Miracle-dz/UniFAR-FTUs huggingface dataset:
Indoor localization using analog output of pyroelectric infrared sensors

Economical, low-power, and easy to deploy indoor localization schemes have always been a challenge. We propose a technique that utilizes the analog output of pyroelectric (or passive) infrared (PIR) sensors for indoor localization. We propose two models for distance estimation based on the characterization of the analog sensor output in terms of the peak to peak value and its relationship with distance from the sensor. The proposed distance estimation models are based on bijective functions: Mbh using a hyperbolic function and Mpl using a piecewise linear function. Once distances of the subject from the PIR sensors (or anchors) are estimated, multilateration or support vector regression (SVR) based techniques are used for computing the location coordinates of the subject. Using four PIR sensors, we demonstrate the localization of a human subject in a 7 m × 7.5 m area with the regression based technique outperforming the other techniques in terms of accuracy and achieving an RMS localization error of 0.65 m using the Mpl model for distance estimation. We also compare the computational complexity and memory or storage requirements of the proposed techniques which are an important consideration for distributed implementation on resource constrained devices such as sensor nodes.
Depletion of Sirt3 leads to the impairment of adipogenic differentiation and insulin resistance via interfering mitochondrial function of adipose-derived human mesenchymal stem cells

Abstract Upregulation of mitochondrial function and oxidative metabolism is a hallmark in the differentiation of stem cells. However, the mechanism underlying the metabolic reprogramming and upregulation of mitochondrial function during the differentiation of human mesenchymal stem cells (hMSCs) is largely unclear. Sirt3 has emerged as a sensor in regulating mitochondrial function and antioxidant defence system in cellular response to energy demand or environmental stimuli, but its roles in stem cell differentiation have not been fully understood. In this study, we used adipose-derived hMSCs (ad-hMSCs) to investigate the role of Sirt3 in adipogenic differentiation and in the function of mature adipocytes. We showed that at the early stage of adipogenic differentiation, Sirt3 upregulation is essential for the activation of biogenesis and bioenergetic function of mitochondria. In addition, we found that induction of Forkhead Box O 3a (FoxO3a), an upstream factor that regulates MnSOD gene transcription, is involved in the upregulation of antioxidant enzymes at the early stage of adipogenic differentiation. Silencing of Sirt3 by shRNA decreased the protein level of FoxO3a and subsequently downregulated a number of FoxO3a-mediated antioxidant enzymes and increased oxidative stress in ad-hMSCs after adipogenic induction. Importantly, depletion of Sirt3 compromised the ability of ad-hMSCs to undergo adipogenic differentiation and led to adipocyte dysfunction and insulin resistance. These findings suggest that Sirt3-mediated protein deacetylation plays an important role in regulating oxidative metabolism and antioxidant defence in stem cell differentiation, and that Sirt3 deficiency may be related to insulin resistance.
Integrating region preferences in multiobjective evolutionary algorithms based on decomposition

User preference is of great importance when dealing with many objective optimization. Using the preference information to obtain preferred parts of the Pareto set has become prevalent in the research domain of Evolutionary Multiobjective Optimization (EMO). In this paper, a target region provided by the decision maker (DM), defined by the preferred range of every objective, is utilized to articulate the preference in-formation. This information is integrated with two well-known multiobjective evolutionary algorithms based on decomposition: MOEA/D and NSGA-III. The newly proposed preference-based algorithms, called T-MOEA/D and T-NSGA-III, can be used both a-priori and interactively. Experiments have demonstrated the benefit of applying them interactively. The DM can easily and quickly adjust the preferences according to the current results, and the proposed algorithms can successfully find non-dominated solutions complying with the preferences. Comparative experiments show that the proposed algorithms outperform the dominance-based algorithm T-NSGA-II on many-objective benchmark problems.
Data and Spectrum Trading Policies in a Trusted Cognitive Dynamic Network Architecture

Future wireless networks will progressively displace service provisioning towards the edge to accommodate increasing growth in traffic. This paradigm shift calls for smart policies to efficiently share network resources and ensure service delivery. In this paper, we consider a cognitive dynamic network architecture (CDNA) where primary users (PUs) are rewarded for sharing their connectivities and acting as access points for secondary users (SUs). CDNA creates opportunities for capacity increase by network-wide harvesting of unused data plans and spectrum from different operators. Different policies for data and spectrum trading are presented based on centralized, hybrid, and distributed schemes involving primary operator (PO), secondary operator (SO), and their respective end users. In these schemes, PO and SO progressively delegate trading to their end users and adopt more flexible cooperation agreements to reduce computational time and track available resources dynamically. A novel matching-with-pricing algorithm is presented to enable self-organized SU-PU associations, channel allocation and pricing for data and spectrum with low computational complexity. Since connectivity is provided by the actual users, the success of the underlying collaborative market relies on the trustworthiness of the connections. A behavioral-based access control mechanism is developed to incentivize/penalize honest/dishonest behavior and create a trusted collaborative network. Numerical results show that the computational time of the hybrid scheme is one order of magnitude faster than the benchmark centralized scheme and that the matching algorithm reconfigures the network up to three orders of magnitude faster than in the centralized scheme.
Short packet physical-layer network coding with mismatched channel state information

Future multi-terminal communication networks such as machine-to-machine, telecommand and remote control communication systems will be based on short-packet transmissions. Physical-layer network coding (PNC) in such multi-terminal communication systems can potentially enhance network throughput and reduce communication latency. For practical PNC systems, preambles are contained in transmissions for accurate estimation of the channel-state-information (CSI). Identifying good preamble-length regimes, however, is critical for good performance of short-packet PNC systems. Long preambles for short packets reduce spectral efficiency. On the other hand, short preambles compromise accuracy of estimated CSI, leading to sub-par packet error rate (PER) performance. This paper studies the impact of preamble length on the performance of short-packet PNC systems. Specifically, we use random coding bound to quantify PER of channel-coded mismatched-CSI PNC systems and identify the preamble-length regime that achieves the target PER with minimum Eb/No. As an example, we consider a simple yet practically relevant setup of a BPSK modulated PNC system in a two-way relay channel operating with short packets of 128 symbols. Our results show that a preamble of 20 to 30 symbols provides the minimum PER for a wide range of Eb/N0 and achieves a target PER of 10−3 with minimum Eb/No.
Comparative analysis of FEC subsystem in fixed satellite broadcasting standards

Satellite communication systems e.g. digital video broadcast satellite/terrestrial (DVB-S2/T2) have readily adopted LDPC code for Forward Error Correction (FEC), mostly due to its near Shannon performance at very low signal to noise. This paper summarizes the differences across FEC subsystems adopted in worldwide standards for next generation fixed satellite broadcasting. The goal of this analysis is to provide system designers an objective view of the different choices made in these standards and facilitate an easier system implementation for the same.
Coordinated Control of Aerial Robotic Manipulators: Theory and Experiments

This brief presents a three-layer control architecture for coordinated control of multiple unmanned aerial vehicle manipulators (UAVMs): the centralized top layer plans the end-effector desired trajectories of each UAVM; the middle layer, local to each vehicle, computes the corresponding motion references; the bottom layer is a low level dynamic motion controller, which tracks the motion references. At second layer, the overall mission is hierarchically decomposed in a set of elementary behaviors, which are combined together, via the null space-based behavioral approach, into more complex compound behaviors. For each UAVM, the suitable compound behavior to be executed is selected by a supervisor. The proposed framework has been tested through an experimental campaign.
Secure lightweight routing(SLR) strategy for wireless body area networks

Wireless Body Area Networks (WBANs) are becoming a popular choice for a wide range of monitoring applications such as healthcare, sport activity and rehabilitation systems. However, lack of security in WBANs may hamper the wide public acceptance of this technology. Open nature of the wireless medium, makes the patients' data prone to eavesdropping, modification, or loss. Few existing WBAN routing protocols can be found on providing secure authentication using encryption mechanisms, however they do not consider lightweight communication approach. In this paper we propose an energy efficient mechanism that prevents malicious intruders from dropping data packets or forwarding fake data. The mechanism is applied to Adhoc On-demand Distance Vector (AODV) protocol though it can work with any other reactive WBAN routing protocol. The protocol is simulated and results show its effectiveness in detecting malicious nodes with low overhead.
Secrecy Outage Analysis for Distributed Antenna Systems in Heterogeneous Cellular Networks

In this paper, we study physical-layer security for a spectrum-sharing heterogeneous cellular network consisting of a macro cell and an underlaying small cell, where a small base station (SBS) and a macro base station (MBS) transmit to their respective small user (SU) and macro user (MU) over their shared spectrum. A common eavesdropper is assumed to tap both the small-cell and macro-cell transmissions. In the macro cell, multiple distributed antennas of MBS are deployed around the far-off MU and only a single antenna is selected to transmit to MU. Meanwhile, SBS directly transmits to SU in the small cell. To improve the spectrum efficiency, we consider underlay spectrum sharing (USS), which allows SBS and MBS to simultaneously access the shared spectrum. We present two USS schemes, namely, the interference-cancelled opportunistic antenna selection (IC-OAS) and interference-limited opportunistic antenna selection (IL-OAS), where a sophisticatedly-designed signal is exploited in the IC-OAS to perfectly cancel out the interference received at MU from SBS. Closed-form expressions of the secrecy outage probability are derived for both the IC-OAS and IL-OAS schemes over Rayleigh fading channels. Numerical results show that the IC-OAS scheme significantly performs better than the IL-OAS scheme for the macro-cell transmission in terms of the secrecy outage probability. Moreover, with an increasing number of distributed antennas, the secrecy outage probabilities of both IC-OAS and IL-OAS decrease substantially.
Lecture 16 Clustering methods ∗

1 Problem setup Understanding unlabelled examples essentially consists of segmenting the data into groups of similar points. For instance, we might want to group customers according to purchase histories, genes according to expression profiles, web-search results according to topics, MySpace users according to interests, etc. This could be useful, for instance, in automatically organizing the data, discovering hidden structures, or representing highdimensional data in a low-dimensional space.
Visual tracking with re-detection based on feature combination

An improved visual tracking method is proposed, which combines the image gradient feature and color feature, and uses correlation filter framework to undergo object tracking. This algorithm uses the Bayesian theory to model the color information, integrates gradient feature's correlation filter output and object confidence integral map obtained from dense object posterior probability for object tracking. Furthermore, this algorithm also evaluates the tracking results, the object redetection process is enabled as the tracking quality is unreliable, which uses the object confidence integral to determine the candidate objects. When the tracking quality is unreliable and no reliable object is re-detected in some frame, model learning shall be bypassed. Experiments show that its tracking precision is obviously improved compared with that of several state-of-the-arts correlation filters, which can avoid the problem of object loss and model drift due to occlusion.
Understanding Privacy Violations in Big Data Systems

Big data systems have been instrumental in solving computational problems for business intelligence and predictive analysis. Despite this, they exhibit serious concerns for user privacy. The authors provide an overview of privacy in the context of big data, categorizing four types of existing privacy violations in big data systems and assessing the strengths and weaknesses of their protection techniques. They also provide measures that can be taken to strengthen users privacy.
Hosting capacity evaluation in networks with parameter uncertainties

Nowadays, the maximum generation that can be hosted by distribution grids and how to increase it without violating technical constraints are main concerns of DSOs. In this paper, a novel model (named Bricks approach) is discussed, that is designed to estimate the hosting capacity of distribution grids even in case of uncertainties in grid parameters or lack of data. The proposed approach results particularly useful when it is not possible to collect all the necessary data for a classical load flow based analysis, as in the case of studies relevant to emerging countries electrification processes, or when data gathering is difficult, as in the case of complex modern distribution grids. In order to validate the approach, a real-life case study relevant to the Italian city of Aosta is presented.
Sound Abstraction and Decomposition of Probabilistic Programs

Probabilistic programming languages are a ﬂexi-ble tool for specifying statistical models, but this ﬂexibility comes at the expense of efﬁcient analysis. It is currently difﬁcult to compactly represent the subtle independence properties of a probabilistic program and to exploit independence properties to decompose inference. Classical graphical model abstractions do capture some properties of the underlying distribution, enabling inference algorithms to operate at the level of the graph topology. However, we observe that graph-based abstractions are often too coarse to capture interesting properties of programs. We propose a form of sound abstraction for probabilistic programs wherein the abstractions are themselves simpliﬁed programs. We provide a theoretical foundation for these abstractions, as well as an algorithm to generate them. Experimentally, we also illustrate the practical beneﬁts of our framework as a tool to decompose probabilistic program inference.
2 × 2 microstrip patch antenna array fed by substrate integrated waveguide for radar applications

A 2×2 microstrip patch antenna array fed by a sub-strate integrated waveguide (SIW) feeding network for 24-GHz radar applications is suggested in this paper. The microstrip patches are aperture-coupled with the feeding network comprising of a perpendicular coax-to-SIW transition and two Y-junction power dividers. The antenna design is performed in the ANSYS HFSS using finite element method for EM solutions and the procured results have been verified by measurement in Lab. At the frequency 24.4 GHz, the prototype has a gain of 9.28 dBi.
Compression perpendicular to grain : a Swedish survey

The transition from different design codes and design principles for stresses perpendicular to grain has been a change to strength levels and how to handle the design situation when it comes to design of supports for wood in the Swedish building industry. A lot of tests and investigations of the strength perpendicular to the grain has been done in the past, some projects are on-going. The defining of a level for rupture is not unambiguous. The level has to be defined in conjunction to some conditions of deformation. The proportional level however can be reasonable defined. A design situation has to consider at least three different details: Compressions by studs on a sill, compression of a wall plate between two studs or between a support of a beam and a stud, and beam support. The Swedish former characteristic strength level of 7 MPa seems to be adequate for a stud 45 mm which is compressing a continuously supported 45 mm thick sill and with an acceptable deformation of approximately. For other situations this level is seems to be too high. Especially for multi-story buildings with wood structures.
Virtual Inertia Control Strategy in Microgrid Based on Virtual Synchronous Generator Technology

Although the virtual inertia algorithm can be used to enhance the inertia of microgrid system, the strong coupling and low precision always limit its popularization and application. Therefore, a novel virtual inertia control strategy is proposed in this paper. Combining with the potential inertia advantages of virtual synchronous generator (VSG) technology, the poor compatibility between the virtual inertia principle and the energy storage control algorithm is analyzed in detail. In order to improve the control precision, this paper focuses on the analysis of frequency response characteristics of alternating current (ac) side and then regulates the ac frequency more directly and accurately by the virtual inertia generated from the energy storage device and the grid-connected inverter. Thus, additional droop characteristic, particular control algorithm of energy storage device, and power given module are designed, respectively, to make the system provide virtual inertia power support actively under multi disturbance operation. The novel virtual inertia control strategy can effectively deal with all kinds of wind speed and ac load mutation and restrain the frequency variation on ac side. Finally, the correctness and feasibility of the proposed scheme are verified by the simulation results.
Design and simulation of a 3 phase induction motor drive based on indirect rotor field orientation using MATLAB Simulink tool

This paper primarily focuses on the implementation of variable frequency drive (VFD) of the induction motor based upon Indirect Rotor field Orientation (IRFO). The dynamic mathematical model of the induction motor has been developed in MATLAB and then its speed is controlled by implementing the VFD based on IRFO. The IRFO method gives a very precise control over the speed of induction motor. The simulation results are obtained by varying the speed and keeping the load torque constant. This model will largely serves as a basis for developing Induction motor test bed for academia and industry of Pakistan. This test bed would serve as the comprehensive R&D facility in the field of AC machines where both steady state and transient response of the motor can be studied.
Optimization of left ventricular lead position based on a computer model of the heart for cardiac resynchronization therapy

Cardiac resynchronization therapy (CRT) is one of the recommended therapy for patients with heart failure and left bundle branch block. However, up to 30% of appropriately selected patients remain non-responders to CRT. This study presents an automatic non-invasive method for optimizing the lead position in the left ventricle (LV). The optimal electrode position was selected by finding the smallest electrical dyssynchrony estimated by the duration of the QRS complex on electrocardiograms. We build the patient-specific anatomical model based on computer tomography (CT) of the torso, lungs and heart and accurate electrophysiology model for simulate electrocardiograms. The location of the right ventricle electrode was fixed and corresponded with original CT position. The position of the LV lead was varied and chosen in the center of one of the 17 segments on the subendocardial layer and subepicardial layer. The result of simulations has demonstrated the CRT effectivity can be improved by optimization of the LV electrode location by 10%.
Intelligent control scheme for SPV-wind-BESS based microgrid

This article proposes a novel control scheme for efficient control of solar photovoltaic (SPV), wind energy system (WES) and battery energy storage system (BESS) based micro-grid. Using this control scheme the voltage in the main DC bus is kept constant irrespective of the load or weather condition. When power requirement at load side is less than the energy produced by both SPV and WES combined, the batteries are charged and in case of any imbalance or excess energy required in case of peak load conditions the BESS provides the remaining energy. The dc voltage thus obtained is converted into ac voltage by using a three-phase inverter, which is operated with sinusoidal pulse width modulation (PWM) technique. The system is designed and tested in MATLAB-SIMULINK and simulated results are demonstrated to validate the concept and design. On account of simulation results, it has been established that the performance of the controllers is quite satisfactory in both transient and steady states.
A retrospective study

One of the major causes of lumbar spinal canal stenosis (LSCS) has been considered facet joint hypertrophy (FJH). However, a previous study asserted that “FJH” is a misnomer because common facet joints are no smaller than degenerative facet joints; however, this hypothesis has not been effectively demonstrated. Therefore, in order to verify that FJH is a misnomer in patients with LSCS, we devised newmorphological parameters that we called facet joint thickness (FJT) and facet joint cross-sectional area (FJA). We collected FJT and FJA data from 114 patients with LSCS. A total of 86 control subjects underwent lumbar magnetic resonance imaging (MRI) as part of routine medical examinations, and axial T2-weighted MRI images were obtained from all participants. We measured FJT by drawing a line along the facet area and then measuring the narrowest point at L4-L5. We measured FJA as the whole cross-sectional area of the facet joint at the stenotic L4-L5 level. The average FJT was 1.60±0.36mm in the control group and 1.11±0.32mm in the LSCS group. The average FJA was 14.46± 5.17mm in the control group and 9.31±3.47mm in the LSCS group. Patients with LSCS had significantly lower FJTs (P< .001) and FJAs (P< .001). FJH, a misnomer, should be renamed facet joint area narrowing. Using this terminology would eliminate confusion in descriptions of the facet joint. Abbreviations: FJA = facet joint cross-sectional area, FJH = facet joint hypertrophy, FJT = facet joint thickness, LSCS = lumbar spinal canal stenosis, MRI = magnetic resonance imaging.