dynamic modes are rarely considered. In this article, three different rheological tests (shear-stress test and compression tests in static and dynamic mode) were carried out on nine CE-marked cross-linked HA fillers. Corresponding shear-stress (G', tanδ) and compression (E', tanδc, normal force FN) parameters were measured. We show here that the tested products behave differently under shear-stress and under compression even though they are used for the same indications. G' showed the expected influence on the tissue volumising capacity, and the same influence was also observed for the compression parameters E'. In conclusion, HA soft-tissue fillers exhibit widely different biophysical characteristics and many variables contribute to their overall performance. The elastic modulus G' is not the only critical parameter to consider amongst the rheological properties: the compression parameters E' and FN also provide key information, which should be taken into account for a better prediction of clinical outcomes, especially for predicting the volumising capacity and probably the ability to stimulate collagen production by fibroblasts.
BTS: Resource capacity estimate for time-targeted science workflows

Workflow technologies have become a major vehicle for easy and efficient development of scientific applications. A critical challenge in integrating workflow technologies with state-of-the-art resource provisioning technologies is to determine the right amount of resources required for the execution of workflows. This paper introduces an approximation algorithm named BTS (Balanced Time Scheduling), which estimates the minimum number of computing hosts required to execute workflows within a user-specified finish time. The experimental results, based on a number of synthetic workflows and several real science workflows, demonstrate that the BTS estimate of resource capacity approaches to the theoretical low bound. The BTS algorithm is scalable and its turnaround time is only tens of seconds, even with huge workflows with thousands of tasks and edges. Moreover, BTS achieves good performance with workflows having MPI-like parallel tasks. Finally, BTS can be easily integrated with any resource description languages and resource provisioning systems since the resource estimate of BTS is abstract.
Predicting the popularity of online articles based on user comments

Understanding user participation is fundamental in anticipating the popularity of online content. In this paper, we explore how the number of users' comments during a short observation period after publication can be used to predict the expected popularity of articles published by a countrywide online newspaper. We evaluate a simple linear prediction model on a real dataset of hundreds of thousands of articles and several millions of comments collected over a period of four years. Analyzing the accuracy of our proposed model for different values of its basic parameters we provide valuable insights on the potentials and limitations for predicting content popularity based on early user activity.
A 3-DOF flexure-based fixture for passive assembly of optical switches

This paper presents the design of a planar compliant fixture for optical switch assembly to automatically accommodate the uncontrollable assembly errors. The fixture comprises a platform movable in x-y-thetas and three flexure-based supporting legs. Compliance performance is a mainly concern in the design. A closed-form formulation is developed to map the stiffness in the joints space into Cartesian space for generic 3-legged planar platforms. Based on the stiffness requirement, the structure and the configuration of the legs are synthesized and designed. Experimental results showed that the performance of the optical switch assembly system is improved significantly after adopting the fixture
Detecting Foggy Images and Estimating the Haze Degree Factor

At present, most outdoor video-surveillance, driver-assistance and optical remote sensing systems have been designed to work under good visibility and weather conditions. Poor visibility often occurs in foggy or hazy weather conditions and can strongly influence the accuracy or even the general functionality of such vision systems. Consequently, it is important to import actual weather-condition data to the appropriate processing mode. Recently, significant progress has been made in haze removal from a single image . Based on the hazy weather classification, specialized approaches, such as a dehazing process, can be employed to improve recognition. Figure 1 shows a sample processing flow of our dehazing program.
Simple Electromagnetic Modeling Procedure: From Near-Field Measurements to Commercial Electromagnetic Simulation Tool

As the first part of a study that aims to propose tools to take into account some electromagnetic compatibility aspects, we have developed a model to predict the electric and magnetic fields emitted by a device. This model is based on a set of equivalent sources (electric and magnetic dipoles) obtained from the cartographies of the tangential components of electric and magnetic near fields. One of its features is to be suitable for a commercial electromagnetic simulation tool based on a finite element method. This paper presents the process of modeling and the measurement and calibration procedure to obtain electromagnetic fields necessary for the model; the validation and the integration of the model into a commercial electromagnetic simulator are then performed on a Wilkinson power divider.
A study of factors that contribute to online review helpfulness

Helpfulness of online reviews is a multi-faceted concept that can be driven by several types of factors. This study was designed to extend existing research on online review helpfulness by looking at not just the quantitative factors (such as word count), but also qualitative aspects of reviewers (including reviewer experience, reviewer impact, reviewer cumulative helpfulness). This integrated view uncovers some insights that were not available before. Our findings suggest that word count has a threshold in its effects on review helpfulness. Beyond this threshold, its effect diminishes significantly or becomes near non-existent. Reviewer experience and their impact were not statistically significant predictors of helpfulness, but past helpfulness records tended to predict future helpfulness ratings. Review framing was also a strong predictor of helpfulness. As a result, characteristics of reviewers and review messages have a varying degree of impact on review helpfulness. Theoretical and practical implications are discussed.
3.6 A 45Gb/s PAM-4 transmitter delivering 1.3Vppd output swing with 1V supply in 28nm CMOS FDSOI

The development of next-generation electrical link technology to support 400Gb/s standards is underway [1-5]. Physical constraints paired to the small area available to dissipate heat, impose limits to the maximum number of serial interfaces and therefore their minimum speed. As such, aggregation of currently available 25Gb/s systems is not an option, and the migration path requires serial interfaces to operate at increased rates. According to CEI-56G and IEEE P802.3bs emerging standards, PAM-4 signaling paired to forward error correction (FEC) schemes is enabling several interconnect applications and low-loss profiles . Since the amplitude of each eye is reduced by a factor of 3, while noise power is only halved, a high transmitter (TX) output amplitude is key to preserve high SNR. However, compared to NRZ, the design of a PAM-4 TX is challenged by tight linearity constraints, required to minimize the amplitude distortion among the 4 levels . In principle, current-mode (CM) drivers can deliver a differential peak-to-peak swing up to 4/3(VDD-VOV), but they struggle to generate high-swing PAM-4 levels with the required linearity. This is confirmed by recently published CM PAM-4 drivers, showing limited output swings even with VDD raised to 1.5V [2-4]. Source-series terminated (SST) drivers naturally feature better linearity and represent a valid alternative, but the maximum differential peak-to-peak swing is bounded to VDD only. In , a dual-mode SST driver supporting NRZ/PAM-4 was presented, but without FFE for PAM-4 mode. In this paper, we present a PAM-4 transmitter leveraging a hybrid combination of SST and CM driver. The CM part enhances the output swing by 30% beyond the theoretical limit of a conventional SST implementation, while being calibrated to maintain the desired linearity level. A 5b 4-tap FIR filter, where equalization tuning can be controlled independently from output matching, is also embedded. The transmitter, implemented in 28nm CMOS FDSOI, incorporates a half-rate serializer, duty-cycle correction (DCC), ≫2kV HBM ESD diodes, and delivers a full swing of 1.3Vppd at 45Gb/s while drawing 120mA from a 1V supply. The power efficiency is ~2 times better than those compared in this paper.
Sim-to-Real Robot Learning from Pixels with Progressive Nets

Applying end-to-end learning to solve complex, interactive, pixeldriven control tasks on a robot is an unsolved problem. Deep Reinforcement Learning algorithms are too slow to achieve performance on a real robot, but their potential has been demonstrated in simulated environments. We propose using progressive networks to bridge the reality gap and transfer learned policies from simulation to the real world. The progressive net approach is a general framework that enables reuse of everything from low-level visual features to highlevel policies for transfer to new tasks, enabling a compositional, yet simple, approach to building complex skills. We present an early demonstration of this approach with a number of experiments in the domain of robot manipulation that focus on bridging the reality gap. Unlike other proposed approaches, our realworld experiments demonstrate successful task learning from raw visual input on a fully actuated robot manipulator. Moreover, rather than relying on modelbased trajectory optimisation, the task learning is accomplished using only deep reinforcement learning and sparse rewards.
An improved centroid classifier for text categorization

In the context of text categorization, Centroid Classifier has proved to be a simple and yet efficient method. However, it often suffers from the inductive bias or model misfit incurred by its assumption. In order to address this issue, we propose a novel batch-updated approach to enhance the performance of Centroid Classifier. The main idea behind this method is to take advantage of training errors to successively update the classification model by batch. The technique is simple to implement and flexible to text data. The experimental results indicate that the technique can significantly improve the performance of Centroid Classifier.
A strategy-based ontology of knowledge management technologies

The purpose of this paper is to distinguish and describe knowledge management (KM) technologies according to their support for strategy.  This study employed an ontology development method to describe the relations between technology, KM and strategy, and to categorize available KM technologies according to those relations. Ontologies are formal specifications of concepts in a domain and their inter-relationships, and can be used to facilitate common understanding and knowledge sharing. The study focused particularly on two sub-domains of the KM field: KM strategies and KM technologies. Findings – ’’KM strategy’’ has three meanings in the literature: approach to KM, knowledge strategy, and KM implementation strategy. Also, KM technologies support strategy via KM initiatives based on particular knowledge strategies and approaches to KM. The study distinguishes three types of KM technologies: component technologies, KM applications, and business applications. They all can be described in terms of ’’creation’’ and ’’transfer’’ knowledge strategies, and ’’personalization’’ and ’’codification’’ approaches to KM.  The resulting framework suggests that KM technologies can be analyzed better in the context of KM initiatives, instead of the usual approach associating them with knowledge processes. KM initiatives provide the background and contextual elements necessary to explain technology adoption and use.  The framework indicates three alternative modes for organizational adoption of KM technologies: custom development of KM systems from available component technologies; purchase of KM-specific applications; or purchase of business-driven applications that embed KM functionality. It also lists adequate technologies and provides criteria for selection in any of the cases.  Among the many studies analyzing the role of technology in KM, an association with strategy has been missing. This paper contributes to filling this gap, integrating diverse contributions via a clearer definition of concepts and a visual representation of their relationships. This use of ontologies as a method, instead of an artifact, is also uncommon in the literature.
Crank-wheel: A brand new mobile base for field robots

In the accident of nuclear disasters or biochemical terrors, there is the strong need for robots which can move around and collect information at the disaster site. The robot should have toughness and high mobility in a location of stairs and obstacles. In this study, we propose a brand new type of mobile base named “crank-wheel” suitable for such use. Crank-wheel consists of wheels and connecting coupler link named crank-leg. Crank-wheel makes simple and smooth wheeled motion on flat ground and automatically transforms to the walking motion on rugged terrain as the crank-legs starts to contact the surface of the rugged terrain and acts as legs. This mechanism features its simple, easiness to maintain water and dust proof structure, and limited danger of biting rubbles in the driving mechanism just as the case of tracked vehicles. Effectiveness of the Crank-wheel is confirmed by several driving experiments on debris, sand and bog.
Creating interactive physics education books with augmented reality

Augmented Books show three-dimensional animated educational content and provide a means for students to interact with this content in an engaging learning experience. In this paper we present a framework for creating educational Augmented Reality (AR) books that overlay virtual content over real book pages. The framework features support for certain types of user interaction, model and texture animations, and an enhanced marker design suitable for educational books. Three books teaching electromagnetism concepts were created with this framework. To evaluate the effectiveness in helping students learn, we conducted a small pilot study with ten secondary school students, studying electromagnetism concepts using the three books. Half of the group used the books with the diagrams augmented, while the other half used the books without augmentation. Participants completed a pre-test, a test after the learning session and a retention test administered 1 month later. Results suggest that AR has potential to be effective in teaching complex 3D concepts.
A Secured Authentication Protocol for Wireless Sensor Networks Using Elliptic Curves Cryptography

User authentication is a crucial service in wireless sensor networks (WSNs) that is becoming increasingly common in WSNs because wireless sensor nodes are typically deployed in an unattended environment, leaving them open to possible hostile network attack. Because wireless sensor nodes are limited in computing power, data storage and communication capabilities, any user authentication protocol must be designed to operate efficiently in a resource constrained environment. In this paper, we review several proposed WSN user authentication protocols, with a detailed review of the M.L Das protocol and a cryptanalysis of Das' protocol that shows several security weaknesses. Furthermore, this paper proposes an ECC-based user authentication protocol that resolves these weaknesses. According to our analysis of security of the ECC-based protocol, it is suitable for applications with higher security requirements. Finally, we present a comparison of security, computation, and communication costs and performances for the proposed protocols. The ECC-based protocol is shown to be suitable for higher security WSNs.
An HMM and structural entropy based detector for Android malware: An empirical study

Smartphones are becoming more and more popular and, as a consequence, malware writers are increasingly engaged to develop new threats and propagate them through official and third-party markets. In addition to the propagation vectors, malware is also evolving quickly the techniques adopted for infecting victims and hiding their malicious nature to antimalware scanning. From SMS Trojans to legitimate applications repacked with malicious payload, from AES encrypted root exploits to the dynamic loading of a payload retrieved from a remote server: malicious code is becoming more and more hard to detect. In this paper we experimentally evaluate two techniques for detecting Android malware: the first one is based on Hidden Markov Model, while the second one exploits structural entropy. These two techniques have been successfully applied to detect PCs viruses in previous works, and only one work in literature analyzes the application of HMM to the detection of Android malware. We demonstrate that these methods, which reveal effective for PCs virus, are also successful for detecting and classifying mobile malware. Our results are promising: we obtain a precision of 0.96 to discriminate a malware application, and a precision of 0.978 to identify the malware family.
Evaluation and design for an integrated modular motor drive (IMMD) with GaN devices

This paper explores the use of GaN MOSFETs and series-connected inverter segments to realize an IMMD. The proposed IMMD topology reduces the segment voltage and offers an opportunity to utilize wide bandgap 200V GaN MOSFETs. Consequently, a reduction in IMMD size is achieved by eliminating inverter heat sink and optimizing the choice of DC-link capacitors. Gate signals of the IMMD segments are shifted (interleaved) to cancel the capacitor voltage ripple and further reduce the capacitor size. Motor winding configuration and coupling effect are also investigated to match with the IMMD design. An actively controlled balancing resistor is programmed to balance the voltages of series connected IMMD segments. Furthermore, this paper presents simulation results as well as experiment results to validate the proposed design.
Combining Visual and Spatial Appearance for Loop Closure Detection in SLAM

In this paper we describe a system for use on a mobile robot that detects potential loop closures using both the visual and spatial appearance of the local scene. Loop closing is the act of correctly asserting that a vehicle has returned to a previously visited location. It is an important component in the search to make SLAM (Simultaneous Localization and Mapping) the reliable technology it should be. Paradoxically, it is hardest in the presence of substantial errors in vehicle pose estimates which is exactly when it is needed most. The contribution of this paper is to show how a principled and robust description of local spatial appearance (using laser rangefinder data) can be combined with a purely camera based system to produce superior performance. Individual spatial components (segments) of the local structure are described using a rotationally invariant shape descriptor and salient aspects thereof, and entropy as measure of their innate complexity. Comparisons between scenes are made using relative entropy and by examining the mutual arrangement of groups of segments. We show the inclusion of spatial information allows the resolution of ambiguities stemming from repetitive visual artifacts in urban settings. Importantly the method we present is entirely independent of the navigation and or mapping process and so is entirely unaffected by gross errors in pose estimation.
Efficient load Balancing in Cloud Computing using Fuzzy Logic

Cloud computing is an expanding area in research and industry today, which involves virtualization, distributed computing, internet, software and web services. A cloud consists of several elements such as clients, data centers and distributed servers, internet and it includes fault tolerance, high availability, effectiveness, scalability, flexibility, reduced overhead for users, reduced cost of ownership, on demand services and etc. The services of cloud computing are becoming ubiquitous, and serve as the primary source of computing power for different applications like enterprises and personal computing applications. In this paper we introduced the novel load balancing algorithm using fuzzy logic in cloud computing, in which load balancing is a core and challenging issue in Cloud Computing. The processor speed and assigned load of Virtual Machine (VM) are used to balance the load in cloud computing through fuzzy logic.
On the Systematic Analysis of Natural Language Requirements with CIRCE

This paper presents Circe, an environment for the analysis of natural language requirements. Circe is first presented in terms of its architecture, based on a transformational paradigm. Details are then given for the various transformation steps, including (i) a novel technique for parsing natural language requirements, and (ii) an expert system based on modular agents, embodying intensional knowledge about software systems in general. The result of all the transformations is a set of models for the requirements document, for the system described by the requirements, and for the requirements writing process. These models can be inspected, measured, and validated against a given set of criteria. Some of the features of the environment are shown by means of an example. Various stages of requirements analysis are covered, from initial sketches to pseudo-code and UML models.
A survey on security in network functions virtualization

Network functions virtualization (NFV) is an emerging network technology. Instead of deploying hardware equipments for each network functions, virtualized network functions in NFV are realized through virtual machines (VMs) running various software on top of industry standard high volume servers or cloud computing infrastructure. NFV decreases hardware equipment costs and energy consumption, improves operational efficiency and optimizes network configuration. However, potential security issues is a major concern of NFV. In this paper, we survey the challenges and opportunities in NFV security. We describe the NFV architecture design and some potential NFV security issues and challenges. We also present existing NFV security solutions and products. We also survey NFV security use cases and explore promising research directions in this area.