Miracle-dz/UniFAR-FTUs huggingface dataset:
Engaging Pedestrians in Designing Interactions with Autonomous Vehicles

Driverless Passenger Shuttles are operating as a public transport alternative in the town of Sion, Switzerland since June'16, and traversing the populated commercial and residential zones of the city center. The absence of a human driver and the lack of dedicated AV-pedestrian interface makes it challenging for road users (pedestrians, cyclists, etc.) to understand the intent or operational state of the vehicle and negotiate road usage. In this article, we present a co-design study aimed at informing the design of interactive communication means between pedestrians and autonomous vehicles (AVs). Conducted in two stages with the local community --which is accustomed to the AV's ecosystem and has interacted with it on a daily basis-- the study highlights the interactive experiences of road users, and furnishes contextualized design guidelines to bridge the communication with the pedestrians.
Design of a 40GHz Thin-Film Microstrip Sampler

This paper mainly describes a 40GHz thin-film microstrip sampler. This sampler can divided into three parts which includes an impulse generator, a balun with microstrip and slot line, a balanced sampling circuit. An improved microstrip and slot line balun is used to reduce the rise time of LO pulse. It has been successfully made and the measured result of conversion loss is about ${10\pm 3\text{dB}}$ with good frequency response. The 40GHz thin film sampler has several advantages of wide frequency band, low cost and easy to process etc. This microstrip sampler has been successfully applied to the microwave frequency counter.
Optimization of Real-World MapReduce Applications With Flame-MR: Practical Use Cases

Apache Hadoop is a widely used MapReduce framework for storing and processing large amounts of data. However, it presents some performance issues that hinder its utilization in many practical use cases. Although existing alternatives like Spark or Hama can outperform Hadoop, they require to rewrite the source code of the applications due to API incompatibilities. This paper studies the use of Flame-MR, an in-memory processing architecture for MapReduce applications, to improve the performance of real-world use cases in a transparent way while keeping application compatibility. Flame-MR adapts to the characteristics of the workloads, managing efficiently the use of custom data formats and iterative computations, while also reducing workload imbalance. The experimental evaluation, conducted in high performance clusters and the Microsoft Azure cloud, shows a clear outperformance of Flame-MR over Hadoop. In most cases, Flame-MR reduces the execution times by more than a half.
Robot active touch exploration: constraints and strategies

The problem of using active touch (haptic) exploration to recognize a 3-D object taken from a known set of models is examined. Two approaches are combined: (1) the use of geometric constraints between components to eliminate interpretations and of interpretation-tree methods for choosing the best active sensing move; and (2) exploratory moves made by tracing continually along the surface of the object (and not through free space). The study is restricted to polyhedra, and a set of geometric constraints tailored for matching components acquired from haptic exploration against components in the models is given. A new constraint using pairs of line segments is presented. A set of active sensing moves, each with an associated cost measure, and strategies for choosing the next move are given. <<ETX>>
Activation of ERK/CREB/BDNF pathway involved in abnormal behavior of neonatally Borna virus-infected rats

Background Neuropsychiatric disorders are devastating illnesses worldwide; however, the potential involvement of viruses in the pathophysiological mechanisms of psychiatric diseases have not been clearly elucidated. Borna disease virus (BDV) is a neurotropic, noncytopathic RNA virus. Materials and methods In this study, we infected neonatal rats intracranially with BDV Hu-H1 and Strain V within 24 hours of birth. Psychological phenotypes were assessed using sucrose preference test, open field test, elevated plus maze test, and forced swim test. The protein expression of ERK/CREB/BDNF pathway was assessed by Western blotting of in vitro and in vivo samples. Results Hu-H1-infected rats showed anxiety-like behavior 8 weeks postinfection while Strain V-infected rats demonstrated a certain abnormal behavior. Phosphorylated ERK1/2 was significantly upregulated in the hippocampi of Strain V- and Hu-H1-infected rats compared with control rats, indicating that Raf/MEK/ERK signaling was activated. Conclusion The data suggested that infection of neonatal rats with BDV Hu-H1 and Strain V caused behavioral abnormalities that shared common molecular pathways, providing preliminary evidences to investigate the underlying mechanisms of psychiatric disorders caused by BDV.
Characterization of High- $Q$  Inductors Up to its Self-Resonance Frequency for Wireless Power Transfer Applications

The primary coil of an efficient asymmetric inductive link (IL) has a high quality factor and operates near its self-resonance frequency (SRF). Therefore, its characterization is challenging, especially because the measurement instruments must be able to measure a large reactance and a very small resistance at a frequency where the inductor radiates. In this letter, we present a method suitable for characterizing high- $Q$ inductors up to its SRF. The proposed method uses an inductive sensor to characterize the inductor under test without galvanic contact. The method was validated by applying it to the primary coil of an asymmetric IL. The empirical results are consistent with the theoretical model and the full-wave simulations.
Facial emotion recognition in the elderly using a SVM classifier

Facial expressions are a spontaneous way of perceiving emotions, which can provide information related to the cognitive state of a person. Facial expression recognition of the elderly is an important aid to better care them, according to their state of mind, although it can be a difficult task because their expressions might not be as easily perceived as those from younger persons. We proposed a model to classify the facial expressions of the elderly, presenting the differences between facial expression recognition in the elder and in other age group, as well as methods to surpass these difficulties. Viola Jones with Haar Features was used to extract the faces and Gabor Filter to extract the facial characteristics. These characteristics are classified using a Multiclass Support Vector Machine. We got an accuracy of 90.32%, 84.61%and 66.6%, when detecting the neutral state, happiness and sadness respectively in the elderly. In the other age group, we got an accuracy of 95.24%, 88.57%, and 80%, while detecting the neutral, happiness, and sadness states and concluded that aging influences negatively the facial expressions recognition tasks.
A Game-theoretical Design Technique for Multi-stage Supply Chains under Uncertainty

We present a design approach for multi-stage Supply Chains (SCs) that allows selecting candidates and assigning them orders under uncertainty. A bargaining game model in its extensive form (i.e., with a time sequencing of moves) and in a fuzzy setting is proposed. The product quantities that each actor requires from the previous SC stage are determined modelling the real behavior of SC stakeholders, which on the one hand act to maximize their own profit, on the other hand cooperate to maximize the overall efficiency of the SC and minimize production costs and lead times. Assignments are determined taking into account stock levels, uncertain production or warehouse capacities, and customers' demand. Thus, the method supports the decision making process providing an agile, cooperative, and resource-efficient design of multi-stage SCs under uncertain parameters. A literature SC is used as a test case to evaluate the effectiveness of the technique.
Attackers Constantly Threaten the Survival of Organisations, but there is a New Shark in the Water: Carcharodon Carcharias Moderator Europa Universalis

Many attackers constantly threaten the very survival of all organisations. They will attack any and every IT component of every organisation, whether financial, industrial, retail, service, educational, charitable or governmental, using whatever means they can to breach these systems. They ignore legislation, regulations and standards, do not care who they inconvenience, or hurt. They have no moral scruples and will have no compunction about attacking the weakest link in any organisation - the people. Why is this a problem? The answer is the European Union General Data Protection Regulation, which is effective from 25th May, 2018. The new regulator will have the power to impose fines for non-compliance to the maximum of 20 million or 4% of the previous year's global turnover. Jurisdiction for organisations requiring to be compliant is now global and these organisations are obliged by regulation to report any breach within 72 hours of discovery, potentially leading to massive fines. In this paper, we highlight the need for all such organisations to be aware of the serious pitfalls they face when considering the impact of this regulation should they fail to be compliant. We make some sensible suggestions for actions that organisations might take to mitigate their risk now. We also outline our plans for a test study to determine how effective our suggestions might be.
Performance Comparison of Stator Winding Connections in Multiphase Drives Under Open Converter Leg

Multiphase machines provide various significant benefits when compared to three-phase ones. In particular, their inherent fault tolerance is often considered their most attractive advantage. Among the possible types of faults, the case of an open converter leg is especially common. On the other hand, multiphase machines with symmetrical winding arrangement offer multiple possibilities for stator winding configurations (SWCs). It has been recently proved that, in five-phase machines under open converter leg, the pentagon SWC attains smaller copper loss (SCL) and larger maximum achievable torque (MAT) than the conventional star SWC. However, it is currently unknown if such conclusion also holds true regarding machines of greater phase numbers and other SWCs, and if so, to which extent. This paper compares for different SWCs and phase numbers the performance of multiphase machines under open converter leg in terms of MAT (derating factor) and SCL. It is shown that the most convenient SWC for all phase numbers is to connect each phase in series with the neighboring ones. In particular, with such SWC the enhancement in MAT with respect to star SWC increases drastically for phase numbers greater than five, becoming very close to the healthy MAT. Simulation results support the theoretical study.
Discrete-Time Modeling and Stability Analysis of Peak-Current-Mode Controlled Buck Converter with Constant Current Load

With the extensive use of light-emitting diode (LED), switching DC-DC converter with constant current load (CCL) is popularity as LED driver. However, unstable phenomenon, which exists in peak-current-mode (PCM) controlled switching DC-DC converter with CCL, is a key factor limiting the performance of the system. Taking PCM controlled buck converter with CCL as a research object, a novel and simple discrete-time modeling is performed in this paper to analyze the stability of the converter. Based on which, the stability boundary equation of the converter is thus derived by Jacobian matrix. It is found from this boundary equation that the duty cycle should be less than 0.5 for the converter without slope compensation to operate in stable. Besides, the stability regions in the parameter space between the proportional coefficient of error amplifier and output capacitance are enlarged by decreasing the duty cycle. However, the equivalent series resistance of output capacitor and the inductance almost have no effect on the stable state. Finally, the experimental waveforms verified the theoretical analysis results.
Extending High Speed Operating Range of Induction Machine Drives Using Deadbeat-Direct Torque and Flux Control with Precise Flux Weakening

Flux weakening techniques have been developed for field oriented control (FOC) drives to achieve the maximum torque capability above the base speed. Deadbeat-direct torque and flux control (DB-DTFC) has the advantages of precise torque and flux control and reduced parameter sensitivity compared to FOC, thus it has the potential benefit of more consistently achieving maximum torque capability in the flux weakening region more accurately. This paper introduces a flux weakening strategy for DB-DTFC. Considering voltage and current limits, a simple solution to the optimal trajectory for the stator flux magnitude is derived to achieve the maximum feasible torque over the entire operating range. Results show that the speed control is extended to a significantly higher range beyond the base speed. Self-sensing is also investigated in the flux weakening region. Challenges of self-sensing are addressed to significantly extend the high speed operating range.
Mejora de imágenes a color utilizando un enfoque morfológico multiescala

La mejora de imágenes tiene aplicaciones prácticas en distintas áreas cient́ıficas. Una estrategia para la mejora de imágenes es la morfoloǵıa matemática. Uno de los desaf́ıos de la morfoloǵıa matemática en imágenes a color es determinar un orden entre las componentes de la imagen. Las imágenes a color se representan mediante estructuras de datos multidimensionales lo que implica que no existe un orden natural entre sus componentes. En este trabajo se propone la mejora de imágenes utilizando la extensión de la morfoloǵıa matemática multiescala para imágenes a color con diferentes espacios de colores y métodos de ordenamiento. Los experimentos realizados muestran que el método de mejora de la imagen propuesto, genera resultados auspiciosos utilizando distintos métodos de ordenamiento en términos de contraste tanto local como global, aśı como la calidad del color la imagen.
Leaks or Not: A Framework for Evaluating Cache Timing Side Channel Attacks in SGX

With the advent of Intel SGX processor, Intel is trying to prove that SGX can completely eliminate the security problems in cloud environment with assisted hardware. However, many studies have demonstrated that SGX cannot prevent some side channel attacks such as the spectre and meltdown attacks. Intel has focused on this issue and tried to solve it, but so far it has not yet released a powerful version. In this paper, we investigate related security works with SGX involving cache timing channel and speculative execution deeply. Based on SGX platform, we are going to take OpenSSL as a case study to validate SGX timing channel security. Besides, we are proposing a test framework to verify and assess whether and how much SGX influenced by timing side channel. Consisting of validating OpenSSL timing channel security and assessing secure cryptography implementation with timing channel mitigation measures in SGX, the framework will also motivate us to evaluate cache protection measures and perform trade-off between timing channel security and performance when using SGX.
A Novel PDR Aided UWB Indoor Positioning Method

Ultra-wide Band (UWB) plays an increasingly important role in indoor positioning due to its advantages of low emission power, high multipath resolution, and centimeter level positioning accuracy. However, the UWB system is vulnerable to Non-Line of Sight (NLOS) because of human or vehicle occlusion. In this paper, a novel Pedestrian Dead Reckoning (PDR) aided UWB indoor positioning method is proposed. Firstly, an NLOS accuracy factor model is constructed according to the distance difference between UWB and PDR. This accuracy factor judges whether UWB works normally or not. Once the accuracy factor exceeds a certain threshold, PDR positioning is adopted. Meanwhile, the direction and the position predicted by the extended extrapolation method from UWB are applied to provide the initial value for PDR processing. If the accuracy factor is within the threshold range, PDR is replaced by UWB. The experimental results show that the method proposed improves the positioning accuracy of UWB, and that the generalized extrapolation model can calculate more reliable initial values before PDR operates. The obtained results have validated that the proposed method can effectively restrain the impact of NLOS on stable and accurate positioning.
Fast VM Startup by Cooperative Image Caching for Cloud Data Centers

Virtual machine (VM) management is one of the key problems in cloud data centers. Many efforts have been put on finding an (approximate) optimal placement of VMs at physical machines (PMs) to achieve high resource utility. In this paper, we consider to reduce the startup delay of VMs, which is a key issue for improving user experience and resource utility. The basic idea of our work is to cache VM images at PMs so as to reduce the time of VM image retrieval. By handling VM placement and image placement jointly and de-centrally, we design a joint placement algorithm and an associated layered transport VM selection algorithm, so as to start VMs quickly in the meanwhile save some calculation resources. The key point of our algorithms lies in how to accelerate the startup of VM with limited information in a distributed fat-tree network. The proposed algorithms are evaluated by extensive simulations using a distributed system simulator SimGrid. The results show that our algorithms just lost a little performance in most cases, compared with the centralized algorithm and a classical cache placement strategy.
Secure Data Provenance in Cloud-Centric Internet of Things via Blockchain Smart Contracts

Mission-critical applications such as industrial control, smart grids, security and surveillance systems are highly dependent on cloud-centric IoT networks. In such networks, the diverse IoT devices harvest the data from the remote environments and relay it to multiple intermediate agents over the wireless links towards the cloud for storage, analysis and decision making. Such systems require highly trustworthy data to guarantee accurate and timely decisions. However, in most of the cases, the IoT data becomes dubious during the transmission towards the cloud. Ensuring data provenance in such a heterogeneous multi-layered system is a critical security issue. Therefore, in this paper, we propose a secure data provenance framework for cloud-centric IoT network by utilizing the immutable, deterministic and public nature of the blockchain smart contracts with the traditional cloud infrastructure. In the framework, the cryptographic hash of the device metadata is stored in the blockchain whereas actual data is stored off-chain i.e., in the cloud, making it highly scalable for a dense deployment of IoT devices in the network. Multiple smart contracts are stationed in the blockchain to guarantee the provenance receipt to the data stored in the cloud. The initial evaluation revealed that the proposed framework is highly acceptable in achieving the data provenance for large-scale cloud-centric IoT networks.
A Real-Time Real-Power Emulator of a Medium-Voltage High-Speed Induction Motor Coupled with a Mechanical Load

This paper provides an experimental discussion on a real-time real-power emulator that play as important role in achieving a total test of medium-voltage, high-power, high-speed induction motor drives. The use of the emulator brings cost and time savings to the test. The test bench including the emulator is characterized by connecting two identical modular multilevel double-star chopper-cell (DSCC) converters in front-to-front (FTF). This paper designs, builds, and tests a 400-Vdc, 10-kW downscaled test bench in which one DSCC converter is used as an inverter under test, and the other as a real-time real-power high-fidelity emulator of an induction motor coupled with load. Experimental waveforms obtained from the downscaled test bench confirm that the emulator can reproduce the electrical and mechanical operating performance of a three-phase 200-V, 10-kW, four-pole, 9000-r/min induction motor loaded with a centrifugal compressor.
GPK: An Efficient Special Symbol Input Method for Keyboards

We introduce a novel typing technique for special symbols in the keyboard-only environment. The technique, called GPK (Gliding on Physical Keyboard), consists of two steps for entering special symbols. First, a user draws the special symbol on the keyboard by gliding over keys; Second, the user can select the desired symbol from the predicted symbols generated by GPK. Users can also switch from this mode to normal typing mode. We also present an application of this input technique based on web browsers. A user study with nine participants who are familiar with keyboard input showed the input efficiency of GPK. We compared the typing efficiency of GPK with other special symbol typing methods. We could deploy this method to office environments where users have desktop computers with a keyboard only. It could also inspire future work of integrating this method into word processors, document preparation systems and web environments.
A Saturation Model of the Synchronous Reluctance Motor and its Identification by Genetic Algorithms

This paper proposes a complete saturation model of the Synchronous Reluctance Motor (SynRM), accounting for both the self-saturation and cross-saturation effects. This model is based on an analytical relationship between the stator flux and current components, and is characterized by parameters presenting an interesting physical interpretation, differently from many other saturation model in the scientific literature. It proposes also an identification technique of such a model based on stand-still tests, without the need of locking the rotor. The proposed saturation model permits the complete description of the magnetic behaviour of the machine with 8 parameters, fewer than those required by other models in the scientific literature. Finally, the parameters of this model have been retrieved by a adopting Genetic Algorithm (GAs). The proposed identification technique has been tested in both numerical simulation and experimentally on a suitably developed test set-up. Experimental results clearly show a good superimposition between the measured stator flux components and those computed with the proposed saturation model, by using the identified parameters.