Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Tumor Segmentation by Means of Deep Convolutional U-Net With Pre-Trained Encoder in PET Images

To assist physicists in developing radiation therapy treatment plans and in evaluating the effects of radiotherapy, an accurate and automatic tumor segmentation approach in positron emission tomography (PET) images is highly demanded in the clinical practice. In the present paper we investigate and construct a neural network architecture for auto-segmenting tumors by leveraging a 14-layer U-Net model with two blocks of a VGG19 encoder pre-trained with ImageNet. For pursuing efficient learning, a series of training strategies are proposed with limited training data. First, we apply a loss function based on Jaccard distance to re-balance the weights of training samples without re-weighting. Because of highly unbalanced data, re-weighting is an essential step but brings additional computation when cross-entropy loss function is used for medical image segmentation. Second, we import the DropBlock technique to replace the normal regularization dropout method as the former can help the U-Net efficiently avoid overfitting. We use a database containing 1309 PET images to train and test the proposed model. The mask, contour, and smoothed contour of a tumor are used as truths for teaching the proposed model. These are provided by expert radiologists. The segmentation accuracy compared to the truths is evaluated by calculating the Dice coefficient, Hausdorff distance, Jaccard index, sensitivity, and precision metrics. Extensive experimental results show that our method has achieved a relatively competitive performance in PET images on tumor segmentation. The volumes of the segmented tumors provided by our model would enable accurate automated identification and serial measurement of tumor volumes in PET images.
Multiwinding based Semi-Dual Active Bridge Converter

Modular converter structures are state of the art for fast charging, since high power and short charging times are required. Multiwinding converter structures can bring several positive advantages, like cost and space reduction. However, the increased complexity due to the magnetically coupled ports needs to be handled. This paper introduces a multiwinding based Semidual-Active-Bridge converter with separated output voltages. The related design challenges in terms of independent charging voltage regulation are evaluated and design guidelines for the medium frequency transformer are presented. The theoretical analysis is validated experimentally.
Predicting students’ performance using survey data

The acquisition of competences for the development of computer programs is one of the main challenges faced by computer science students. As a result of not being able to develop the abilities needed (for example, abstraction), students drop out the subjects and sometimes even the course. There is a need to study the causes of student success (or failure) in introductory curricular units to check for behaviours or characteristics that may be determinant and thus try to prevent and change said causes. The students of one programming curricular unit were invited to answer four surveys. We use machine learning techniques to try to predict the students’ grades based on the answers obtained on the surveys. The results obtained enable us to plan the semester accordingly, by anticipating how many students might need extra support. We hope to increase the students’ motivation and, with this, increase their interest on the subject. This way we aim to accomplish our ultimate goal: reducing the drop out and increasing the overall average student performance.
Decentralized Solution Based on Small-AC-Signal Injection for Accurate Power Sharing in Islanded Microgrids with Complex Line Impedances

To address the power sharing accuracy problem caused by mismatched line impedances in a real distributed microgrid with dispersed sources and loads, a decentralized solution based on the injection of an extra small AC signal into the output voltage of each inverter is proposed in this paper. Without the aid of communication links, appropriate virtual impedances could be obtained to compensate the mismatched line impedances in full frequency range, and hence the active, reactive, unbalanced and harmonic powers could be shared accurately among parallel inverters under various load conditions. Moreover, the proposed method also considers the impact of complex line impedances, and this makes it a promising strategy in practical microgrid applications. Finally, a comprehensive case is provided to validate its effectiveness.
A Data-Driven Method Based on Quadratic Programming for Distance-Based Formation Control of Euler–Lagrange Systems

Distance-based formation control of second-order autonomous agents can be seen as a physical system of particles linked by springs, whose evolution may be described by a Lagrangian function. In this letter we present a method based on quadratic programming to approximate the unknown Lagrangian function associated with the distance-based formation control of second-order agents from a set of sample data.
An Optimized Isolated Swiss-Forward Three-Phase Rectifier

Swiss-rectifier (SR) is a novel type of rectifier structure which contains a three phase unfolder circuit and two symmetric DC-DC converters. In order to implement a simplified isolated rectifier system, two forward converters or phase-shift full bridge converters are used to achieve power factor correction (PFC). However, this kind of replacement requires two same transformers. Using more than one transformer is not conducive to the reduction of the volume. Therefore, an optimized isolated Swiss forward rectifier (OSFR) is proposed. Only one double-forward structure is used when the power is transmitting. Two voltage clamp branches are used to implement the PFC principle of the SWISS-rectifier. The principle of the operation is discussed specifically. The performances of the proposed converter are verified on a prototype with 90kHz switching frequency.
A Cascaded Multimodal Natural User Interface to Reduce Driver Distraction

Natural user interfaces (NUI) have been used to reduce driver distraction while using in-vehicle infotainment systems (IVIS), and multimodal interfaces have been applied to compensate for the shortcomings of a single modality in NUIs. These multimodal NUIs have variable effects on different types of driver distraction and on different stages of drivers’ secondary tasks. However, current studies provide a limited understanding of NUIs. The design of multimodal NUIs is typically based on evaluation of the strengths of a single modality. Furthermore, studies of multimodal NUIs are not based on equivalent comparison conditions. To address this gap, we compared five single modalities commonly used for NUIs (touch, mid-air gesture, speech, gaze, and physical buttons located in a steering wheel) during a lane change task (LCT) to provide a more holistic view of driver distraction. Our findings suggest that the best approach is a combined cascaded multimodal interface that accounts for the characteristics of a single modality. We compared several combinations of cascaded multimodalities by considering the characteristics of each modality in the sequential phase of the command input process. Our results show that the combinations speech + button, speech + touch, and gaze + button represent the best cascaded multimodal interfaces to reduce driver distraction for IVIS.
High Isolation Auxiliary Power Supply for Medium-Voltage Power Electronics Building Block

The Austin SuperMOS is an intelligent 7.2kV/60A SiC power switch integrated with a gate driver and an isolated auxiliary power supply. Design considerations for the auxiliary power supply in a 5kV Austin SuperMOS based full bridge power electronic building block (PEBB), in terms of electrical performance and insulation against high voltages, are presented in this paper. In the presented auxiliary power supply, an LLC resonant converter along with 4 individual floated voltage sources including high frequency and high-voltage isolation transformers are developed. The design of individual floating sources is based on circuit and FEM simulations as well as necessary engineering calculation. Partial discharge measurements are also conducted to validate the proposed high voltage transformer design. Electrical measurements performed on the fabricated full bridge PEBB reveal stable and proper operation of the system.
Vision-based UAV Obstacle Avoidance Algorithm on the Embedded Platform

Due to the limited budget for power and memory consumption on the mobile/IoT platforms make deep learning algorithm hard to get the ideal efficiency and accuracy on the obstacle detection and avoidance for unmanned aerial vehicle (UAV) with monocular version. To resolve this, we design a learning based virtual odometry method and combine it with a quantization scheme which can be added into the training framework. During the obstacle detection networks training process it will reduce the accuracy loss on the original models caused by the quantization. By evaluating the feature detection and matching we used in the avoidance detection on MS-COCO dataset, our method can archive 8-bit inference accuracy loss less than 3%, almost close to the float pipeline.
Associative Media Learning With Smartwatches

We report the results of a study that investigated the usage of a consumer-grade smartwatch for associative media learning. In a study with 29 participants, we investigated the effects of learning the Morse code alphabet purely visual versus learning with an associated vibration pattern. Our results show a trend that participants who received the vibration stimulus in addition to the visual stimulus learned faster and retained more knowledge than the group who learned using only the visualization, as measured by two post-tests one and three days after the learning took place.
An Isolated Multilevel Bi-directional DC-DC Converter to Interface HV Battery and Traction Inverter in EVs

This paper proposes a soft-switched isolated multilevel DC-DC converter topology to interface the high voltage battery pack and the traction inverter in the electric vehicles. Compared to existing topologies, the proposed converter provides higher DC voltage gain. The multilevel voltage obtained by virtue of the circuit configuration results in a significant reduction of the output DC voltage ripple. Consequently, a substantial reduction in filter sizing can be obtained which accounts for the higher power density of the converter. The soft-switching of the primary side devices further boosts the efficiency of the converter. A detailed analysis of the various modes of operation and the proposed switching scheme is presented in this paper including a design guideline for the selection of output filter parameters. The performance of the proposed converter is evaluated through relevant simulation and experimental verification on a 1kW laboratory prototype.
New Advances Reconstructing the Y Chromosome Haplotype of Napoléon the First Based on Three of his Living Descendants

This paper describes the findings of the complete reconstruction of the lineage Y chromosome haplotype of the French Emperor Napoleon I. In a previous study (Lucotte et al., 2013) we reconstructed, for more than one hundred Y-STRs (Y–short tandem repeats), the Y-chromosome haplotype of Napoleon I based on data comparing STR allelic values obtained from the DNA of two of his living descendants: Charles Napoleon (C.N.) and Alexandre Colonna Walewski (A.C.W.); in the present study we compare STR allelic values of C.N. and A.C. W. to those of Mike Clovis (M.C.), a living fifth generation descendant of Lucien (one of Napoleon’s brothers). When compared between M.C. , C.N. and A.C. W. , STR allelic values are identical for a total of 93 STRs; that permits us to propose those values, for which the three living descendants are identical, as expected allelic values of Napoleon I’s Y-chromosome haplotype. For seven STRs, allele values are variable between M.C. , C.N. and A.C. W. ; we propose for three of them (DYS442, DYS454 and DYS712) expected allelic values, based on data concerning the allele distributions of these STRs in the population.
Carbon dioxide evolution from snow-covered agricultural ecosystems in Finland

Hiilidioksidin vapautumista lumipeitteisesta ja paljaasta maasta mitattiin suorasti ja epasuorasti Suomen maaperasta. Mittaukset tehtiin turve-, hiekka- ja savimaasta. Suorissa mittauksissa kaytettiin suljetun kammion menetelmaa ja epasuorissa Fickin diffuusiomallia.Kaikkien em. maalajien talvilampotila vaihteli 2 cm:n syvyydessa Oja +1 °C valilla. Hiilidioksidipitoisuus lumikerroksen sisalla oli sita korkeampi mita paksumpi lumikerros oli. Lumen hiilidioksidipitoisuudesta mitattu keskimaarainen hiilidioksidivirtaus vaihteli 10-27 mg CO2 m-2 h-1 diffuusiomallilla ja 18-27 mg CO2m-2 h-1 suljetun kammion menetelmalla mitattuna. Taman tutkimuksen mukaan lumi on hyva maan lampoeriste, ja CO2:n tuotanto jatkuu maassa lampo-tilojen pysyessa lumipeitteen alla jaatymispisteen ylapuolella. Maaperasta vapautuu ilmakehaan hiilidioksidia lumipeitteen lapi. Hiilidioksidin muodostumista talvella ja kesalla kuvaavan suhdeluvun arvioitiin olevan noin 4 %. Taten merkittava osa vuotuisista hiilidioksidipaastoista syntyy talvella.
Satellite and Terrestrial Multi-Connectivity for 5G: Making Spectrum Sharing Possible

This paper reports the first results of the 5G- ALLSTAR project [1] aiming at providing solutions and enablers for spectrum sharing in a 5G cellular and satellite multi-connectivity context. First, we present an exhaustive study of the frequency bands eligible for these systems in the short and medium term. A ray-tracing based and a geometry-based stochastic channel models developed in the project are then described. These models can be used to simulate systems involving terrestrial and non- terrestrial networks. We then describe three different ways investigated in the project for managing interference: signal processing (hardware implementation of a 5G New Radio compatible physical layer), beamforming (steering and switching beams in order to avoid the interference while preserving the spectral efficiency) and radio resource management (tool designed for joint optimization of satellite and terrestrial resource sharing).
Concept of Intelligent Agent for Verification of Considering the Subject Area Information

The development of software systems requires considering the subject area's information (SAI) at all stages of their design and development in order to improve their reliability, functional security, survivability and dependability. Therefore, verification of considering the subject area's information into the software systems' development process is an important and urgent task. The paper analyzes the known intelligent agents, and this analysis showed that the known intelligent agents don't solve the task of verification of considering the subject area's information in the process of development of software systems. Therefore, it is necessary to develop the concept of activity of such an intelligent agent(s). The paper first time proposes the intelligent agent of verification of considering the subject area information in the process of software systems development, which is based on the comparison of ideal and real ontologies, which contain, respectively, the necessary and available information at each stage of the software system life cycle. This pairwise comparison of the respective ontologies will make it possible to identify the information losses (and knowledge gaps) at each stage of the life cycle and to estimate their volume.
Multi-Band Multi-Hop WLANs for Disaster Relief and Public Safety Applications

Calamities like tsunami and flood cause communication outage by damaging the communication infrastructure and power supply. As an alternate communication facility, multi-hop relay networks are deployed. Deploying these networks is quick and easy, however, the performance is deteriorated due to the use of relays in such environments. Similarly, given the surge in bandwidth hungry applications, performance parameters such as high throughput and low end-to-end delay are also daunting challenges in the traditional one-hop wireless LANs (WLANs). In this context, simultaneous transmission over multiple bands has the potential to improve the capacity of relay networks and accommodate the future unforeseen bandwidth-hungry applications. Manipulating the attributive diversity of different bands will yield prolific gains in terms of performance. However, for multi-hop transmissions in such multi- band networks, channel conditions and bit-rates over different bands, different links tend to be different. This causes significant degradation in the performance in terms of throughput and end-to- end delay. To address this problem, considering the channel conditions and bitrates of each band on either side of the relay, we exploit Shapley value to distribute the load in such a way that maximizes throughput and minimizes end-to-end delay in multi- band networks. Illustrative numerical results demonstrate the effectiveness of our proposed scheme.
Scalable and Secure Big Data IoT System Based on Multifactor Authentication and Lightweight Cryptography

Organizations share an evolving interest in adopting a cloud computing approach for Internet of Things (IoT) applications. Integrating IoT devices and cloud computing technology is considered as an effective approach to storing and managing the enormous amount of data generated by various devices. However, big data security of these organizations presents a challenge in the IoT–cloud architecture. To overcome security issues, we propose a cloud-enabled IoT environment supported by multifactor authentication and lightweight cryptography encryption schemes to protect big data system. The proposed hybrid cloud environment is aimed at protecting organizations’ data in a highly secure manner. The hybrid cloud environment is a combination of private and public cloud. Our IoT devices are divided into sensitive and nonsensitive devices. Sensitive devices generate sensitive data, such as healthcare data; whereas nonsensitive devices generate nonsensitive data, such as home appliance data. IoT devices send their data to the cloud via a gateway device. Herein, sensitive data are split into two parts: one part of the data is encrypted using RC6, and the other part is encrypted using the Fiestel encryption scheme. Nonsensitive data are encrypted using the Advanced Encryption Standard (AES) encryption scheme. Sensitive and nonsensitive data are respectively stored in private and public cloud to ensure high security. The use of multifactor authentication to access the data stored in the cloud is also proposed. During login, data users send their registered credentials to the Trusted Authority (TA). The TA provides three levels of authentication to access the stored data: first-level authentication - read file, second-level authentication - download file, and third-level authentication - download file from the hybrid cloud. We implement the proposed cloud–IoT architecture in the NS3 network simulator. We evaluated the performance of the proposed architecture using metrics such as computational time, security strength, encryption time, and decryption time.
Design and Multi-Objective Optimization of Coil and Magnetic for Wireless Power Transfer in Auxiliary Power Network

This paper proposes a coil and magnetic design and multi-objective optimization method for wireless power transfer in auxiliary power network for 10 kV SiC MOSFET based power electronics building block. This paper summarizes basic parameters extraction methods for coil to avoid time-consuming 3D FEA simulations during the optimization process. In addition, effect of magnetic shielding layer is also analyzed. Self- and mutual-inductance calculation using mirror method when magnetic shielding is applied are also given. Coil optimization process considering efficiency, isolation capacitance and insulation capability is given. A wireless power transfer converter prototype is built that features in 48 V to 48 V conversion, 100 W, 92 % efficiency, 4pF isolation capacitance, and 24 kV insulation voltage to validate the optimization result.
V2X Operation of Integrated Single-Phase Bidirectional Electric Vehicle Charger

The higher cost of electric vehicles (EVs) compared to combustion vehicles is a roadblock to the adoption of EVs. As the higher cost is mainly due to the battery pack, it cannot be significantly reduced, however it can be made a better value if the EV can provide additional functionalities. Vehicle-to-everything (V2X) operation can allow the EV to operate as a mobile power source, eliminating the need for separate backup/portable generators and standalone power inverters. This paper presents the V2X operation of an integrated single phase charger based on the dual-inverter drive. As this integrated charger re-uses the existing high-power traction inverter and motor, this saves additional costs over previously presented V2X capable discrete on-board chargers, while offering a higher power output. This paper describes the principle of operation and control, along with experimental results using a full-scale 110 kWpk dual-inverter drive consisting of a liquid cooled EV motor. Real world functionality is demonstrated by powering resistive loads and non-linear loads, as well as a jigsaw power tool. Finally, efficiency measurments are provided, with a peak efficiency of 96%.
Efficiency Optimized Design Procedure of low-Q LLC Resonant Converter for Wide Input Voltage and Load Range Application

LLC resonant dc-dc converter has become a de-facto resonant topology in many emerging industrial applications. This paper proposes a simple to implement design approach for LLC dc-dc resonant converter suitable for operation under wide input voltage and load range for fixed output voltage applications. For such applications, selecting a design with low inductance ratio (K) and high-quality factor (Q) ensures narrow switching frequency variation but at the cost of efficiency and power density. However, maximizing power efficiency throughout the required range of line and load conditions with output voltage regulation requires optimal selection of K and Q. The proposed design approach is compared with two other existing design approaches and tested on an experimental prototype of 300W LLC converter for 2:1 input voltage range (20-40V). The proposed design shows rated efficiency improvement of 3% over existing methods.
Enteral Feeding of Critical Patients in Juan A Fernandez Hospital in Buenos Aires, Argentina. Does it Lead to Protein Deficit and Caloric Excess?

Introduction: The critical patient is characterised by an alteration in the function of one or several organs or systems, a situation that may compromise his survival. The purpose of the present study was to deduce if patients who were fed by Enteral Nutrition (NE) in the Intensive Care Unit (ICU) had a protein deficit combined with caloric overfeeding. Methods: This cross-sectional study was undertaken between August 2013 and April 2014 in the ICU, Hospital General deAgudos “Juan A. Fernández“, Buenos Aires, Argentina. The energy and protein prescriptions were obtained from medical indications. For the estimation of energy, the recommendations of the American Society of Parenteral and Enteral Nutrition (ASPEN) of less than 20-25 kcal/kg/day during the acute phase were taken into account. T-test and Mann-Whitney U test for comparison of groups was calculated with significance at p <0.05. Results: This study had a sample of 52 patients.The average daily energy requirements, calculated from the third day of ICU admission, was 1637 kcal (SD +/385, CI 95% 1529.8/1744.1), while the mean daily energy delivered was 1726 Kcal (DE +/365, IC95% 1624.4/1827.6). All patients had negative Accumulated Protein Balance (APB). Conclusion: The majority of the patients presented with energy over-prescription and protein deficit. Energy overfeeding could lead to an increase in hospital stay, which would further increase health costs