Miracle-dz/UniFAR-FTUs huggingface dataset:
Light-Field Raw Data Synthesis From RGB-D Images: Pushing to the Extreme

Light-field raw data captured by a state-of-the-art light-field camera is limited in its spatial and angular resolutions due to the camera’s optical hardware. In this paper, we propose an all-software algorithm to synthesize light-field raw data from a single RGB-D input image, which is driven largely by the need in the research area of light-field data compression. Our synthesis algorithm consists of three key steps: (1) each pixel of the input image is regarded as a spot lighting source that emits directional light rays with an equal strength; (2) the optical path of each directional light ray through the camera’s main lens as well as the corresponding micro lens is considered as accurately as possible; and (3) the occlusion of light rays among objects at different distances within the input image is handled with the depth information. The spatial and angular resolutions of our synthesized light-field data can be scaled up when the input RGB-D image has a higher and higher spatial resolution. Meanwhile, for a given input image with a fixed size, we pay a special attention to what would be the extreme we can push the parameters involved in our synthesis algorithm, such as the number of rays emitted from each pixel, the number of micro lenses, and the number of sensors associated with each micro lens. The usefulness of our synthesized data is validated by refocusing, all-in-focus, and sub-aperture reconstructions. In particular, all-in-focus images are evaluated objectively by computing the structural similarity (SSIM) index, which allows us to reach the goal of pushing to the extreme through selecting various parameters mentioned above.
Secrecy Performance Analysis for An-Aided Linear ZFBF in MU-MIMO Systems with Limited Feedback

Although there have been extensive works on artificial-noise-aided (AN-aided) secure transmission schemes for multi-antenna systems, there is still lack of study on the AN-aided scheme employing the widely used linear zero-forcing beamforming (ZFBF) for systems with multiple distributed users. Particularly, there is no analytical secrecy performance for general system settings with neither perfect nor imperfect channel state information of the legitimate users at the transmitter (CSIT). This paper considers the AN-aided ZFBF based on the quantized CSIT for secure communication in the downlink multiuser multi-antenna systems with an external multi-antenna eavesdropper. We develop an approximated closed-form lower bound on the ergodic rate of each legitimate user (LU), and also a closed-form upper bound on the maximum achievable ergodic rate for each LU's messages over the eavesdropper's channel without assuming any asymptotes for system parameters. Then, an approximated closed-form lower bound on the ergodic secrecy rate of each LU follows. Simulation results validate our analytical secrecy performance results and also the effectiveness of AN in enhancing the secrecy performance of linear ZFBF.
Evaluating Cadet Leadership Positions at the U.S. Air Force Academy.

Abstract : The U.S. Air Force relies on effective leadership to complete its mission. The U.S. Air Force Academy exists to develop leaders of character for the Air Force through a four-year program. Part of this program involves cadets participating in leadership positions. By exploring nine types of cadet leadership positions, this dissertation aims to assist the Academy in assessing the value of admission criteria, awarding leadership positions, and designing leadership position experiences. Informing decisions in these areas is likely to improve the Academy's ability to develop effective leaders for the Air Force. This dissertation provides evidence of a positive relationship between participation in a cadet line position and promotion to Lieutenant Colonel. This positive relationship existed for individuals in both rated and non-rated career fields. The magnitude of the relationship varied significantly according to other individual characteristics such as military performance average and grade point average. Participation rates for line positions varied according to demographics such as race, gender, and prep school attendance. Most admission information related to leadership was positively associated with participation in a line leadership position at the Academy.
MVO Algorithm for Optimal Simultaneous Integration of DG and DSTATCOM in Standard Radial Distribution Systems Based on Technical-Economic Indices

Distributed Generation (DG) involving clean renewable energy resources and power electronic devices for control have been the main focus of researchers in electrical power engineering nowadays. The paper presents a new technique for obtaining the best locations and ratings of the DG units, which are based on photovoltaic solar panels, and the Distribution Static Compensator (DSTATCOM), in Radial Distribution Systems (RDSs). The objective function deployed is subject to equality and inequality constraints and aims to minimize three technical-economic system indices, which are Apparent Power Loss (APL), Total Voltage Variation (TVV), and Annual Losses Cost (ALC). Multi-Verse Optimizer (MVO) is a recently developed nature-inspired algorithm, which is utilized to obtain the optimal integration of DG and DSTATCOM into the system. In this paper, four case studies are considered, which involve the base-case, the individual deployment of either DG or DSTATCOM, and the simultaneous deployment of DG and DSTATCOM to test the system performance, while using the MVO algorithm. To verify its validity, the algorithm is tested on the standard IEEE 33- and 69-bus RDSs whose results are compared with the results obtained when using other existing algorithms. Comparison among results reflects the strength and suitability of the suggested MVO algorithm in minimizing the real power losses and enhancing the voltage profile.
AP-Assisted Online Task Assignment for Mobile Crowdsensing

With the widespread of smart devices, mobile crowdsensing has become an attractive way to perceive and collect sensing data. In this paper, we focus on studying AP-assisted task assignment in mobile crowdsensing. The objective is to effectively reduce the average or worst-case makespan of tasks. We focus on a scenario that a task requester needs the assistance of mobile users for task accomplishment while they can meet directly or via APs in an opportunistic manner. We model the crowdsensing system and then formulate the problems under study. We then propose an AP-assisted average makespan sensitive online task assignment (AP-AOTA) algorithm and an AP-assisted largest makespan sensitive online task assignment (AP-LOTA) algorithm. In the proposed algorithms, task assignment at each step considers both the inter-encountering time between requester and each user and that between them while going through APs. We present design details of the proposed algorithms. We derive their computational complexities to be $O(mn^2)$, where $m$ is the number of tasks and $n$ is the number of users. Finally, trace-driven simulation results show that the proposed algorithms outperform existing work.
Factors Affecting Maternal Health Care Seeking Behavior in Rwanda

In this paper we examine factors affecting maternal health care seeking behavior in Rwanda using three rounds of Rwanda Demographic and Health Survey (RDHS) data (1992 2000 and 2005). We pool the three cross-sectional data sets to construct a wealth index based on household assets that are available in all the three rounds of data. Results show that women who gave birth in the five years preceding the 2000 and 2005 RDHS are less likely to deliver in a health facility than those who gave birth in the five years preceding the 1992 RDHS. We also find that women are more likely to deliver at home with professional assistance in 2000 and 2005 compared to 1992. The findings of this study provide insight that progress towards increasing the share of assisted deliveries has been slow. There has been no significant increase in the proportion of women seeking antenatal care. This could partially explain why a large proportion of women continue to deliver at home without professional assistance.
Overstimulation and β-cell function

Previous and present evidence ascribes an important role to overstimulation of β-cells for the secretory abnormalities associated with type 2 diabetes. The abnormality most clearly linked to overstimulation is the elevated ratio of circulating proinsulin to insulin. Evidence obtained in human pancreatic islets suggests that aberrations in insulin oscillations that occur in type 2 diabetes could at least in part be linked to abnormalities in cytoplasmic Ca 2+ oscillations induced by overstimulation. Furthermore, in a transplantation model, we have obtained evidence for long-lasting, perhaps irreversible, effects of overstimulation, implying that this is a causative factor for the well-recognized deterioration of insulin secretion with increasing duration of type 2 diabetes. The mechanisms behind the effects of overstimulation are only partly clarified, but it is clear that reduced insulin secretion after overstimulation is only partly explained by decreased insulin stores. In cultured human pancreatic islets, overstimulation by high glucose leads to a rise in cytoplasmic Ca 2+ levels, which persists after normalization of the glucose levels. Persistent elevation of cytoplasmic Ca + may trigger apoptosis, thus participating in long-term irreversible deterioration of β-cell function. These data provide sufficient rationale for clinical studies to test the beneficial effects of relative β-cell rest in type 2 diabetic patients.
A Game-Theoretic Approach for Non-Cooperative Load Balancing Among Competing Cloudlets

To deliver high performance and reliability to the mobile users in accessing mobile cloud services, the major interest is currently given to the integration of centralized cloud computing and distributed edge computing infrastructures. In such a heterogeneous network ecosystem, multiple cloudlets from different service providers coexist. However, to meet the stringent latency requirements of computation-intensive and mission-critical applications, overloaded cloudlets can offload some of the incoming job requests to their relatively under-loaded neighboring cloudlets. In this paper, we propose a novel economic and non-cooperative game-theoretic model for load balancing among competitive cloudlets. This model aims to maximize the utilities of all the competing cloudlets while meeting the end-to-end latency of the users. We characterize the problem as a generalized Nash equilibrium problem and investigate the existence and uniqueness of a pure-strategy Nash equilibrium. We design a variational inequality based algorithm to compute the pure-strategy Nash equilibrium. We show that all the competing cloudlets are able to maximize their utilities by employing our proposed Nash equilibrium computation offload strategy in both under- and overloaded conditions. We also show through numerical evaluations that our load balancing model outperforms some of the existing game-theoretic load balancing frameworks, especially in a highly overloaded condition.
DOA estimation on CACIS-type array based on fast-Rvm algorithm

Aiming at the fast and high-precision DOA estimation problem on CACIS-type array, this paper proposes a fast-RVM algorithm which can be used for complex data. Firstly, the CACIS-type array structure is analyzed. Secondly, based on the virtual array expansion principle, a sparse signal model based on complex data is constructed. Finally, the real data processing is performed to make it applicable to the data structure of the fast-RVM algorithm. The simulation results show that the proposed method has ideal effects in both direction finding accuracy and computational complexity.
Multiuser MISO Broadcast Channels with Imperfect CSI: Discrete Signaling without SIC

In this paper, we study the communication problem of multiuser multiple-input single-output (MISO) broadcast channels with imperfect channel state information (CSI) at the transmitter. Zero-forcing precoding based on the imperfect CSI is adopted so that the channel can be transformed into a Gaussian interference channel. We consider a practical setting where only discrete input signalings are employed and all the receivers adopt single-user treating-interference-as-noise (TIN) decoding, as opposed to rate-splitting and successive interference cancellation. Under this setting, we first use the deterministic model to approximate the original channel model and develop communication schemes to achieve the entire capacity region. By translating the results of the deterministic model back to the MISO model, we develop a systematic way to design discrete input signalings for the original problem. Our simulation results show that our scheme is capable of approaching the (outer bound of) capacity region of the Gaussian interference channel.
Generalized Single-Valued Neutrosophic Power Aggregation Operators Based on Archimedean Copula and Co-Copula and Their Application to Multi-Attribute Decision-Making

Single-valued neutrosophic set (SVN) can valid depict the incompleteness, nondeterminacy and inconsistency of evaluation opinion, and the Power average (PA) operator can take into account the correlation of multiple discussed data. Meanwhile, Archimedean copula and co-copula (ACC) can significant generate operational laws based upon diverse copulas. In this paper, we first redefine several novel operational laws of single-valued neutrosophic number (SVNN) based on ACC and discuss the associated properties of them. In view of these operational rules, we propound several novel power aggregation operators (AOs) to fuse SVN information, i.e., SVN copula power average (SVNCPA) operator, weighted SVNCPA (WSVNCPA) operator, order WSVNCPA operator, and SVN copula power geometric (SVNCPG) operator, weighted SVNCPG (WSVNCPG) operator, order WSVNCPG operator. At the same time, several significant characteristics and particular cases of these operators are examined in detail. Moreover, we extend these operators to their generalized form named generalized SVNCPA and SVNCPG operator. In addition, a methodology is designed based on these operators to cope with multi-attribute decision-making (MADM) problems with SVN information. Consequently, the effectiveness and utility of the designed approach is validated by a empirical example. A comparative and sensitivity analysis are carried out to elaborate the strength and preponderance of the propounded approach.
Modeling of human information processing in hard-soft fusion (Poster)

With the advent of human-in-the-loop systems, it is necessary to design machines that are optimal for human use. For this purpose, it is important to understand and build models of human behavior. In this paper, human information processing is modeled as a communication channel and information-theoretic metrics are used to quantify amount of information processed by humans in a two-choice inference task. Single-shot inference and sequential inference frameworks are considered and the expected information transfer is derived for human decision makers (HDMs). The results are also extended to derive upper bounds on expected amount of information transfer for the case of a network of HDMs. Ordering principles based on these metrics are presented. Such representations of soft sensors' data guide the design principles of hard sensors and the hard-soft fusion algorithms.
Fabrication and Results of the First MgB2 Round Coil Superferric Magnet at LASA

The LASA Laboratory (INFN, Milan) is working in the High Luminosity LHC program to develop, in collaboration with CERN, six different types of High Order corrector magnets. In this framework, in parallel with a conventional design of superferric magnets with LTS conductor, the LASA is focusing on the research of new superconducting materials which may have applications in particle accelerator magnets. To this purpose, LASA is developing a new type of superferric magnet suitable to arbitrary multipole order, called Round Coil Superferric Magnets (RCSM). The iron yoke shaped with an arbitrary number of poles is able to create the desired harmonic component using only one single round coil with a large bending radius suitable for very strain-sensitive superconductors. The electromagnetic design of a sextupole configuration of the magnet and the production of the first superconducting MgB2 round coil prototype have been already presented. In this paper, we expose the optimization of the iron yoke and polar expansions assembly of the first magnet semi-module prototype. The results of the whole powering test are described in detail and the analysis of the magnetic performances are compared with those of classical superferric correctors.
QoE-Aware Power Control for UAV-Aided Media Transmission with Reinforcement Learning

Unmanned aerial vehicles (UAVs) are widely utilized to capture and compress videos of the target area and then transmit the processed videos to the control station (CS) on the ground. The media transmissions in the UAV-aided network face many challenges due to the highly dynamic network topology and limited resources such as bandwidth and energy. This paper introduces a media transmission scheme in the UAV-aided network utilizing reinforcement learning algorithms to efficiently process and transmit the captured video, which is able to improve the quality-of-experience (QoE) and reduce the energy consumption. Exploiting the proposed reinforcement learning algorithm, the UAV dynamically selects the quantization parameter in the source coding process and determines the transmit power without knowing the video transmission model. Simulation results demonstrate that the proposed scheme is capable of achieving a higher video quality and utility with lower energy consumption compared with the state-of-the-art schemes.
Partial Discharge Inception Voltage Characteristics for Nano-micro Composites under Impulse Voltage in SF6 Gas

The authors have investigated effect of epoxy resin nanocomposites on improvement of creepage discharge withstand voltage so as to reduce the size of the gas insulated switchgear (GIS). This paper deals with the effect of nanofiller loading into microcomposite on partial discharge inceptio voltage (PDIV) in SF6 gas under standard lightning impulse voltage application using an electrode system with wedge gap. The influence of the nanofiller on the dielectric properties and the electric field distribution around the wedge gap was investigated in order to understand this discharge mechanism. As a result, PDIV in a model electrode with a wedge gap improved with small amounts of nanosized silica and titania, and decreases with strontium titanate. The higher the relative permittivity of the insulator, the larger the value of the sample surface electric field around the wedge gap. Nano-micro composites(NMC) containing silica or titania are found to provide higher PDIV than the microcomposite MC, while the NMC have higher relative permittivity than the MC and enhance the electric field in the wedge gap. The increase in PDIV of NMC is interpreted to be due to suppression of electron emission from the sample surface, which is brought by the nanofiller to give rise to deep electron trap level.
The Influence of SPWM Frequency on the Endurance of Inverter-fed Motor Insulation

The influence of sinusoidal pulse-width modulation (SPWM) voltage switching frequency and fundamental frequency on the endurance (lifetime) of polyimide film were investigated. Endurance tests at SPWM voltages with switching frequency from 6~18 kHz and fundamental frequency from 10~200 Hz were carried out on polyimide film insulation keeping the peak to peak voltage and rise & fall time of the square wave voltage at 3 kV and 260 ns, respectively. Experimental results show that, the endurance of polyimide decrease with increasing switching frequency and tends to increase with fundamental frequency at the SPWM with the same switching frequencies. When assessing the lifetime of insulation systems of inverter-fed motors by the endurance obtained at repetitive square wave voltage with 50% duty cycles, the above influence should be considered.
Modeling, Simulation and Classification of Power Transformer Faults Based on FRA Test

Frequency response analysis (FRA) is gaining global popularity in detecting power transformer winding and core deformations due to its sensitivity to electrical and mechanical changes that may occur in transformers. Although there are many researches on fault diagnosis using FRA method, there is still no universally accepted interpretation technique for these tests. Since FRA depends on graphical analysis, interpretation of its signatures is still a great challenge that requires an expert opinion to detect the type of fault. This paper simulates different types of transformer faults at different conditions also some statistical parameters are calculated for the simulated faults to help determining the type of fault.
Interference Mitigation under Degrees-of-Freedom Sensing Uncertainties in Opportunistic Transmission

Inter-system interference may limit the performance of co-existing systems in dense heterogeneous wireless networks. Context-aware waveform design can profitably overcome this limitation. However, the latter substantially depends on degrees-of-freedom (DoF) sensing mechanisms. In this work, we show that total least-squares (TLS)-based waveform design is robust against sensing uncertainties. Given the equivalence of minimum norm and TLS, the latter exhibits the good properties of linear predictors, which are of paramount importance to guarantee minimum inter-system interference and detectability by neighboring nodes. Additionally, since derived solution relies on orthogonal projector onto the so- called noise subspace, we can efficiently and iteratively construct an orthogonal waveform-book enabling the presented transmission scheme in multi-carrier scenarios. Simulation results are presented to support our theoretical contributions, and to highlight any potential advantage of proposed solution in crowded heterogenous wireless networks.
Design and Analysis of Low-Power 16-bit Parallel-Prefix Adiabatic Adders

Adders are the elementary components of all the general-purpose microprocessors and signal processing units which include filters, MAC, Arithmetic Logic Unit, … The efficient design of an adder determines the overall performance efficiency of the system. Parallel Prefix Algorithm is one of the proficient way of implementing an adder. The increase in the number of portable devices has increased the need for low power design techniques. Adiabatic Logic is the one of the promising technique to recover and recycle the power back to the source. This work provides a comparison in terms of area, power and latency between Adiabatic Ripple-Carry adder (RCA), Kogge-Stone Adder (KSA) and Han-Carlson Adder (HCA) and their Static CMOS counterparts. CMOS 180 nm technology is used for schematic entry. Functional verification is performed using Cadence Virtuoso - Spectre Simulator. Analysis of the adders shows that Adiabatic KSA has the least latency, whereas Adiabatic HCA provides a good trade-off between latency and power dissipation.