nils-herrmann/clean_scirepeval huggingface dataset:
Solving ill-posed inverse problems using iterative deep neural networks

We propose a partially learned approach for the solution of ill posed inverse problems with not necessarily linear forward operators. The method builds on ideas from classical regularization theory and recent advances in deep learning to perform learning while making use of prior information about the inverse problem encoded in the forward operator, noise model and a regularizing functional. The method results in a gradient-like iterative scheme, where the “gradient” component is learned using a convolutional network that includes the gradients of the data discrepancy and regularizer as input in each iteration. We present results of such a partially learned gradient scheme on a non-linear tomographic inversion problem with simulated data from both the Sheep-Logan phantom as well as a head CT. The outcome is compared against filtered backprojection and total variation reconstruction and the proposed method provides a 5.4 dB PSNR improvement over the total variation reconstruction while being significantly faster, giving reconstructions of 512× 512 pixel images in about 0.4 s using a single graphics processing unit (GPU).
Genetic analysis of host resistance: Toll-like receptor signaling and immunity at large.

Classical genetic methods, driven by phenotype rather than hypotheses, generally permit the identification of all proteins that serve nonredundant functions in a defined biological process. Long before this goal is achieved, and sometimes at the very outset, genetics may cut to the heart of a biological puzzle. So it was in the field of mammalian innate immunity. The positional cloning of a spontaneous mutation that caused lipopolysaccharide resistance and susceptibility to Gram-negative infection led directly to the understanding that Toll-like receptors (TLRs) are essential sensors of microbial infection. Other mutations, induced by the random germ line mutagen ENU (N-ethyl-N-nitrosourea), have disclosed key molecules in the TLR signaling pathways and helped us to construct a reasonably sophisticated portrait of the afferent innate immune response. A still broader genetic screen--one that detects all mutations that compromise survival during infection--is permitting fresh insight into the number and types of proteins that mammals use to defend themselves against microbes.
Mind how you answer me!: transparently authenticating the user of a smartphone when answering or placing a call

In this paper we propose a new biometric measure to authenticate the user of a smartphone: the movement the user performs when answering (or placing) a phone call. The biometric measure leverages features that are becoming commodities in new smartphones, i.e. accelerometer and orientation sensors. We argue that this new biometric measure has a unique feature. That is, it allows a transparent authentication (not requiring an additional specific interaction for this) to check that the user that is answering (or placing) a phone call is the one authorized to do that. At the same time, this biometric measure can also be used as a non transparent authentication method, e.g. the user may need to move the phone as if answering a call, in order to unlock the phone to get access to SMSs or emails. As a consequence of being a biometric measure, an adversary that spies on the movement (e.g. captures it with a camera) and tries to replicate it, will not be granted access to the phone.
 We prototyped our solution and conducted several experiments to assess its feasibility. Results show that the method is effective, and the performance is comparable to that of other transparent authentication methods, like face or voice recognition.
EFFICIENCY ENHANCEMENT OF BASE STATION POWER AMPLIFIERS USING DOHERTY TECHNIQUE

The power amplifiers are typically the most power-consuming block in wireless communication systems. Spectrum is expensive, and newer technologies demand transmission of maximum amount of data with minimum spectrum usage. This requires sophisticated modulation techniques, leading to wide, dynamic signals that require linear amplification. Although linear amplification is achievable, it always comes at the expense of efficiency. Most of the modern wireless applications such as WCDMA use non-constant envelope modulation techniques with a high peak to average ratio. Linearity being a critical issue, power amplifiers implemented in such applications are forced to operate at a backed off region from saturation. Therefore, in order to overcome the battery lifetime limitation, a design of a high efficiency power amplifier that can maintain the efficiency for a wider range of radio frequency input signal is the obvious solution. A new technique that improves the drain efficiency of a linear power amplifier such as Class A or AB, for a wider range of output power, has been investigated in this research. The Doherty technique consists of two amplifiers in parallel; in such a way that the combination enhances the power added efficiency of the main amplifier at 6dB back off from the maximum output power. The classes of operation of power amplifier (A, AB,B, C etc), and the design techniques are presented. Design of a 2.14 GHz Doherty power amplifier has been provided in chapter 4. This technique shows a 15% increase in power added efficiency at 6 dB back off from the compression point. This PA can be implemented in WCDMA base station transmitter.
Vision-Based Traffic Sign Detection and Analysis for Intelligent Driver Assistance Systems: Perspectives and Survey

In this paper, we provide a survey of the traffic sign detection literature, detailing detection systems for traffic sign recognition (TSR) for driver assistance. We separately describe the contributions of recent works to the various stages inherent in traffic sign detection: segmentation, feature extraction, and final sign detection. While TSR is a well-established research area, we highlight open research issues in the literature, including a dearth of use of publicly available image databases and the over-representation of European traffic signs. Furthermore, we discuss future directions of TSR research, including the integration of context and localization. We also introduce a new public database containing U.S. traffic signs.
StyleCheck : An Automated Stylistic Analysis Tool

StyleCheck is a user-friendly tool with multiple functions designed to aid in the production of quality writing. Its features include stylistic analysis (on both documentwide and individual-sentence scales) and spelling and grammar check, as well as generating suggested replacements for all types of errors. In addition, StyleCheck includes the capability to identify the famous author (out of a limited corpus) with the style most similar to the user’s. The source code for StyleCheck is available online at: https://github.com/alexpwelton/StyleCheck Dartmouth Computer Science Technical Report TR2014-754
HanGuard: SDN-driven protection of smart home WiFi devices from malicious mobile apps

A new development of smart-home systems is to use mobile apps to control IoT devices across a Home Area Network (HAN). As verified in our study, those systems tend to rely on the Wi-Fi router to authenticate other devices. This treatment exposes them to the attack from malicious apps, particularly those running on authorized phones, which the router does not have information to control. Mitigating this threat cannot solely rely on IoT manufacturers, which may need to change the hardware on the devices to support encryption, increasing the cost of the device, or software developers who we need to trust to implement security correctly. In this work, we present a new technique to control the communication between the IoT devices and their apps in a unified, backward-compatible way. Our approach, called HanGuard, does not require any changes to the IoT devices themselves, the IoT apps or the OS of the participating phones. HanGuard uses an SDN-like approach to offer fine-grained protection: each phone runs a non-system userspace Monitor app to identify the party that attempts to access the protected IoT device and inform the router through a control plane of its access decision; the router enforces the decision on the data plane after verifying whether the phone should be allowed to talk to the device. We implemented our design over both Android and iOS (> 95% of mobile OS market share) and a popular router. Our study shows that HanGuard is both efficient and effective in practice.
Accelerometer Gesture Recognition

Our goal is to make gesture-based input for smartphones and smartwatches accurate and feasible to use. With a custom Android application to record accelerometer data for 5 gestures, we developed a highly accurate SVM classifier using only 1 training example per class. Our novel Dynamic-Threshold Truncation algorithm during preprocessing improved accuracy on 1 training example per class by 14% and the addition of axis-wise Discrete Fourier Transform coefficient features improved accuracy on 1 training example per class by 5%. With 5 gesture classes, 1 training example for each class, and 30 test examples for each class, our classifier achieves 96% accuracy. With 5 training examples per class, the classifier achieves 98% accuracy, which is greater than the 10-example accuracy of other efforts using HMM’s[1, 2]. This makes it feasible for a real-time implementation of accelerometer-based gesture recognition to identify user-defined gestures with high accuracy while requiring little training effort from the user.
Methodology of band rejection / addition for microstrip antennas design using slot line theory and current distribution analysis

Radio or wireless communication means to transfer information over long distance without using any wires. Millions of people exchange information every day using pager, cellular, telephones, laptops, various types of personal digital assistance (PDAs) and other wireless communication products. The worldwide interoperability for microwave access (Wi-Max) aims to provide wireless data over a long distance in variety of ways. It was based on IEEE 802.16 standard. It is an effective metropolitan area access technique with many favorable features like flexibility, cost, efficiency and fast networking, which not only provides wireless access, but also serves to expand the access to wired network. The coverage area of Wi-Max is around 30-50 km. it can provide high 100 Mbps data rates in 20 MHz bandwidth on fixed and nomadic applications in the 2-11 GHz frequencies. In this paper, a methodology of band rejection/addition for microstrip antennas design using slot line theory and current distribution analysis has been introduced and analyzed. The analysis and design are done by a commercial software. The radiation characteristics, such as; return loss, VSWR, input impedance, and the surface current densities have been introduced and discussed. Finally, the proposed optimum antenna design structure has been fabricated and the measured S-parameters of the proposed structure can be analyzed with network analyzer and compared with simulation results to demonstrate the excellent performance and meet the requirements for wireless communication applications.
Building Optimal Question Answering System Automatically using Configuration Space Exploration (CSE) for QA4MRE 2013 Tasks

Different software systems for automatic question answering have been developed in recent years. Some systems perform well on specific domains, but may not be appropriate for other domains. As the complexity and scaling of such information systems become ever greater, it is much more challenging to effectively and efficiently determine which toolkits, algorithms, knowledge bases or other resources should be integrated into a system so that one can achieve a desired or optimal level of performance on a given task. In this working notepaper, we present a generic framework that can be used for any machinereading task and automatically find the best configuration of algorithmic components as well as values of their corresponding parameters. Although we have designed the framework for all QA4MRE-2013 tasks (i.e. Main task, Biomedical about Alzheimer’s and Entrance Exam), our analysis will mostly focus on Biomedical about Alzheimer’s task. We introduce the Configuration Space Exploration (CSE) framework, an extension to the Unstructured Information Management Architecture (UIMA) which provides a general distributed solution for building and exploring possible configurations for any intelligent information system. For the Biomedial about Alzheimer’s task, CSE was used to generate more than 1000 different configurations from existing components; we selected the 3 best runs for submission. We achieved an average c@1 of 0.27; our highest score was 0.60 for reading-test-1, and our lowest was 0.0 for reading-test3. We further enhanced the system by introducing point-wise mutual information (PMI) scoring for answer ranking, which produced an average c@1 of 0.4025, with a highest score of 0.77 for reading test-1 and a lowest score of 0.2 for reading test-2.
Continuous Queries over Append-Only Databases

In a database to which data is continually added, users may wish to issue a permanent query and be notified whenever data matches the query. If such continuous queries examine only single records, this can be implemented by examining each record as it arrives. This is very efficient because only the incoming record needs to be scanned. This simple approach does not work for queries involving joins or time. The Tapestry system allows users to issue such queries over a database of mail and bulletin board messages. The user issues a static query, such as “show me all messages that have been replied to by Jones,” as though the database were fixed and unchanging. Tapestry converts the query into an incremental query that efficiently finds new matches to the original query as new messages are added to the database. This paper describes the techniques used in Tapestry, which do not depend on triggers and thus be implemented on any commercial database that supports SQL. Although Tapestry is designed for filtering mail and news messages, its techniques are applicable to any append-only database.
Random Projection Based Representations for Learning Policies in Deterministic Atari Games

Recent advances in sample efficient reinforcement learning algorithms in quasi-deterministic environments highlight the requirement for computationally inexpensive visual representations. Here we investigate non-parametric dimensionality reduction techniques based on random linear transformations and we provide empirical evidence on the importance of high-variance projections using sparse random matrices in the context of episodic controllers learning deterministic policies. We also propose a novel Maximum-Variance Random Projection and improve on the performance of the original Model-Free Episodic Control results with respect to both sample efficiency and final average score.
Vehicle Velocity Observer Design Using 6-D IMU and Multiple-Observer Approach

This paper mainly focuses on the accurate estimation of the vehicle velocities of all axes, using the data received from a low-cost 6-D inertial measurement unit. The data include the vehicle linear acceleration and angular rates of all axes. In addition, the observer uses the wheel speed sensors and steering wheel angle information, which are already available on most recent production cars. Utilizing the aforementioned information, based on the combination of a bicycle model and a kinematic model, a multiple-observer system that computes the weighted sum estimation that is dependent on cornering stiffness adaptation is adopted to observe the lateral vehicle velocity, as well as longitudinal and vertical velocities. The stability of each component of the proposed observer is investigated, and a set of assessments to confirm the performance of the entire system is arranged through experiments using a real production sport utility vehicle.
Person Re-identification Meets Image Search

For long time, person re-identification and image search are two separately studied tasks. However, for person reidentification, the effectiveness of local features and the “query-search” mode make it well posed for image search techniques. In the light of recent advances in image search, this paper proposes to treat person re-identification as an image search problem. Specifically, this paper claims two major contributions. 1) By designing an unsupervised Bag-ofWords representation, we are devoted to bridging the gap between the two tasks by integrating techniques from image search in person re-identification. We show that our system sets up an effective yet efficient baseline that is amenable t o further supervised/unsupervised improvements. 2) We contribute a new high quality dataset which uses DPM detector and includes a number of distractor images. Our dataset reaches closer to realistic settings, and new perspectives are provided. Compared with approaches that rely on feature-feature match, our method is faster by over two orders of magnitude. Moreover, on three datasets, we report competitive results compared with the state-of-the-art methods.
Software Defined Radio Implementation of a QPSK Modulator/Demodulator in an Extensive Hardware Platform Based on FPGAs Xilinx ZYNQ

Vitor Chaves de Oliveira Electrical Engineering Faculty, Mackenzie Presbyterian University, São Paulo/SP, CEP 01302-907, Brazil Email: vitor_chaves_oliveira@yahoo.com.br Abstract: Software Defined Radio (SDR) technology enables wireless devices deployment with support to multiple interfaces in modulation formats and it has gained importance due to the current wireless standards proliferation. In order to activate these functionalities it is necessary to apply SDR inside a reconfigurable hardware such as the Field Programmable Gate Array (FPGA). In this study, design procedures developments are presented resulting in a Quadrature Phase Shift Keying (QPSK) modulator/demodulator based on a hardware architecture of the Xilinx FPGA Zynq family. Also in the modem’s conception it was employed the Xilinx Vivado-tool combined with Matlab, Simulink and development with ISE/EDK apparatuses. As for the reconfigurable hardware platform applied to this, it was utilized the ZedBoard along with the Analog Devices FMCCOMMS1 radio module. In addition, it is noteworthy to indicate that the entire software-hardware solution was initially carried out through a simulation that achieved the system scheme, including the hardware platform, before any hard implementation of the QPSK modem itself. The central goal in this investigation is to fully demonstrate how to construct a feasible radio system through software as close to the state of the art as possible.
Step-Up DC–DC Converters: A Comprehensive Review of Voltage-Boosting Techniques, Topologies, and Applications

DC–DC converters with voltage boost capability are widely used in a large number of power conversion applications, from fraction-of-volt to tens of thousands of volts at power levels from milliwatts to megawatts. The literature has reported on various voltage-boosting techniques, in which fundamental energy storing elements (inductors and capacitors) and/or transformers in conjunction with switch(es) and diode(s) are utilized in the circuit. These techniques include switched capacitor (charge pump), voltage multiplier, switched inductor/voltage lift, magnetic coupling, and multistage/-level, and each has its own merits and demerits depending on application, in terms of cost, complexity, power density, reliability, and efficiency. To meet the growing demand for such applications, new power converter topologies that use the above voltage-boosting techniques, as well as some active and passive components, are continuously being proposed. The permutations and combinations of the various voltage-boosting techniques with additional components in a circuit allow for numerous new topologies and configurations, which are often confusing and difficult to follow. Therefore, to present a clear picture on the general law and framework of the development of next-generation step-up dc–dc converters, this paper aims to comprehensively review and classify various step-up dc–dc converters based on their characteristics and voltage-boosting techniques. In addition, the advantages and disadvantages of these voltage-boosting techniques and associated converters are discussed in detail. Finally, broad applications of dc–dc converters are presented and summarized with comparative study of different voltage-boosting techniques.
Minimum Cross Entropy Thresholding for SAR Images

Vision plays the most important role in human perception, which is limited to only the visual band of the electromagnetic spectrum. Therefore, the need for Radar imaging systems, to recover some sources that are not within human visual band, is raised. This paper presents a new algorithm for Synthetic Aperture Radar (SAR) images segmentation based on thresholding technique. Generally, segmentation of a SAR image falls into two categories; one based on grey levels and the other based on texture. The present paper deals with SAR images segmentation based on grey levels. We developed a new formula using Minimum Cross Entropy Thresholding (MCET) method for estimating optimal threshold value based on Gamma distribution to analyzing data on images; that means histogram of SAR images is assumed to be a mixture of Gamma distributions. The proposed method is iterative which decreases the number of operation to converge tends to the optimal solution. It is applied on bi-modal and multimodal scenarios. The results obtained are promising.
Taming THC: potential cannabis synergy and phytocannabinoid-terpenoid entourage effects.

Tetrahydrocannabinol (THC) has been the primary focus of cannabis research since 1964, when Raphael Mechoulam isolated and synthesized it. More recently, the synergistic contributions of cannabidiol to cannabis pharmacology and analgesia have been scientifically demonstrated. Other phytocannabinoids, including tetrahydrocannabivarin, cannabigerol and cannabichromene, exert additional effects of therapeutic interest. Innovative conventional plant breeding has yielded cannabis chemotypes expressing high titres of each component for future study. This review will explore another echelon of phytotherapeutic agents, the cannabis terpenoids: limonene, myrcene, α-pinene, linalool, β-caryophyllene, caryophyllene oxide, nerolidol and phytol. Terpenoids share a precursor with phytocannabinoids, and are all flavour and fragrance components common to human diets that have been designated Generally Recognized as Safe by the US Food and Drug Administration and other regulatory agencies. Terpenoids are quite potent, and affect animal and even human behaviour when inhaled from ambient air at serum levels in the single digits ng·mL(-1) . They display unique therapeutic effects that may contribute meaningfully to the entourage effects of cannabis-based medicinal extracts. Particular focus will be placed on phytocannabinoid-terpenoid interactions that could produce synergy with respect to treatment of pain, inflammation, depression, anxiety, addiction, epilepsy, cancer, fungal and bacterial infections (including methicillin-resistant Staphylococcus aureus). Scientific evidence is presented for non-cannabinoid plant components as putative antidotes to intoxicating effects of THC that could increase its therapeutic index. Methods for investigating entourage effects in future experiments will be proposed. Phytocannabinoid-terpenoid synergy, if proven, increases the likelihood that an extensive pipeline of new therapeutic products is possible from this venerable plant. http://dx.doi.org/10.1111/bph.2011.163.issue-7.