Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of a Waveguide Test Cell for Q Band Liquid Permittivity Measurements

We present a novel design of a rectangular waveguide test cell for measurements of complex liquid permittivity in a 33-50 GHz microwave band. The cell allows for multistate 2-port measurements with a vector network analyzer and is compatible with the standard WR-22 waveguide flange. Using electromagnetic simulations, we investigate the permittivity error introduced by the liquid inlet depending on its position, inner diameter and length.
Joint Pedestrian Gesture Recognition and Orientation Estimation from Multistatic Radar Data

Radar-based detection of traffic gestures can play an important role in the interaction between autonomous vehicles (AVs) and vulnerable road users (VRUs). However, it is error-prone without information about the orientation of the VRU, from which the recipient of the gesture's message can be inferred. Hence, this paper proposes a neural network with two output branches for joint gesture classification and orientation estimation. As input serve radar target lists derived from data measured by an incoherent radar sensor network. By training the whole model on a combined loss, the neural network simultaneously produces a gesture prediction and an orientation estimate. The proposed method is validated on a comprehensive dataset containing radar data over a broad range of orientations from 35 participants. On this dataset, it achieves a gesture recognition accuracy of 92.43 % and a mean orientation estimation error of 8.02°.
Design of a 5G Application CML Frequency Divider for Improved Efficiency

An injection locked frequency divide-by-two current mode logic (CML) with injection directly through the bias tail current is implemented with reduced circuitry complexity and reduced power consumption. The proposed topology is capable of operating with a lower voltage supply compared to a conventional CML frequency divider topology with a maintained output voltage swing. A design guide for a given self-resonance frequency suitable for first cut design is proposed to estimate the optimal power consumption. A proof-of-concept of the proposed topology together with a conventional CML divider are implemented in an in-house BiCMOS process. The proposed topology occupies a silicon area of 0.0014 mm2, and on-chip measurements show a locking range of 41.5 GHz, from 2 GHz to 43.5 GHz. The DC power consumption is 3.55 mW.
The Use of Machine Learning Algorithms for Evaluating Water Quality Index: A Survey and Perspective

The quality of water is determined by its components, called the water parameters. The effect of each parameter on the water quality is different. To assess the water quality, sampling and measuring the value of these parameters are required. The water quality index (WQI) is a special indicator that integrates the value of many parameters into a single value. This value can be used to reflect effectively the quality of water. In this study, we present a survey on the application of machine learning (ML) method to estimate the WQI. A case study is also conducted to illustrate the use of the ML algorithm in the context.
Overview of Single-Stage Isolated AC-DC Topologies for Interfacing DC and AC Grids

The large-scale deployments of dc appliances and renewable generation have increased industry and research interest in dc electrical distribution systems for homes, offices, and other small buildings. In these systems, it is necessary to provide an isolated active front-end (AFE) interface between an ac grid and a residential dc microgrid/nanogrid. These power devices are often referred to as isolated active front-end (i-AFE) or grid interface converters. Single-stage isolated ac-dc converters can be a promising solution for the concept of the i-AFE converters. Single-stage topologies have no intermediate dc bus and potentially lead to reduced system weight, volume, and cost, compared to traditional two-stage solutions (ac-dc/dc-dc). Despite the potential advantages, single-stage isolated ac-dc converters are still an emerging topic in power electronics, which has not yet gained wide industrial adoption. This paper provides an overview of single-stage isolated ac-dc topologies, for dc microgrids application.
Dielectric Properties of Monoclinic RbD2PO4. The Influence of Hydrostatic Pressure

We proposed a modified proton ordering model for the quasi-one-dimensional monoclinic RbD2PO4, that takes into account linear over strains ϵi and ϵ5 contributions to the proton subsystem energy. Within the framework of the model, using the two-particle cluster approximation we calculate the static dielectric permittivity of the crystal. The dynamic dielectric permittivity of the crystal is calculated within the D.N. Zubarev nonequilibrium statistical operator method. The available experimental data for static and dynamic permittivities, are described. The effect of hydrostatic pressure on the physical characteristics of the crystal is explored.
An Asynchronous Gradient Descent Based Method for Distributed Resource Allocation With Bounded Variables

This article considers the distributed resource allocation problem over a network of n agents with individual optimization functions and coupled resource constraints. The optimization variables are bounded for each agent. We propose an asynchronous distributed gradient descent based method, which is able to tackle time-varying communication networks and communication problems. The main ideas are twofold. First, the degree of freedom of the network is reduced to deal with the global constraint. Second, we utilize delay compensation to counteract the delay of asynchronous communication. We prove that the convergence rate is $O(\frac{1}{k})$ and analyze both the communication complexity and the time complexity. This method is applied into the parallel pump control problem in HVAC system and shows good numerical results.
Analysis of Electrical Parameters of Various Liquids in a Coaxial Cell

Determination of physical, chemical, biological and other properties of liquids is relevant for many branches of human life. Therefore, we are constantly searching for optimal methods and devices that allow us to evaluate the characteristics of various liquids at a minimal cost. The use of microwave devices seems to be one of the promising ones. They are easy to use and do not require preliminary preparation of the test samples. In this regard, the work considers a coaxial cell and a technique used to analyze liquids with different chemical compositions. During the analysis, it was suggested that expanding the measured range would allow obtaining more information about the object. In this regard, a proposed method allows such an analysis to be performed for liquids in a wide frequency range. It consists of a device created based on a coaxial transmission line, which can provide an integrated approach to analyzing the physical properties of the materials under study. We measured the frequency characteristics of the S-parameters of liquids with different chemical compositions. These measurements showed that liquids placed in the measuring cell affect the frequency dependence. It is clearly shown that chemicals dissolved in water change their physical properties, which is observed when comparing the registered frequency dependencies. The proposed technique demonstrated that the coaxial cell could be employed to analyze multicomponent liquids and lead to developing new monitoring devices and techniques.
Cambricon-P: A Bitflow Architecture for Arbitrary Precision Computing

Arbitrary precision computing (APC), where the digits vary from tens to millions of bits, is fundamental for scientific applications, such as mathematics, physics, chemistry, and biology. APC on existing platforms (e.g., CPUs and GPUs) is achieved by decomposing the original data into small pieces to accommodate to the low-bitwidth (e.g., 32-/64-bit) functional units. However, such fine-grained decomposition inevitably introduces large amounts of intermediates, bringing in intensive on-chip data traffic and long, complex dependency chains, so that causing low hardware utilization.To address this issue, we propose Cambricon-P, a bitflow architecture supporting monolithic large and flexible bitwidth operations for efficient APC processing, which avoids generating large amounts of intermediates from decomposition. Cambricon- P features a tightly-integrated computational architecture for processing different bitflows in parallel, where full bit-serial data paths are deployed. The bit-serial scheme still needs to eliminate the dependency chain of APC for exploiting parallelism within one monolithic large-bitwidth operation. For this purpose, Cambricon-P adopts a carry parallel computing mechanism, which enables recursively transforming the multiplication into smaller inner-products that can be performed in parallel between bit-indexed IPUs (Inner-Product Units). Furthermore, to improve the computing efficiency of APC, Cambricon- P employs a bit-indexed inner-product processing scheme, namely BIPS, to eliminate intra-IPU bit-level redundancy. Compared to Intel Xeon 6134 CPU, Cambricon-P achieves 100.98$\times$ performance on monolithic long multiplication, and 23.41$\times$/30.16$\times$ speedup and energy benefit over four real-world APC applications on average. Compared to NVidia V100 GPU, Cambricon-P also delivers the same throughput, as well as 430$\times$/60.5$\times$ lesser area and power, respectively, on batch-processing multiplications.
Towards multi-hop real-time communications over LoRa networks for industrial applications

Industrial applications that require low power consumption and wide coverage range may benefit from the adoption of the LoRa communication technology. Unfortunately, the Medium Access Control protocol standardized for LoRa, i.e., LoRaWAN, is not suitable for industrial contexts, as it lacks support for real-time flows. Moreover, to achieve a high number of message transmissions over LoRa while keeping low duty cycle values, a multi-hop communication protocol is required. This work discusses how to combine the support for real-time flows with multi-hop transmissions over LoRa, outlining the basic design choices. A preliminary assessment based on analytical calculations is also provided.
Planar High-Order Broad-Band Bandpass Filters Based on Two-Stage Quadrature Couplers and Their Digital Modeling

Planar two-stage branch-line directional power couplers are applied in this paper to the design of transversal-signal-interference high-order wide-band bandpass filters (BPFs) with very-sharp-rejection characteristics. In comparison with the previously-reported experimental BPF demonstrators of their precursors-i.e., those using transversal filtering sections (TFSs) with one-stage branch-line couplers loaded by longer dissimilar stubs-, an enlarged-bandwidth passband with a higher number of in-band reflection zeros and lower amplitude variation can be obtained. Moreover, multiple transmission zeros (TZs) can be created in the out-of-band region owing to the intrinsic signal-energy cancelation phenomena of the transversal signal-interference philosophy, which result in high-selectivity filtering capabilities. As further conceptual understanding of the devised two-stage-coupler signal-interference BPFs, a digital-modeling interpretation for various illustrative synthesis examples is provided. In addition, for experimental-validation purposes, single- and two-TFS-based microstrip prototypes of wide-band BPFs centered at 2 GHz are manufactured and characterized. In these circuits, inter-digital-type input/output feeding sections are co-integrated. They allow to extend the lower/upper stopband bandwidths with regard to those inherent to their isolated two-stage-coupler-based TFSs.
Classification of Software Developer Skills Using Analysis of Russian Job Ads

In this paper we present our findings in IT job market analysis and share our ideas of how they could be applied for designing new software development educational programs. This is relevant the current situation, when university programs cannot keep up with the changes in technologies and skills that employers require, also be constrained by Russian professional standards. To solve the problem of compatibility of educational programs with labor market requirements, we propose to create flexible educational programs based on the most common competencies in the most popular professions found in IT job advertisements. In total, we analyzed about 380000 IT vacancies for 2021-2022 downloaded from HeadHunter, the top Russian job website. The paper describes our results in classification of software engineering skills extracted from the job ads, and how one can apply these results for teaching new professions based on these skills.
Traffic Condition Estimation at the Smart City Edge using Deep Learning: A Ro-Pax Terminal Case Study

The technology and innovations introduced by information systems have revolutionized how public institutions use their infrastructures and manage their assets. Even more, the need to carry out maintenance and to guarantee adequate standards of safety, efficiency, and quality of the services provided has prompted administrations and managers to integrate, in their management plans, the use of Information Computer Technologies (ICT). They are used as a tool through which it is possible to ensure the transition between the previous management and the new needs in the context of Smart mobility and, in general, Smart City. In this sense, this paper introduces a remote monitoring system built at the port terminal of Tremestieri (located in the city of Messina, Italy) that exploits deep learning to perform an Automatic Number Plate Recognition (ANPR) of vehicles transiting the area. Using a set of cameras installed at the terminal, this system allows to compute synthetic traffic indicators (e.g., arrival distribution, travel time, platooning and queuing phenomena) that can be used to infer the traffic conditions and the overall operability of the infrastructure in a non-invasive manner, highlighting daily peak hours and trends in the use of the terminal, also achieving an estimation of congestion phases.
CorePerfDSL: A Flexible Processor Description Language for Software Performance Simulation

Instruction set simulators (ISSs) model the functional behavior of embedded processors for early software development. While they offer high simulation speeds, an ISS usually does not model the timing behavior of the processor accurately. Existing software performance simulators are typically either specific to a certain microarchitecture or their description language mixes functional and microarchitectural aspects.In this paper, we introduce CorePerfDSL, an architecture description language (ADL) specifically designed to model the timing behavior of processor microarchitectures for software performance estimation. CorePerfDSL is clearly separated from any functional description of the modelled processor by a generic trace definition. As such, it is well suited to generate performance simulators that can be paired with an existing ISS, which supplies an execution trace. In addition, CorePerfDSL provides a high degree of flexibility, supporting the fast generation of models for various microarchitecture variants, which can be used for rapid architectural exploration. We demonstrate the flexibility of CorePerfDSL by describing several variants of a single-issue five-stage RISC-V microarchitecture and estimate their performances for a software benchmark program.
Keyless Entry Security System based on Gait Context

In recent years, the keyless entry system has been popularized in various vehicles, which greatly facilitates the daily travel life of car owners. If the keyless entry system is attacked by criminals, it will pose a serious threat to the safety of the entire car, which requires great attention. This paper studies the security protection of the keyless entry system in old-gen cars. Aiming at the problems that most of the existing protection schemes are difficult to apply on old models, a keyless entry security protection system based on gait semantics is designed. Based on the original keyless entry protocol, the security protection system uses a smartphone to analyze the owner's gait activity analysis to resist attacks. Aiming at the collected gait data of the acceleration sensor and gyroscope sensor in smartphone, this paper introduces a semantic segmentation model to process the gait data in the keyless entry scene, and divides the gait data sequence into gait activity sequences by designing the model. To determine the legitimacy of the unlock request, it has been proved by tests that the recognition accuracy of the gait semantic recognition model reaches 93.8%. Excellent, in the normal state (walking, stationary) unlocking experiment, the accuracy of legality determination reached 98.3% (177/180), which can better complete the protection function.
Metal Oxide Varistor (MOV) Lifetime Estimation with Impulse-Based Testing in PV Inverter Systems

Surges caused by lightning strikes could damage electrical components in photovoltaic (PV) systems. Metal oxide varistors (MOVs) are commonly used to protect PV systems from lightning strikes. This paper proposes a holistic impulse-based MOV lifetime estimation framework. The impacts of peak current and fault duration induced by lightning events are considered in the MOV lifetime estimation framework. Moreover, the impact of different parameter combinations on MOV lifetime estimation is analyzed. The effectiveness of the proposed work is validated in a PV inverter test system developed in MATLAB/Simulink.
A Metamorphic Relation Identification Method based on GEP

Metamorphic testing is one of the effective methods to alleviate the test oracle problem. Metamorphic relation is the core of metamorphic testing, and there is no effective automatic identification technology. This paper transforms the metamorphic relation recognition issue into a symbolic expression regression problem. The test input pairs are generated using the preset input pattern, and the output pattern is mined by gene expression programming. After reduction and verification, a valid metamorphic relation is obtained. Experiments show that this method can identify the relation obtained by static analysis and a more significant number. At the same time, compared with existing technologies, it has apparent advantages in effectiveness, reliability, and performance.
IDIO: Network-Driven, Inbound Network Data Orchestration on Server Processors

High-bandwidth network interface cards (NICs), each capable of transferring 100s of Gigabits per second, are making inroads into the servers of next-generation datacenters. Such unprecedented data delivery rates impose immense pressure, especially on the server’s memory subsystem, as NICs first transfer network data to DRAM before processing. To alleviate the pressure, the cache hierarchy has evolved, supporting a direct data I/O (DDIO) technology to directly place network data in the last-level cache (LLC). Subsequently, various policies have been explored to manage such LLC and have proven to effectively reduce service latency and memory bandwidth consumption of network applications. However, the more recent evolution of the cache hierarchy decreased the size of LLC per core but significantly increased that of midlevel cache (MLC) with a non-inclusive policy. This calls for a re-examination of the aforementioned DDIO technology and management policies. In this paper, first, we identify three shortcomings of the current static data placement policy placing network data to LLC first and the non-inclusive policy with a commercial server system: (1) ineffectively using large MLC, (2) suffering from high rates of writebacks from MLC to LLC, and (3) breaking the isolation between application and network data enforced by limiting cache ways for DDIO. Second, to tackle the three shortcomings, we propose an intelligent direct I/O (IDIO) technology that extends DDIO to MLC and provides three synergistic mechanisms: (1) self-invalidating I/O buffer, (2) network-driven MLC prefetching, and (3) selective direct DRAM access. Our detailed experiments using a full-system simulator — capable of running modern DPDK userspace network functions while sustaining 100Gbps + network bandwidth — show that IDIO significantly reduces data movement (up to 84% MLC and LLC writeback reduction), provides LLC isolation (up to 22% performance improvement), and improves tail latency (up to 38% reduction in 99th latency) for receive-intensive network applications.
Influence of Sintered Conditions on Electrophysical Properties of the Ceramics Based on BeO with a Dopant of a TiO2 Powder

The BeO-based ceramics with adding micro and nano-size powders of TiO2 have a number of unique properties such as a high specific thermal conductivity, high insertion loss values for an electromagnetic wave propagating through the material under research. All of these features of BeO-based ceramics give us the possibility to use this material for a high power load realization in the RF range. The investigation of the influence of the sintering temperature of ceramics on electrophysical properties of studying materials in the frequency range from 8 to 12 GHz has been presented in this article. The vector network analyzer R&S ZVA50 with a set of measuring equipment consisting of the waveguide transmission line WR90 standard and calibration kit for performing TRL calibration procedure has been used for performing measurement of electrodynamics properties of researching materials. Structural characteristics of BeO-based ceramic samples with the addition of TiO2 micro and nanopowders were investigated using scanning electron microscopy and differential thermal analysis. The density of research samples was defined by the hydrostatic weighing method. The comparison of ceramic samples with different sintering temperatures of ceramics 1550 0C and 1660 0C was presented in the article. The frequency dependences of the complex dielectric permittivity of studied samples are given.
A Bi-directional Flyback Micro-inverter for Power Flow Control of a Grid-connected Solar PV Module

This paper discusses the development of a bi-directional flyback micro-inverter for grid-connected solar photovoltaic module power control. This micro-inverter uses a transformer with a primary winding that is double wound. Each winding conducts current from a solar PV module via two alternately operating power switches. The power angle control is used to regulate the flow of energy from solar PV to the grid. Matlab software is used to implement and test the control circuit design. Several experiments were conducted by varying the power angle value and analyzing the active power, reactive power, and power factor. The experimental results indicate that changing the power angle significantly affects the active power injection. It has no noticeable impact on reactive power flow, though. The power factor profile tends to stay very much the same. However, increasing the value of the power angle by more than 90 degrees causes the power injection to become unstable.
Real-time Train Wagon Counting and Number Recognition Algorithm

In this work we present an efficient solution for counting train wagons and recognizing their numbers using deep learning computer vision models. The proposed method is a good alternative for radio-frequency identification (RFID) method in terms of low cost and ease of use. Our system shows 99% accuracy in real-world scenarios, including corrupted wagon numbers and night shooting conditions. At the same time, the proposed method is capable to process video-stream in real-time speed without GPU-acceleration.