nils-herrmann/clean_scirepeval huggingface dataset:
Sparse Higher-Order Principal Components Analysis

Traditional tensor decompositions such as the CANDECOMP / PARAFAC (CP) and Tucker decompositions yield higher-order principal components that have been used to understand tensor data in areas such as neuroimaging, microscopy, chemometrics, and remote sensing. Sparsity in high-dimensional matrix factorizations and principal components has been well-studied exhibiting many benefits; less attention has been given to sparsity in tensor decompositions. We propose two novel tensor decompositions that incorporate sparsity: the Sparse Higher-Order SVD and the Sparse CP Decomposition. The latter solves an `1-norm penalized relaxation of the single-factor CP optimization problem, thereby automatically selecting relevant features for each tensor factor. Through experiments and a scientific data analysis example, we demonstrate the utility of our methods for dimension reduction, feature selection, signal recovery, and exploratory data analysis of high-dimensional tensors.
ProM: The Process Mining Toolkit

Nowadays, all kinds of information systems store detailed information in logs. Process mining has emerged as a way to analyze these systems based on these detailed logs. Unlike classical data mining, the focus of process mining is on processes. First, process mining allows us to extract a process model from an event log. Second, it allows us to detect discrepancies between a modeled process (as it was envisioned to be) and an event log (as it actually is). Third, it can enrich an existing model with knowledge derived from an event log. This paper presents our tool ProM, which is the world-leading tool in the area of process mining.
Chapter 2 Depression and a Stepped Care Model

Given the public health significance of depression and the limited resources available for providing evidence-based treatment, there is a need to develop effective models of care to reduce the personal and societal costs of the disorder. Within stepped care service provisions, all patients presenting with symptoms of depression generally are first offered the lowest intensity and least intrusive intervention deemed necessary following assessment and triage. Only when patients do not show improvement do they move to higher, more intensive levels of care. However, stepped care models also provide information to aid clinicians in decision making regarding selection of treatment strategies that are most appropriate for an individual patient. For some individuals, lower levels of care would never be appropriate or may not be preferred by the consumer. Thus, stepped interventions offer a variety of treatment options to match the intensity of the patient’s presenting problem as well as potential patient preference. In this chapter, we discuss various strategies for treating depression consistent with a stepped model of care beginning with least intensive treatment and then moving up through the hierarchy of steps of care. While this is not a comprehensive review of all available treatments for depression, the chapter is designed to make clinicians aware of specific strategies for addressing depressive symptoms and to provide guidance about resources available at the various levels of care.
Anonymous voting by two-round public discussion

In 2006, Hao and Zieliński proposed a two-round anonymous veto protocol (called AV-net), which provided exceptional efficiency compared to related techniques. In this study, the authors add a self-tallying function to the AV-net, making it a general-purpose voting protocol. The new protocol works in the same setting as the AV-net – it requires no trusted third parties or private channels, and participants execute the protocol by sending two-round public messages. Compared with related voting protocols in past work, this is significantly more efficient in terms of the number of rounds, computational cost and bandwidth usage.
Joint state and measurement time-delay estimation of nonlinear state space systems

Sensor fusion algorithms often assume perfect time synchronization of the sensor clocks. In a practical sensoractuator setup this is often difficult to achieve which in turn can give rise to systematic errors in the sensor fusion. In this article we suggest how the effect of the synchronization error from an unknown static or slowly varying measurement time-delays in a nonlinear state space system can be handled by linearizing the measurement equation in time. Based on the linearization an augmented system is constructed from which the system states and the delays can be jointly estimated. Expressions for the system, measurement, and covariance matrices of the augmented system are derived. Finally, the feasibility of the suggested approach is demonstrated by an example and a Monte-Carlo simulation.
RFID Localisation For Internet Of Things Smart Homes: A Survey

The Internet of Things (IoT) enables numerous business opportunities in fields as diverse as e-health, smart cities, smart homes, among many others. The IoT incorporates multiple long-range, short-range, and personal area wireless networks and technologies into the designs of IoT applications. Localisation in indoor positioning systems plays an important role in the IoT. Location Based IoT applications range from tracking objects and people in real-time, assets management, agriculture, assisted monitoring technologies for healthcare, and smart homes, to name a few. Radio Frequency based systems for indoor positioning such as Radio Frequency Identification (RFID) is a key enabler technology for the IoT due to its costeffective, high readability rates, automatic identification and, importantly, its energy efficiency characteristic. This paper reviews the state-of-the-art RFID technologies in IoT Smart Homes applications. It presents several comparable studies of RFID based projects in smart homes and discusses the applications, techniques, algorithms, and challenges of adopting RFID technologies in IoT smart home
A Broadband Planar Monopulse Antenna Array of C-Band

In this letter, a broadband planar monopulse antenna array of C-band for the application of monopulse radars is presented. A novel wideband monopulse comparator as the sum-difference feed network has been designed, and a multilayer 4 × 4 microstrip antenna array as the radiation part has been fabricated. The measurement results demonstrate that the impedance bandwidth (VSWR ¿ 2) of the proposed monopulse antenna array is up to 28.2% and the null depth can reach -28 dB, which ranges from 5.05 to 6.675 GHz. At the same time, the peak sum beam gain is up to 18.4 dB. Compared to other monopulse antennas, the proposed monopulse antenna array exhibits excellent characteristics.
Amplitude Modulated Video Camera - Light Separation in Dynamic Scenes

Controlled light conditions improve considerably the performance of most computer vision algorithms. Dynamic light conditions create varying spatial changes in color and intensity across the scene. These condition, caused by a moving shadow for example, force developers to create algorithms which are robust to such variations. We suggest a computational camera which produces images that are not influenced by environmental variations in light conditions. The key insight is that many years ago, similar difficulties were already solved in radio communication, As a result each channel is immune to interference from other radio channels. Amplitude Modulated (AM) video camera separates the influence of a modulated light from other unknown light sources in the scene, Causing the AM video camera frame to appear the same - independent of the light conditions in which it was taken. We built a prototype of the AM video camera by using off the shelf hardware and tested it. AM video camera was used to demonstrate color constancy, shadow removal and contrast enhancement in real time. We show theoretically and empirically that: 1. the proposed system can produce images with similar noise levels as a standard camera. 2. The images created by such camera are almost completely immune to temporal, spatial and spectral changes in the background light.
A 61 GHz frequency synthesizer in SiGe BiCMOS for 122 GHz FMCW radar

In this paper, a fractional-N phase-locked loop (PLL) with an integrated chirp generation circuit block for frequency-modulated continuous-wave (FMCW) radar systems is reported. The circuit is composed of a push-push voltage controlled oscillator (VCO), a feedback divider including pre-scaler and programmable divider stages, a phase-frequency detector followed by a current steering charge pump, a sigma-delta modulator (SDM) with an 18-bit resolution, a chirp generator and a serial-peripheral-interface (SPI) for programming the chirp generator. The circuit occupies an area of 2.6 mm2, consumes 310 mW from a 3.3 V voltage supply. In integer-N mode, the PLL phase noise is better than -95 dBc/Hz at 1 MHz offset from 60 GHz center frequency. The rms frequency error is 134 kHz when the chirp slope is 0.4 GHz / 1.28 ms. The circuit is fabricated in a 0.13 μm SiGe BiCMOS technology. It is well suited for sub-harmonic transceiver frontend of an FMCW radar system at 122GHz and offers full programmability in ramp type, ramp duration and ramp bandwidth.
Path selection based on local terrain feature for unmanned ground vehicle in unknown rough terrain environment

In this paper, we propose an autonomous navigation for Unmanned Ground Vehicles (UGVs) by a path selection method based on local features of terrain in unknown outdoor rough terrain environment. The correlation between a local terrain feature obtained from a path and a value of the path obtained from the global path planning is extracted in advance. When UGV comes to a branch while it is running, the value of path is estimated using the correlation with local terrain feature. Thereby, UGV navigation is performed by path selection under the criterion of shortest time in unknown outdoor environment. We experimented on a simulator and confirmed that the proposed method can select more effective paths in comparison with a simple path selection method.
Confidence intervals in within-subject designs: A simpler solution to Loftus and Masson's method

Within-subject ANOVAs are a powerful tool to analyze data because the variance associated to differences between the participants is removed from the analysis. Hence, small differences, when present for most of the participants, can be significant even when the participants are very different from one another. Yet, graphs showing standard error or confidence interval bars are misleading since these bars include the between-subject variability. Loftus and Masson (1994) noticed this fact and proposed an alternate method to compute the error bars. However, i) their approach requires that the ANOVA be performed first, which is paradoxical since a graph is an aid to decide whether to perform analyses or not; ii) their method provides a single error bar for all the conditions, masking information such as the heterogeneity of variances across conditions; iii) the method proposed is difficult to implement in commonly-used graphing software. Here we propose a simple alternative and sow how it can be implemented in SPSS.
Evaluation of mobile app paradigms

The explosion of mobile applications both in number and variety raises the need of shedding light on their architecture, composition and quality. Indeed, it is crucial to understand which mobile application paradigm fits better to what type of application and usage. Such understanding has direct consequences on the user experience, the development cost and sale revenues of mobile apps. In this paper, we identified four main mobile application paradigms and evaluated them from the developer, user and service provider viewpoints. To ensure objectivity and soundness we start by defining high level criteria and then breaking down in finer-grained criteria. After a theoretical evaluation an implementation was carried out as a practical verification. The selected application is object recognition app, which is both exciting and challenging to develop.
Flux-Weakening Control of Electric Starter–Generator Based on Permanent-Magnet Machine

This paper presents the control analysis and design for a permanent-magnet machine (PMM) operated in the flux-weakening (FW) mode for an aircraft electric starter–generator (SG) application. Previous literature has focused on FW control of PMMs in the motoring (starting) mode; however, the system stability and control in the generating mode have been inadequately studied. This paper reports detailed, rigorous control analysis and design for a PMM-based aircraft electric SG operated in the FW mode. It is shown that an unstable area of operation exists. A novel control scheme which eliminates this instability is proposed. The key analytical findings of the paper are verified by experimental investigation. This paper therefore concludes that the presented technique is able to ensure system stability under all modes of operation. Furthermore, it is noted that the findings of this work are also valuable for any two-quadrant PMM drive with frequent change between starting and generating regimes under current-limiting operation.
Phylogenetic relationships in Opuntia (Cactaceae, Opuntioideae) from southern South America

The patterns of relationships between species of Opuntia from southern South America are scarcely known in spite of the importance of this region as a diversification center for the Cactaceae. This paper contributes to the better understanding of the genetic and phylogenetic relationships of 15 Opuntia species from Argentina, Bolivia, Brazil, Paraguay, and Uruguay by generating new genetic data through Inter-Simple Sequence Repeat (ISSR) genotyping and the sequencing of plastid intergenic spacers trnL-trnF and psbJ-petA. The species surveyed are: O. anacantha, O. arechavaletae, O. aurantiaca, O. bonaerensis, O. colubrina, O. discolor, O. elata, O. megapotamica, O. monacantha, O. penicilligera, O. quimilo, O. salmiana, O. schickendantzii, O. sulphurea, and O. ventanensis. The genetic distance-based analysis of 110 ISSR bands, applying the Neighbor-Joining and NeighborNet algorithms, evidenced considerable intraspecific variation in O. aurantiaca, O. elata, O. discolor, and O. salmiana. The emergent clustering pattern and the species assignment to taxonomic series show a general agreement for Armatae and Aurantiacae. The phylogenetic relationships were investigated via haplotype network and maximum likelihood approaches, within a broader sampling that involves most species currently accepted for South America, and samples from throughout the American continent. Hence, 15 haplotypes are recognized for southern South American opuntias whereas eight haplotypes are established for Northern Hemisphere opuntias. Biparentally and maternally inherited genetic data yield partially consistent results, giving genetic support for morphologically defined taxonomic series.
Finding an emotional face in a crowd: emotional and perceptual stimulus factors influence visual search efficiency.

In this article, we examine how emotional and perceptual stimulus factors influence visual search efficiency. In an initial task, we run a visual search task, using a large number of target/distractor emotion combinations. In two subsequent tasks, we then assess measures of perceptual (rated and computational distances) and emotional (rated valence, arousal and potency) stimulus properties. In a series of regression analyses, we then explore the degree to which target salience (the size of target/distractor dissimilarities) on these emotional and perceptual measures predict the outcome on search efficiency measures (response times and accuracy) from the visual search task. The results show that both emotional and perceptual stimulus salience contribute to visual search efficiency. The results show that among the emotional measures, salience on arousal measures was more influential than valence salience. The importance of the arousal factor may be a contributing factor to contradictory history of results within this field.
A 12-bit 1.6 GS/s interleaved SAR ADC with dual reference shifting and interpolation achieving 17.8 fJ/conv-step in 65nm CMOS

A 12-bit SAR ADC architecture with dual reference shifting and interpolation technique has been proposed and implemented with 8-way time interleaving in 65nm CMOS. The proposed technique converts 4 bits per SAR conversion cycle with reduced overhead, which is a key to achieve both high speed and resolution while maintaining low power consumption. The measured peak SNDR is 72dB and remains above 65.3dB at 1-GHz input frequency at sample rate of 1.6 GS/s. It achieves a record power efficiency of 17.8fJ/conv-step among the recently published high-speed/resolution ADCs.
Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph

While conversing with chatbots, humans typically tend to ask many questions, a significant portion of which can be answered by referring to large-scale knowledge graphs (KG). While Question Answering (QA) and dialog systems have been studied independently, there is a need to study them closely to evaluate such real-world scenarios faced by bots involving both these tasks. Towards this end, we introduce the task of Complex Sequential QA which combines the two tasks of (i) answering factual questions through complex inferencing over a realistic-sized KG of millions of entities, and (ii) learning to converse through a series of coherently linked QA pairs. Through a labor intensive semi-automatic process, involving in-house and crowdsourced workers, we created a dataset containing around 200K dialogs with a total of 1.6M turns. Further, unlike existing large scale QA datasets which contain simple questions that can be answered from a single tuple, the questions in our dialogs require a larger subgraph of the KG. Specifically, our dataset has questions which require logical, quantitative, and comparative reasoning as well as their combinations. This calls for models which can: (i) parse complex natural language questions, (ii) use conversation context to resolve coreferences and ellipsis in utterances, (iii) ask for clarifications for ambiguous queries, and finally (iv) retrieve relevant subgraphs of the KG to answer such questions. However, our experiments with a combination of state of the art dialog and QA models show that they clearly do not achieve the above objectives and are inadequate for dealing with such complex real world settings. We believe that this new dataset coupled with the limitations of existing models as reported in this paper should encourage further research in Complex Sequential QA.
Hardware Acceleration of OpenSSL Cryptographic Functions for High-Performance Internet Security

The Transport Layer Security (TLS) protocol is currently the predominant method of implementing Internet security. This paper proposes an FPGA-based embedded system integrating hardware that accelerates the cryptographic algorithms used in the SSL/TLS protocol. OpenSSL, an open source implementation of the SLL v3 and TLS v1 protocol, is deployed in the proposed embedded system powered with a Nios-2 embedded soft-core processor. Nios2-Linux RTOS is applied, which serves to provide Ethernet connectivity, multitasking, and support for the OpenSSL library. Key cipher functions used in SSL-driven connections, which include AES-256 symmetric encryption, SHA-2 hashing, RSA-2048 publickey cryptography, are accelerated in hardware. The embedded cryptosystem is prototyped completely on an Altera Stratix II FPGA development board. Experimental results show significant improvements in performance of the SSL transactions when the proposed embedded cryptosystem is deployed in the networking system.
A 4-GHz All Digital PLL With Low-Power TDC and Phase-Error Compensation

This paper presents a 4-GHz all-digital fractional-N PLL with a low-power TDC operating at low-rate retimed reference clocks, a compensator preventing big phase-error downfalls, and a loop settling monitor. Two retimed reference clocks, nCKR and pCKR, are employed in the TDC to estimate the fractional phase error between the low-rate reference and high-rate oscillator clocks. Applying the retimed reference clocks does not only reduce a dynamic power in its delay chain, but simplify a fractional phase-error correction. The phase-error compensator is introduced to avoid big phase-error downfalls caused by large output glitches originating from a high-speed accumulator. In addition, a loop-settling monitor is invented to allow the DCO operation mode to be shifted seamlessly and fast. By consuming 9.6 mW, the ADPLL achieves -97 dBc in-band phase noise, - 38 dBc/Hz integrated noise, and 740 ns settling time.
A Forensic Analysis of the CASIA-Iris V 4 Database

The photo response non-uniformity (PRNU) of a digital image sensor can be useful to enhance a biometric systems security by ensuring the authenticity and integrity of the images acquired with the biometric sensor, i.e. by identifying the image source or detecting a possible tampering of the images presented to the biometric system. Passive image forensic techniques have shown to be suited for this tasks for digital consumer cameras. Previous studies regarding the feasibility of this application using biometric sensors have been conducted for iris and fingerprint sensors by studying the differentiability of the sensors PRNU fingerprints. The results obtained on the CASIA-Iris V4 database showed a high variation among the various subsets of the database. The researchers assumed that this high variation could either be caused by the highly correlated data or come from the usage of different sensors for the acquisition of the subsets. To investigate the latter issue a forensic investigation on the CASIA-Iris V4 database has been performed in this thesis, where an existing forensic technique has been applied and additionally several novel forensic techniques have been proposed to detect the presence of images from multiple sensors in the image data sets. Furthermore, the forensic techniques have been applied on a test data set with a known number of sensors first to evaluate their performance. Since there is no specific documentation on the number of sensors used for the acquisition, the investigation on the CASIA-Iris V4 database has been conducted in a blind manner and without any a priori knowledge about the sensors. In addition different PRNU enhancement approaches have been applied for the investigation to reduce the contamination of the PRNU fingerprints by the image content, which is an issue in this scenario due to the strong correlation of the content among all images under investigation.
Propulsion Drive Models for Full Electric Marine Propulsion Systems

Integrated full electric propulsion systems are being introduced across both civil and military marine sectors. Standard power systems analysis packages cover electrical and electromagnetic components, but have limited models of mechanical subsystems and their controllers. Hence electromechanical system interactions between the prime movers, power network and driven loads are poorly understood. This paper reviews available models of the propulsion drive system components: the power converter, motor, propeller and ship. Due to the wide range of time-constants in the system, reduced order models of the power converter are required. A new model using state-averaged models of the inverter and a hybrid model of the rectifier is developed to give an effective solution combining accuracy with speed of simulation and an appropriate interface to the electrical network model. Simulation results for a typical ship manoeuvre are presented.