Miracle-dz/UniFAR-FTUs huggingface dataset:
On The Rate-Cost of Gaussian Linear Control Systems with Random Communication Delays

This work considers Gaussian linear control systems where the goal is to guarantee system-state mean-square stability (i.e., $E(\Vert{\mathrm{x}}(t)\Vert^{2})\ \leq\ \mathsf{D}$) while minimizing the traffic rate $R$ between the sensor(s) and the controller. Most existing results either assume zero delay or focus on the asymptotic setting that overlooks the impact of delay. Nonetheless, in practice the communication delay is randomly distributed due to varying channel/network conditions. When the sensor measurement finally arrives at the controller, the age-of-information is thus random. Heuristically, an “old” measurement provides less valuable information than a “young” measurement but the quantitative impact of random delay on the optimal rate-cost tradeoff $R^{\ast}(\mathsf{D})$ remains an open problem. This work provides the first lower bound $R_{\mathrm{LB}}(\mathsf{D})$ for the random delay setting and designs a simple scheme that leads to a numerically evaluated upper bound $R_{\mathrm{UB}}(\mathsf{D})$. Jointly $R_{\mathrm{LB}}(\mathsf{D})$ and $R_{\mathrm{UB}}(\mathsf{D})$ bracket the optimal tradeoff $R^{\ast}(\mathrm{D})$. The new $R_{\mathrm{LB}}(\mathsf{D})$ is asymptotically tight when either $\mathsf{D}\rightarrow\infty$ or $R\rightarrow\infty$, and sheds further insights on how the (random) age of information could impact the performance of a cyber-physical control system.
Incremental Discovery of Crowd from Evolving Trajectory Data

Discovering the useful knowledge from the evolving trajectory data stream contributes to real-world applications such as animal movement behavior analysis, traffic monitoring, and weather forecasting. Among these explorations, moving objects' crowd detection is a challenging task and enabling to find anomalies in the traffic system. In a real application, a large volume of trajectory data stream arrives continuously for immediate data analysis. Due to the changes of these trajectory data, there is a remaining challenge to discover crowd efficiently. In this paper, we propose incremental crowd discovery framework over evolving data stream to reduce computational time complexity. In our framework, firstly we discover the group by proposing micro-group based clustering, and then we incrementally detect the crowd structure form. Experiments of our proposed system will conduct on real taxi trajectory data and synthetic data.
Mitigation of Flooding and Slow DDoS Attacks in a Software-Defined Network

Distributed denial of service (DDoS) attacks are a constant threat for services in the Internet. This year, the record for the largest DDoS attack ever observed was set at 1.7 Tbps. Meanwhile, detection and mitigation mechanisms are still lacking behind. Many mitigation systems require the assistance by the victim - or the victim's administrator themself has to become active to mitigate attacks. We introduced a system that can detect attacks, identify attackers, and mitigate the attacks purely within the network infrastructure. With the improved flexibility of software-defined networks, new possibilities to mitigate such attacks can be implemented. In addition to our short paper on the mitigation of reflective DDoS attacks on LCN 2018, we also like to demonstrate our work on mitigating flooding attacks presented at LCN 2017 and our mitigation of slow DDoS attacks. In our demo, we show how these systems can be combined and how they work when faced with such different attacks.
Quality-Aware Pricing for Mobile Crowdsensing

Mobile crowdsensing has been considered as a promising approach for large scale urban data collection, but has also posed new challenging problems, such as incentivization and quality control. Among the other incentivization approaches, posted pricing has been widely adopted by commercial systems due to the reason that it naturally achieves truthfulness and fairness and is easy to be implemented. However, the fundamental problem of how to set the “right” posted prices in crowdsensing systems remains largely open. In this paper, we study a quality-aware pricing problem for mobile crowdsensing, and our goal is to choose an appropriate posted price to recruit a group of participants with reasonable sensing qualities for robust crowdsensing, while the total expected payment is minimized. We show that our problem is NP-hard and has close ties with the well-known Poisson binomial distributions (PBDs). To tackle our problem, we first discover some non-trivial submodular properties of PBD, which have not been reported before, and then propose a novel “ironing method” that transforms our problem from a non-submodular optimization problem into a submodular one by leveraging the newly discovered properties of PBD. Finally, with the ironing method, several approximation algorithms with provable performance ratios are provided, and we also conduct extensive numerical experiments to demonstrate the effectiveness of our approach.
Emotion-focused therapy for binge-eating disorder: A review of six cases.

OBJECTIVE This study aimed to provide preliminary evidence of the usefulness of emotion-focused therapy (EFT) for binge-eating disorder (BED). METHODS We used a single-subject design in which 12 weeks of individual EFT were applied nonconcurrently to six female adult participants with BED, following three weekly baseline sessions. Participants were assessed for binge-eating psychopathology and emotion regulation difficulties on a weekly basis during baseline and treatment. They were assessed on a 2-, 4-, and 8-week basis during posttreatment, and they were assessed for binge-eating episodes, eating disorder attitudes, alexithymia, and psychiatric comorbidity at pretreatment and posttreatment. RESULTS All cases experienced reliable recovery from binge-eating psychopathology and a significant decrease in binge-eating frequency. For all cases, there was reliable improvement or recovery on eating and shape concerns, and there was improvement on weight concern for the majority of cases. For all cases, reliable recovery or improvement occurred in overall emotion regulation. Most cases that were in the clinical range pretreatment recovered for anxiety, and reliable improvement in or recovery from depression occurred for all cases. There was reliable recovery or improvement in alexithymia for half of the cases; however, the other half experienced no change or deteriorated. There were no treatment dropouts. CONCLUSION Individual EFT demonstrates potential as a psychological treatment for BED. The current study provides preliminary evidence to guide the development of a more extensive trial to test the efficacy of individual EFT for BED as well as to identify possible mechanisms of change.
Passivity and Decentralized MPC of Switched Graph-Based Power Flow Systems*

This paper presents a decentralized approach to certifying closed-loop passivity for a class of switched graph-based dynamic models. The switched modeling framework is particularly suited to power flow systems in which paths of power flow are switched on and off. Passivity is shown to be preserved under the interconnection of multiple such graph-based models, allowing for the formation of passive “systems of systems. ” Decentralized Model Predictive Controllers paired with each system can then be formulated with a passivity-preserving constraint to ensure closed-loop stability. This allows complex energy systems to be stabilized with decentralized or distributed control architectures, while centralized control may not be practical due to the inherent computational complexity or communication bandwidth limitations. A numerical example demonstrates the efficacy of the proposed approach on a fluid tank system.
Busy tone based coexistence algorithm for WRAN and WLAN systems in TV white space

TV White Space (TVWS) refers to frequency band reserved only for licensed terrestrial TV broadcasting and is opened to unlicensed use under regulatory conditions. While regulations protect licensed systems from interference, interference among unlicensed systems is left mainly to manufacturers. Consequently, there is a need to develop new coexistence approaches between TVWS networks. Busy tone broadcasting is a coexistence method, which can be used by TVWS networks to announce the selected frequency band is occupied. In this paper, a busy tone based coexistence algorithm is proposed for IEEE 802.11af and IEEE 802.22 networks and analyzed by considering different client distributions experiencing log-normal shadowing, where the exact interfering packet rate and successful packet transmission rate expressions are obtained and validated by simulations for different scenarios. The results show that with the proposed coexistence approach, a WLAN can reliably detect the busy tone signal to change its frequency band and can reduce interference to WRAN. Even if there is no available frequency band for the WLAN, the WRAN still maintains its enhanced successful packet transmission performance. The deployment of the proposed algorithm is important for successful coexistence between cognitive wireless networks, where interference is not regulated, such as in TVWS bands.
Geometric trajectory tracking with attitude planner for vectored-thrust VTOL UAVs

This paper addresses the trajectory tracking problem for VTOL UAVs in which the thrust vector can be delivered only in a fixed direction with respect to the aircraft frame. The proposed control law, based on an inner-outer loop strategy, guarantees robust tracking of a desired position trajectory. The attitude error dynamics, associated to the inner loop, is stabilized by a control torque that does not cancel non-harmful nonlinearities and that tracks at the same time a desired heading direction. This choice results in a non-autonomous feedback interconnection between the attitude and position loops, the stability of which is studied within the framework of differential inclusions. The proposed control force accounts for attitude errors to improve transient performance compared to other designs. The control scheme is tested on a multi-body model of a hexacopter UAV with actuators dynamics and aerodynamics effects, not included in the control design model.
Novel Model-based Methods for Performance Optimization of Multithreaded 2D Discrete Fourier Transform on Multicore Processors

In this paper, we use multithreaded fast Fourier transforms provided in three highly optimized packages, FFTW-2.1. 5, FFTW-3.3. 7, and Intel MKL FFT, to present a novel model-based parallel computing technique as a very effective and portable method for optimization of scientific multithreaded routines for performance, especially in the current multicore era where the processors have abundant number of cores. We propose two optimization methods, PFFT-FPM and PFFT-FPM-PAD, based on this technique. They compute 2D-DFT of a complex signal matrix of size NxN using p abstract processors. Both algorithms take as inputs, discrete 3D functions of performance against problem size of the processors and output the transformed signal matrix. Based on our experiments on a modern Intel Haswell multicore server consisting of 36 physical cores, the average and maximum speedups observed for PFFT-FPM using FFTW-3.3. 7 are 1.9x and 6.8x respectively and the average and maximum speedups observed using Intel MKL FFT are 1.3x and 2x respectively. The average and maximum speedups observed for PFFT-FPM-PAD using FFTW-3.3. 7 are 2x and 9.4x respectively and the average and maximum speedups observed using Intel MKL FFT are 1.4x and 5.9x respectively.
Between autonomy and control: Strategies of arbitrage in the “on-demand” economy

The “on-demand” economy is built upon company strategies of arbitrage between worker autonomy and worker control. Using ethnographic and interview data, I show how these strategies undermine the economic theory that justifies the on-demand business model. The increased freedom and flexibility on offer to workers is countered by “softer” and less visible forms of workforce surveillance and control. These take hold through information asymmetries, which narrow workers’ decision-making capacities and thus undercut arguments for workers’ designation as independent contractors. However, I also show that these forms of control ultimately hinge on workers’ willingness to conform to the calculative rationalities that companies project onto them, and that workers’ motivations diverge from these company assumptions. I conclude by countering the notion of calculability with that of “qualculation,” an affective style of reasoning that workers employ in response to algorithmic workforce management and which highlights how on-the-job decisions are made within a shifting moral economy of work.
Alvis Data Graphs

Alvis is a formal modelling language intended for describing behaviour of concurrent systems. The formal verification of Alvis models is mainly based on Labelled Transition Systems (LTS graphs) and model checking techniques. The paper deals with the concept of data graphs for Alvis models. Data graphs can be used for verifying Alvis models focused on data flow and manipulation. The graphs are used for reduction of the size of original LTS graphs and for exposing information related to data processing. The presented approach shows that the language can also be used for modelling systems where the data flow rather than the control flow plays the key role.
Skin stiffness in ray‐finned fishes: Contrasting material properties between species and body regions

The skin of aquatic vertebrates surrounds all the mechanical lineages of the body and must, therefore, play an important role in locomotion. A cross‐woven collagenous dermal design has converged across several clades of vertebrates. Despite this intriguing pattern, the biomechanical role of skin in swimming fishes remains largely unknown. A direct force transmission role for fish skin has been proposed, a hypothesis that is supported by the arrangement of the connective tissues linking the skin to the axial musculature. To evaluate this direct force‐transmission hypothesis, we undertook hundreds of uniaxial tensile tests on skin samples from coho salmon (Oncorhynchus kisutch), Florida pompano (Trachinotus carolinus), and red snapper (Lutjanus campechanus). To do this, we developed highly precise, low‐cost, custom‐built material testing units. To augment our data, we also assembled a data set of skin stiffness of four additional species of actinopterygians fishes from previously published studies. We found that stiffness varies significantly between species and that the skin of our study species was increasingly stiff along a rostrocaudal gradient. Placing our results in the context of the limited body of previous work, we found that species with lower skin stiffness exhibit shorter propulsive wavelengths and low thrust production at the caudal fin and species with higher skin stiffness possess longer propulsive wavelengths and high thrust production at the caudal fin. In addition, we found that mean collagen fiber angle was close to 50° and that fiber angle was lower in posterior samples than in anterior and midlateral samples. Taken as a whole, our mechanical and morphological results support the hypothesis that the skin functions as an important direct force‐transmission device in actinopterygians whereby muscular force generated in anterior myotomes is transmitted to the posterior of the body through the increasingly stiff skin.
Multi-Objective Optimisation Based Planning of Power-Line Grid Expansions

German nuclear power phase out in 2022 leads to significant reconstruction of the energy transmission system. Thus, efficient identification of practical transmission routes with minimum impact on ecological and economical interests is of growing importance. Due to the sensitivity of Germany’s public to grid expansion (especially in case of overhead lines), the participation and planning process needs to provide a high degree of openness and accountability. Therefore, a new methodological approach for the computer-assisted finding of optimal power-line routes considering planning, ecological and economic decision criteria is presented. The approach is implemented in a tool-chain for the determination of transmission line routes (and sets of transmission line route alternatives) based on multi-criteria optimisation. Additionally, a decision support system, based on common Geographic Information Systems (GIS), consisting of interactive visualisation and exploration of the solution space is proposed.
Optimization of Tune-in and End-to-end Delay in DASH Broadcast Over ROUTE

DASH broadcast is a recent topic and many standardization bodies are incorporating it. This work provides optimizations for the key metrics that determine the QoE for ATSC 3.0 object-based broadcast: the end-to-end latency, tune-in delay, and channel change times. The system employs DASH broadcast over IP-based ROUTE protocol. The performance of different encoding schemes is compared and encoding-dependent end-to-end latency is evaluated. The receiver-end optimization for tune-in delay exploiting hybrid capability of DASH/ROUTE system is proposed. The quantitative results demonstrate the performance enhancements achieved.
A Characterization of All Retrofit Controllers

In this paper, we give a characterization of all retrofit controllers for control of large-scale network systems. A retrofit controller is a local plug-in controller such that, rather than an entire network system model, only a model of the subsystem of interest is required for controller design. The retrofit controller guarantees the entire system stability for any (norm-unbounded) variations of neighboring subsystems, other than the subsystem of interest, as long as the network of the subsystem and neighboring subsystems is stable. Although a design procedure of a retrofit controller has been already proposed, how to characterize all retrofit controllers still remains an open question. We consider two cases where the interconnection signal is available and unavailable as a feedback signal. It is revealed that, in the case where the interconnection signal is available, all retrofit controllers are composed of a localizing compensator that cancels out the input-to-output map from the interconnection signal to the measurement signal, and a local controller that locally stabilizes the subsystem. It is also found that, in the case where the interconnection signal is unavailable, the effect from the measurement signal to the control input must be cancelled out in the controller. Finally, the effectiveness of retrofit control is verified through a numerical example of a benchmark model representing the bulk power system in the eastern half of Japan.
Big Data Privacy Preserving in Multi-Access Edge Computing for Heterogeneous Internet of Things

With the popularity of smart devices, multi-access edge computing (MEC) has become the mainstream of dealing with big data in heterogeneous Internet of Things (H-IoT). MEC makes full use of the computing power of edge nodes, which greatly reduces the computing pressure of data centers, and brings great convenience to the storage and processing of big data. However, it is easy to become the object of hacker attacks due to the lack of centralized management of distributed nodes. Once these nodes are compromised, a series of privacy issues can happen. In this article, we first overview the architecture of MEC for H-IoT. The MEC covers three-level advanced functional entities, including moblie edge (ME) system-level, ME host-level and ME network- level. Second, we draw our attention to the privacy issues in the MEC, especially in data aggregation and data mining. In addition, we consider machine learning privacy preserving as a case study in the application of MEC. Simulation results are shown to reveal the feasibility of the proposed method. Finally, we propose open issues for future work.
Mobile Decision Support and Data Provisioning for Low Back Pain

The authors present Back Pain Buddy, a mobile application offering decision support and coaching for people with low back pain (LBP). The application takes advantage of smartphones powerful capabilities and provides a crowd-sourced decision support system for discovering treatments and a mobile sensing solution for collecting data about users activities that are crucial in LBP research.
Discrimination Between Ascending/Descending Pitch Arpeggios

Automatic music transcription can be defined as the analysis of the acoustic signal to extract a symbolic representation of music. Existing transcription systems typically consider just the notes played at a given moment; however, other aspects such as expressiveness and playing technique can also be considered. This work is focused on how chords are played. Specifically, we consider a special type of chords, those played in arpeggio style, or simply arpeggios, in which the notes are played fast, sequentially from the lowest to the highest pitched note or vice versa and with a large overlap of the notes’ sound. The main goal of this paper is to determine the pitch direction in which the arpeggiated chord was played. Two different classification methods are considered: a Fisher linear discriminant and an SVM linear classification scheme. Different features are presented for this task: one is based on the Mel-frequency cepstral coefficients (MFCCs) and two others, specifically designed for this task, rely on different analyses of the spectrogram. Evaluations have been done with a wide number of musical instruments. The results show that the pitch direction can be reliably detected using the proposed methods.
Fully endoscopic laser stapedotomy: is it comparable with microscopic surgery?

Abstract Background: Microscopic stapedotomy is very successful and has long history, but it still has some constraints. Thus, otoendoscopy is increasingly popular nowadays. Aims/Objectives: The retrospective review study was to investigate the role of endoscopic laser stapedotomy in treating patients with otosclerosis. Materials and methods: Seventeen patients who received endoscopic laser stapedotomy from April 2014 to July 2017 were enrolled and compared to 13 patients who had microscopic stapedotomy from February 2009 to March 2012. The anatomical structures, operative time, and postoperative hearing outcomes were assessed in two groups. Relation between external acoustic canal and operative time was also analyzed. Results: Using an endoscope, the operative field was clear, with easily identified anatomy, without need to sacrifice bony structures. The operative time was significantly longer in the endoscopic group in 2014 and decreased in the following years. There was no significant difference of hearing improvements between the two groups. There was a weak correlation between the width of the external auditory canal and the operative time. Conclusions and significance: Fully endoscopic stapes surgery is a feasible and safe surgical technique and results in satisfactory hearing outcomes. However, surgeons take longer to master the technique and to achieve shorter endoscopic operative times.