Miracle-dz/UniFAR-FTUs huggingface dataset:
A new bound on Erd\H{o}s distinct distances problem in the plane over prime fields

In this paper we obtain a new lower bound on the Erd\H{o}s distinct distances problem in the plane over prime fields. More precisely, we show that for any set $A\subset \mathbb{F}_p^2$ with $|A|\le p^{7/6}$, the number of distinct distances determined by pairs of points in $A$ satisfies $$ |\Delta(A)| \gg |A|^{\frac{1}{2}+\frac{149}{4214}}. $$ Our result gives a new lower bound of $|\Delta{(A)}|$ in the range $|A|\le p^{1+\frac{149}{4065}}$. The main tools we employ are the energy of a set on a paraboloid due to Rudnev and Shkredov, a point-line incidence bound given by Stevens and de Zeeuw, and a lower bound on the number of distinct distances between a line and a set in $\mathbb{F}_p^2$. The latter is the new feature that allows us to improve the previous bound due Stevens and de Zeeuw.
The Impact of PCA-Scale Improving GRU Performance for Intrusion Detection

A device or software appliance monitors a network or systems for malicious activity is an Intrusion Detection System (IDS). Conventional IDS does not detect elaborate cyber-attacks such as a low-rate DoS attack as well as unknown attacks. Machine Learning has attracted more and more interests in recent years to overcome these limitations. In this paper, we propose a novel method to improve intrusion detection accuracy of Gated Recurrent Unit (GRU) by embedding the proposed PCA-Scale with two options including PCA-Standardized and PCA-MinMax into the layer of GRU. Both optional methods explicitly enforce the learned object feature maps by affecting the direction of maximum variance with positive covariance. This approach can be applied to GRU model with negligible additional computation cost. We present experimental results on two real-world datasets such as KDD Cup 99 and NSL-KDD demonstrate that GRU model trained with PCA-Scaled method achieves remarkable performance improvements.
On Scheduling of High-Throughput Scientific Workflows under Budget Constraints in Multi-Cloud Environments

With the rapid development and deployment of cloud computing infrastructures, many applications in various scientific domains are increasingly utilizing cloud resources for big data storage and analysis. Particularly, it has become a significant challenge to manage and execute big data scientific workflows in multi-cloud environments to process streaming datasets. In this paper, within a three-layer workflow architecture with inter-and intra-cloud data transfer, we formulate a scientific workflow mapping problem under budget constraints to achieve the maximum throughput of streaming workflow applications. We propose a scheduling algorithm to identify the global bottleneck and maximize the throughput under budget constraints. Extensive simulation results show that the proposed algorithm exhibits superior performance over existing heuristic algorithms in scheduling streaming workflow applications.
Sensing the Frictional State of a Robotic Skin via Subtractive Color Mixing

The perception of surface properties such as shape and slipperiness is crucial to ensure that the hand-held object is stable. Without touch, precise manipulation becomes difficult. Some robotic tactile sensors use cameras that observe the elastic deformation of a membrane to detect edges or slippage of the contact. The perception of the contact state drove innovative control strategies. However, previous methods on these lines do not include quantitative means of measuring the three-dimensional (3-D) deformation of the skin or suffer from a lack of spatial resolution. Here, we present a tactile sensor based on a subtractive color mixing process designed to track the 3-D displacement of an array of markers, using the information delivered by the color channel of off-the-shelf cameras. The distributed shear and normal deformation can be assessed from the spectrum of the light reflected and refracted by an array of diffusive and transmissive markers placed on two superimposed layers. The markers show various blends of colors, depending on the displacement at the surface. The color pattern of each marker can be tracked with little computation and remains robust to external lighting. The ability to sense the 3-D deformation field can improve robotic perception of frictional properties that have applications in the fields of robotic control and human-robot interactions.
What Could Go Wrong?! 2nd Workshop: Lessons Learned When Doing HRI User Studies with Off-the-Shelf Social Robots

Nowadays, off-the-shelf social robots are used more frequently by the HRI community to research social interactions with different types of users across a range of domains such as education, retail, health care, public places and other domains. Everyone doing HRI research with end-users is invited to submit a case study to our workshop. We are particularly interested in case studies where things did not go as planned. Case studies describing research in the lab or in the wild are both welcome. Examples of unplanned experiences could include, but are not limited to, unexpected responses from the user, issues with the experimental setup or simply having challenges with transferring theory to the real world. In this workshop, we focus on off-the-shelf robots. In order to generalize and compare differences across multiple HRI domains and create common solutions, we will provide a template for your case study. We are interested in learning how such unexpected HRI results can be reported. In the workshop, we will discuss and study how failures are reported and be inspired to create a list of good ways to report failures, which can hopefully be inspiring for the HRI community.
Uniformly valid confidence intervals for conditional treatment effects in misspecified high-dimensional models.

Eliminating the effect of confounding in observational studies typically involves fitting a model for an outcome adjusted for covariates. When, as often, these covariates are high-dimensional, this necessitates the use of sparse estimators such as the Lasso, or other regularisation approaches. Naiive use of such estimators yields confidence intervals for the conditional treatment effect parameter that are not uniformly valid. Moreover, as the number of covariates grows with sample size, correctly specifying a model for the outcome is non-trivial. In this work, we deal with both of these concerns simultaneously, delivering confidence intervals for conditional treatment effects that are uniformly valid, regardless of whether the outcome model is correct. This is done by incorporating an additional model for the treatment-selection mechanism. When both models are correctly specified, we can weaken the standard conditions on model sparsity. Our procedure extends to multivariate treatment effect parameters and complex longitudinal settings.
CRSP: Network Congestion Control through Credit Reservation

In HPC, endpoint congestion can lead to the generation of saturated trees, which seriously affect the performance of network systems. Endpoint congestion can be mitigated by reducing the injection rate of the source, but requires fast reaction time to avoid the formation of congestion. In remote direct memory access (RDMA) network interface card (NIC) enabled with offload functions, tasks are transmitted in the form of flow for applications. Therefore, flow completion time and throughput are important factors that determine the efficiency of the application execution. However, the existing hardware solutions do not take into consideration of the impact of flow completion time on the applications. For a time-division reservation protocol, such as speculative reservation protocol (SRP), multiple flows in the source may conflict due to the overlap of the grant time. The reservation operation is inaccurate as a result. Therefore, we present CRSP, a novel, low-cost credit-reserved scheduling protocol to efficiently avoid the endpoint congestion in HPC. The CRSP avoids the formation of endpoint congestion by making reservations to the credit of the destination, while also minimizing the overhead caused by the reservation operation. We evaluate our CRSP protocol against the reservation based protocol, SRP, and the simulation results show that the average flow latency can be reduced by 29.67% in hot spot mode compared with SRP.
Parametric Sparse Recovery Method for TWR Imaging with Unknown Wall Parameter

Radar imaging based on compressive sensing can produce high resolution. However, the wall parameter is unknown in reality. This paper presents a parametric sparse recovery method with unknown wall parameter. The sparse reconstruction problem is a joint optimization one. An efficient algorithm combining orthogonal matching pursuit with least square is proposed to estimate the best wall parameter and recovery the sparse signal. The experiment shows the reliability of the proposed algorithm.
Negotiating Consumerism and Feminism on Instagram

In this preliminary research paper, we identify and characterize the current practices of top Norwegian female social influencers on Instagram. We introduce theories of social influence, consumerism, and new feminism to enlighten our discussion of how the social influencers exercise their influence. We present the results and analysis of the visual and textual content of 5,083 Instagram postings as well as supplementary online content. In our conclusion, we discuss the significance of the social influencers' negotiation of consumerism and feminism on Instagram as well as directions for future research.
Hydrologic Evaluation of TRMM and GPM IMERG Satellite-Based Precipitation in a Humid Basin of China

Tropical Rainfall Measurement Mission (TRMM) is one of the most popular global high resolution satellite-based precipitation products with a goal of measuring precipitation over the oceans and tropics. However, in recent years, the TRMM mission has come to an end. Its successor, Global Precipitation Measurement (GPM) mission was launched to measure the earth's precipitation structure, with an aim to improve upon the TRMM project. Both of the precipitation products have their own strengths and weaknesses in resolution, accuracy, and availability. The aim of this study is to evaluate the hydrologic utilization of the TRMM and GPM products in a humid basin of China. The main findings of this study can be summarized as follows: (1) 3B42V7 generally outperforms 3B42V6 in terms of hydrologic performance. Meanwhile, 3B42RTV7 significantly outperforms 3B42RTV6, and showed close performance with the bias-adjusted TRMM Multi-satellite Precipitation Analysis (TMPA) products. (2) The GPM showed better agreement with gauge observation than the TMPA products with lower RB and higher correlation coefficient (CC) values at different time scales. (3) The VIC hydrological model generally outperformed the XAJ hydrological model with lower RB, higher Nash–Sutcliffe Coefficient of Efficiency (NSCE) and CC values; though the 3B42RTV6 and 3B42RTV7 showed higher CC values in simulating the streamflow hydrograph by using the VIC and XAJ hydrological models. It can be found that the conceptual hydrological model was enough for the hydrologic evaluation of TRMM and GPM IMERG satellite-based precipitation in a humid basin of China. This study provides a reference for the comparison of multiple models on watershed scale.
Fluctuation Theorem of Information Exchange between Subsystems that Co-Evolve in Time

Sagawa and Ueda established a fluctuation theorem of information exchange by revealing the role of correlations in stochastic thermodynamics and unified the non-equilibrium thermodynamics of measurement and feedback control. They considered a process where a non-equilibrium system exchanges information with other degrees of freedom such as an observer or a feedback controller. They proved the fluctuation theorem of information exchange under the assumption that the state of the other degrees of freedom that exchange information with the system does not change over time while the states of the system evolve in time. Here we relax this constraint and prove that the same form of the fluctuation theorem holds even if both subsystems co-evolve during information exchange processes. This result may extend the applicability of the fluctuation theorem of information exchange to a broader class of non-equilibrium processes, such as a dynamic coupling in biological systems, where subsystems that exchange information interact with each other.
Performance of underwater quantum key distribution with polarization encoding.

Underwater quantum key distribution (QKD) has potential applications in absolutely secure underwater communication. However, the performance of underwater QKD is limited by the optical elements, background light, and dark counts of the detector. In this paper, we propose a modified formula for the quantum bit error rate (QBER), which takes into account the effect of detector efficiency on the QBER caused by the background light. Then we calculate the QBER of the polarization encoding BB84 protocol in Jerlov-type seawater by analyzing the effect of the background light and optical components in a more realistic situation. Finally, we further analyze the final key rate and the maximum secure communication distance in three propagation modes, i.e., upward, downward, and horizontal modes. We find that secure QKD can be performed in the clearest Jerlov-type seawater at a distance of hundreds of meters, even in the worst downward propagation mode. Specifically, by optimizing the system parameters, it is possible to securely transmit information with a rate of 67 kbits/s at a distance of 100 m in the seawater channel with an attenuation coefficient of 0.03/m at night. For practical underwater QKD, the performance can also be improved by using decoy states. Our results are useful for long-distance underwater quantum communication.
A Ku-Band Substrate Integrated Image Guide Low Sidelobe Level Leaky-Wave Antenna

A Ku-band low sidelobe level (SLL) leaky-wave antenna fed by the substrate integrated image guide (SIIG) is proposed in this paper. By utilizing the single-layer PCB technology, the fabrication complexity for an SIIG is reduced. The element spacing of the antenna based on the SIIG can be reduced because the SIIG owns a small waveguide wavelength. Rectangular strips are etched on the top of the SIIG as radiation elements, which exhibit strong radiation ability. Thus, the antenna based on the structure can be realized in a short length with high gain and shaped beam. The gain is 14.4dBi at 13.6 GHz, and the SLL is – 19.2dB. The radiation efficiency is 84.5%.
Second Language Tutoring Using Social Robots: A Large-Scale Study

We present a large-scale study of a series of seven lessons designed to help young children learn English vocabulary as a foreign language using a social robot. The experiment was designed to investigate 1) the effectiveness of a social robot teaching children new words over the course of multiple interactions (supported by a tablet), 2) the added benefit of a robot's iconic gestures on word learning and retention, and 3) the effect of learning from a robot tutor accompanied by a tablet versus learning from a tablet application alone. For reasons of transparency, the research questions, hypotheses and methods were preregistered. With a sample size of 194 children, our study was statistically well-powered. Our findings demonstrate that children are able to acquire and retain English vocabulary words taught by a robot tutor to a similar extent as when they are taught by a tablet application. In addition, we found no beneficial effect of a robot's iconic gestures on learning gains.
Stop Doing it! Approaching Strategy for a Robot to Admonish Pedestrians

We modeled a robot's approaching behavior for giving admonishment. We started by analyzing human behaviors. We conducted a data collection in which a guard approached others in two ways: 1) for admonishment, and 2) for a friendly purpose. We analyzed the difference between the admonishing approach and the friendly approach. The approaching trajectories in the two approaching types are similar; nevertheless, there are two subtle differences. First, the admonishing approach is slightly faster (1.3 m/sec) than the friendly approach (1.1 m/sec). Second, at the end of the approach, there is a ‘shortcut’ in the trajectory. We implemented this model of the admonishing approach into a robot. Finally, we conducted a field experiment to verify the effectiveness of the model. A robot is used to admonish people who were using a smartphone while walking. The result shows that significantly more people yield to admonishment from a robot using the proposed method than from a robot using the friendly approach method.
A data-driven approach to precipitation parameterizations using convolutional encoder-decoder neural networks

Numerical Weather Prediction (NWP) models represent sub-grid processes using parameterizations, which are often complex and a major source of uncertainty in weather forecasting. In this work, we devise a simple machine learning (ML) methodology to learn parameterizations from basic NWP fields. Specifically, we demonstrate how encoder-decoder Convolutional Neural Networks (CNN) can be used to derive total precipitation using geopotential height as the only input. Several popular neural network architectures, from the field of image processing, are considered and a comparison with baseline ML methodologies is provided. We use NWP reanalysis data to train different ML models showing how encoder-decoder CNNs are able to interpret the spatial information contained in the geopotential field to infer total precipitation with a high degree of accuracy. We also provide a method to identify the levels of the geopotential height that have a higher influence on precipitation through a variable selection process. As far as we know, this paper covers the first attempt to model NWP parameterizations using CNN methodologies.
Systematic evaluation of statistical methods for identifying looping interactions in 5C data

Chromosome-Conformation-Capture-Carbon-Copy (5C) is a molecular technology based on proximity ligation that enables high-resolution and high-coverage inquiry of long-range chromatin looping interactions. Computational pipelines for analyzing 5C data involve a series of inter-dependent normalization procedures and statistical methods that markedly influence downstream biological results. A detailed analysis of the trade-offs inherent to all stages of 5C analysis has not been reported, but is essential for understanding the biological basis of looping. Here, we provide a comparative assessment of method performance at each step in the 5C analysis pipeline, including sequencing depth and library complexity correction, bias mitigation, spatial noise reduction, distance-dependent expected and variance estimation, modeling, and loop detection. We present a detailed discussion of methodological advantages/disadvantages at each step and provide a full suite of algorithms, lib5C, to allow investigators to test the range of approaches on their own high-resolution 5C data. Principles learned from our comparative analyses will have broad impact on many other forms of Chromosome-Conformation-Capture-based data, including Hi-C, 4C, and Capture-C.
Decentralized  ${H_{\infty}}$  Filtering for Large-Scaled System Based on T-S Fuzzy Model With the Integrated Event-Triggered Strategy

Considering the characteristics of data transmission between the channels, this paper studies the decentralized <inline-formula> <tex-math notation="LaTeX">${H_\infty }$ </tex-math></inline-formula> filter for the large-scaled system with an integrated event-triggered strategy. The Takagi–Sugeno fuzzy model is used to approximate the large-scaled system. Different from the event-triggered control with the single condition, an event-triggered control with an integrated condition is presented to determine when the measurement output should be broadcast and transmitted to its filter and thus leading to a high efficiency of data transmissions. By applying a Lyapunov–Krasovskii functional and linear matrix inequalities, a method of the integrated event-triggered <inline-formula> <tex-math notation="LaTeX">${H_\infty }$ </tex-math></inline-formula> filter performance analysis and designing is developed so that the overall filtering error system concerned to be asymptotically stable with a given disturbance attenuation level. A simulation is finally given to show these effective methods in this paper.
GaiaGPU: Sharing GPUs in Container Clouds

Containers are widely used in clouds due to their lightweight and scalability. GPUs have powerful parallel processing capabilities that are adopted to accelerate the execution of applications. In a cloud environment, containers may require one or more GPUs to fulfill the resource requirement of application execution, while on the other hand exclusive GPU resource of a container usually results in underutilized resource. Therefore, how to share GPUs among containers becomes an attractive problem to cloud providers. In this paper, we propose an approach, called GaiaGPU, to sharing GPU memory and computing resources among containers. GaiaGPU partitions physical GPUs into multiple virtual GPUs and assigns the virtual GPUs to containers as request. Elastic resource allocation and dynamic resource allocation are adopted to improve resource utilization. The experimental results show that GaiaGPU only causes 1.015% of overhead by average and it effectively allocates and isolates GPU resources among containers
PLMP – Point-Line Minimal Problems in Complete Multi-View Visibility

We present a complete classification of all minimal problems for generic arrangements of points and lines completely observed by calibrated perspective cameras. We show that there are only 30 minimal problems in total, no problems exist for more than 6 cameras, for more than 5 points, and for more than 6 lines. We present a sequence of tests for detecting minimality starting with counting degrees of freedom and ending with full symbolic and numeric verification of representative examples. For all minimal problems discovered, we present their algebraic degrees, i.e.the number of solutions, which measure their intrinsic difficulty. It shows how exactly the difficulty of problems grows with the number of views. Importantly, several new minimal problems have small degrees that might be practical in image matching and 3D reconstruction.
Using Skin Texture Change to Design Emotion Expression in Social Robots

We evaluate the emotional expression capacity of skin texture change, a new design modality for social robots. In contrast to the majority of robots that use gestures and facial movements to express internal states, we developed an emotionally expressive robot that communicates using dynamically changing skin textures. The robot's shell is covered in actuated goosebumps and spikes, with programmable frequency and amplitude patterns. In a controlled study ($n=139$) we presented eight texture patterns to participants in three interaction modes: online video viewing, in person observation, and touching the texture. For most of the explored texture patterns, participants consistently perceived them as expressing specific emotions, with similar distributions across all three modes. This indicates that a texture changing skin can be a useful new tool for robot designers. Based on the specific texture-to-emotion mappings, we provide actionable design implications, recommending using the shape of a texture to communicate emotional valence, and the frequency of texture movement to convey emotional arousal. Given that participants were most sensitive to valence when touching the texture, and were also most confident in their ratings using that mode, we conclude that touch is a promising design channel for human-robot communication.