Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Reinjection for Intermittent MPTCP Connections

Combining multiple networks at a host to access the Internet (multi-homing) allows for continuous data transmission even in scenarios with one intermittent connection. To this end, a multi-path capable transport layer protocol, such as multi-path TCP (MPTCP), is required to simultaneously use two or more networks for data transmission. A typical use case is to combine WLAN and cellular networks, in which the user stays connected to the cellular network, if the WLAN connection is lost due to user mobility. In that scenario, multi-path protocols have to detect the connection loss and have to retransmit corresponding lost packets immediately, so that the receiving network stack can forward the packets in sequence to the application.This paper analyzes MPTCPs connection loss detection mechanism and the corresponding process of the reinjection of lost packets. We show that the mechanisms for connection loss detection originate from single-path TCP (SPTCP) and have been simply adopted to MPTCP. They work slowly and cause large application level delays. Therefore, we propose a new reinjection method to speed up the reinjection after a connection loss. We evaluate our approach with emulation and real-world experiments and show that we reduce application level delays by up to 80%.
A 10-bit 50-MS/s SAR ADC with Split-Capacitor Array Using Unity-Gain Amplifiers Applied in FOG Systems

This paper presents a 10-bit 50-MHz SAR ADC with novel split-capacitor array design for FOG (fiber optic gyroscope) systems. Unlike the traditional SAR ADCs using bridge capacitors for the split capacitor array, this design uses the unity-gain buffer to replace the bridge capacitor. Thus, the linearity and the immunity to the process variation of the capacitor array could be improved. Besides, the settling time and the size of the capacitor array are both reduced. The proposed design is implemented with a typical 40 nm CMOS process. The DNL and INL are simulated to be 0.51 LSB and 0.56 LSB, respectively. The simulated SNDR is 51.23 dB with the 12.5 MHz input signal to show ENOB=8.22 bits at the 50 MS/s sampling rate.
1.2 kV 4H-SiC VDMOSFETs with Si-implanted Surface: Performance Enhancement and Reliability Evaluation

This paper reports on the performance improvement in 1.2KV 4H-SiC VDMOSFETs using a Si-implanted surface technique. Firstly, the devices with Si implantation on the surface shows a decrease of carbon atom percentage from XPS and EDX analysis, an improvement of subthreshold slope (SS) and mobility in n-MOSFETs, and a lower interface state density (DIT) near the conduction band edge from n-MOS capacitors. Secondly, high-voltage VDMOSFETs with Si implantation on the surface shows an improvement in SS, ID, breakdown voltage, and electrical safe operating area (SOA). Finally, the reliability including positive/negative bias temperature instability (PBTI/NBTI) and RON stability under high-voltage pulses are evaluated in high-voltage VDMOSFETs. Therefore, the Si-implanted surface technique is effective in enhancing the performance of 4H-SiC power VDMOSFETs without stability concerns.
Ideating and Developing a Visualization Dashboard to Support Teachers Using Educational Games in the Classroom

Technology has become an integral part of our everyday life, and its use in educational environments keeps growing. Additionally, video games are one of the most popular mediums across cultures and ages. There is ample evidence that supports the benefits of using games for learning and assessment, and educators are mainly supportive of using games in classrooms. However, we do not usually find educational games within the classroom activities. One of the main problems is that teachers report difficulties to actually know how their students are using the game so that they can analyze properly the effect of the activity and the interaction of students. To support teachers, educational games should incorporate learning analytics to transform data generated by students when playing useful information in a friendly and understandable way. For this work, we build upon Shadowspect, a 3D geometry puzzle game that has been used by teachers in a group of schools in the US. We use learning analytics techniques to generate a set of metrics implemented in a live dashboard that aims to facilitate that teachers can understand students’ interaction with Shadowspect. We depict the multidisciplinary design process that we have followed to generate the metrics and the dashboard with great detail. Finally, we also provide uses cases that exemplify how teachers can use the dashboard to understand the global progress of their class and each of their students at an individual level, in order to intervene, adapt their classes and provide personalize feedback when appropriate.
Chain of Interdependent Vehicular Micro Clouds

Vehicular micro cloud is a promising solution in which connected vehicles offer their resources as services to others and collaborate on tasks through vehicular networks. The properties of the vehicular micro cloud are generally set when it is formed at the core area and they remain static. However, a change in the environment could leave the micro cloud unable to respond adequately as its static properties become obsolete. Reacting to changes in the environment, on the other hand, requires dynamic updates on the properties of the vehicular micro cloud. In this paper, we address this dilemma and propose a chain of interdependent vehicular micro clouds. To respond to the changes in the environment, interdependent micro clouds are formed around the first vehicular micro cloud. Guidance information is transmitted before members of the dependent micro clouds arriving at the core area of the first micro cloud. Extensive simulations in different vehicular micro cloud settings show that the chain of interdependent vehicular micro clouds significantly improves the ability to respond to changes within the first micro cloud. Through the provided guidance information, members of dependent micro clouds are collectively prepared before they arrive at the core area.
A Novel Heap-Based Optimizer for Scheduling of Large-Scale Combined Heat and Power Economic Dispatch

Cogeneration systems economic dispatch (CSED) provides an optimal scheduling of heat/ power generating units. The CSED aims to minimize the whole fuel cost (WFC) of the cogeneration units taking into consideration their technical and operational limits. Then, the current paper examines the first implementation of dominant bio-inspired metaheuristic called heap-based optimization algorithm (HBOA). The HBOA is powered by an adaptive penalty functions for getting the optimal operating points. The HBOA is inspired from the organization hierarchy, where the mechanism consists of the interaction among the subordinates and their immediate boss, the interaction among the colleagues, and the employee’s self-contribution. Based on the infeasible solutions’ remoteness from the nearest feasible point, HBOA penalizes them with various degrees. Four case studies of the CSED are implemented and analyzed, which comprise of 4, 24, 84 and 96 generating units. The HBOA is proposed to solve CSED problem with consideration of transmission losses and the valve point impacts. An investigation with the recent optimization algorithms, which are supply demand optimization (SDO), jellyfish search optimization algorithm (JFSOA), and marine predators’ optimization algorithm (MPOA), the improved MPOA (IMPOA) and manta ray foraging (MRF), is developed and elaborated. From the obtained results, it is clearly observed that the optimal solutions gained, in terms of WFC, reveal the feasibility, capability, and efficiency of HBOA compared with other optimizers especially for large-scale systems. case
Revisiting the Utility of Transmission Gate and Passtransistor Logic Styles in CMOS VLSI Design

Modern microelectronic circuits are progressing from nanoseconds per instruction to picoseconds per instruction. The miniaturization of transistors, interconnects, and power supplies in integrated circuits have sparked this revolution. Because feature sizes are constantly shrinking, manufacturing process tools have less confidence in controlling design specifications (parameters). To minimize the number of transistors in a particular logic gate, the passtransitor logic can be used at the cost of weak logic output voltages. Transmission gate (TG) logic overcomes the weakness of the passtransistor logic at the expense of an extra transistor for each transmission gate. This study explores the implementation of a two-input OR gate (transmission gate logic), a two-input AND gate (passtransistor logic), and a two-input XOR gate (both) with the simulation results of area, power, and delay metrics.
Deep Reinforcement Learning for Edge Computing Resource Allocation in Blockchain Network Slicing Broker Framework

With the constant development of 5G technology, such as softwareization and virtualization, the novel concept of network slicing has been appeared. Blockchain is a decentralized technology for managing transactions and data which can ensure the security of transaction. Recently, the classical mobile network introduces a new role such as network slice agent to provide slices for one or across multiple operators, providing services for users or vertical industries over a larger time and space range. In this paper, we propose the blockchain network slicing broker (BNSB), an intermediate broker, which receive resources request and response then allocation resources between Network Slice Tenants (NST) and then schedule physical resources from Infrastructure Provider (InP) through smart contracts. The topology information is obtained according to the Complex Network theory and the value of nodes is defined according to their importance. In addition, Deep Reinforcement Learning algorithms is used to explore the optimal policy under the condition of meeting the service Level Agreement (SLA).
Comparison of Permanent Magnet Machines Equipped with Unbalanced Fractional-Slot Distributed Windings vs. Balanced Fractional-Slot Concentrated Windings

Fractional-slot concentrated winding permanent magnet (PM) machines have been gaining interest over the last decade in various applications. In this paper, a comparison of various conventional fractional-slot PM machines with an unconventional and unbalanced fractional-slot distributed winding PM motor is presented. The motors are designed for the same torque-speed curve, same design envelope, same electrical loading and magnet weight. No skewing is utilized in the designs for a fair comparison. It is found that 12-slot/10-pole and 27-slot/12-pole combinations stand out in terms of meeting the same torque-speed profile of the baseline machine with 39-slot/12-pole while having comparable performance metrics especially when it comes to reducing torque ripple.
The ORLS-Based DoA Estimation for Unknown Mixtures of Uncorrelated and Coherent Signals Under Unknown Number of Sources

In this letter, the order recursive least squares (ORLS) is applied to the azimuth-only ULA to probe the DoA estimation under the unknown number of external sources. In the ORLS-based method, the iterative measured matrix equations are feasibly constructed by combining the two spatial modified Yule-Walker (MYW) systems of linear equations and are required to remain Hankel-block-matrix structure of augmented matrices after arrangement order of the unknowns and the maximum number of detectable sources are preset. Under the stationary assumption on source signals and noises, the remarkable advantage of the proposed method lies in that it can theoretically provide the zero LS error as iteration times is equal to the number of sources. The zero LS error is an evident mark to judge the number of sources, especially for the scenario of the unknown noise variances. The proposed method is free of uncorrelated and coherent signals and the corresponding various mixtures and remains computationally efficient in estimation owing to no eigenvalue decomposition (EVD) and matrix inversion operation. The effectiveness of the determination of the number and azimuth angles of sources versus the different SNRs and numbers of snapshots is numerically confirmed.
Effect of Growth Temperature on the Characteristics of β-Ga203 Thin Films Grown on 4H-SiC (0001) Substrates by Low Pressure Chemical Vapor Deposition

Herein, we report on $\beta$-Ga$_{\mathbf{2}} \mathbf{O} _{\mathbf{3}}$ thin films grown on 4H-SiC (0001) substrates by Low pressure chemical vapor deposition (LPCVD). The influences of growth temperature on the crystal quality, optical properties, surface morphology of $\beta$-Ga$_{\mathbf{2}} \mathbf{O} _{\mathbf{3}}$ films were investigated using X-ray diffraction (XRD), UltravioletVisible (UV-Vis) Scanning Spectrophotometer, Scanning Electron Microscope (SEM) and Atomic Force Microscope (AFM). It was found that the surface morphology, grain size and strain of the $\beta \mathbf{Ga} _{\mathbf{2}} \mathbf{O} _{\mathbf{3}}$ thin films could obviously be influenced by the growth temperature in the range from 600 to $800 ^{\circ}\mathrm{C}$. The XRD results indicate that $\beta$-Ga$_{\mathbf{2}} \mathbf{O} _{\mathbf{3}}$textbf thin films were preferentially along the (201) oriented. At $750 ^{\circ}\mathrm{C}$, it is found that the $\beta$-Ga$_{\mathbf{2}} \mathbf{O} _{\mathbf{3\, }}$film with relatively high crystal quality. Geometrical epitaxial relationship between the $\beta$-Ga$_{\mathbf{2}} \mathbf{O} _{\mathbf{3\, }}$ (201) film and 4H-SiC (0001) substrate is revealed as $\beta$-Ga$_{\mathbf{2}} \mathbf{O} _{\mathbf{3}}$ $[010]\vert \vert 4\mathrm{H}-$SiC [1 –1 0] and $\beta$-Ga$_{\mathbf{2}} \mathbf{O} _{\mathbf{3}}$ $[102]\vert \vert 4\mathrm{H}-$SiC [1 1 0]. The lattice mismatch along $\beta$-Ga$_{\mathbf{2}} \mathbf{O} _{\mathbf{3}}$ [0 1 0] and $\beta \mathbf{Ga} _{\mathbf{2}} \mathbf{O} _{\mathbf{3}}$ [1 0 2] direction are 0.98% and 6.5%, respectively.
A Comparison of Fault Detection Efficiency Between Adaptive Random Testing and Greedy Combinatorial Testing for Control Logics in Nuclear Industrial Distributed Control Systems

Due to the complexity of the nuclear industrial distributed control system (DCS), input-domain testing techniques, including random testing and combinatorial testing, are usually utilized to test the control logics in nuclear industrial DCS. To improve the fault detection efficiency of random testing, the adaptive random testing technique selects a test case that significantly differs from all existing test cases. Similarly, to improve the fault detection efficiency of combinatorial testing, the greedy combinatorial testing technique adopts a greedy strategy to generate test cases that cover more uncovered tuple-combinations of parametric values. In this paper, we designed an experiment to compare the fault detection efficiency between adaptive random testing technique and greedy combinatorial testing technique for control logics of nuclear industrial DCS. Through the analysis of the fault detection ratios, the $f$ -measure values, and the values of average percent of faults detected (APFD) on two experimental subjects, including the commonly used benchmarks in the field of Boolean-specification testing as well as a group of Boolean expressions extracted from the control logics in nuclear industrial DCS, the experimental results give us the following conclusions: (1) If the test suites’ sizes are relatively small, the fault detection efficiencies of the two techniques are very close though there is a slight advantage in adaptive random testing; (2) With the gradual increase of test suites’ sizes, the fault detection efficiency of greedy combinatorial testing is beyond adaptive random testing gradually. Such a result can help us select the appropriate testing techniques in the testing of the control logics in nuclear industry DCS.
Research on Engineering Application of the Nonintrusive Load Monitoring Technology

In this paper, the demonstration application project of non-intrusive load monitoring (NILM) technology is introduced, including the NILM-based smart meter, low voltage residential power information acquisition system of Jiangsu Province, data acquisition and display, etc. On this basis, considering the practical conditions, four technical characteristics of NILM system are expounded, which are processing data in different devices, pushing information with different time delays, interacting with users, improving performance continuously. A NILM research platform called cloud-terminal coordination system is built, and an unsupervised learning algorithm is explored, which provides a way of performance evolution for the system. This paper is expected to provide reference for researchers who committee to promoting the engineering application of NILM technology.
Integrated Thermally Tuned Mach-Zehnder Interferometer in Z-Cut Lithium Niobate Thin Film

We propose and demonstrate a type of highly efficient tunable Mach-Zehnder interferometer (MZI) in Z-cut lithium niobate thin film (TFLN) based on the thermo-optical effect. By placing the electrode directly above the TFLN waveguide, a more uniform and higher heat distribution was obtained, compared with the conventional horizontal structure. Both the principle and design strategies of the proposed scheme are described. The process flow of the device fabrication is demonstrated in Z-cut TFLN. The measured static results accord well with the simulations. About 0.121 nm/V tuning efficiency is observed, which is nearly double the tuning efficiency based on the electro-optic effect, and may prove useful when high switching speed is not the primary consideration. The presented thermo-optic tuning scheme can be extended to other scenarios easily and may satisfy many different application requirements in integrated lithium niobate photonics (LNPs).
Design and Analysis of Electrically Small 915MHz Antenna for Wireless Applications

This paper demonstrates the design and analysis of an electrically small antenna on Polydimethylsiloxane (PDMS) substrate targeting medical application. The proposed antenna design consists of parasitic component structure and microstrip excitation line etched on the patch surface. Miniaturization and perfect matching at 915MHz are attained using the metamaterial structure and the feedline. Proposed compact electrically small antenna (ka=0.251 at 915MHz), exhibits reasonable frequency bandwidth and its complete dimension is 7mm×10 mm ×1.5mm (0.021λ0×0.031 λ0 × 0.0046 λ0), which is one of the compact designs at 915MHz. For the validation of its use free space has been considered for evaluating its parameters.
Experimental of Folded Accumulation Lateral Double-diffused Transistor with Low Specific On Resistance

In power devices, the resistance of the drift region becomes a dominant portion of the total device. In order to reduce the on resistance, the folded accumulation lateral double-diffused MOSFET (FALDMOS) is proposed and manufactured. The drift region of FALDMOS is etched to form the folded surface, which is similar to the FinFET structure. The drift region is surrounded by the extended gate. The electric field of the drift region can be modulated by the extended gate in three-dimensional when the device is turned off. Therefore, the concentration of the drift region can be greatly increased. When the device is turned on, a large amount of electrons can be introduced in the sidewall of the drift region to increase the conductivity, thereby obtaining ultra-low on resistance. The FALDMOS is manufactured by 0. 35μm BCD technology and the experimental results show that the specific on resistance of FALDMOS is only 9.3 mΩ•mm2, while that of the conventional LDMOS is 36. 2mΩ•mm2, which is reduced by 74.3% with the same breakdown voltage of 36V. In addition, the current density of FALDMOS is 5 times higher than the conventional LDMOS in the same area.
Need for Interpretable Student Performance Prediction

The education domain is growing at an exponential rate, maturing with the introduction of innovative and improved offerings to the learning community aided by various Education Data Mining techniques (EDM). Significant amount of research is being carried out around EDM, using various dimensions like student’s performance, dropout rates, individual cognitive capabilities, teacher's, administrators' performance, course delivery, and content authoring. Several data analytics techniques are adopted to gain knowledge from educational data. However, the prediction models generated are complex and not interpretable in understanding why and how a prediction has arrived at from the produced results. The interpretability of the model becomes increasingly important when dealing with large datasets and complex models. The derived analytics and the models will be acceptable and trusted if they are interpretable. It helps the educational organizations to advance their learning processes in boosting students' performance and reduction in the student dropout rate. This study reviews EDM focusing on the factors influencing student's predictions, various algorithms used, and identified the gaps. The study also gives an insight into how the "black-box" decisions of the prediction model are made, the role of various eXplainable AI (XAI) techniques in making the model results interpretable, and their contribution to producing explainable results.
Experimental Evaluation of UL-NOMA system with FD-STBC

In this paper, we propose a novel uplink non-orthogonal multiple access (UL-NOMA) for massive communications under the number of user equipments (UEs) that send signals simultaneously is larger than the number of receive antennas. The base station (BS) separates the superimposed signals through minimum mean square error (MMSE) spatial filtering with successive interference cancellation (SIC). In order to improve the signal separation performance, frequency domain-space time block coding (FD-STBC) is adopted as transmit diversity in the uplink. As FD-STBC, we examine two ways of transmit power allocation method for each UE. The proposed methods are evaluated by computer simulations and also experiments, which were performed under condition when up to 6 UEs transmit signals simultaneously. Performance evaluation is given by packet error rate (PER) by sending 16 bytes a packet as the signal. The results of the computer simulation and the experiments show good agreement, and the experimental results with the power difference for each UE, show that PER is less than 10% in single transmission without repetition when the number of UEs is up to 6. These are the results when the overloaded ratio, which is the ratio of the number of UEs to the number of the receive antennas, is up to 300%. And these results showed that it is effective to make a power difference for each UE.