Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing Performances of SIDO Buck Converters

This paper compares two topologies of single input dual output (SIDO) buck converters. The two topologies explored in literature for SIDO buck converters are based on the single inductor and coupled inductor and named as SI-SIDObu and CI-SIDObu in this paper. Cross-regulation and cross-coupling issues are the main challenges in SIDO converters and controllers are proposed in the literature for SI-SIDObu and CI-SIDObu converters. However, there is no literature which compares and finds which of the two topologies has lesser cross-regulation and cross-coupling. This paper compares the cross-regulation, cross-coupling, and stability of SI-SIDObu and CI-SIDObu. The two topologies are analyzed in detail, simulated in Matlab/Simulink environment and results presented.
3D Motion Reconstruction From 2D Motion Data Using Multimodal Conditional Deep Belief Network

In this paper, we propose a deep generative model named multimodal conditional deep belief network (MCDBN) for cross-modal learning of 3D motion data and their non-injective 2D projections on the image plane. This model has a three-sectional structure, which learns conditional probability distribution of 3D motion data given 2D projections. Two distinct conditional deep belief networks (CDBNs), encode the real-valued spatiotemporal patterns of 2D and 3D motion time series captured from the subjects’ movements into compact representations. The third part includes a multimodal restricted Boltzmann machine which in the training process, learns the relationship between the compact representations of data modalities by variation information criteria. As a result, conditioned on a 2D motion data obtained from a video, MCDBN can regenerate 3D motion data in the generation phase. We introduce Pearson correlation coefficient of the ground truth and the regenerated the motion signals as a new evaluation metric in motion reconstruction problems. The model is trained with human motion capture data and the results show that the real and the regenerated signals are highly correlated, which means the model can reproduce the dynamical patterns of the motion accurately.
Emerging Access Technologies and Open Challenges in 5G IoT: From Physical Layer Perspective

Internet of Things (IoT) is expected to play a prominent role in the envisioned networked society. In IoT ecosystem, Machine Type Communication (MTC) is the access technology that ensures wireless connectivity for end-user devices to the network. Diverse IoT applications pose conflicting requirements and challenges that must be resolved to fully realize the IoT ecosystem. Although the right access technology to address all these challenges is not available yet, notable progress has been made in the recent times to address most of the key requirements. Extended Coverage (EC)-GSM-IoT and Narrow Band (NB)-IoT have been standardized by 3GPP in Release 13 as the access technologies for IoT. Among non-3GPP community, Long Range (LoRa) has attracted significant attention. In this paper, the suitability of the aforementioned access technologies to various IoT services in terms of the relevant system parameters is explored. We have also identified many system design parameters that will have adverse implications if not configured correctly for the right IoT use case. Important open challenges to be addressed from physical layer (PHY) perspective are highlighted here that will help to realize a truly connected world.
REDUCING VARIANCE IN UNIVARIATE SMOOTHING

A variance reduction technique in nonparametric smoothing is proposed: at each point of estimation, form a linear combination of a preliminary estimator evaluated at nearby points with the coefficients specified so that the asymptotic bias remains unchanged. The nearby points are chosen to maximize the variance reduction. We study in detail the case of univariate local linear regression. While the new estimator retains many advantages of the local linear estimator, it has appealing asymptotic relative efficiencies. Bandwidth selection rules are available by a simple constant factor adjustment of those for local linear estimation. A simulation study indicates that the finite sample relative efficiency often matches the asymptotic relative efficiency for moderate sample sizes. This technique is very general and has a wide range of applications.
Hybrid Pseudo-stationary Iterative Detection Algorithm for Uplink Massive MIMO Systems

Massive multiple-input multiple-output (MIMO) is a core technology for 5G and beyond systems. However, symbol detection in massive MIMO requires high complexity matrix inversions. To tackle this problem, a novel and robust low complexity hybrid algorithm (HA) is proposed for uplink symbol detection in massive MIMO systems with a large number of users. Proposed HA integrates two novel techniques; non-stationary Newton iteration (NSNI) and improved sequential Richardson iteration (ISRI), which are proposed in this paper. Newton iteration (NI) is a promising technique for approximate matrix inversion, however, in this paper, Newton iteration (NI) is realized as the stationary iterative method which uses constant step size for all iterations. Consequently, NI suffers from performance-complexity trade-off. To address this issue, NSNI is proposed, which utilizes non-stationary step size that changes at each iteration. Moreover, Richardson iteration is a simple but efficient algorithm for massive MIMO detection, however, RI suffers from intersymbol interference (ISI) which is a major reason for the low performance of RI when the number of users scales up in massive MIMO system. Hence, symbols are updated sequentially to extenuate ISI in RI. In addition, to further improve the performance of RI, optimal step sizes based on each symbol-index in RI are computed and hence, an improved stationary Richardson iteration (ISRI) is introduced. Finally, to further boost bit error rate (BER), NSNI and RI are integrated into pseudo-stationary iterative HA for low complexity symbol detection in massive MIMO systems. Simulation results validate low complexity, superior BER performance and robustness of proposed HA as compared to recently reported several massive MIMO detection techniques, under both perfect and imperfect channel state information at the receiver.
Retrieval practice as a learning strategy for individuals with Down syndrome A preliminary study

ABSTRACT. Remembering recently studied materials (i.e., retrieval practice) is more beneficial for learning than restudying these materials. Objective: To investigate whether retrieval practice benefits learning for individuals with Down syndrome. Methods: Eighteen individuals with Down syndrome (mean age=21.61 years, SD=5.93) performed a task entailing a first read of an encyclopedic text covering a series of target words. After reading the text twice, participants recalled half of the target words (retrieval practice), and reread the other half (restudy). After 48 hours, participants answered a multiple-choice test including all target words. Subsequently, WASI’s Vocabulary and Matrix reasoning subtests were administered to estimate intelligence. Results: The benefit of retrieval practice for learning was numerically greater than the benefit of restudy, although this advantage did not reach statistical significance. Inspection of individual data suggested that the benefit of retrieval practice was greater than the benefit of restudy for the majority of the participants, independently of the participants’ vocabulary or reasoning abilities. Conclusion: Although more research is needed before retrieval practice can be recommended as a learning strategy for individuals with Down syndrome, the data suggest that retrieval practice can be a useful teaching tool for at least part of this population.
Development of a Single-Phase Inverter for Application in a Hybrid Solar UPS

Conversion of solar energy into a useful source of electric power at high efficiency is a challenge. In order to utilize the solar energy to its maximum potential a closed loop single phase inverter is developed for a 1kVA stand-alone hybrid solar UPS, capable of supplying a domestic load of 600W, with a worst-case power factor of 0.6, and a backup time of one hour. The control scheme is based on sensing the output voltage and using it in a feedback loop to ensure that the load voltage is regulated to the rated value. Sine triangle PWM technique is used to minimize the total harmonic distortions. Different topologies of snubber circuits utilized are compared and discussed. The simulations are carried out using MATLAB/SIMULINK and the hardware model of the system is developed and tested under various conditions.
Young Children's Reactions to War-Related Stress: A Survey and Assessment of an Innovative Intervention

OBJECTIVE. The goal was to assess stress reactions in young children during and after war and the effects of a new brief intervention. METHODS. Two separate studies were conducted. In study I, we assessed war exposure and stress reactions of 74 children (2–7 years of age) in a sheltered camp during the second Israel-Lebanon war (July to August 2006). Their exposure to war experiences and their stress reactions were assessed through parental reports during the last week of the war. In addition to standard care, 35 children received a brief intervention (Huggy-Puppy intervention) aimed at encouraging them to care for a needy Huggy-Puppy doll that was given to them as a gift. The effects of the Huggy-Puppy intervention were assessed in a follow-up interview 3 weeks after the war. Study II assessed the efficacy of group administration of the Huggy-Puppy intervention to 191 young children, compared with 101 control subjects. The effects of the intervention on stress-related symptoms after the war were assessed in telephone interviews with the parents. RESULTS. Study I indicated that, during the war, most children had significant exposure to war-related experiences and had severe stress reactions. The Huggy-Puppy intervention was associated with significant reductions in stress reactions in the postwar assessment. A higher level of attachment and involvement with the doll was associated with better outcomes. The results of study II indicated that group administration of the Huggy-Puppy intervention was associated with significant reductions in stress reactions. CONCLUSION. These studies suggest that the Huggy-Puppy intervention may offer pediatricians and other child health care professionals a promising, cost-effective intervention for children during stressful times.
Demo: OpenAirInterface: an open LTE network in a PC

LTE 4G cellular networks are gradually being adopted by all major operators in the world and are expected to rule the cellular landscape at least for the current decade. They will also form the starting point for further progress beyond the current generation of mobile cellular networks to chalk a path towards fifth generation mobile networks. The lack of open cellular ecosystem has limited applied research in this field within the boundaries of vendor and operator R&D groups. Furthermore, several new approaches and technologies are being considered as potential elements making up such a future mobile network, including cloudification of radio network, radio network programability and APIs following SDN principles, native support of machine-type communication, and massive MIMO. Research on these technologies requires realistic and flexible experimentation platforms that offer a wide range of experimentation modes from real-world experimentation to controlled and scalable evaluations while at the same time retaining backward compatibility with current generation systems. In this work, we present OpenAirInterface (OAI) as a suitably flexible platform towards open LTE ecosystem and playground [1]. We will demonstrate an example of the use of OAI to deploy a low-cost open LTE network using commodity hardware with standard LTE-compatible devices. We also show the reconfigurability features of the platform.
Switched-Capacitor-Based Three-Phase Five-Level Inverter Topology With Reduced Components

This paper presents a new five-level multilevel inverter (MLI) based on retrofitting of the conventional two-level (2L) three-phase inverter modules with minimum structural reconfigurations for low-voltage and high-power-quality demanding applications. It comprises two such inverter modules connected in series with 2L switched-capacitor units (SCUs). It requires only two isolated dc sources which are shared by all inverter output phases and thus eliminates the chances of output phase unbalance. Further, the voltage across the floating capacitors of the SCUs are naturally regulated without any sensors, thus makes the proposed topology more elegant for industrial applications. Further, an extensive comparison with the recent other MLI topologies attests the reduced requirement of the components in devising the proposed topology. Finally, experimental results from a low-power hardware prototype are presented to validate the feasibility of the proposed configuration.
20-Gb/s ON–OFF-Keying Modulators Using 0.25- $\mu$ m InP DHBT Switches at 290 GHz

Performances of high-speed switches operating as terahertz on–off-keying (OOK) modulators are reported. Two types of switches, a passive shunt switch and an amplifier switch, are fabricated using 0.25-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> InP double heterojuction bipolar transistor (DHBT) technology. Small-signal tests show that the amplifier switch possesses superior on–off ratio, but the passive switch has broader bandwidth and smaller group delay ripples. A modulator test setup is built with 20-dB path loss between the transmitter and the receiver. The results indicate that carrier power levels of 14 dBm for the shunt switch and 8 dBm for the amplifier switch are required for 20-Gb/s OOK modulation with bit error rate (BER) of 10<sup>−2</sup> at 290 GHz.
Bressem (Eds.) Body-Language-Communication: An International Handbook on Multimodality in Human Interaction. Handbooks of Linguistics and Communication Science (HSK) 38/2 Berlin, Boston: De Gruyter: Mouton

The chapter outlines a theoretical proposal on abstract concepts and words, called WAT: Words As social Tools. The proposal has four central principles: 1) both concrete and abstract concepts are embodied and grounded; 2) the linguistic mediation and the social influence is more crucial for acquiring abstract than concrete words; 3) abstract concepts activate more linguistic brain areas than concrete concepts; 4) linguistic variability affects more abstract than concrete concepts. The proposal is presented in light of recent supporting evidence. Embodied cognition and word acquisition: The challenge of abstract words
Efficient Scalable Video Coding Based on Matching Pursuits

Efficient encoding of motion residuals is essential for low-delay video applications in which videos are encoded by hybrid motion compensation and a residual encoding structure. Current standard video coding systems use hybrid motion compensation and the discrete cosine transform (DCT), where the number of bases needed to encode a residual block is the same as the number of the pixels in the block. An encoded frame is predicted from its previous reconstructed frame, and a residual image is then encoded by a non-redundant transformation, such as the DCT, or an approximation of the DCT using integer coefficients. As well as nonredundant transformation, a frame-based technique called matching pursuit (MP) has been proposed to encode motion residual images. Mallat and Zhang (Mallat & Zhang, 1993) were the first to propose a matching pursuit algorithm that decomposes a signal into a linear combination of bases within an overcomplete dictionary. Vetterli and Kalker have translated motion compensation and DCT hybrid video coding into a matching pursuit technique, and encoded frames by the matching pursuit algorithm and a dictionary composed of motion blocks and DCT bases (Vetterli & Kalker, 1994). In (Neff & Zakhor, 1997), Neff and Zakhor show that using a matching pursuit algorithm to encode motion residual images achieves a better performance than a DCT-based algorithm in terms of PSNR and perceptual quality at very low bit rates. The results in (Lin et al., 2005) also demonstrate that the matching pursuit FGS coding scheme performs better than MPEG-4 FGS at very low bit rates. Unlike a transform-based decoder, a matching pursuit decoder does not require an inverse transform; therefore, it is less complex. In a transform-based decoder, loop filtering and post processing are usually applied at very low bit rates to remove blocking and ringing artifacts, whereas a matching pursuit decoder can achieve comparable quality without such filtering and processing (Neff et al., 1998). Because the matching pursuit algorithm is a data-dependent frame-based representation, a matching pursuit video coding technique cannot be directly translated from conventional transform-based approaches. We must therefore develop a new matching pursuit video coding technique that can deal with quantization noise in the matching pursuit algorithm (Neff & Zakhor, Sept. 2000; Vleeschouwer & Zakhor, 2002), multiple description coding for reliable transmission (Tang & Zakhor, 2002), scalable bitstream generation (Al-Shaykh et al., 1999; Vleeschouwer & Macq, 2000; Rose & Regunathan, 2001), and dictionary learning and adaptation (Engan et al., 2000).
A DC-DC Synchronous Buck Regulator with Mode Changing Control Strategy for Low Voltage Applications

This work presents a novel mode changing control strategy for enhancing the overall performance of low voltage DC-DC Synchronous Buck switching regulators for portable applications. Hysteretic mode control with Zero Voltage Switching (ZVS) is employed in the light load range to optimize the switching and conduction losses and also, to regulate the inductor current ripple and hence the switching frequency. In the high load range, conventional voltage mode control is implemented to maintain high conversion efficiency. The converter can flexibly switch between the two modes based on the load current to achieve higher efficiency over a broad range of load current.
Exploring Team Passing Networks and Player Movement Dynamics in Youth Association Football

Understanding how youth football players base their game interactions may constitute a solid criterion for fine-tuning the training process and, ultimately, to achieve better individual and team performances during competition. The present study aims to explore how passing networks and positioning variables can be linked to the match outcome in youth elite association football. The participants included 44 male elite players from under-15 and under-17 age groups. A passing network approach within positioning-derived variables was computed to identify the contributions of individual players for the overall team behaviour outcome during a simulated match. Results suggested that lower team passing dependency for a given player (expressed by lower betweenness network centrality scores) and high intra-team well-connected passing relations (expressed by higher closeness network centrality scores) were related to better outcomes. The correlation between the dyads’ positioning regularity and the passing density showed a most likely higher correlation in under-15 (moderate effect), indicating a possible more dependence of the ball position rather than in the under-17 teams (small/unclear effects). Overall, this study emphasizes the potential of coupling notational analyses with spatial-temporal relations to produce a more functional and holistic understanding of teams’ sports performance. Also, the social network analysis allowed to reveal novel key determinants of collective performance.
A geometric model of spatial distortions in virtual and augmented environments

The 3D structure of a virtual or augmented scene is affected by distortions that can affect the natural fruition of the experience. Here, we consider the distortions of the spatial layout of virtual scenes, specifically the underestimation of egocentric distances, as experienced by users.The aim of our work is to develop a computer vision based modeling that is able to describe such an underestimation. In particular, we propose that the spatial misperception has origin from the fact that the world is seen by a user through an uncalibrated camera, thus producing a virtual view of a distorted space for him/her. The proposed geometric model is able to explain the experimental evidence of the egocentric distance underestimation that is reported in the literature.
Street object classification via LIDARs with only a single or a few layers

LIDAR sensors are part of the sensor system of several intelligent vehicles and transportation systems providing both object and free-space detection capabilities. In this paper a recognition method is proposed for LIDARs with only a few detection planes. Our method is especially useful in the case when angular resolution of the scan is sufficient, but in the vertical direction the planes are far from each other. The proposed method uses new features including Fourier based descriptor, deep learning classification and exploits additional 3D information if it is available. We tested the method on ten thousands of samples from a large public database. This paper gives an effective solution for a hard problem of LIDAR based recognition problems, namely the far-object detection in case of mobile LIDARs of limited or poor vertical resolution.
A Heuristic Method for Large-Scale Cognitive-Diagnostic Computerized Adaptive Testing

In formative assessments, one wants to provide a useful feedback to the examinee at the end of the test. In order to reduce the number of questions asked in an assessment, adaptive testing models have been developed for cognitive diagnosis, such as the ones encountered in knowledge space theory. However, when the number of skills assessed is very huge, such methods cannot scale. In this paper, we present a new method to provide adaptive tests and useful feedback to the examinee, even with large databases of skills. It will be used in Pix, a platform for certification of digital competencies for every French citizen.
IAE and ISE Performance Criterion Based Loop Filter Tuning of Transport Delay-Phase Locked Loop (TD-PLL) for Single Phase Grid Connected Inverters

Transport delay based Phase Locked Loop (TD-PLL) algorithm has gained wide acceptance for interconnecting a single phase grid connected inverters (GCIs) with the utility grid owing to its straightforward implementation. This paper proposes a new design procedure to obtain the value of loop filter parameter of TD-PLL using time domain Performance Index Optimization based on non-linear optimization technique. The proposed tuning method was evaluated with established tuning methodologies under different grid disturbances. Numerical simulation results using MATLAB/ Simulink shows that the proposed tuning method provides an optimum parameter value and enable a better dynamic response without significant overshoot and steady state error in TD-PLL response.
“RISK SHARING AND SUPPLIER SWITCHING CONTRACTS” BARDIA KAMRAD

Using a real options framework, we value and analyze supply contracts characterized by exchange rate uncertainty, order quantity flexibility and supplier-switching options. Analogous to the portfolio optimization framework, our framework analyzes the incentives that the suppliers face in accepting order level flexibility. The resulting tradeoff (for the supplier) is a balance between greater volatility in the supply schedule and the prices that the producer pays. In this context, we explicitly model how flexibility can be beneficial to both the producer and multiple suppliers. In other words, how a contract with quantity flexibility can be Pareto optimal, with neither the producer nor the suppliers being worse off as compared to inflexible contracts. This implies that option to switch between suppliers is not costless, thus resulting in the producer having to compensate suppliers in a manner consistent with a profit maximization objective for all parties.