nils-herrmann/clean_scirepeval huggingface dataset:
Mouse Trap: Exploiting Firmware Updates in USB Peripherals

Although many users are aware of the threats that malware pose, users are unaware that malware can infect peripheral devices. Many embedded devices support firmware update capabilities, yet they do not authenticate such updates; this allows adversaries to infect peripherals with malicious firmware. We present a case study of the Logitech G600 mouse, demonstrating attacks on networked systems which are also feasible against airgapped systems. If the target machine is air-gapped, we show that the Logitech G600 has enough space available to host an entire malware package inside its firmware. We also wrote a file transfer utility that transfers the malware from the mouse to the target machine. If the target is networked, the mouse can be used as a persistent threat that updates and reinstalls malware as desired. To mitigate these attacks, we implemented signature verification code which is essential to preventing malicious firmware from being installed on the mouse. We demonstrate that it is reasonable to include such signature verification code in the bootloader of the mouse.
Time-series Extreme Event Forecasting with Neural Networks at Uber

Accurate time-series forecasting during high variance segments (e.g., holidays), is critical for anomaly detection, optimal resource allocation, budget planning and other related tasks. At Uber accurate prediction for completed trips during special events can lead to a more efficient driver allocation resulting in a decreased wait time for the riders. State of the art methods for handling this task often rely on a combination of univariate forecasting models (e.g., Holt-Winters) and machine learning methods (e.g., random forest). Such a system, however, is hard to tune, scale and add exogenous variables. Motivated by the recent resurgence of Long Short Term Memory networks we propose a novel endto-end recurrent neural network architecture that outperforms the current state of the art event forecasting methods on Uber data and generalizes well to a public M3 dataset used for time-series forecasting competitions.
Mathematical model to assess the control of Aedes aegypti mosquitoes by the sterile insect technique.

We propose a mathematical model to assess the effects of irradiated (or transgenic) male insects introduction in a previously infested region. The release of sterile male insects aims to displace gradually the natural (wild) insect from the habitat. We discuss the suitability of this release technique when applied to peri-domestically adapted Aedes aegypti mosquitoes which are transmissors of Yellow Fever and Dengue disease.
Can a “poor” verification system be a “good” identification system? A preliminary study

The matching accuracy of a biometric system is typically quantified through measures such as the False Match Rate (FMR), False Non-match Rate (FNMR), Equal Error Rate (EER), Receiver Operating Characteristic (ROC) curve and Cumulative Match Characteristic (CMC) curve. In this work, we analyze the relationship between the ROC and CMC curves, which are two measures commonly used to describe the performance of verification and identification systems, respectively. We establish that it is possible for a biometric system to exhibit “good” verification performance and “poor” identification performance (and vice versa) by demonstrating the conditions required to produce such outcomes. Experimental analysis using synthetically generated match scores confirms our hypothesis that the ROC or CMC alone cannot completely characterize biometric system performance.
Identification and Detection of Phishing Emails Using Natural Language Processing Techniques

Phishing refers to fraudulent social engineering techniques used to elicit sensitive information from unsuspecting victims. In this paper, our scheme is aimed at detecting phishing mails which do not contain any links but bank on the victim's curiosity by luring them into replying with sensitive information. We exploit the common features among all such phishing emails such as non-mentioning of the victim's name in the email, a mention of monetary incentive and a sentence inducing the recipient to reply. This textual analysis can be further combined with header analysis of the email so that a final combined evaluation on the basis of both these scores can be done. We have shown that this method is far better than the existing Phishing Email Detection techniques as this covers emails without links while the pre-existing methods were based on the presumption of link(s).
Parametric Voice Conversion Based on Bilinear Frequency Warping Plus Amplitude Scaling

Voice conversion methods based on frequency warping followed by amplitude scaling have been recently proposed. These methods modify the frequency axis of the source spectrum in such manner that some significant parts of it, usually the formants, are moved towards their image in the target speaker's spectrum. Amplitude scaling is then applied to compensate for the differences between warped source spectra and target spectra. This article presents a fully parametric formulation of a frequency warping plus amplitude scaling method in which bilinear frequency warping functions are used. Introducing this constraint allows for the conversion error to be described in the cepstral domain and to minimize it with respect to the parameters of the transformation through an iterative algorithm, even when multiple overlapping conversion classes are considered. The paper explores the advantages and limitations of this approach when applied to a cepstral representation of speech. We show that it achieves significant improvements in quality with respect to traditional methods based on Gaussian mixture models, with no loss in average conversion accuracy. Despite its relative simplicity, it achieves similar performance scores to state-of-the-art statistical methods involving dynamic features and global variance.
A Formal Security Analysis of the Signal Messaging Protocol

Signal is a new security protocol and accompanying app that provides end-to-end encryption for instant messaging. The core protocol has recently been adopted by WhatsApp, Facebook Messenger, and Google Allo among many others, the first two of these have at least 1 billion active users. Signal includes several uncommon security properties (such as "future secrecy" or "post-compromise security"), enabled by a novel technique called ratcheting in which session keys are updated with every message sent. Despite its importance and novelty, there has been little to no academic analysis of the Signal protocol. We conduct the first security analysis of Signal's key agreement and double ratchet as a multi-stage key exchange protocol. We extract from the implementation a formal description of the abstract protocol, and define a security model which can capture the "ratcheting" key update structure. We then prove the security of Signal's core in our model, demonstrating several standard security properties. We have found no major flaws in the design, and hope that our presentation and results can serve as a starting point for other analyses of this widely adopted protocol.
Adversarial Stain Transfer for Histopathology Image Analysis

It is generally recognized that color information is central to the automatic and visual analysis of histopathology tissue slides. In practice, pathologists rely on color, which reflects the presence of specific tissue components, to establish a diagnosis. Similarly, automatic histopathology image analysis algorithms rely on color or intensity measures to extract tissue features. With the increasing access to digitized histopathology images, color variation and its implications have become a critical issue. These variations are the result of not only a variety of factors involved in the preparation of tissue slides but also in the digitization process itself. Consequently, different strategies have been proposed to alleviate stain-related tissue inconsistencies in automatic image analysis systems. Such techniques generally rely on collecting color statistics to perform color matching across images. In this work, we propose a different approach for stain normalization that we refer to as stain transfer. We design a discriminative image analysis model equipped with a stain normalization component that transfers stains across datasets. Our model comprises a generative network that learns data set-specific staining properties and image-specific color transformations as well as a task-specific network (e.g., classifier or segmentation network). The model is trained end-to-end using a multi-objective cost function. We evaluate the proposed approach in the context of automatic histopathology image analysis on three data sets and two different analysis tasks: tissue segmentation and classification. The proposed method achieves superior results in terms of accuracy and quality of normalized images compared to various baselines.
Bicycling for transportation and health: the role of infrastructure.

This paper aims to provide insight on whether bicycling for everyday travel can help US adults meet the recommended levels of physical activity and what role public infrastructure may play in encouraging this activity. The study collected data on bicycling behavior from 166 regular cyclists in the Portland, Oregon metropolitan area using global positioning system (GPS) devices. Sixty percent of the cyclists rode for more than 150 minutes per week during the study and nearly all of the bicycling was for utilitarian purposes, not exercise. A disproportionate share of the bicycling occurred on streets with bicycle lanes, separate paths, or bicycle boulevards. The data support the need for well-connected neighborhood streets and a network of bicycle-specific infrastructure to encourage more bicycling among adults. This can be accomplished through comprehensive planning, regulation, and funding.
Improved Local Search in Artificial Bee Colony using Golden Section Search

Artificial bee colony (ABC), an optimization algorithm is a recent addition to the family of population based search algorithm. ABC has taken its inspiration from the collective intelligent foraging behavior of honey bees. In this study we have incorporated golden section search mechanism in the structure of basic ABC to improve the global convergence and prevent to stick on a local solution. The proposed variant is termed as ILS-ABC. Comparative numerical results with the state-of-art algorithms show the performance of the proposal when applied to the set of unconstrained engineering design problems. The simulated results show that the proposed variant can be successfully applied to solve real life problems.
Chaotic block ciphers: from theory to practical algorithms

Digital chaotic ciphers have been investigated for more than a decade. However, their overall performance in terms of the tradeoff between security and speed, as well as the connection between chaos and cryptography, has not been sufficiently addressed. We propose a chaotic Feistel cipher and a chaotic uniform cipher. Our plan is to examine crypto components from both dynamical-system and cryptographical points of view, thus to explore connection between these two fields. In the due course, we also apply dynamical system theory to create cryptographically secure transformations and evaluate cryptographical security measures
Fast Collision Attack on MD5

We presented the first single block collision attack on MD5 with complexity of 2 MD5 compressions and posted the challenge for another completely new one in 2010. Last year, Stevens presented a single block collision attack to our challenge, with complexity of 2 MD5 compressions. We really appreciate Stevens’s hard work. However, it is a pity that he had not found even a better solution than our original one, let alone a completely new one and the very optimal solution that we preserved and have been hoping that someone can find it, whose collision complexity is about 2 MD5 compressions. In this paper, we propose a method how to choose the optimal input difference for generating MD5 collision pairs. First, we divide the sufficient conditions into two classes: strong conditions and weak conditions, by the degree of difficulty for condition satisfaction. Second, we prove that there exist strong conditions in only 24 steps (one and a half rounds) under specific conditions, by utilizing the weaknesses of compression functions of MD5, which are difference inheriting and message expanding. Third, there should be no difference scaling after state word q25 so that it can result in the least number of strong conditions in each differential path, in such a way we deduce the distribution of strong conditions for each input difference pattern. Finally, we choose the input difference with the least number of strong conditions and the most number of free message words. We implement the most efficient 2-block MD5 collision attack, which needs only about 2 MD5 compressions to find a collision pair, and show a single-block collision attack with complexity 2.
Efficient Data Compression Methods for Multidimensional Sparse Array Operations Based on the EKMR Scheme

In our previous work, we have proposed the extended Karnaugh map representation (EKMR) scheme for multidimensional array representation. In this paper, we propose two data compression schemes, EKMR Compressed Row/ Column Storage (ECRS/ECCS), for multidimensional sparse arrays based on the EKMR scheme. To evaluate the proposed schemes, we compare them to the CRS/CCS schemes. Both theoretical analysis and experimental tests were conducted. In the theoretical analysis, we analyze the CRS/CCS and the ECRS/ ECCS schemes in terms of the time complexity, the space complexity, and the range of their usability for practical applications. In experimental tests, we compare the compressing time of sparse arrays and the execution time of matrixmatrix addition and matrix-matrix multiplication based on the CRS/CCS and the ECRS/ECCS schemes. The theoretical analysis and experimental results show that the ECRS/ECCS schemes are superior to the CRS/CCS schemes for all the evaluated criteria, except the space complexity in some cases.
Lucid dreaming treatment for nightmares: a pilot study.

The goal of this pilot study was to evaluate the effects of the cognitive-restructuring technique 'lucid dreaming treatment' (LDT) on chronic nightmares. Becoming lucid (realizing that one is dreaming) during a nightmare allows one to alter the nightmare storyline during the nightmare itself.



After having filled out a sleep and a posttraumatic stress disorder questionnaire, 23 nightmare sufferers were randomly divided into 3 groups; 8 participants received one 2-hour individual LDT session, 8 participants received one 2-hour group LDT session, and 7 participants were placed on the waiting list. LDT consisted of exposure, mastery, and lucidity exercises. Participants filled out the same questionnaires 12 weeks after the intervention (follow-up).



At follow-up the nightmare frequency of both treatment groups had decreased. There were no significant changes in sleep quality and posttraumatic stress disorder symptom severity. Lucidity was not necessary for a reduction in nightmare frequency.



LDT seems effective in reducing nightmare frequency, although the primary therapeutic component (i.e. exposure, mastery, or lucidity) remains unclear.
HTTPS traffic analysis and client identification using passive SSL/TLS fingerprinting

The encryption of network traffic complicates legitimate network monitoring, traffic analysis, and network forensics. In this paper, we present real-time lightweight identification of HTTPS clients based on network monitoring and SSL/TLS fingerprinting. Our experiment shows that it is possible to estimate the User-Agent of a client in HTTPS communication via the analysis of the SSL/TLS handshake. The fingerprints of SSL/TLS handshakes, including a list of supported cipher suites, differ among clients and correlate to User-Agent values from a HTTP header. We built up a dictionary of SSL/TLS cipher suite lists and HTTP User-Agents and assigned the User-Agents to the observed SSL/TLS connections to identify communicating clients. The dictionary was used to classify live HTTPS network traffic. We were able to retrieve client types from 95.4 % of HTTPS network traffic. Further, we discussed host-based and network-based methods of dictionary retrieval and estimated the quality of the data.
Power-Loss Breakdown of a 750-V 100-kW 20-kHz Bidirectional Isolated DC–DC Converter Using SiC-MOSFET/SBD Dual Modules

This paper describes the design, construction, and testing of a 750-V 100-kW 20-kHz bidirectional isolated dual-active-bridge dc-dc converter using four 1.2-kV 400-A SiC-MOSFET/SBD dual modules. The maximum conversion efficiency from the dc-input to the dc-output terminals is accurately measured to be as high as 98.7% at 42-kW operation. The overall power loss at the rated-power (100 kW) operation, excluding the gate-drive and control circuit losses, is divided into the conduction and switching losses produced by the SiC modules, the iron and copper losses due to magnetic devices, and the other unknown loss. The power-loss breakdown concludes that the sum of the conduction and switching losses is about 60% of the overall power loss and that the conduction loss is nearly equal to the switching loss at the 100-kW and 20-kHz operation.
A CMOS Low Noise, Chopper Stabilized Low-Dropout Regulator With Current-Mode Feedback Error Amplifier

Low 1/f noise, low-dropout (LDO) regulators are becoming critical for the supply regulation of deep-submicron analog baseband and RF system-on-chip designs. A low-noise, high accuracy LDO regulator (LN-LDO) utilizing a chopper stabilized error amplifier is presented. In order to achieve fast response during load transients, a current-mode feedback amplifier (CFA) is designed as a second stage driving the regulation FET. In order to reduce clock feed-through and 1/f noise accumulation at the chopping frequency, a first-order digital SigmaDelta noise-shaper is used for chopping clock spectral spreading. With up to 1 MHz noise-shaped modulation clock, the LN-LDO achieves a noise spectral density of 32 nV/radic(Hz) and a PSR of 38 dB at 100 kHz. The proposed LDO is shown to reduce the phase noise of an integrated 32 MHz temperature compensated crystal oscillator (TCXO) at 10 kHz offset by 15 dB. Due to reduced 1/f noise requirements, the error amplifier silicon area is reduced by 75%, and the overall regulator area is reduced by 50% with respect to an equivalent noise static regulator. The current-mode feedback second stage buffer reduces regulator settling time by 60% in comparison to an equivalent power consumption voltage mode buffer, achieving 0.6 mus settling time for a 25-mA load step. The LN-LDO is designed and fabricated on a 0.25 mum CMOS process with five layers of metal, occupying 0.88 mm2.
Metcalfe's law, Web 2.0, and the Semantic Web

The power of the Web is enhanced through the network effect produced as resources link to each other with the value determined by Metcalfe’s aw. In Web 2.0 applications, much of that effect is delivered through social linkages realized via social networks online. Unfortunately, the ssociated semantics for Web 2.0 applications, delivered through tagging, is generally minimally hierarchical and sparsely linked. The Semantic eb suffers from the opposite problem. Semantic information, delivered through ontologies of varying amounts of expressivity, is linked to other erms (within or between resources) creating a link space in the semantic realm. However, the use of the Semantic Web has yet to fully realize the ocial schemes that provide the network of users. In this article, we discuss putting these together, with linked semantics coupled to linked social etworks, to deliver a much greater effect.
A 56Gb/s PAM4 wireline transceiver using a 32-way time-interleaved SAR ADC in 16nm FinFET

A 56Gb/s PAM4 wireline transceiver testchip is implemented in 16nm FinFET. The CML transmitter incorporates an auxiliary current injection at the output nodes to maintain PAM4 amplitude linearity. The receiver consists of continuous-time linear equalizers with constant DC-gain and a 28GSa/s 32-way time-interleaved SAR ADC. The transceiver achieves 1e-8 BER over a backplane channel with 25dB loss at 14GHz while consuming 550mW power, excluding DSP.
A Corpus of Natural Language for Visual Reasoning

Property-based Features Given a sentencerepresentation pair, for each property listed in Table 2, we compute if it holds for the representation. For each property that holds and for each n-gram in the sentence we trigger a feature. Consider the first example in Table 1. The features triggered for this example include touches-wall#two-boxes-have and touches-wall#touching-the-side computed from the property touches-wall and the tri-grams two boxes have and touching the side. We observe that the MaxEnt model learns a higher weight for features which combine similar properties of the world and the sentence, such as touches-wall#touching-the-side.
Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors

We propose several econometric measures of connectedness based on principalcomponents analysis and Granger-causality networks, and apply them to the monthly returns of hedge funds, banks, broker/dealers, and insurance companies. We find that all four sectors have become highly interrelated over the past decade, likely increasing the level of systemic risk in the finance and insurance industries through a complex and time-varying network of relationships. These measures can also identify and quantify financial crisis periods, and seem to contain predictive power in out-of-sample tests. Our results show an asymmetry in the degree of connectedness among the four sectors, with banks playing a much more important role in transmitting shocks than other financial institutions. & 2011 Elsevier B.V. All rights reserved.
60-GHz $2 \times 2$ LTCC Patch Antenna Array With an Integrated EBG Structure for Gain Enhancement

This letter presents a 60-GHz 2 × 2 low temperature co-fired ceramic (LTCC) aperture-coupled patch antenna array with an integrated Sievenpiper electromagnetic band-gap (EBG) structure used to suppress TM-mode surface waves. The merit of this EBG structure is to yield a predicted 4-dB enhancement in broadside directivity and gain, and an 8-dB improvement in sidelobe level. The novelty of this antenna lies in the combination of a relatively new LTCC material system (DuPont Greentape 9K7) along with laser ablation processing for fine line and fine slot definition (50-μm gaps with +/ - 6 μm tolerance) allowing the first successful integration of a Sievenpiper EBG structure with a millimeter-wave LTCC patch array. A measured broadside gain/directivity of 11.5/14 dBi at 60 GHz is achieved with an aperture footprint of only 350 × 410 mil2 (1.78λ × 2.08λ) including the EBG structure. This thin (27 mil) LTCC array is well suited for chip-scale package applications.