Miracle-dz/UniFAR-FTUs huggingface dataset:
Aerial Camera Network for Observing Moving Targets

This paper considers a network of camera-equipped quad-rotors (aerial cameras) as aerial camera network (ACN) where each aerial camera is smart in the sense that it is mobile and can process, store, and wirelessly communicate information. This paper then presents an algorithm for decentralized and cooperative motion planning of these aerial cameras in 3-D environment to observe multiple targets moving on the ground. The proposed algorithm enables the ACN to observe targets from different elevations with the objective of jointly maximizing duration and quality (resolution) of observation for each target. This multi-scale observation depends on the field-of-view (FOV) of aerial camera and the quality of observation depends on the elevation and/or zoom level of aerial camera. The algorithm uses a quad-tree data structure to model not only the discrete movement decisions of aerial cameras in a 3-D environment but also the variations in the FOVs and qualities of observations. The use of artificial forces in the algorithm allows the aerial cameras to avoid collisions and to share the workload of assigning locations and targets to themselves. Simulation results present the effectiveness and performance evaluation of the proposed algorithm by comparison with the existing approaches of multi-target cooperative observation.
Millimeter wave high gain antenna based on gap waveguide technology

In this work, we present wideband gap waveguide planar array antenna for millimeter wave point to point backhauling systems. The proposed antenna is designed using ridge gap waveguide technology and the design is based on the cavity-backed slots as the core radiating elements. There exists a coupling slot in the cavity layer which allows the excitation of the radiating slot elements using ridge gap waveguide feeding section. The designed antennas have 8×8 or 16×16 radiating slot elements and the antenna operate over 15% relative bandwidth from 56–67GHz frequency range with −11 dB reflection coefficient. The measured gain for the slot arrays are within the range from 27 dBi–33dBi at the center of the band.
$H_2$ Output-Feedback Control With Finite Multiple Measurement Information

This paper proposes a new <inline-formula><tex-math notation="LaTeX">$H_2$</tex-math></inline-formula> output-feedback control with finite multiple measurement information for discrete-time systems with disturbances. This control is called an <inline-formula><tex-math notation="LaTeX">$H_2$</tex-math></inline-formula> finite multiple measurement output-feedback control (H2FMMOFC). The new control ascertains the <inline-formula> <tex-math notation="LaTeX">$H_2$</tex-math></inline-formula> performance for disturbances and the equivalence to the <inline-formula><tex-math notation="LaTeX">$H_2$</tex-math></inline-formula> state-feedback control without disturbances on a finite measurement horizon. The boundedness and exponential stability of the proposed H2FMMOFC are also investigated. The gain matrices of the H2FMMOFC are obtained by solving a convex problem utilizing the linear matrix inequality tool. Via a numerical example, the H2FMMOFC is shown to ensure the <inline-formula> <tex-math notation="LaTeX">$H_2$</tex-math></inline-formula> performance as well as the excellent robustness property against unexpected temporary model uncertainty although the uncertainty is not considered in its design.
Preemptive Scheduling of Latency Critical Traffic and Its Impact on Mobile Broadband Performance

In this paper, we present an exhaustive system level analysis of using preemptive scheduling for latency critical traffic in coexistence with mobile broadband for the 3GPP 5G New Radio. Enhanced recovery and HARQ retransmission mechanisms exploiting base station a priori knowledge of punctured radio resources from using preemptive scheduling are proposed. It is demonstrated that a scheme with HARQ multi-bit feedback and selective retransmission of punctured resources is an attractive solution. Furthermore, the performance sensitivity from using either fully interleaved or frequency-first code block layouts is assessed. The impact on the mobile broadband performance is evaluated at TCP-level, studying both the penalty on throughput and smoothened TCP round trip time to assess how preemptive scheduling affects the end-to-end performance of other traffic.
Skin Tissue Substitutes and Biomaterial Risk Assessment and Testing

Tremendous progress has been made over the past few decades to develop skin substitutes for the management of acute and chronic wounds. With the advent of tissue engineering and the ability to combine advanced manufacturing technologies with biomaterials and cell culture systems, more biomimetic tissue constructs have been emerged. Synthetic and natural biomaterials are the main constituents of these skin-like constructs, which play a significant role in tissue grafting, the body's immune response, and the healing process. The act of implanting biomaterials into the human body is subject to the body's immune response, and the complex nature of the immune system involves many different cell types and biological processes that will ultimately determine the success of a skin graft. As such, a large body of recent studies has been focused on the evaluation of the performance and risk assessment of these substitutes. This review summarizes the past and present advances in in vitro, in vivo and clinical applications of tissue-engineered skins. We discuss the role of immunomodulatory biomaterials and biomaterials risk assessment in skin tissue engineering. We will finally offer a roadmap for regulating tissue engineered skin substitutes.
Induction of apoptosis and necrosis in human acute erythroleukemia cells by inhibition of long non-coding RNA PVT1

Recent advances in molecular medicine have proposed new therapeutic strategies for cancer. One of the molecular research lines for the diagnosis and treatment of cancer is the use of long non-coding RNAs (LncRNAs) which are a class of non-coding RNA molecules longer than 200 base pairs in length that act as the key regulator of gene expression. Different aspects of cellular activities like cell growth, proliferation, differentiation, apoptosis and migration are regulated by lncRNAs. In various cancers, aberrant expression of lncRNAs has been reported. One of the lncRNAs that showed upregulation in human acute myeloid leukemia (AML) is lncRNA plasmacytoma variant translocation 1 (PVT1). Here, we performed blockage of lncRNA PVT1 in human acute erythroleukemia (AEL) cell line (KG1) using antisense LNA GapmeRs. Then, at different time points (24, 48 and 72 hours) after transfection, qRT‑real‑time PCR and AnnexinV/Propidium Iodide staining assay were performed. The data were processed using the ANOVA test. At all three time points, the ratio of apoptotic cells in the PVT1 antisense LNA GapmeRs treated group was higher than the other groups. The ratio of necrotic cells in the antisense LNA GapmeRs group was also higher than the other groups. These assessments show that inhibition of lncRNA PVT1 could significantly induce apoptosis and necrosis in KG1 cells. Our findings can be used in translational medicine for future investigation in acute erythroleukemia and treatment approach based on antisense therapy.
Location-Based Scheduling for Cellular V2V Systems in Highway Scenarios

In intelligent transport systems (ITS), vehicular users broadcast messages with ego information such as position, speed, and other. For exchanging ITS messages directly among vehicles via cellular sidelink transmission, the base station assigns dedicated V2V radio resources for users in coverage. To improve spectral efficiency, the same radio resource can be simultaneously scheduled to multiple vehicles within a cell, e.g., based on a minimum vehicle distance. This distance can be determined by location information obtained from ITS messages. In this work, we introduce a framework for location-based scheduling, exposing basic relations among cell spectral efficiency, communication range and reliability. Based on the framework we show that an optimal scheduling distance exists, which maximizes the cell throughput by guaranteeing range and reliability constraints. The optimized distance can then be utilized by the base station scheduler, which benefits from a closed form solution for the outage probability, derived in this work. We validate that the proposed form with its simplifications achieves a similar performance compared with the optimal solution, obtained by Monte Carlo simulations.
A Collaborative Filtering Recommender System in Primary Care: Towards a Trusting Patient-Doctor Relationship

We propose a collaborative filtering recommender system to match patients with doctors in primary care. In particular, we model patient trust in primary care doctors using a large-scale dataset of consultation histories, and account for the temporal dynamics of their relationships, defined in a novel quantitative measure of patient-doctor trust. Our proposed approach shows higher predictive accuracy than a heuristic baseline, as well as a collaborative filtering approach without the trust measures.
Precoding, Scheduling, and Link Adaptation in Mobile Interactive Multibeam Satellite Systems

This paper deals with the problem of precoding, scheduling, and link adaptation in next generation mobile interactive multibeam satellite systems. In contrast to the fixed satellite services, when the user terminals move across the coverage area, additional challenges appear. Due to the time varying channel, the gateway has only access to a delayed version of the channel state information (CSI), which can eventually limit the overall system performance. However, in contrast to general multiuser multiple-input multiple-output terrestrial systems, the CSI degradation in multibeam mobile applications has a very limited impact for typical fading channel and system assumptions. Under realistic conditions, the numerical results show that precoding can offer an attractive gain in the system throughput compared with the conservative frequency reuse allocations.
Graph Distance from the Topological View of Non-backtracking Cycles

Whether comparing networks to each other or to random expectation, measuring dissimilarity is essential to understanding the complex phenomena under study. However, determining the structural dissimilarity between networks is an ill-defined problem, as there is no canonical way to compare two networks. Indeed, many of the existing approaches for network comparison differ in their heuristics, efficiency, interpretability, and theoretical soundness. Thus, having a notion of distance that is built on theoretically robust first principles and that is interpretable with respect to features ubiquitous in complex networks would allow for a meaningful comparison between different networks. Here we introduce a theoretically sound and efficient new measure of graph distance, based on the "length spectrum" function from algebraic topology, which compares the structure of two undirected, unweighted graphs by considering their non-backtracking cycles. We show how this distance relates to structural features such as presence of hubs and triangles through the behavior of the eigenvalues of the so-called non-backtracking matrix, and we showcase its ability to discriminate between networks in both real and synthetic data sets. By taking a topological interpretation of non-backtracking cycles, this work presents a novel application of Topological Data Analysis to the study of complex networks.
A UAV-Based Traffic Monitoring System - Invited Paper

Traffic monitoring is important in urban areas. Traffic sensing solutions based on static cameras, however, do not offer a flexible, inexpensive solution for short-term traffic studies. To overcome the limitations of static solutions, we propose an aerial traffic monitoring system. It uses unmanned aerial vehicles (UAV) and onboard cameras to capture traffic video, which is sent and processed in the cloud. To validate the proposed system, we implemented a prototype with a quadcopter, an onboard camera with video and data processing algorithms, and a web application. The video processing module includes a vehicle detection stage based on the Haar cascade model and a frame-by-frame tracking stage. After experimental testing based on videos collected by the UAV, we conclude that the designed system can monitor traffic with high accuracy and flexibility.
Map reduce programming model for parallel K-mediod algorithm on hadoop cluster

This paper presents result analysis of K-Mediod algorithm, implemented on Hadoop Cluster by using Map-Reduce concept. Map-Reduce are programming models which authorize the managing of huge datasets in parallel, on a large number of devices. It is especially well suited to constant or moderate changing set of data since the implementation point of a position is usually high. MapReduce is supposed to be framework of "big data". The MapReduce model authorizes for systematic and instant organizing of large scale data with a cluster of evaluate nodes. One of the primary affect in Hadoop is how to minimize the completion length (i.e., make span) of a set of MapReduce duty. For various applications like word count, grep, terasort and parallel K-Mediod Clustering Algorithm, it has been observed that as the number of node increases, execution time decreases. In this paper we verified Map Reduce applications and found as the amount of nodes increases the completion time decreases.
Variational Memory Encoder-Decoder

Introducing variability while maintaining coherence is a core task in learning to generate utterances in conversation. Standard neural encoder-decoder models and their extensions using conditional variational autoencoder often result in either trivial or digressive responses. To overcome this, we explore a novel approach that injects variability into neural encoder-decoder via the use of external memory as a mixture model, namely Variational Memory Encoder-Decoder (VMED). By associating each memory read with a mode in the latent mixture distribution at each timestep, our model can capture the variability observed in sequential data such as natural conversations. We empirically compare the proposed model against other recent approaches on various conversational datasets. The results show that VMED consistently achieves significant improvement over others in both metric-based and qualitative evaluations.
Preference-Aware Caching Based on Cooperative Game for D2D Communication Networks (Invited Paper)

In cache enabled D2D communication networks, the cache space in a mobile terminal is relatively small compared with the huge amounts of multimedia contents. As such, how to cache the diverse contents in the multiple cache enabled mobile users, namely, the caching deployment, has substantial impact on network performance. In this paper, we propose a preference-aware caching based on cooperative game to incentivize users to cache contents for others, and then maximize the total cache utility by allocating cache space. We formulate a preference-aware cooperative game for cache utility maximization problem, which considers the user preference, physical distance, cache placement cost and cache space allocation. We divide the game into caching decision sub-game and cache space allocation sub-game. In caching decision sub-game, we obtain the Nash equilibrium solution by a heuristic caching decision method to minimize the total cost of getting objective contents. In cache space allocation sub-game, we solve the cache space allocation problem by using Lagrange method to finally maximize the total cache utility of the whole network. The convergence of the proposed algorithm is validated by simulation results. Compared with the existing caching schemes, the proposed scheme can achieve significant improvement on cache utility, cache hit ratio and content access delay gains.
A Data Fusion-Based Hybrid Sensory System for Older People’s Daily Activity and Daily Routine Recognition

Sensor-based human activity recognition (HAR) has received considerable attention due to its wide applications in health care. Each sensor modality has its advantages and limitations. Single sensor modalities sometimes may not cope with complex situations in practice. To resolve this challenge, we design and develop a practical hybrid sensory HAR system for older people. To enhance the performance of the system, we propose a unique data fusion method through combining both wearable sensors and ambient sensors. The wearable sensors in this paper are used for identifying the specific daily activities. The ambient sensors delivering the occupant’s room-level daily routine provide a more comprehensive surveillance with the wearable sensors together; meanwhile, the captured room-level location information is also used in the data fusion to trigger the sub classification models pretrained by wearable data. We also explore a new feature set extracted from wearable sensors to improve the system performance. We experimentally evaluate our system by applying four typical mutual information-based feature selection methods and the support vector machines classification algorithm instead of other complex algorithms, with the aim of exploring a practical way to improve recognition accuracy. The ground-truth data are gathered from 21 subjects, including 17 daily activities with the sample size of 2,142,000. The experimental results demonstrate the effectiveness of our method. The new feature set help improve the accuracy to 96.82% ± 0.15 from 89.81% ± 0.54 using wearable data only; and the data fusion with ambient information achieves a further increased accuracy of 98.32%.
Measurement-based vehicle exterior channel characteristics in 45-GHz band

The 45-GHz vehicle exterior channel is measured using an automatic measurement system in the Electromagnetic Compatibility laboratory environment. The frequency domain sweeping method is used to obtain large-scale and small-scale fading characteristics. Both the Close-In model and Alpha-Beta-Gamma model are used to analyze the effects of antenna polarization mode and vehicle structure on the path loss and shadow fading. The millimeter-wave space-time characteristics around the vehicle are also discussed, such as power delay profile, root-mean-square delay spread and clustering.
Health-Related Quality of Life of Older Adults in Costa Rica as Measured by the Short-Form-36 Health Survey

Objective: To test the validity of a common measure of health-related quality of life (Short-Form-36 [SF-36]) in cognitively healthy older adults living in rural and urban Costa Rica. Method: Confirmatory factor analysis was applied to SF-36 data collected in 250 older adults from San Jose and Guanacaste, Costa Rica. Results: The best fitting model for the SF-36 was an eight first-order factor structure. A high correlation between the Mental Component Summary and Physical Component Summary scores was found. Region differences indicated that rural dwellers perceive a poorer health-related quality of life compared with the urban group. Discussion: Costa Rican older adults perceived health as a unidimensional construct. Age and urbanity of older adult Costa Ricans should be appreciated when trying to measure self-reported physical and mental health. Cultural context of the individuals should be considered when studying health-related quality of life.
Heterologous Expression of Biopreservative Bacteriocins With a View to Low Cost Production

Bacteriocins, a heterogenous group of antibacterial ribosomally synthesized peptides, have potential as bio-preservatives in in a wide range of foods and as future therapeutics for the inhibition of antibiotic-resistant bacteria. While many bacteriocins have been characterized, several factors limit their production in large quantities, a requirement to make them commercially viable for food or pharma applications. The identification of new bacteriocins by database mining has been promising, but their potential is difficult to evaluate in the absence of suitable expression systems. E. coli has been used as a heterologous host to produce recombinant proteins for decades and has an extensive set of expression vectors and strains available. Here, we review the different expression systems for bacteriocin production using this host and identify the most important features to guarantee successful production of a range of bacteriocins.
Microfluidic viscometry using magnetically actuated micropost arrays

Here we describe development of a microfluidic viscometer based on arrays of magnetically actuated micro-posts. Quantitative viscosities over a range of three orders of magnitude were determined for samples of less than 20 μL. This represents the first demonstration of quantitative viscometry using driven flexible micropost arrays. Critical to the success of our system is a comprehensive analytical model that includes the mechanical and magnetic properties of the actuating posts, the optical readout, and fluid-structure interactions. We found that alterations of the actuator beat shape as parameterized by the dimensionless “sperm number” must be taken into account to determine the fluid properties from the measured actuator dynamics. Beyond our particular system, the model described here can provide dynamics predictions for a broad class of flexible microactuator designs. We also show how the model can guide the design of new arrays that expand the accessible range of measurements.
RASI: Relay-Assisted Physical-Layer Key Generation in Unmanned Aerial Vehicles

In this paper, we address physical-layer key generation between two unmanned aerial vehicles (UAVs) in flight, which are hindered by a dominant line-of-sight component (LOS) in their wireless channel. Although strong LOS component yields better error-performance in data transmission, it is well known that limited randomness in the channel variation will render the underlying physical-layer key generation algorithms ineffective. Pointing at this disadvantage, we explore a relay-based secret-key generation technique between the two UAVs, wherein a ground- stationed relay assists the two UAVs to witness a common source of randomness with higher entropy than their direct channel. We propose the Relay- Assisted Selective Inversion (RASI) protocol, which selectively offers common randomness from either of the channels from the relay to the two UAVs. To showcase the benefits of the RASI protocol, we first obtain theoretical lower bounds on the differential entropy of the common source of randomness, and subsequently employ a practical key-generation algorithm to synthesize the digital keys. We show that RASI can help the two UAVs to generate keys with higher key-rate than using the direct channel only. Finally, we also show that RASI outperforms an existing state-of-the-art relay-based method in terms of key-rate and computational complexity at the UAVs, while marginally losing to the latter in communication- overhead.