Miracle-dz/UniFAR-FTUs huggingface dataset:
Considering Curtailment in 110 kV Grid Planning to Mitigate Uncertainties in the Integration of Renewables

Feed-in curtailment in critical situations for the grid is one option to reduce grid expansion needs in systems with a high increase of distributed renewable energy sources (DRES). The consideration of curtailment at the planning stage furthermore offers an opportunity to handle uncertainties regarding location and capacity of DRES. This paper presents a method to assess the impact of curtailment on 110 kV grid expansion objected to regional uncertainties. Using a Monte Carlo approach, critical branches, the expected curtailed energy and the possible reduction of required grid expansion measures are determined. The results show a notable impact of regional uncertainty of DRES increase on the expected curtailed energy. Using this information, expansion measures can be assessed and optimized regarding the aforementioned uncertainties.
Assessment of spectrum-based fault localization for practical use

SOUZA, H. A. de Assessment of Spectrum-based Fault Localization for Practical Use. 2018. 146 p. Doctoral Thesis in Computer Science – Institute of Mathematics and Statistics, University of São Paulo, São Paulo, 2018. Debugging is one of the most time-consuming activities in software development. Several fault localization techniques have been proposed in the last years, aiming to reduce development costs. A promising approach, called Spectrum-based Fault localization (SFL), consists of techniques that provide a list of suspicious program elements (e.g., statements, basic blocks, methods) more likely to be faulty. Developers should inspect a suspiciousness list to search for faults. However, these fault localization techniques are not yet used in practice. These techniques are based on assumptions about the developer’s behavior when inspecting such lists that may not hold in practice. A developer is supposed to inspect an SFL list from the most to the least suspicious program elements (e.g., statements) until reaching the faulty one. This assumption leads to some implications: the techniques are assessed only by the position of a bug in a list; a bug is deemed as found when the faulty element is reached. SFL techniques should pinpoint the faulty program elements among the first picks to be useful in practice. Most techniques use ranking metrics to assign suspiciousness values to program elements executed by the tests. These ranking metrics have presented similar modest results, which indicates the need for different strategies to improve the effectiveness of SFL. Moreover, most techniques use only control-flow spectra due to the high execution costs associated with other spectra, such as data-flow. Also, little research has investigated the use of SFL techniques by practitioners. Understanding how developers use SFL may help to clarify the theoretical assumptions about their behavior, which in turn can collaborate with the proposal of techniques more feasible for practical use. Therefore, user studies are a valuable tool for the development of the area. The goal of this thesis research was to propose strategies to improve spectrum-based fault localization, focusing on its practical use. This thesis presents the following contributions. First, we investigate strategies to provide contextual information for SFL. These strategies helped to reduce the amount of code to be inspected until reaching the faults. Second, we carried out a user study to understand how developers use SFL in practice. The results show that developers can benefit from SFL to locate bugs. Third, we explore the use of data-flow spectrum for SFL. Data-flow spectrum singles out faults significantly better than control-flow spectrum, improving the fault localization effectiveness.
Automotive LiDAR performance verification in fog and rain

This article focuses on testing and investigating further development needs for LiDARs in self-driving cars in adverse weather. The article compares two different LiDARs (Ibeo Lux and Velodyne PUCK), which both use the 905 nm wavelengths, which are used in more than 95% of currently available LiDARs. The performance was tested and estimated in stabilized fog conditions at Cerema fog chamber facilities. This provides a good basis for repeating the same validation procedure multiple times and ensuring the right development decisions. However, performance of the LiDARs suffers when the weather conditions become adverse and visibility range decreases. A 50% reduction in target detection performance was observed over the exhaustive tests. Therefore, changing to higher wavelengths (1550 nm) was considered using redesigned “pre-prototype LiDAR”. The preliminary results indicate that there is no reason to not use 1550 nm wavelength, which due to eye safety regulations gives an opportunity to use 20 times more power compared to the traditional 905 nm. In order to clarify the expected benefits, additional feasibility studies are still needed.
Statistical Sensor Modelling for Autonomous Driving Using Autoregressive Input-Output HMMs

Advanced driver assistance systems (ADAS) are standard features in many vehicles today and they have been proven to significantly increase the traffic safety. This paved way for development of autonomous driving (AD). To enable this, the vehicles are equipped with many sensors such as cameras and radars in order to scan the surrounding environment. The sensor outputs are used to implement decision and control modules. Verification of AD is a challenging task and requires collecting data from at least hundreds of millions of autonomously driven miles. We are therefore interested in virtual verification methods that simulate interesting and relevant situations, so that many scenarios can be tested in parallel. Realistic simulations require accurate sensor models, and in this paper we propose a probabilistic model based on the hidden Markov model (HMM) for modelling the sequential data produced by the sensors used in ADAS and AD. Moreover, we propose an efficient way to estimate parameters that scales well to big data sets. The results show that extending the HMM to use autoregression and input dependent transition probabilities is important in order to model the sensor characteristics and substantially improves the performance.
Interspecies Hybridisation and Genome Chimerisation in Saccharomyces: Combining of Gene Pools of Species and Its Biotechnological Perspectives

Over the last one and a half decade, interspecies hybridisation has gained continuously increasing attention as a breeding technique suitable for transferring of genetic information between Saccharomyces species and mixing of their gene pools without genetic engineering. The hybrids frequently show positive transgressive phenotypes. Segregation of the hybrid genome results in mosaic (chimeric) strains that can outperform both the parents and the hybrids or exhibit novel positive phenotypic properties. Mitotic segregation can take place during the vegetative propagation of the sterile allodiploid hybrid cells. Meiotic segregation becomes possible after genome duplication (tetraploidisation) if it is followed by break-down of sterility. The allotetraploid cells are seemingly fertile because they form viable spores. But because of the autodiploidisation of the meiosis, sterile allodiploid spores are produced and thus the hybrid genome does not segregate (the second sterility barrier). However, malsegregation of MAT-carrying chromosomes in one of the subgenomes during allotetraploid meiosis (loss of MAT heterozygosity) results in fertile alloaneuploid spores. The breakdown of (the second) sterility barrier is followed by the loss of additional chromosomes in rapid succession and recombination between the subgenomes. The process (genome autoreduction in meiosis or GARMe) chimerises the genome and generates strains with chimeric (mosaic) genomes composed of various combinations of the genes of the parental strains. Since one of the subgenomes is preferentially reduced, the outcome is usually a strain having an (almost) complete genome from one parent and only a few genes or mosaics from the genome of the other parent. The fertility of the spores produced during GARMe provides possibilities also for introgressive backcrossing with one or the other parental strain, but genome chimerisation and gene transfer through series of backcrosses always with the same parent is likely to be less efficient than through meiotic or mitotic genome autoreduction. Hybridisation and the evolution of the hybrid genome (resizing and chimerisation) have been exploited in the improvement of industrial strains and applied to the breeding of new strains for specific purposes. Lists of successful projects are shown and certain major trends are discussed.
A matching based clustering algorithm for categorical data

Cluster analysis is one of the essential tasks in data mining and knowledge discovery. Each type of data poses unique challenges in achieving relatively efficient partitioning of the data into homogeneous groups. While the algorithms for numeric data are relatively well studied in the literature, there are still challenges to address in case of categorical data. The main issue is the unordered structure of categorical data, which makes the implementation of the standard concepts of clustering algorithms difficult. For instance, the assessment of distance between objects, the selection of representatives for categorical data is not as straightforward as for continuous data. Therefore, this paper presents a new framework for partitioning categorical data, which does not use the distance measure as a key concept. The Matching based clustering algorithm is designed based on the similarity matrix and a framework for updating the latter using the feature importance criteria. The experimental results show this algorithm can serve as an alternative to existing ones and can be an efficient knowledge discovery tool.
Secure Transmission to the Strong User in Non-Orthogonal Multiple Access

With non-orthogonal multiple access (NOMA) in a passive eavesdropping scenario, we tackle the maximization of the secrecy rate for the strong user subject to a maximum allowable secrecy outage probability while guaranteeing a constraint on the transmission rate to the weak user. For the first time, the dependence between the eavesdropper’s ability to conduct successive interference cancellation and her channel quality is considered. We determine the exact optimal power allocation and redundancy rate, based on which the cost of security in terms of the reduction in the strong user’s secrecy rate is examined, and the benefits of NOMA for secure transmissions are revealed.
Speckle Reduction for Long Distance Fourier Ptychography Using Truncated Amplitude Flow and Filtering

Fourier Ptychography (FP) is a new method for long-distance, sub-diffraction imaging. However, due to the coherence of laser-illumination and the scattering of the objects' surface, there will be obvious laser speckle noise in measured images. In this work, we reconstruct the high-resolution image following two steps: the first step is to recover the Fourier spectrum using truncated amplitude flow algorithm, and the second step is to enhance the noisy recovered images using denoisers during reconstruction. It's demonstrated that this method can effectively suppress speckle noise, improve PSNR about 7dB and improve SSIM about 0.2 compared with other algorithms.
Interpersonal Coordination in Soccer: Interpreting Literature to Enhance the Representativeness of Task Design, From Dyads to Teams

Interpersonal coordination in soccer has become a trending topic in sports sciences, and several studies have examined how interpersonal coordination unfolds at different levels (i.e., dyads, sub-groups, teams). Investigations have largely focused on interactional behaviors at micro and macro levels through tasks from dyadic (i.e., 1 vs. 1) to team (i.e., 11 vs. 11) levels. However, as the degree of representativeness of a task depends on the magnitude of the relationship between simulated and intended environments, it is necessary to address a discussion on the correspondence between competitive and practice/experimental settings in soccer. The aims of this paper are to: (i) provide a brief description of the main concepts underlying the subject of interpersonal coordination in sports teams; (ii) demonstrate, through exemplar research findings, how interpersonal coordination in soccer unfolds at different scales; and (iii), discuss how coaches and researchers may ensure representativeness for practice and experimental tasks. We observed that papers addressing the analysis of interpersonal coordination tendencies in soccer often resort to dyadic (one vs. one) or sub-group (many vs. many) experimental tasks, instead of full-sized (11 vs. 11) games. Consequently, the extent to which such patterns reflect those observed in competition is somewhat uncertain. The design of practice and/or experimental tasks that rely on sub-phases of the game (e.g., 1 vs. 1, 4 vs. 4) should ensure the preservation of players’ behavior patterns in intended match conditions (11 vs. 11). This can be accomplished by measuring the level of action fidelity of the task, ensuring correspondence and successful transfer across contexts.
SmartOTPs: An Air-Gapped 2-Factor Authentication for Smart-Contract Wallets

With the recent rise of cryptocurrencies' popularity, the security and management of crypto-tokens have become critical. We have witnessed many attacks on users and providers, which have resulted in significant financial losses. To remedy these issues, several wallet solutions have been proposed. However, these solutions often lack either essential security features, usability, or do not allow users to customize their spending rules. In this paper, we propose SmartOTPs, a smart-contract wallet framework that gives a flexible, usable, and secure way of managing crypto-tokens in a self-sovereign fashion. The proposed framework consists of four components (i.e., an authenticator, a client, a hardware wallet, and a smart contract), and it provides 2-factor authentication (2FA) performed in two stages of interaction with the blockchain. To the best of our knowledge, our framework is the first one that utilizes one-time passwords (OTPs) in the setting of the public blockchain. In SmartOTPs, the OTPs are aggregated by a Merkle tree and hash chains whereby for each authentication only a short OTP (e.g., 16B-long) is transferred from the authenticator to the client. Such a novel setting enables us to make a fully air-gapped authenticator by utilizing small QR codes or a few mnemonic words, while additionally offering resilience against quantum cryptanalysis. We have made a proof-of-concept based on the Ethereum platform. Our cost analysis shows that the average cost of a transfer operation is comparable to existing 2FA solutions using smart contracts with multi-signatures.
Different Traffic Density Connectivity Probability Analysis in VANETs with Measured Data at 5.9 GHz

This paper finds the matched path loss models under three kinds of traffic flow conditions: high, medium and low traffic density based on the analysis of measured vehicle-to-vehicle (V2V) data at 5.9 GHz. We use the data of different traffic conditions in the Vehicular Ad Hoc Networks (VANETs) model to simulate the connectivity of VANETs. After simulating, the VANETs connectivity under different traffic flows based on the measured data is obtained as well as the obstruction considered effective communication coverage. The results show that the integrated VANETs connectivity model based on measured data can accurately reflect the V2V communication environment under real conditions.
Multi-Hypothesis Multi-Model Driver's Gaze Target Tracking

For a safe handover of the driving task or driver-adaptive warning strategies the driver's situation awareness is a helpful source of information. In order to estimate and track the driver's focus of attention over time in a dynamic automotive scene, a Multi-Hypothesis Multi-Model probabilistic tracking framework was developed in which we postulate consistency between machine and human perception during gaze fixations. Within this framework, we explicitly included target object motion in the spatial transition step and integrated spatiotemporal models of human-like gaze behavior for fixations and saccades in the motion transition. This elaborate design makes the target estimation robust and yet flexible. At the same time, the representation in continuous 2D coordinates makes the algorithm run in real time on a standard laptop. By incorporating dynamic and static potential gaze targets from an object list and a free space spline, the algorithm is in principle independent from the applied sensor setup. The benefit of the proposed model is presented on real world data where the filter's tracking performance as well as the driver's visual sampling are presented based on an exemplary scene.
Photobiomodulation at Multiple Wavelengths Differentially Modulates Oxidative Stress In Vitro and In Vivo

Photobiomodulation (PBM) is emerging as an effective strategy for the management of multiple inflammatory conditions, including oral mucositis (OM) in cancer patients who receive chemotherapy or radiotherapy. Still, the poor understanding of the mechanisms by which the light interacts with biological tissues and the heterogeneity of light sources and protocols employed worldwide significantly limits its applicability. Reactive oxygen species (ROS) are massively generated during the early phases of OM and play a major role in the pathogenesis of inflammation in general. Here, we report the results of a clinical and experimental study, aimed at evaluating the effect of laser light at different wavelengths on oxidative stress in vivo in oncologic patients suffering from OM and in vitro in two cell types abundantly present within the inflamed oral mucosa, neutrophil polymorphonuclear (PMN) granulocytes, and keratinocytes. In addition to standard ROS detection methods, we exploited a roGFP2-Orp1 genetically encoded sensor, allowing specific, quantitative, and dynamic imaging of redox events in living cells in response to oxidative stress and PBM. We found that the various wavelengths differentially modulate ROS production. In particular, the 660 nm laser light increases ROS production when applied either before or after an oxidative stimulus. In contrast, the 970 nm laser light exerted a moderate antioxidant activity both in the saliva of OM patients and in both cell types. The most marked reduction in the levels of ROS was detected in cells exposed either to the 800 nm laser light or to the combination of the three wavelengths. Overall, our study demonstrates that PBM exerts different effects on the redox state of both PMNs and keratinocytes depending on the used wavelength and prompts the validation of a multiwavelength protocol in the clinical settings.
Relationship of External Field Strength With Local and Whole-Body Averaged Specific Absorption Rates in Anatomical Human Models

The International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines and the IEEE C95.1 standard are currently under revision. In the guidelines/standard, the dominant effect for electromagnetic field exposures at frequencies above 100 kHz is the thermal effect. The whole-body-and 10g-averaged specific absorption rates (SARs), which are surrogates for core and local temperature elevations, respectively, are set as metrics for exposure evaluation. The external field strengths or incident power density, corresponding to the limit for SARs, are also used as metrics for practical compliance purposes. Although the limits for the SARs are identical amongst the guidelines/standard, the limits for the external field strengths differ by a factor of 7.4–12.9 in an intermediate frequency range (100 kHz–100 MHz). Due to the fact that the standard/guidelines were published before the computation with anatomical human models was available, it is worth revisiting the relationship between the SARs and external field strengths by computations using the human models. Intercomparison using different numerical codes was also performed to verify the results. For the main finding, as expected, the 10g-averaged SAR was a less restrictive factor for whole-body exposure over the frequencies considered in this paper. It was also found that the relationship between SARs and external field strength was satisfied, but was more conservative in the ICNIRP guidelines, whereas there were slight discrepancies below 30 MHz in the IEEE standard. The computational results would be useful for revising the permissible external field strength based on scientific results.
A Robot for Reconstructing Presentation Behavior in Lecture

In universities, lecturers often use presentation slides to present their lecture contents with non-verbal behavior involving paralanguage, gaze and gesture, which is so important for promoting learners' understanding. However, it is not simple for the lecturers to appropriately control non-verbal behavior depending on the lecture contents. This paper proposes a lecture robot, which substitutes for lecturers, and which reconstructs their non-verbal behavior conducted in their lecture. Towards such reconstruction, we have designed a model of presentation behavior in lecture. This paper also demonstrates a lecture robot system, which detects insufficient/inappropriate behavior to reconstruct and reproduce by following the presentation behavior model. In addition, this paper reports a case study using the system with 31 participants, whose purpose was to compare the video-recorded lecture conducted by a lecturer and the lecture reconstructed by the robot system. The results indicate that gaze, face direction, and pointing gesture for keeping and controlling learners' attention reconstructed by the lecture robot are more acceptable and understandable. It is also suggested that the robot could promote their concentration by means of eye contact with them, and that it has a potential to promote their understanding of the lecture contents.
Zero Initialization of modified Gated Recurrent Encoder-Decoder Network for Short Term Load Forecasting

Single layer Feedforward Neural Network(FNN) is used many a time as a last layer in models such as seq2seq or could be a simple RNN network. The importance of such layer is to transform the output to our required dimensions. When it comes to weights and biases initialization, there is no such specific technique that could speed up the learning process. We could depend on deep network initialization techniques such as Xavier or He initialization. But such initialization fails to show much improvement in learning speed or accuracy. In this paper we propose Zero Initialization (ZI) for weights of a single layer network. We first test this technique with on a simple RNN network and compare the results against Xavier, He and Identity initialization. As a final test we implement it on a seq2seq network. It was found that ZI considerably reduces the number of epochs used and improve the accuracy. The developed model has been applied for short-term load forecasting using the load data of Australian Energy Market. The model is able to forecast the day ahead load accurately with error of 0.94%.