bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Main Indicators of the Hemostasis System in Patients with Severe Burn Injury and their Relationship with the Outcome
Authors: Скакун П.В. , Жилинский Е.В. , Алексеев С.А.
Published: April 2023

Введение. Термическая травма является одной из ведущих в структуре внешних причин смерти и связана со значительными социально-экономическими последствиями, которые затрагивают все социальные группы населения. Частым осложнением ожоговой болезни является системная коагулопатия, однако четкие критерии диагностики и лечения коагулопатии у пациентов с тяжелыми ожогами на данный момент отсутствуют, поэтому дальнейшее изучение данного феномена является перспективным. Цель. Проанализировать изменения показателей системы гемостаза у пациентов в раннем периоде ожоговой болезни (периоды ожогового шока и ожоговой токсемии). Материалы и методы. Выполнены анализ медицинской документации и исследование биологического материала 46 пациентов, находящихся на лечении в УЗ «Городская клиническая больница скорой медицинской помощи» в 2019–2022 гг. с целью изучения лабораторных показателей системы гемостаза. Результаты и заключение. При анализе системы гемостаза у пациентов с ожоговой болезнью при неблагоприятном исходе в 1–3-и сутки уровни АЧТВ, ПТВ были достоверно выше, чем у пациентов с благоприятным исходом, что отражает более тяжелые гипокоагуляционные изменения у умерших пациентов и может быть использовано для создания систем прогнозирования развития жизнеугрожающих нарушений свертывания у тяжелообожженных.

Introduction. Thermal injury is one of the leading external causes of death in the structure and is associated with significant socio-economic consequences that affect all social groups of the population. A frequent complication of burn disease is systemic coagulopathy, however, there are currently no clear criteria for the diagnosis and treatment of coagulopathy in patients with severe burns, so further study of this phenomenon is promising. Purpose. To analyze changes in the parameters of the hemostasis system in patients in the early period of burn disease (periods of burn shock and burn toxemia). Materials and methods. The analysis of medical documentation and the study of biological material of 46 patients treated at the City Clinical Emergency Hospital in 2019–2022 was carried out. in order to study the laboratory parameters of the hemostasis system. Results and conclusion. When analyzing the hemostasis system in patients with burn disease with an unfavorable outcome on days 1–3, the levels of APTT and PTT were significantly higher than in patients with a favorable outcome, which reflects more severe hypocoagulation changes in deceased patients and can be used to create systems predicting the development of life-threatening coagulation disorders in severely burned patients.
Cctv customer location data processing on webgis based a & s security system
Authors: Zulmi Zefri
Published: April 2023

Geographic Information System (GIS) is a computer-based information system, designed to work with data that has spatial information (spatial reference). Currently the information data about the location of CCTV Customers on the A & S Security System in Medan City has not been inventoried in a spatial-based web information system, the mapping data for CCTV Customer locations on the A & S Security System in Medan City still uses Microsoft Word and not programmed. For this reason, the authors created a solution with a Geographic Information System, which is an information system that is used to enter, process, and produce geographically or geospatially referenced data, to support decision making in planning. This information system will later have a visualization in the form of a web that is used to map the location of CCTV Customers on the A & S Security System in Medan City. In the development of the CCTV customer location processing system at the A & S Security System in Medan City, PHP and MySql programming languages ​​were used as database systems.
Occlusion effects by bone-conducted sound to the facial parts assessed by hearing threshold and ear canal sound pressure
Authors: Miwa Asuka , Otsuka Sho , Nakagawa Seiji
Published: April 2023

Bone conduction (BC) is used in devices such as hearing aids and earphones. Audio devices using BC on the face have been developed; however, limited research has addressed the perception of BC sounds on the face. BC also entails an occlusion effect (OE), wherein the loudness of low-frequency sounds is enhanced when the ear canal is occluded. We evaluated the characteristics of OE by measuring hearing thresholds and ear canal sound pressure (ECSP) during BC stimulation of several facial parts. We compared them with those of conventionally used parts. OE, the difference in hearing thresholds between the open and occluded ears, was equal to or larger than that of conventionally used parts. The difference in ECSP was smaller than that in OE, indicating that BC components transmitted to the middle and inner ears affected OE in these facial parts. The complicated structure of the face may have affected the results.
Mechanism analysis of CuInS2 and Cu(In,Ga)S2 growth via KCN- and H2S-free process and solar-cell application
Authors: Suzuki Yota , Egyna Dwinanri , Shibata Tomoki , Nishimura Takahito , Yamada Akira
Published: April 2023

In this article, CuInS2 (CIS) and Cu(In,Ga)S2 (CIGS) absorbers are prepared via sulfurization by a sulfur powder source for co-evaporated Cu–In(–Ga) metal precursors without toxic KCN and H2S. The CIS and CIGS growth mechanism during sulfurization and their application to solar cells are discussed. X-ray diffraction and Raman spectroscopy analyses indicate that CuS and (In,Ga)2S3 exist at the frontside and the backside, respectively, in the CIGS films at the temperature between 250 °C and 350 °C. Then, these intermediate phases react at 400 °C or higher forming CIGS. Finally, CIS and CIGS solar cells with efficiencies of 3.7% and 7.2% are achieved, utilizing an optimum temperature of 600 °C.
Penerapan Metode Pembelajaran Explicit Instruction (EI) Untuk Meningkatkan Pemahaman Konsep Siswa Sekolah Dasar
Authors: Armadi Meissy , Nazlimar Nazlimar
Published: April 2023

Penelitian ini bertujuan untuk meningkatkan pemahaman konsep siswa melalui metode pembelajaran explicit instruction di kelas V Sekolah Dasar Negeri 016 Bukit Ranah. Penelitian ini dilatarbelakangi oleh rendahnya tingkat pemahaman konsep siswa. Penelitian ini merupakan penelitian tindakan kelas. Subjek dalam penelitian ini adalah 1 orang guru dan 13 orang siswa. Penelitian ini dilaksanakan degan 2 siklus yang masing-masing siklus terdiri dari 2 pertemuan. Teknik pengumpulan data menggunakan tes tertulis dan dokumentasi. Berdasarkan hasil penelitian menunjukkan bahwa penerapan metode explicit instruction dapat meningkatkan pemahaman konsep siswa. Hal ini dapat dilihat dari hasil rata-rata tes pemahaman konsep peserta didk sebelum tindakan hanya mencapai rata-rata 55,76 dengan ketegori kurang. Setelah dilakukan tindakan pada siklus I mencapai 71,92 dengan kategori cukup. Dan meningkat pada siklus II menjadi 85 dengan kategori baik. Dengan demikian dapat disimpulkan bahwa penerapan metode explicit instruction daat meningkatkan pemahaman konsep siswa kelas V Sekolah Dasar Negeri 016 Bukit Ranah.
 

Kata Kunci : Metode Explicit Instruction, Pemahaman Konsep, dan Sekolah Dasar.
Nilai Karakter Gotong Royong Dalam Pendidikan Pancasila Kelas IV di Sekolah Implementasi Dasar
Authors: Hanafiah Diana , Martati Badruli , Mirnawati Lilik Binti
Published: April 2023

Penelitian ini bertujuan untuk mengetahui pengimplementasian karakter gotong royong pada saat pembelajaran pendidikan pancasila. Penelitian menggunakan metode deskriptif kualitatif dengan subyek penelitian guru kelas IV A, kepala sekolah dan siswa kelas IV A di SD Muhammadiyah 13 Surabaya. Teknik pengumpulan data yang di gunakan pada penelitian ini yaitu menggunakan trianggulasi teknik dan triangulasi sumber. Triangulasi teknik di dapatkan dari hasil observasi siswa dan dokumentasi, sedangkan triangulasi sumber di dapatkan dari hasil wawancara kepala sekolah dan guru kelas, serta dokumentasi berupa gambar. Hasil penelitian ini menyatakan, implementasi karakter gotong royong sudah ada beberapa indikator telah terpenuhi di dalam kelas IV A yaitu tolong-menolong, solidaritas dan menghargai, akan tetapi masih terdapat indikator lain yang belum  di terapkan oleh siswa dalam kehidupan sehari-hari. Pendidikan karakter gotong royong pada mata pelajaran pendidikan Karakter ini dapat dijadikan sebagai modal siswa di lingkungan sekitarnya, karena gotong royong sendiri merupakan kegiatan sosial yang sering dilakukan di tengah kehidupan masyarakat.

Kata Kunci : Nilai Karakter, Pendidikan Pancasila, Gotong Royong
An Application of Fuzzy Logic to Bank Ranking: A study of the Banking Sector in Bangladesh
Authors:   Department of General Educational Development, Daffodil International University, Bangladesh, Kobra Khadijatul , Rahman Md. Atiqur ,   Department of Computer Science and Engineering, Daffodil International University, Bangladesh, Rahman Syeda Maria ,   Department of Software Engineering, Daffodil International University, Birulia, Bangladesh., Imran Nafees ,   Department of Information Technology and Management,Daffodil International University, Birulia, Bangladesh, Kabir Md Faisal ,   South Bangla Agriculture, Commerce Bank, Bangladesh.
Published: April 2023

Creditors, investors, policymakers, and other stakeholders are all significantly impacted by banks’ performance ratings since these ratings affect how well banks are able to compete in the banking industry, which is crucial for the growth of this industry. The criteria used to evaluate a bank’s success in the banking industry are nebulous and vague. Consequently, it is no longer possible to precisely determine the state of a bank using the analytical method. Furthermore, there is no standard framework that can evaluate private commercial banks using the CAMELS criterion and eliminates ambiguity that we can witness in Bangladesh. The literature shows that two multi-criteria decision-making procedures, FAHP and TOPSIS, are employed in many countries to rank banks according to the CAMELS criteria. However, in Bangladeshi private commercial banks, we have never used such models using the CAMELS criteria. In order to assess the performance of Bangladeshi private commercial banks, this study aims to propose a Fuzzy Multi-Criteria Decision Model (FCDM) that can handle uncertain and ambiguous data. The CAMELS (Capital Adequacy, Asset Quality, Management Efficiency, Earnings, Liquidity, and Sensitivity to Market Risk) criteria are used to analyze and rank the ten commercial banks in Bangladesh. The suggested model incorporates the Fuzzy Analytic Hierarchy Process (FAHP) and Technique of Order Performance by Similarity to Ideal Solution (TOPSIS) methodologies. The weights are input into the TOPSIS algorithm to rank the Banks after determining the weight vector of the CAMELS criteria based on the opinions of experts using FAHP. The outcome displays the ten Bangladeshi commercial banks’ final rankings.
Se non scriviamo daccordissimo andiamo d’accordo
Authors: Ranier Franz
Published: April 2023

Vari lettori domandano se si possa usare legittimamente la forma daccordissimo.
On the Computation of Meaning, Language Models and Incomprehensible Horrors
Authors: Bennett Michael Timothy
Published: April 2023

[Accepted to the 16th Annual Conference on Artificial General Intelligence]

We bring together foundational theories of meaning and a mathematical formalism of artificial general intelligence to provide a mechanistic explanation of meaning, communication and symbol emergence. We establish circumstances under which a machine might mean what we think it means by what it says, or comprehend what we mean by what we say. We conclude that a language model such as ChatGPT does not comprehend or engage in meaningful communication with humans, though it may exhibit complex behaviours such as theory of mind.
Resource-efficient PUF Implementation Through FPGA Resource Re-utilization
Authors: Vega Christopher
Published: April 2023

The Field Programmable Gate Array (FPGA) market has seen significant growth due to the low cost and reduced time to market when compared to ASIC circuits. However, FPGAs' reconfigurable nature introduces security vulnerabilities that can be exploited by adversaries to obtain sensitive information. Physical Unclonable Functions (PUFs) have shown to be valuable security primitives. By leveraging manufacturing variations in a device one can generate unique signatures that can be used for authentication and generation of secret keys. However, PUF implementation can be costly, taking up FPGA resources and requiring long design times. In this paper, we propose a method which takes advantage of the FPGA Look Up Table (LUT) architecture to embed the PUF into functional logic circuits, reducing the cost and design time. We provide detailed implementation guidelines and evaluate the PUF's signature quality and stability under different environmental variations using a set of testbench circuits. Our results demonstrate the effectiveness of our method in securing FPGA designs while reducing implementation costs and design time. 
EEG-to-EEG: Scalp-to-Intracranial EEG Translation using a Combination of Variational Autoencoder and Generative Adversarial Networks
Authors: Abdi-Sargezeh Bahman , valentin antonio , Alarcon Gonzalo , Sanei Saeid
Published: April 2023

A generative adversarial network (GAN) enables mapping a data sample from one domain to another one. It has extensively been employed in image-to-image and text-toimage translation. We propose an EEG-to-EEG translation model based on a GAN structure in which a conditional GAN (cGAN) is combined with a variational autoencoder (VAE), named as VAE-cGAN. Scalp EEG (sEEG) is plagued by noise and suffers from low resolution. On the other hand, intracranial EEG (iEEG) recordings enjoy high resolution. Here, we consider the task of mapping the sEEG to iEEG to enhance the sEEG resolution.  

 
Deep Reinforcement Learning-based Online Resource Management for UAV-Assisted Edge Computing with Dual Connectivity
Authors: Hoang Linh , Nguyen Chuyen T. , Pham Anh T
Published: April 2023

Mobile Edge Computing (MEC) is a key technology towards delay-sensitive and computation-intensive applications in future cellular networks. In this paper, we consider a multi-user, multi-server system where the cellular base station is assisted by a UAV, both of which provide additional MEC services to the terrestrial users. Via dual connectivity (DC), each user can simultaneously offload tasks to the macro base station and the UAV-mounted MEC server for parallel computing, while also processing some tasks locally. We aim to propose an online resource management framework that minimizes the average power consumption of the whole system, considering long-term constraints on queue stability and computational delay of the queueing system. Due to the coexistence of two servers, the problem is highly complex and formulated as a multi-stage mixed integer non-linear programming (MINLP) problem. To solve the MINLP with reduced computational complexity, we first adopt Lyapunov optimization to transform the original multi-stage problem into deterministic problems that are manageable in each time slot. Afterward, the transformed problem is solved using an integrated learning-optimization approach, where model-free Deep Reinforcement Learning (DRL) is combined with modelbased optimization. Via extensive simulation and theoretical analyses, we show that the proposed framework is guaranteed to converge and can produce nearly the same performance as the optimal solution obtained via an exhaustive search.
Spiking Neural Networks for Detecting Satellite-Based Internet-of-Things Signals
Authors: Dakic Kosta , Al Homssi Bassel , Walia Sumeet , Al-Hourani Akram
Published: April 2023

The obtained results demonstrate a significantly enhanced detection performance under heavy interference conditions when employing spiking-based and deep learning detection techniques, as opposed to traditional baseline matched-filter methods. Although spiking-based detection approaches exhibit error rates comparable to those of deep learning techniques, they consume considerably less power – several orders of magnitude lower, in fact. Owing to their power efficiency, spiking-based detection networks emerge as the optimal choice for signal detection in resource-limited systems, such as low-Earth orbit satellites.
A Primary-side Maximum Efficiency Transfer Solution in Wireless Power Transfer Systems: Theory and Validation
Authors: Celentano Andrea , Paolino Carmine , Pareschi Fabio , Valente Virgilio , Rovatti Riccardo , Serdijn Wouter A. , Setti Gianluca
Published: April 2023

In this paper, we investigate the primary-side control of a Wireless Power Transfer (WPT) link, i.e., the capability of delivering the optimal power level to the load without compromising system efficiency, by only sensing quantities available at the primary side. When adding a simple power regulator at the secondary side, we observe and analyze the existence of a Maximum Efficiency Transfer point, easily detectable at the primary side, and corresponding to the additional power regulator being barely on, with negligible dissipated power. More important, the approach does not require any advanced system modeling, nor the estimation of the system parameters. A theoretical model is developed and verified by measurements on a prototype built upon a 60 mW-class-E based WPT link working at 6.78 MHz.
When Technical Solutions aren’t Enough: Using Software Concepts to Analyse Challenges at Delivery Processes between Mixed-Signal IC Team Members
Authors: Pereira Vidigal Tiago , Prodanov William , Rocha Carla
Published: April 2023

Scientific works on integrated circuits usually focus on technical challenges and contribute to improving the solutions. They often neglect intertwined social aspects that highly impact project success, as shown in recent Software Engineering research. This work is a case study to identify challenges in delivery processes between digital and analog disciplines on mixed-signal projects at a specific design house, considering technical and social perspectives. We performed 17 semi-structured interviews and examined the available process documents, analyzing the data using Socio-Technical Grounded Theory. We mapped 14 constructs, 13 propositions, and two explanations to identify those challenges faced by mixed-signal teams. This study contributes to the discussion of social aspects of Semiconductor’s scientific works and presents a list of possible delivery challenges in the context of the focal company. The proposed root causes are the incipient specification processes and the lack of practices related to collaboration in cross-functional teams. Requirement Engineering and DevOps studies provide insights to define implications for improvement in the organization. 
Artificial intelligence to detect buried objects
Authors: Gharamohammadi Ali , Shaker George , Crowley Mark
Published: April 2023

 The detection of targets under the ground is an important procedure that is typically performed by a human non-automatically. Recent studies have automated this process using artificial intelligence (AI) based on radar images. There are three main steps before feeding reconstructed radar images to a neural network. The first step is segmentation which can make the detection task straightforward. We have proposed an Otsu-based segmentation algorithm in this paper. The proposed segmentation algorithm is effectively able to distinguish between all the targets. In the second step before employing AI to detect targets, a local sliding window has been taken into consideration to improve the results. The image is divided into smaller parts by this sliding window after it has been reconstructed. In the third step, two different methods have been considered for data augmentation. The first method is a novel approach for generating synthetic radar data. It is applied before radar image reconstruction based on the summation of two receivers’ signals with different coefficients. In the second augmentation method, some conventional data augmentation methods like flip and rotating are applied to complete this task. To discriminate targets from background, it is necessary to classify input images to AI-based aproaches. This task can be accomplished by classical machine learning approaches like the scalar vector machine (SVM). Gabor filters have been utilized in this paper to extract the features. There also exist two classification approaches using convolutional neural networks (CNN) to automatically detect targets after image reconstruction. Two different CNN have been implemented. Without data augmentation, the SVM-based approach works better than CNN, and its accuracy is 86.9%. Overall, the second CNN algorithm outperformed SVM after the data augmentation by reaching 96% accuracy. 
Advanced hardware-in-the-loop testing chain for investigating interactions between smart grid components during transients
Authors: Paspatis Alexandros , Kontou Alkistis , Kotsampopoulos Panos , Lagos Dimitris , Vassilakis Athanasios , Hatziargyriou Nikos
Published: April 2023

Aiming to investigate the possible interactions between smart grid components during transient events, an advanced hardware-in-the-loop testing chain for the validation of novel smart grid solutions is proposed in this paper. The testing chain is directed towards both academic and industrial HIL users, e.g., relay manufacturers, power electronics manufacturers and DSOs/TSOs. All different hardware-in-the-loop simulation setups, ranging from simple local simulations up to more elaborate, geographically distributed hardware-in-the-loop simulations, are discussed, forming a solid testing chain. The interactions during transients, which can be investigated at each step, are analytically derived to emphasize the insights that each step can offer to the performed component validation. To highlight the applicability of the proposed hardware-in-the-loop testing chain, when validating smart grid components, a case study concerning the testing of a microgrid transition algorithm, between the interconnected and islanded modes of operation, is considered for a real microgrid. Particularly, the interactions between an advanced grid-forming inverter and the already existing grid-following inverters of the microgrid are investigated during normal and abnormal grid conditions, while following the appropriate steps of the proposed testing chain.
Simplified modelling of frequency dependent network for converter control system design
Authors: Nesterov Dimitri
Published: April 2023

The integration of renewable generation in the energy mix has led to a massive penetration of converter-interfaced generators (CIG) in the electrical network. However, CIG's is reported to be susceptible to interactions with electrical resonances and  other equipment. It became common practice to conduct electromagnetic transient (EMT) studies to assess these risks, define the mitigation measures and design the control systems. To perform the controllers design efficiently, the EMT analysis can be complemented with an analysis of linearized systems, for which numerous efficient methods have been developed.

 The paper presents a method to construct the linearized system which is believed to be sufficiently accurate for being used for controllers tuning, and sufficiently simple to be efficiently used on real-life cases. It takes into account the frequency dependent electrical network, and is based on the approach previously used for torsional analyses, but applied to a wider spectrum. It is illustrated on a simple numerical example, demonstrating the challenges that the electrical resonances might pose on the stability margins. A comparison of the results obtained from linearized model and EMT model is presented, aiming to validate the findings from the linearized model and the proposed approach.
Deep Graph Unfolding for Beamforming in MU-MIMO Interference Networks
Authors: CHOWDHURY ARINDAM , Verma Gunjan , Swami Ananthram , Segarra Santiago
Published: April 2023

We develop an efficient and near-optimal solution for beamforming in multi-user multiple-input-multiple-output single-hop wireless ad-hoc interference networks. Inspired by the weighted minimum mean squared error (WMMSE) method, a classical approach to solving this problem, and the principle of algorithm unfolding, we present unfolded WMMSE (UWMMSE) for MU-MIMO. This method learns a parameterized functional transformation of key WMMSE parameters using graph neural networks (GNNs), where the channel and interference components of a wireless network constitute the underlying graph. These GNNs are trained through gradient descent on a network utility metric using multiple instances of the beamforming problem. Comprehensive experimental analyses illustrate the superiority of UWMMSE over the classical WMMSE and state-of-the-art learning-based methods in terms of performance, generalizability, and robustness.
MiFL: Multi-Input Neural Networks in Federated Learning
Authors: Casella Bruno , Riviera Walter , Aldinucci Marco , Menegaz Gloria
Published: April 2023

Driven by the Deep Learning (DL) revolution, Artificial   intelligence (AI) has become a fundamental tool for many Bio-Medical tasks, including AI-assisted diagnosis. These include analysing and classifying images (2D and 3D), where, for some tasks, DL exhibits superhuman performance. Diagnostic imaging, however, is not the only diagnostic tool. Tabular data, such as personal data, vital signs, and genomic/blood tests, are commonly collected for every patient entering a clinical institution. However, it is rarely considered in DL pipelines, although it carries diagnostic information. The training of DL models requires large datasets, so large that every institution might need more data that should be pooled from different sites. Data pooling generates newfound concerns about data access and movement across other institutions spawning multiple dimensions, such as performance, energy efficiency, privacy, criticality, and security. Federated Learning (FL) is a cooperative learning paradigm aiming at addressing these concerns by moving models instead of data across different institutions. This paper proposes a Federated multi-input model that leverages images and tabular data, providing a proof of concept of the feasibility of multi-input FL architectures. The proposed model was evaluated on two showcases: the prognosis of CoViD-19 disease and the patients’ stratification for Alzheimer’s disease. Results show that enabling multi-input architectures in the FL framework allows for improving the performance regarding both accuracy and generalizability with respect to non-federated models while ensuring security and data protection peculiar to FL.
Adaptation Metrics for Low-Order Mobile Line-of-Sight-MIMO Links
Authors: Anim-Appiah Kofi , Haque Tanbir
Published: April 2023

Adaptation metrics for low-order mobile line-of-sight-MIMO links. These are linked to the mean-square error (MSE) and channel MIMO matrix conditioning.
Enhancing Wind Speed Forecasting Accuracy Using a GWO-Nested CEEMDAN-CNN-BiLSTM Model
Authors: Phan Quoc Bao , Nguyen Tuy
Published: April 2023

In the past few years, accurate wind speed forecasting has become progressively important due to the growing demand for renewable energy sources. In this study, we propose a novel artificial model, Grey Wolf Optimization (GWO)-nested Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-Convolutional Neural Network (CNN)-Bidirectional Long Short-Term Memory (BiLSTM), for wind speed forecasting. The proposed model integrates three powerful techniques: CEEMDAN, CNN, and BiLSTM. Firstly, CEEMDAN with two nested layers is used to decompose the wind speed time series into a set of intrinsic mode functions (IMFs) to enhance the accuracy of the model. CNN is then applied to extract features from the IMFs, and BiLSTM is used to capture the temporal dependencies and make accurate predictions. To improve the performance of the model further, we also introduce GWO and apply it to select the best hyperparameters for the forecasting models based on decomposition results. The model is tested using wind speed data collected in Basel in 2022. The final combination result demonstrates that the proposed model achieve a better performance compared to several modern AI-base models in the wind speed forecasting field, with high accuracy reflected by a mean absolute percentage error (MAPE) of nearly 3%.
An Integrated Dual-mode Pulse-echo Ultrasonic Measurement System Under Pulsed/Static Magnetic Field
Authors: Qiu Wenjie , Zhang Jian , Luo Yongkang , Han Xiaotao
Published: April 2023

Ultrasonic measurements at high magnetic field and low temperature necessitate ultra-fast excitations, ultra-high dynamic range of duty-cycle adjustments, as well as real-time, precise and automatic analysis. This paper proposes a dual-mode ultrasonic measurement system, which means the capability of carrying out acoustic measurements in both pulsed and static high magnetic field with low temperature. Based on the “counter-delay-chain” series structure and adaptive jitter compensation in the field-programmable-gate-array(FPGA), the timing control accuracy of 5 nanoseconds and the timing jitter below 160 picoseconds are realized for high-resolution excitation generation and precise sampling window adjustment. The duty cycle adjustment achieves a high dynamic range from 0.23 ppb to 10 % to realize both pulsed field mode and static field mode (denoted as PF-mode and SF-mode) ultrasonic measurements. The independent sampling window adjustment reduces the data size by more than 80%, extends the maximum testing duration and reduces the analysis consuming. Combined with the automatic cross-correlation analysis method, this system can automatically carry out PF-mode tests with a repetition rate above 100 kHz and SF-mode tests for hours with sound velocity accuracy of 2%. Experiments have proved the reliability and feasibility of the system and revealed its application prospect in condensed matter physics experiments. 
Noise Driven Coupled Nonlinear Systems: A “Dynamical Multilayer Perceptron” Demonstrating XOR Functionality
Authors: de la Houssaye Paul , Mauger Justin , Hutchens Chriswelll , Bulsara Adi , Migliori Benjamin
Published: April 2023

Coupled dynamical systems, especially those comprised of hysteretic elements, possess remarkable behavioral similarities to some aspects of neural activity in living systems.  While some features of this similarity have been explored, the results have not yet been leveraged to improve machine learning techniques or artificial neural networks. In this work, a dynamical system of coupled overdamped bistable elements subject to a noise floor assists in information transfer. With the noise allowing the system elements to switch randomly between their stable states, the system response is quantified via a steady state probability distribution. A simple five element realization of this network is used to produce the analog equivalent of an XOR gate, an “XOR transform”, through the proper choice of coupling coefficients and controllable external biases. The demonstration of the XOR transform indicates the ability of the system to synthesize more general functions, a necessary prerequisite for machine learning and computing applications. Finally, a silicon implementation is proposed and simulated using a verified process model that could be fabricated to generate a working analog computing system.
Thermal behavior and reaction to fire of European beech (Fagus sylvatica) treated with various salts and mineralization formulations
Authors: Franke Tom , Larnøy Erik
Published: April 2023

The reaction-to-fire properties of wood can be improved by the application of fire-retardants. However, a wide variety of fire retardants are of ecological and health-issue concerns. The objective of this study was to investigate and compare the effects of various harmless and eco-friendly salts and after carrying out a 2-step mineralization process to obtain a calcium oxalate mineralized beech (Fagus sylvatica). Two mineralization formulations to obtain CaC2O4 were applied. First Formulation was a combination of the water- soluble salts K2C2O4 and CaCl2, where the second formulation was a combination of K2C2O4 and Ca(CH3COO)2. The two particular salts were impregnated into the wood, successively. These salts are intended to react in-situ to the heavily water-soluble mineral CaC2O4. To determine the impact of the various precursors, the reaction by products, which are appear during the mineralization process, as well as various retentions were focus of this study. The thermal behavior of the various treatments was determined by means of TGA measurements. The reaction to fire was carried out with a mass loss calorimeter.  Special emphasis is set on the impact of the precursors and by products on the thermal behavior and the reaction to fire, as well as the performance of CaC2O4 after the by-products were leached out. An influence on the thermal degradation of beech wood after treatment with the salts and after the 2-step mineralization process could be demonstrated. Furthermore, the impact of various precursors and by-products on the reaction to fire was determined. Thereby, chlorine containing treatments show to have the biggest impact in improvement of the fire retardancy of wood. However, after leaching of the by-products, specimens which only contained CaC2O4 indicate satisfying improvement on the reaction to fire of the beech.
Convex Lens in Double Slit Experiment
Authors: peng hui
Published: April 2023

The classical interpretation of Young’s double slit experiment is that, before and after passing through the double slit, the light behaves as waves. It is “the only mystery [of quantum mechanics] (Feynman). We proposed Postulates of convex lens for utilizing lens in wave experiments. By applying convex lens, we observed new phenomena of the double slit experiments, and referred as “new mystery”. 

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In this article, we show the focal point related phenomena attribute to a thin lens, and confirm Postulates of convex lens. The combination of Postulates of the convex lens and the geometrical theory of the lens may describe the function of the lens in the wave experiments. The convex lens is helpful in studying the mystery of the double slit experiment. It is the challenge to interpret the convex lens related phenomena in the wave experiments.
Chatbots: A game changer in mHealth
Authors: Chowdhury Md Naseef-Ur-Rahman , Haque Ahshanul
Published: April 2023

This is a review of chatbots in the field of mHealth
A Short Survey on Malware Behavioural Features Collection from AgTech Environments
Authors: Aras Asim Ozan
Published: April 2023

Agriculture is considered one of the most critical domains for human beings. Currently, agriculture and supply chain businesses are becoming increasingly reliant on technology and interconnectivity. However, this inevitable necessity also brings about potential risks. Due to the widespread use of new technologies to improve productivity in agriculture, cybersecurity risks have inevitably emerged. To proactively mitigate the risks related to cybersecurity, it is important to understand the attack vectors, such as malware. Thus, malware analysis is indispensable for understanding the characteristics and behaviors of malware and developing defense strategies against malicious attacks based on data collected from the results.In the literature, two different techniques have been widely used to analyze malware: Static Analysis and Dynamic Analysis. While Static Analysis aims to investigate the structure of the malicious software at a low level, Dynamic Analysis focuses on the behavior of the malware when it is being executed. As executing malware may harm the host system, an isolated environment should be established for Dynamic Analysis.This study focuses on Malware Analysis in terms of the dynamic analysis approach. Additionally, an isolated, automated dynamic analysis platform was developed, and analysis was implemented in a virtual environment using Cuckoo and VirtualBox to collect data from analyzing various malware behaviors. This data can be used to create a partial test dataset that may contribute to developing defense strategies against malware. 
On the Performance of an Improved Energy Detector with Threshold Modification for Cognitive Radio Networks
Authors: Chauhan Narendrakumar , Kavaiya Sagar
Published: April 2023

An Improved Energy Detector (IED) based on Nakagami-m fading channel and Maximal Ratio Combining (MRC) is presented in this paper. With the MRC, the IED is used uniformly, exponentially, and Multiple Input Multiple Output (MIMO). An optimization problem involving 𝑁 secondary users (SU) and one primary user (PU) is the subject of our research. Using Kummer’s solution for Cognitive Radio (CR), we can derive the expression for the likelihood of miss detection using p-based Energy Detection (ED). In order to enhance the detection performance, we perform threshold operations such as addition, subtraction, mean, and median. The error rate is also evaluated in terms of how well it performs. The generated expressions are tested for validity and accuracy using simulations. Combined correlated fading and static distance have a significant effect on detection performance over faulty CSI is also demonstrated in this study. Further, the impact of correlation coefficient is also examine through the simulation. We see that the antennas connected in an exponential manner perform much better than antennas connected in a uniform manner.
Identifying underlying individuality across running, walking, and handwriting patterns with conditional cycle–consistent generative adversarial networks
Authors: Burdack Johannes , Giesselbach Sven , Simak Marvin , Ndiaye Mamadou , Marquardt Christian , Schöllhorn Wolfgang Immanuel
Published: April 2023

In recent years, the analysis of movement patterns has increasingly focused on the individuality of movements. After long speculations about weak individuality, strong individuality is now accepted, and the first situation–dependent fine structures within it are already identified. Methodologically, however, only signals of the same movements have been compared so far. The goal of this work is to detect cross-movement commonalities of individual walking, running, and handwriting patterns using data augmentation. A total of 17 healthy adults (35.8 ± 11.1 years, eight women and nine men) each performed 627.9 ± 129.0 walking strides, 962.9 ± 182.0 running strides, and 59.25 ± 1.8 handwritings. Using the conditional cycle-consistent generative adversarial network (CycleGAN), conditioned on the participant’s class, a pairwise transformation between the vertical ground reaction force during walking and running and the vertical pen pressure during handwriting was learned in the first step. In the second step, the original data of the respective movements were used to artificially generate the other movement data. In the third step, whether the artificially generated data could be correctly assigned to a person via classification using a support vector machine trained with original data of the movement was tested. The classification F1–score ranged from 46.8% for handwriting data generated from walking data to 98.9% for walking data generated from running data. Thus, cross–movement individual patterns could be identified. Therefore, the methodology presented in this study may help to enable cross–movement analysis and the artificial generation of larger amounts of data.
HCM-based Indoor Optical Wireless Communications: Timing and Data Recovery
Authors: Johar Masoud , Salehiyan Alireza , emadi mj , Nezamalhosseini S.Alireza
Published: April 2023

Light-fidelity (Li-Fi) is a promising solution to provide high-rate, secure, and green communications to be used in the next generation of wireless networks. Since visible or infrared (IR) light-emitting diodes (LEDs) are used as the optical source and have a nonlinear transfer function, the transmitted modulated signal can be distorted if the signal has a high peak-to-average power ratio (PAPR). Recently, a new modulation scheme called Hadamard-coded modulation (HCM) is proposed which has a low PAPR and produces symbols with discrete levels. In the HCM technique, the symbol levels can be created using multiple LEDs. Therefore, each LED operates in its linear region and just switches on or off. In this paper, a low-complexity transceiver architecture for the HCM-based communication links is proposed and a complete synchronization procedure based on the spread spectrum techniques is presented. Finally, the bit error rate of the system is evaluated by Monte Carlo simulations, and effects of system parameters such as preamble length, fall and rise time of optical devices, and timing jitter on the bit error rate of the link are discussed.

 
Robust Detection Method of Low-Voltage Islanding for Grid-Forming Inverters Operated in Conjunction with Existing PV Inverters
Authors: Winter Björn Oliver , Schwung Julian , Engel Bernd
Published: April 2023

With the gradual exit from fossil and nuclear based power generation, a replacement for the reducing grid inertia is urgently needed. Due to this reason, grid-forming inverter technology is discussed as possible future replacement but will need to be implemented in massive scales to be an adequate source of transient grid stability. Therefore, different projects, such as ‘Grid Control 2.0’ or ‘VerbundnetzStabil’ have looked into the potential for grid integration of grid-forming inverters down to the low-voltage level to utilize as much future renewable grid integration for inertia provision as possible. However, the incorporation of grid-forming converters that lack dependable islanding detection mechanisms may significantly diminish the efficacy of current procedures employed by existing grid-following converters. Consequently, islanded grids that emerge due to faults or planned maintenance may not be reliably deactivated during a fault.

This paper presents a solution for detecting islanding in grid-forming converters. The authors analyze the limitations of a commonly used active islanding detection method (slip-mode frequency shift) on a grid-following inverter, whose basic assumptions are undermined if a grid-forming system is operated in parallel and propose an adapted detection procedure for grid-forming converters. The proposed '-Q-f-droop’ method is shown to be capable of reliable islanding detection in both standalone and interconnected operation with existing plants by non-detection zones created with a suitable setup in simulation. The results are verified through laboratory tests using grid-following and grid-forming PHIL inverters. The developed method ensures reliable shutdown of formed island grids even with the integration of grid-forming systems into the low-voltage level.
Capacity Enhancement for Multiple Reconfigurable Intelligent Surface based Index Modulation
Authors: Suwanda Nadhira Azizah , Lee Hye Yeong , Shin Soo Young
Published: April 2023

This study proposes the multiple reconfigurable intelligent surface (RIS) based index modulation (IM) called as MRB-IM, in order to improve the channel capacity by activating one or more RISs among multiple RIS (MRIS) and utilizing its number of combinations. The ergodic capacity analysis is derived to prove the validity of the simulation for the Rayleigh fading channel. Generally, MRIS suffers from inter-RIS interference (IRI) which is considered as the leverage of the secondary reflection amongst the MRIS. Despite having a larger capacity, the proposed MRB-IM has less of an impact on IRI because occurs among active MRIS. Simulation results demonstrate that the proposed system outperforms the existing MRIS in terms of capacity with and without IRI. In addition, bit error rates with different activation numbers of elements and RISs are shown. Here, the maximum likelihood on the receiver side is adopted to estimate the selected RIS index and information symbols in this study. 
МЕТАЛУРГІЙНІ ПРОЦЕСИ ПЛАВЛЕННЯ І ПЕРЕНЕСЕННЯ ЕЛЕКТРОДНОГО ТА ПРИСАДНОГО МАТЕРІАЛІВ У ШЛАКОВІЙ ВАННІ ПРИ ЕЛЕКТРОШЛАКОВОМУ НАПЛАВЛЕННІ
Authors: Захаров А. В. , Рибалко І. М. , Сайчук О. В.
Published: April 2023

У статті досліджуються актуальні проблеми проведення процесу плавлення і перенесення електродного та присадного матеріалів під час електрошлакового наплавлення. Метою статті є визначення оптимальних металургійних процесів для отримання якісного наплавленого металу з необхідними показниками зносостійкості. У ході дослідження встановлено, що обертання шлакової ванни до 150 обертів за хвилину суттєво не впливає на тривалість знаходження в шлаку зернистої присадки, але прискорює процеси теплообміну між шлаком та частинками присадки, а також збільшує відносну масу шлаку, що взаємодіє з частинками. Це призводить до інтенсифікації процесу рафінування наплавленого металу. При частоті обертання шлакової ванни вище 150 оберті за хвилину в кристалізаторах діаметром 100 мм і більше тривалість процесу перенесення частинок збільшується. Іноді зернистий присадний матеріал подається не на дзеркало шлакової ванни, а укладається разом з флюсом на поверхню, що наплавляється, або вводиться в об’єм шлакової ванни, наприклад у вигляді трубчастого електрода, заповненого присадкою. В цьому випадку частинки, маючи велику питому поверхню, плавляться при значно менших витратах тепла, ніж це потрібно для розплавлення такої кількості монолітного металу. Виявлено, що вільне перенесення частинок в шлаку і подальше ковзання частинок по стінці кристалізатора, яке можна назвати двохстадійне, забезпечує повне розплавлення частинок великого діаметру (більше 3 мм) вже у шарі шлаку, без їх доплавлення у металевій ванні. Доведено, що при використанні рідкого присадного матеріалу відсутні стадії плавлення, а також формування та утворення краплі. Зі шлаком взаємодіє не крапля, а рідкий струмінь металу, подальша взаємодія відбувається на межі розподілу металевої та шлакової ванн. Визначені основні напрями проведення подальших досліджень процесів плавлення і перенесення електродного та присадного матеріалів у шлаковій ванні. Сформульовані конкретні завдання з дослідження металургійної взаємодії між наплавним матеріалом і шлаком. Подальші дослідження повинні бути спрямовані на визначенні ефективності застосування електродних та присадних матеріалів різного складу.