Miracle-dz/UniFAR-FTUs huggingface dataset:
IPLS: A Framework for Decentralized Federated Learning

The proliferation of resourceful mobile devices that store rich, multidimensional and privacy-sensitive user data motivate federated learning, a paradigm that enables mobile devices to produce a machine-learning model without sharing their data. However, the majority of the existing federated frameworks follow a centralized approach. In this work, we introduce IPLS, a fully decentralized federated learning framework that is partially based on the interplanetary file system (IPFS). By using IPLS and connecting into the corresponding private IPFS network, any party can initiate the training process of a machine-learning model or join an ongoing training process that has been started by another party. IPLS scales with the number of participants, is robust against intermittent connectivity and dynamic participant departures/arrivals, requires minimal resources and guarantees that the accuracy of the trained model quickly converges to that of a centralized federated learning framework with a negligible accuracy drop of less than 1‰.
A Multilayer Correlated Topic Model

We proposed a novel multilayer correlated topic model (MCTM) to analyze how the main ideas inherit and vary between a document and its different segments, which helps understand an article's structure. The variational expectation-maximization (EM) algorithm was derived to estimate the posterior and parameters in MCTM. We introduced two potential applications of MCTM, including the paragraph-level document analysis and market basket data analysis. The effectiveness of MCTM in understanding the document structure has been verified by the great predictive performance on held-out documents and intuitive visualization. We also showed that MCTM could successfully capture customers' popular shopping patterns in the market basket analysis.
Quantum manipulation of a two-level mechanical system

We consider a nonlinearly coupled electromechanical system, and develop a quantitative theory for two-phonon cooling. In the presence of two-phonon cooling, the mechanical Hilbert space is effectively reduced to its ground and first excited states, allowing for quantum operations at the level of individual phonons and preparing nonclassical mechanical states with negative Wigner functions. We propose a scheme for performing arbitrary Bloch sphere rotations, and derive the fidelity in the specific case of a π-pulse. We characterise detrimental processes that reduce the coherence in the system, and demonstrate that our scheme can be implemented in state-of-the-art electromechanical devices.
Predicting the observability of population III stars with ELT-HARMONI via the helium 1640 Å emission line

Population III (Pop. III) stars, as of yet, have not been detected, however as we move into the era of extremely large telescopes this is likely to change. One likely tracer for Pop. III stars is the HeIIλ1640 emission line, which will be detectable by the HARMONI spectrograph on the European Extremely Large Telescope (ELT) over a broad range of redshifts (2 ≤ z ≤ 14). By post-processing galaxies from the cosmological, AMR-hydrodynamical simulation NEWHORIZON with theoretical spectral energy distributions (SED) for Pop. III stars and radiative transfer (i.e. the Yggdrasil Models and CLOUDY look-up tables respectively) we are able to compute the flux of HeIIλ1640 for individual galaxies. From mock 10 hour observations of these galaxies we show that HARMONI will be able to detect Pop. III stars in galaxies up to z ∼ 10 provided Pop. III stars have a top heavy Initial Mass Function (IMF). Furthermore, we find that should Pop. III stars instead have an IMF similar to those of the Pop. I stars, the HeIIλ1640 line would only be observable for galaxies with Pop. III stellar masses in excess of 10 M , average stellar age < 1Myr at z = 4. Finally, we are able to determine the minimal intrinsic flux required for HARMONI to detect Pop. III stars in a galaxy up to z = 10.
Recent Development in Analytical Model for Graphene Field Effect Transistors for RF Circuit Applications

The MOS devices are the basic building block of any digital and analog circuits, where silicon (Si) is the most commonly used material. The International Technology Roadmap Semiconductor (ITRS) report predicts the gate length of the MOS device will shrink to 4.5 nm up to 2023, this may create severe short channel effects (SCEs). Therefore, new channel materials have been realized, which have shown their potential to maintain the proper balance between device performance and SECs. Among them, graphene has shown its strong presence as an alternative channel material in terms of its fascinating electrical and mechanical properties. It has ultra-high carrier mobility (77,000 cmVs) and saturation velocity (4.5 ×10cm s), which makes it compatible with high-speed circuit applications. This review paper has a detailed report on the several analytical modeling approaches for graphene-based FET device, which includes the drift-diffusion, gradual channel approximation, virtual source, and ballistic approaches. The device modeling plays an important role to predict the device performance and used to reveal the physics behind it. In addition, the compact model of the device will use in the development of electronic design automation (EDA) tools, which are used for the circuits simulation.
Toward location-aware in-body terahertz nanonetworks with energy harvesting

Nanoscale wireless networks are expected to revolutionize a variety of domains, with significant advances conceivable in in-body healthcare. These nanonetworks will consist of energy-harvesting nanodevices passively flowing through the bloodstream, taking actions at certain locations, and communicating results to a more powerful Body Area Network (BAN). Assuming such a setup and electro-magnetic nanocommunication in the Terahertz (THz) frequencies, we propose a network architecture that can support fine-grained localization of the energy-harvesting in-body nanonodes, as well as their two-way communication with the outside world. The main novelties of our proposal lie in the utilization of location-aware and Wake-up Radio (WuR)-based wireless nanocommunication paradigms, as well as Software-Defined Metamaterials (SDMs), for supporting the envisioned functionalities in THz-operating energy-harvesting in-body nanonetworks. We argue that, on a high level, the proposed architecture can handle a large number of nanonodes, while simultaneously dealing with a short range of THz in-body propagation and highly constrained nanonodes.
An A* Curriculum Approach to Reinforcement Learning for RGBD Indoor Robot Navigation

Training robots to navigate diverse environments is a challenging problem as it involves the confluence of several different perception tasks such as mapping and localization, followed by optimal path-planning and control. Recently released photo-realistic simulators such as Habitat allow for the training of networks that output control actions directly from perception: agents use Deep Reinforcement Learning (DRL) to regress directly from the camera image to a control output in an end-to-end fashion. This is data-inefficient and can take several days to train on a GPU. Our paper tries to overcome this problem by separating the training of the perception and control neural nets and increasing the path complexity gradually using a curriculum approach. Specifically, a pre-trained twin Variational AutoEncoder (VAE) is used to compress RGBD (RGB&depth) sensing from an environment into a latent embedding, which is then used to train a DRL-based control policy. A*, a traditional path-planner is used as a guide for the policy and the distance between start and target locations is incrementally increased along the A* route, as training progresses. We demonstrate the efficacy of the proposed approach, both in terms of increased performance and decreased training times for the PointNav task in the Habitat simulation environment. This strategy of improving the training of direct-perception based DRL navigation policies is expected to hasten the deployment of robots of particular interest to industry such as co-bots on the factory floor and last-mile delivery robots.
Analysis of the native structure of starch granules with small angle x‐ray microfocus scattering

Small angle x-ray microfocus scattering patterns were obtained from 4 μm regions of hydrated potato starch granules. The 9 nm lamellar reflection was found to be modulated along two fiat streaked layer lines symmetrically related, and arranged in a weak four point pattern. This provides evidence for two populations of tilted lamellae in the granule present in equal quantities, but opposite angles of tilt. The paucity of reflections in the scattering patterns implies the existence of correlated disorder between the lamellae, and is a product of either their liquid crystallinity or a well- developed defect structure between the constituent amylopectin helices. The angular position of the four point modulation (17.25°) on the scattering patterns is compared with the values predicted from a superhelical lamellar model containing cumulative disorder along its axis, and good agreement is found with the data. The physical basis for the occurrence of these helical lamellae is examined on the basis of the model of amylopectin as a chiral side chain liquid-crystalline polymer (T. A. Waigh et al., Macromolecules, 1997, Vol. 30, pp. 3813-3820; Faraday Discussions, 1996, Vol. 103, pp. 325- 337). Small angle x-ray microfocus scattering patterns were obtained from 4 μm regions of hydrated potato starch granules. The 9 nm lamellar reflection was found to be modulated along two flat streaked layer lines symmetrically related, and arranged in a weak four point pattern. This provides evidence for two populations of tilted lamellae in the granule present in equal quantities, but opposite angles of tilt. The paucity of reflections in the scattering patterns implies the existence of correlated disorder between the lamellae, and is a product of either their liquid crystallinity or a well-developed defect structure between the constituent amylopectin helices. The angular position of the four point modulation (17.25°) on the scattering patterns is compared with the values predicted from a superhelical lamellar model containing cumulative disorder along its axis, and good agreement is found with the data. The physical basis for the occurrence of these helical lamellae is examined on the basis of the model of amylopectin as a chiral side chain liquid-crystalline polymer.
Dynamic Prioritization for Conflict-Free Path Planning of Multi-Robot Systems

Planning collision-free paths for multi-robot systems (MRS) is a challenging problem because of the safety and efficiency constraints required for real-world solutions. Even though coupled path planning approaches provide optimal collision-free paths for each agent of the MRS, they search the composite space of all the agents and therefore, suffer from exponential increase in computation with the number of robots. On the other hand, prioritized approaches provide a practical solution to applications with large number of robots, especially when path computation time and collision avoidance take precedence over guaranteed globally optimal solution. While most centrally-planned algorithms use static prioritization, a dynamic prioritization algorithm, PD*, is proposed that employs a novel metric, called freedom index, to decide the priority order of the robots at each time step. This allows the PD* algorithm to simultaneously plan the next step for all robots while ensuring collision-free operation in obstacle ridden environments. Extensive simulations were performed to test and compare the performance of the proposed PD* scheme with other state-of-the-art algorithms. It was found that PD* improves upon the computational time by 25% while providing solutions of similar path lengths. Increase in efficiency was particularly prominent in scenarios with large number of robots and/or higher obstacle densities, where the probability of collisions is higher, suggesting the suitability of PD* in solving such problems.
Network of

We study the evolution of networks through ‘triplets’ — three-node graphlets. We develop a method to compute a transition matrix of these triplets to describe their evolution in temporal networks. To identify the network dynamics’ non-pairwise interactions, we compare both arti-ﬁcial and real-world data to a pairwise interaction model. The signiﬁcant diﬀerences between the computed matrix and the calculated matrix from the ﬁtted parameters demonstrate that non-pairwise interactions exist for various real-world data sets. Furthermore, diﬀerent entries of the matrix diﬀerences reveal the real-world systems have diﬀerent higher-order interaction patterns which are seldomly reported in the previous researches. We then use these transition matrices as the basis of a link prediction algorithm. We investigate our algorithm’s performance on four temporal networks comparing our approach against ten other link prediction methods. Our results show that higher-order interactions play a crucial role in the evolution of networks as we ﬁnd our method along with two other methods based on non-local interactions, give the best overall performance. The results also conﬁrm the concept that the higher-order interaction patterns, i.e., triplet dynamics, can help us understand and predict diﬀerent real-world systems’ evolution.
Quadratic Chabauty for modular curves: algorithms and examples

We describe how the quadratic Chabauty method may be applied to determine the set of rational points on modular curves of genus $g>1$ whose Jacobians have Mordell–Weil rank $g$. This extends our previous work on the split Cartan curve of level 13 and allows us to consider modular curves that may have few known rational points or non-trivial local height contributions at primes of bad reduction. We illustrate our algorithms with a number of examples where we determine the set of rational points on several modular curves of genus 2 and 3: this includes Atkin–Lehner quotients $X_0^+(N)$ of prime level $N$, the curve $X_{S_4}(13)$, as well as a few other curves relevant to Mazur's Program B. We also compute the set of rational points on the genus 6 non-split Cartan modular curve $X_{\scriptstyle \mathrm { ns}} ^+ (17)$.
Exploring Semi-Supervised Learning for Predicting Listener Backchannels

Developing human-like conversational agents is a prime area in HCI research and subsumes many tasks. Predicting listener backchannels is one such actively-researched task. While many studies have used different approaches for backchannel prediction, they all have depended on manual annotations for a large dataset. This is a bottleneck impacting the scalability of development. To this end, we propose using semi-supervised techniques to automate the process of identifying backchannels, thereby easing the annotation process. To analyze our identification module’s feasibility, we compared the backchannel prediction models trained on (a) manually-annotated and (b) semi-supervised labels. Quantitative analysis revealed that the proposed semi-supervised approach could attain 95% of the former’s performance. Our user-study findings revealed that almost 60% of the participants found the backchannel responses predicted by the proposed model more natural. Finally, we also analyzed the impact of personality on the type of backchannel signals and validated our findings in the user-study.
Abusive Advertising: Scrutinizing socially relevant algorithms in a black box analysis to examine their impact on vulnerable patient groups in the health sector

The targeted direct-to-customer marketing of unapproved stem cell treatments by a questionable online industry is directed at vulnerable users who search the Internet in the hope of a cure. This behavior especially poses a threat to individuals who find themselves in hopeless and desperate phases in their lives. They might show low reluctance to try therapies that solely promise a cure but are not scientifically proven to do so. In the worst case, they suffer serious side-effects. Therefore, this thesis examines the display of advertisements of unapproved stem cell treatments for Parkinson’s Disease, Multiple Sclerosis, Diabetes on Google’s results page. The company announced a policy change in September 2019 that was meant to prohibit and ban the practices in question. However, there was evidence that those ads were still being delivered. A browser extension for Firefox and Chrome was developed and distributed to conduct a crowdsourced Black Box analysis. It was delivered to volunteers and virtual machines in Australia, Canada, the USA and the UK. Data on search results, advertisements and top stories was collected and analyzed. The results showed that there still is questionable advertising even though Google announced to purge it from its platform.
Cooling process of brown dwarfs in Palatini 
f(R)
 gravity

We present an analytical model for the evolution of brown dwarfs in quadratic Palatini f(R) gravity. We improve previous studies by adopting a more realistic description of the partially-degenerate state that characterizes brown dwarfs. Furthermore, we take into account the hydrogen metallic-molecular phase transition between the interior of the brown dwarf and its photosphere. For such improved model, we revise the cooling process of sub-stellar objects.
Multi-Cell, Multi-Channel URLLC with Probabilistic Per-Packet Real-Time Guarantee

—Ultra-reliable, low-latency communication (URLLC) represents a new focus in 5G-and-beyond networks, and it is expected to enable mission-critical sensing and control as well as AR/VR applications. URLLC requires controlling the communication quality of individual packets. Prior studies have considered probabilistic per-packet real-time guarantees for single-cell, single-channel networks with implicit deadline constraints, but they have not considered real-world complexities such as inter-cell interference and multiple communication channels. Towards ensuring URLLC in multi-cell, multi-channel wireless networks, we propose a real-time scheduling algorithm based on local-deadline-partition (LDP) . The LDP algorithm is suitable for distributed implementation, and it ensures probabilistic per-packet real-time guarantee for multi-cell, multi-channel networks with general deadline constraints. We also address the associated challenge of the schedulability test of URLLC trafﬁc. In particular, we propose the concept of feasible set and identify a closed-form sufﬁcient condition for the schedulability of URLLC trafﬁc. We propose a distributed algorithm for the schedulability test, and the algorithm includes a procedure for ﬁnding the minimum sum work density of feasible sets which is of interest by itself. We also identify a necessary condition for the schedulability of URLLC trafﬁc, and use numerical studies to understand a lower bound on the approximation ratio of the LDP algorithm. We experimentally study the properties of the LDP algorithm and observe that the URLLC trafﬁc supportable by the LDP algorithm is signiﬁcantly higher than that of a state-of-the-art algorithm.
Latency Overhead of ROS2 for Modular Time-Critical Systems

—The Robot Operating System 2 (ROS2) targets distributed real-time systems. Especially in tight real-time control loops, latency in data processing and communication can lead to instabilities. As ROS2 encourages splitting of the data-processing pipelines into several modules, it is important to understand the latency implications of such modularization. In this paper, we investigate the end-to-end latency of ROS2 data-processing pipeline with different Data Distribution Service (DDS) middlewares. In addition, we proﬁle the ROS2 stack and point out latency bottlenecks. Our ﬁndings indicate that end-to-end latency strongly depends on the used DDS middleware. Moreover, we show that ROS2 can lead to 50% latency overhead compared to using low-level DDS communications. Our results imply guidelines for designing modular ROS2 architectures and indicate possibilities for reducing the ROS2 overhead.
Improving Training Result of Partially Observable Markov Decision Process by Filtering Beliefs

In this study I proposed a filtering beliefs method for improving performance of Partially Observable Markov Decision Processes(POMDPs), which is a method wildly used in autonomous robot and many other domains concerning control policy. My method search and compare every similar belief pair. Because a similar belief have insignificant influence on control policy, the belief is filtered out for reducing training time. The empirical results show that the proposed method outperforms the point-based approximate POMDPs in terms of the quality of training results as well as the efficiency of the method.
Investigating the Efficacy of Music Version Retrieval Systems for Setlist Identification

The setlist identification (SLI) task addresses a music recognition use case where the goal is to retrieve the metadata and times-tamps for all the tracks played in live music events. Due to various musical and non-musical changes in live performances, developing automatic SLI systems is still a challenging task that, despite its industrial relevance, has been under-explored in the academic literature. In this paper, we propose an end-to-end workflow that identifies relevant metadata and timestamps of live music performances using a version identification system. We compare 3 of such systems to investigate their suitability for this particular task. For developing and evaluating SLI systems, we also contribute a new dataset that contains 99.5 h of concerts with annotated metadata and timestamps, along with the corresponding reference set. The dataset is categorized by audio qualities and genres to analyze the performance of SLI systems in different use cases. Our approach can identify 68% of the annotated segments, with values ranging from 35% to 77% based on the genre. Finally, we evaluate our approach against a database of 56.8 k songs to illustrate the effect of expanding the reference set, where we can still identify 56% of the annotated segments.
Conical square functionals on Riemannian manifolds

Let $L = \Delta + V$ be Schr{\"o}dinger operator with a non-negative potential $V$ on a complete Riemannian manifold $M$. We prove that the conical square functional associated with $L$ is bounded on $L^p$ under different assumptions. This functional is defined by $$ \mathcal{G}_L (f) (x) = \left( \int_0^\infty \int_{B(x,t^{1/2})} |\nabla e^{-tL} f(y)|^2 + V |e^{-tL} f(y)|^2 \frac{\mathrm{d}t \mathrm{d}y}{Vol(y,t^{1/2})} \right)^{1/2}. $$For $p \in [2,+\infty)$ we show that it is sufficient to assume that the manifold has the volume doubling property whereas for $p \in (1,2)$ we need extra assumptions of $L^p-L^2$ of diagonal estimates for $\{ \sqrt{t} \nabla e^{-tL}, t\geq 0 \}$ and $ \{ \sqrt{t} \sqrt{V} e^{-tL} , t \geq 0\}$. Given a bounded holomorphic function $F$ on some angular sector, we introduce the generalized conical vertical square functional$$\mathcal{G}_L^F (f) (x) = \left( \int_0^\infty \int_{B(x,t^{1/2})} |\nabla F(tL) f(y)|^2 + V |F(tL) f(y)|^2 \frac{\mathrm{d}t \mathrm{d}y}{Vol(y,t^{1/2})} \right)^{1/2}$$ and prove its boundedness on $L^p$ if $F$ has sufficient decay at zero and infinity. We also consider conical square functions associated with the Poisson semigroup, lower bounds, and make a link with the Riesz transform.