bluuebunny/crossref_metadata_2025 huggingface dataset:
Jacques Paul Migne: A Biographical Portrait
Authors: Холопов Сергей Геннадиевич
Published: November 2022

В статье рассматриваются жизнь и деятельность Ж. П. Миня (1800-1875). Делом всей его жизни была публикация святоотеческих текстов и важнейших христианских и научных текстов. А главным его издательским проектом стало создание универсальной религиозной библиотеки - «Bibliothèque universelle du clergé et des laiques instruits» («Всеобщая библиотека духовенства и образованных мирян»), - в которую вошли творения святых отцов Церкви, документы церковных соборов, свидетельства гонений на Церковь, постановления светских властей. Помимо этого, в библиотеку были включены материалы светских наук, а также энциклопедии и справочники. Статья может быть полезна всем интересующимся личностью Ж. П. Миня и его издательской деятельностью.

In the article is presented the life and publishing works of J. P. Migne (1800-1875). His life's work was the publication of patristic texts and the most important Christian and scienti c works. His main publishing project was the creation of a universal religious library - «Bibliothèque universelle du clergé et des laiques instruits» («Universal Library of the Clergy and Educated Laity»), which included the works of the Holy Fathers of the Church, documents of Church councils, evidence of persecution of the Church, secular rulings. In addition, the library included materials from secular sciences, as well as encyclopedias and reference books. The article may be useful to all those interested in the personality of J. P. Migne and his publishing activities.
On the Sart-Kalmyk Written Sources
Authors: Boskha Borlykova
Published: November 2022

The article is devoted to the study of Sart-Kalmyk written sources (letters, genealogical trees, S.S. Nasymbatov’s handwritten dictionary), stored in the Scientific Archive of the Kalmyk Scientific Center of the Russian Academy of Sciences, in private collections of residents of Chelpek village of Ak-Suu district, Issyk-Kul region of Kyrgyzstan and in personal authors’ archive. All of the described sources have not been introduced into scholarly circulation yet and remain unknown to researchers. The most important source for studying the spoken Sart-Kalmyk language is the dictionary in manuscript form compiled in the 1990s by a local historian Sultan Nasymbatov (1925–2003). As our study demonstrates, this unfinished manuscript (A–K) has no transparent structure; there is no thematic breakdown of words, collocations and everyday expressions. It has been established that the main purpose of compiling the handwritten dictionary was to teach and preserve the spoken Sart-Kalmyk language.
Peter Simon Pallas and the Making of Academic Field Lexicography in Russia
Authors: Karpov Vladimir I.
Published: November 2022

The article addresses the expedition notes of Peter Simon Pallas (1741–1811) in order to evaluate their role in the making of academic field lexicography in Russia. Pallas’ travel notes can be regarded an important work that advanced the Russian field research, conducted on behalf of the Imperial Academy of Sciences. Pallas records information on the ethnography and history of local peoples, writes down the vocabulary of their languages, and provides a detailed description of geography, geology, botany and zoology. He develops a professional platform for scientists to discuss and interpret little-known or completely new phenomena, objects, artifacts, etc. Pallas’ research principles resemble today’s ideas about field work: organization of expeditions, direct contact with native speakers, targeted interviewing to get the necessary information, taking into account the ‘human’ factor, etc. The paper focuses on the vocabulary of three large thematic blocks: toponyms, phytonyms and ethnographic lexemes, recorded by Pallas during his visit to the Middle Volga region. This region is considered a territory that is within today’s borders of the Samara and Ulyanovsk regions. The ethnographic material is limited to the Chuvash ethnic group. Only the most remarkable examples are selected from the phytonyms listed by Pallas.The etymological analysis, as well as the facts collected by Pallas in the process of field work, allow a critical look at some modern interpretations of onomastic, botanical and ethnographic vocabulary and contribute to a deeper study of the history of Russian science.
Mechanism of Theme-Formation in a Text as it was Represented by Boris Tomashevsky and Georgij Shengeli (Based on the Works of 1925)
Authors: Gindin Sergei I.
Published: November 2022

In the mid-1930s, linguists began to spot problems, which cannot be solved without analysis of textual and discursive phenomena. Up to that moment some of such problems have been already pointed out and considered in the adjacent fields of Humanitarian theory and practice. The article deals with one of such anticipations made simultaneously by prominent Russian theorists Boris Tomashevsky and Georgij Shengeli in their studies of literary composition. They discovered that theme-formation in a text is based on the unity of meanings in neighboring sentences (Tomashevsky) or on semantic interaction of consecutive utterances (Shengeli).
Нова парадигма української класики: вистави Івана Уривського на камерних сценах Києва
Authors: Бойко Тетяна , Татаренко Марина
Published: November 2022

Мета дослідження – висвітлити особливості нової парадигми української класики та проаналізувати концепти І. Уривського у виставах «Украдене щастя» (2016) і «Лимерівна» (2019) на камерних сценах Києва. Методологія дослідження спирається на такі загальнонаукові методи, як аналітичний (для осмислення естетико-художніх орієнтирів сучасного театрального процесу та розуміння етапів формування нової парадигми української класики), історико- порівняльний (для визначення особливостей режисерських концептів Івана Уривського в ретроспективі вітчизняного театру), феноменологічний (для розкриття специфіки режисури І. Уривського й окреслення її оригінальних рис і творчих прийомів). Наукова новизна цієї статті полягає в уведенні до наукового обігу частини режисерського доробку Івана Уривського, в аналізі специфіки та жанрово-стилістичних особливостей його вистав на камерній сцені. Висновки. Мистецька діяльність режисера Івана Уривського базується на засадах креативності, інтелектуалізму й домінантного інтересу до текстів класичної драматургії. Пошук символів історичного часопростору п’єс та умотивування їх до фантазійної реальності стають головним концептом вистав «Украдене щастя» (Івана Франка) та «Лимерівна» (Панаса Мирного). У цих виставах режисер працює з природними матеріалами (або їх майстерною імітацією) і предметною сценографією, приділяє велику увагу пластичній роботі акторів та світло-шумовим ефектам створення атмосфери сценічної дії. Його презентація сценічної класики не заперечує традиційних змістів, а навпаки поглиблює й збагачує їх образну лексику. Молодий режисер розробляє власні версії як сублімацію етнографічно-фольклорного колориту й універсальності сюжетних колізій.
Friction Stir Welding of Magnesium AZ31B and Aluminum Al-6062
Authors: Mughal Mohammad Pervez , Nawaz Amir , Raza Syed Farhan
Published: November 2022

Magnesium alloys, due to their attractive characteristics, are being utilized as lightweight structural materials in aerospace, automotive, and various other industries. Further design flexibility can be obtained by joining the Mg alloys to other materials with outstanding performance, such as aluminum alloys. In this study, Al-6062 and Magnesium AZ31B have been joined through friction stir welding (FSW) using the high-speed steel (HSS) tool. The impact of two important process parameters, including spindle speed and welding speed, has been evaluated on ultimate tensile strength (UTS). In addition, the effect of the advancing side has also been assessed. Analysis of variance has been performed based on full factorial design. For maximum UTS, the study suggests spindle speed and welding speed of 100 rpm and 50 mm/min respectively with magnesium on the advancing side. The weld strength is 110% higher than that of magnesium-magnesium weld joint.
Surface Roughness Analysis in High Speed Micro-Milling of Monel 400 Alloy Using Statistical Methods
Authors: Baig Amjad , Jaffery Syed Husain Imran , Khan Mushtaq
Published: November 2022

Monel 400 is a nickel based super alloy containing copper as the main alloying element. Its usage in the industries like marine, aerospace and chemical, makes it an attractive choice for research. It exhibits high strength and excellent corrosion resistance. It is also classified as hard to cut material because of its lower thermal conductivity, higher hardness value and ability to react with cutting tool at higher temperature. High speed micro-milling coupled with different tool coatings was used to analyze machinability of Monel. The surface finish as a result of this study contributes towards the use of this alloy in multiple applications. Key Process parameters including cutting speed, depth of cut, feed rate per tooth and multiple tool coatings were selected as input variables. Effect of these key process parameters on surface roughness was analyzed through statistical analysis of variance (ANOVA). Feed rate having confidence level of 95% was found to be most significant parameter with contribution ratio of 27.86%.
Towards Predictive Design: Tracking a CNC Fixture Design Process to Identify the Requirements
Authors: Vasantha Gokula , Purves David , Corney Jonathan , Canavan Michael , Quigley John , Sherlock Andrew
Published: November 2022

Training novice production engineers to design manufacturing fixtures is a time-consuming process involving significant input from experienced experts. Motivated by the vision of providing an intelligent support system for general mechanical design, this paper develops a list of requirements for predictive suggestion mechanisms focused on creating fixtures for holding components during machining. To do this, the email communications between nine novices and one expert during the design of machining fixtures were studied. The analysis classified the expert’s feedback into ten coded themes. The significance of these themes was assessed by quantifying the resulting changes in the CAD models of the fixtures designs and fixture requirements. The identified results lay the foundation for developing a comprehensive CAD predictive suggestion system to support fixture design. Novice designers will benefit from this predictive suggestion system by correcting their design errors in real-time and reducing the need for experts’ time in the training process.
Towards a Disciplinary Framework for Engineering and Manufacture
Authors: Carey Emily , Sajdakova Jana , Newnes Linda , Lattanzio Susan
Published: November 2022

This paper presents the need to create a disciplinary conceptual framework. As participants and interactions of expertise in a project rise so too can costs, meaning if a project is transdisciplinary, being at higher levels of disciplinarity could become an expensive option. However, approaches for measuring levels of disciplinarity remain ill-defined and lack structure, so progress in this area is difficult to measure with a multiplicity of disciplinary scales identified. It is our view to guide rigorous scientific progress and meaningful industry support, a definitive conceptual framework, is required to underpin appropriate measures. This is currently lacking and to this end here, we outline interrelated studies to develop a disciplinary conceptual framework, detailing two studies to establish core transdisciplinary concepts for engineering and manufacturing. We conclude detailing ongoing work to measure aspects of disciplinarity in industry, leading to the creation of a disciplinary indexing tool/process.
Towards the Implementation of the Digital Twin in Machining Process: Opportunities and Challenges
Authors: Gaha Raoudha , Durupt Alexandre , Eynard Benoit
Published: November 2022

The use of Digital Twin (DT) is adopted by manufacturers and have positive effects on the product manufacturing process. The use of Digital Twin (DT) is adopted by manufacturers and have positive effects on the product manufacturing process. The aim of this paper is to present opportunities and challenges of the application of DT concept in machining process extracted from a literature review conducted on the use of DT on CNC machining process. Hence, firstly, we review related studies based on existing DT orientations and usages for machining process. Secondly, a discussion about possible DT functionalities and opportunities is conducted, this allows to present a clear vision on gaps needed to be studied to enrich and propose a DT model for machining process. Finally, a conclusion and perspectives for future are presented.
Feature Reduction and Selection for Use in Machine Learning for Manufacturing
Authors: Alrufaihi Duaa , Oleghe Omogbai , Almanei Mohammed , Jagtap Sandeep , Salonitis Konstantinos
Published: November 2022

In a complex manufacturing system such as the multistage manufacturing system, maintaining the quality of the products becomes a challenging task. It is due to the interconnectivity and dependency of factors that can affect the final product. With the increasing availability of data, Machine Learning (ML) approaches are applied to assess and predict quality-related issues. In this paper, several ML algorithms, including feature reduction/selection methods, were applied to a publicly available multistage manufacturing dataset to predict the characteristic of the output measurements in (mm). A total of 24 prediction models were produced. The accuracy of the prediction models and the execution time were the evaluation metrics. The results show that uncontrolled variables are the most common features that have been selected by the selection/reduction methods suggesting their strong relationship to the quality of the product. The performance of the prediction models was heavily dependent on the ML algorithm.
A Framework of Key Stakeholders and Their Influence on Sustainable Supply Chain Management Adoption
Authors: Mourtaka Samah , Sabar Mohamed
Published: November 2022

The topic of sustainable supply chain has become of great value for the community of researchers and practitioners. Supply chain professionals become not only cost managers, but they also had to manage relationships with key stakeholders. These latter are demanding that organizations address and manage the environmental and social issues which are impacted by their operations. Therefore, the aim of this paper is to understand the influence of stakeholders on the decision of adopting sustainability practices into the supply chain. We conduct a literature review, including content analysis, examining publications on sustainable supply chains published in English. We form the link between the institutional isomorphism as a driver for SSCM and its relation with stakeholders of the organization. The study draws on institutional theory and stakeholder theory in building its framework. We’ll conclude by discussing the limits and critics of this framework, while proposing future research directions.
Machine Learning Algorithm for Sorting of Battery Packs at Smart Manufacturing Industries
Authors: Mohammad Ashraf , Chang Jieh-Ren , Chang Tien-Tai
Published: November 2022

Energy conversion, high efficiency, and longer product life batteries are required to allow the strong enabling and efficient integration of battery technology into our society. Lithium-ion cells are used for the formation of battery packs due to their good characteristics provided for a long time. In manufacturing industries, battery packs are produced at a massive rate. Pouch cell capacity inside the pack has to be balanced to make the output of the battery stable and efficient. Sorting pouch cells became a critical task to build a battery pack. So, the pouch cells have to be sorted into groups based on their capacity. A methodology was proposed in this paper for sorting pouch cells using the hybrid clustering algorithm. Results were compared on various clustering algorithms. Optimal clustering was selected by analyzing the results of the machine learning model.
Synthesis and Characterization of Titanium and Graphite Powder Mixed Electric Discharge Machining on Inconel 718
Authors: Bhowmick Sovan , Paul Arindam , Biswas Nisantika , De Jhumpa , Sarkar Subhasish , Majumdar Gautam
Published: November 2022

Electric discharge machining is extensively used to process difficult to cut materials such as superalloys, composite materials etc. The quality of machining can be improved by adding particles into the dielectric fluid which is commonly known as powder mixed electric discharge machining (PMEDM). In the present study, titanium and graphite powder are added to dielectric fluid and the effects of the powders have been analysed on material removal rate, surface roughness, microhardness and surface morphology analysis. Six experiments have been conducted considering each powder with three different levels of pulse current 4A, 8A and 12A. The analysis of the result indicates MRR, surface roughness and microhardness significantly increase with the increase of pulse current. Titanium mixed EDM improves the MRR and microhardness but reduces the surface quality. The SEM investigations elucidate that the samples machined with Titanium powder mixed with EDM have fewer surface defects, cracks, microholes and layer deposition compared to the sample machined with Graphite powder.
Designing of a Tunable Fractional Order Chebyshev High Pass Filter Using Particle Swarm Optimization
Authors: Daryani Ritu , Aggarwal Bhawna
Published: November 2022

Fractional order Chebyshev high pass filters have been designed in this paper for orders (1+α), (2+α) and (3+α), α representing the fractional component. The work in this paper has been done by using the nature-inspired evolutionary metaheuristic technique called particle swarm optimization. MATLAB simulations for these filters have been shown with α varying from 0.1 to 0.9 at a step of 0.1. The attenuation values are compared with the ideal values. The canonical forms of the (1+α) order filters have been realized using OTA based KHN filter. Circuit element values are calculated for orders 1.2, 1.5 and 1.8 using factional order capacitors. These capacitors are approximated as Foster 1 form.
Numerical Analysis of Aerodynamic Drag for the Hyperloop System
Authors: Prabhakar Anmol , Shekhar Arya , Jain Bhuvan , Zunaid Mohammad , Ansari Naushad Ahmad
Published: November 2022

The Hyperloop vehicle is a means of transport in which the pod advances at a fast velocity inside a low-pressure tube to reduce the coefficient of drag. Aerodynamic drag is one of the most significant elements to consider while studying such systems. The design was created on ANSYS SpaceClaim and it consists of a Two-Dimensional model with tapered ends to diminish the drag. Since both ends are tapered, the drag is reduced significantly as compared to the other designs. In this paper, the pod design is analyzed at different speeds, namely 60 ms-1, 120 ms-1, 180 ms-1, 260 ms-1, and 300 ms-1 on ANSYS FLUENT and numerical simulations were performed keeping the blockage ratio fixed. Appropriate conditions, equations and k-epsilon turbulence model were applied to produce the desired result. All the drag coefficient values were analyzed, and hence, the graph was plotted. It was observed that the drag coefficient of the pod decreases with an increase in velocity.
Numerical Study of Deep Drawability Using Johnson-Cook Model
Authors: Bansal Srijan , Gautam Vijay , Prakash Ved
Published: November 2022

In the Deep-drawing process, a blank is drawn into a hollow element taking the shape of a die by the operation of a punch. This process has numerous advantages and applications in the automobile, aerospace, kitchenware, and packaging industries. The primary purpose of this study is to design and simulate the deep drawing process in LS-Dyna PrePost(R) V4.6.17 using Johnson-Cook flow stress as a material model. An appropriate and judicious characterization of material that accounts for the combined effect of strain, strain rate, and as well as temperature in the deep drawing operation is essential to predict the behavior of the material as close to the real scenario. Uniaxial tensile tests are performed on the UTM machine to obtain stress-strain readings at four different strain rates and also at four different temperatures in the environmental chamber of UTM. These readings were utilized to find material constants such as A, B, C, n, and M which are used in the MAT-015 material card of LS-Dyna. To conclude, the limiting draw ratio of the model is calculated which came out to be around 1.971.
Designing of Fractional Order Inverse Chebyshev Low Pass Filter Using Particle Swarm Optimization
Authors: Daryani Ritu , Aggarwal Bhawna
Published: November 2022

The design of fractional order inverse Chebyshev low pass filter has been presented in this paper. The (1+α) order inverse Chebyshev filters have been designed by comparing the transfer function of fractional order low pass notch filter with the second-order inverse Chebyshev low pass filter. Particle swarm optimization has been utilized to derive the coefficients of the fractional-order filters by varying α from 0.1 to 0.9. The canonical forms of these filters have been realized using multiple input Biquad circuits. The value of circuit elements for each order has been derived. Further, the values for the equivalent RC ladder network of the constant phase element have been derived by fifth-order continuous fractional expansion for the orders 1.2, 1.5 and 1.8. The magnitude plots for the 1.2 and 1.8 order inverse Chebyshev low pass filter have been plotted in SPICE and the magnitude plot for the 1.8 order filter has been compared with PSO approximated plot to confirm the feasibility of the OP-Amp based realized circuit with a mean error of 0.495dB.
Using Quantum Cryptography for End-to-End Encryption
Authors: Tiwari Akshat , Singh Mayank
Published: November 2022

These days almost everyone is involved in online communication. With the advancement in quantum computing the messaging system brings the current state of major public encryption systems into mind which can be hacked to be broken. Many developers working in the industry are just discovering this and will soon be looking at changing their communication systems to be protected in quantum time. This paper documents the tried-and-tested constructions of the encryption system used in the real-life android application. Implementation of Quantum Key Distribution is shown to work well with a quantum computer that is monitoring the whole process of sharing the transferred key. It will detect any third-party interaction and take instant action. This paper states tried and tested way of encrypting systems with the help of QRNG application and Qiskit SDK.
Design of a Smart Phone Self-Charging Device Based on Permanent Magnets
Authors: Vishwakarma Anubhav , Komelj Matej
Published: November 2022

A smartphone-battery magnetic-induction-based charger, utilizing an oscillation of a permanent magnet is adopted. To provide maximum portability of the device, it is necessary to minimize its parts of which the magnet is the most critical. At the same time, it is necessary to keep the production, including the magnetizing process, simple and affordable. In this manner, we propose a design of a notched magnet to reduce its weight, save the material, and avoid the necessity for a non-uniform magnetization configuration, required to obtain a high-enough induced voltage. By means of the finite-element-based simulations, it is demonstrated that the considered solution can be successfully applied to a self-charger device.
DarthYOLO: Using YOLO for Real-Time Image Segmentation
Authors: Bagla Kartikay , Diwan Amogh Dhar , Agarwal Kshitij
Published: November 2022

Image segmentation is a common use case of image processing. It enables a wide variety of activities, from self-driving cars to traffic systems that are capable of governing them. Most state of the art models like Mask R-CNN and other transformer-based models perform well but have very high inference times. Therefore in this paper, a novel model architecture is proposed that can run on consumer grade hardware while giving near real time image segmentation. This is done by creating masks on regions of interest proposed by a lightweight object detection algorithm that is the YOLOv4. Such an algorithm allows for image segmentation in near-real time for resource constrained environments as compared to other state of the art models that have high inference times are unsuitable for deployment in said environments.
Gesture Controlled Mobile Robot with the Collaboration of MATLAB and PROTEUS
Authors: Revoo Aditya , Giri Shubhika , Anand Sourabh
Published: November 2022

Gesture recognition is a type of technology that can be used to control robots, manipulators, and other devices. Human-Computer Interaction (HCI) and research into creating simple-to-use interfaces by utilising natural communication have gotten a lot of press recently, as have human manipulation skills. When using gesture recognition, the user who is making the gesture is not necessary to wear any equipment or gadgets on their body. A camera linked to a device reads the body’s gestures and produces an output. The major purpose of this paper is to use MATLAB to control motor direction in proteus while also combining both software with VSPE (visual serial port emulator). Before immediately implementing this method on a robot, we can first simulate the outcomes to improve accuracy or correct models.
Analysis of Multiplication Based on Vedic Mathematics
Authors: Lakshmi K. T. S. , Kishore D. , Kumar Sanjeev
Published: November 2022

The usual segmentation methods were addressed here: edge detection, clustering, and region growth. The problem with segmentation is that no one approach is suited for a certain type of picture, nor are all techniques applicable to all images. The importance of multiplication is rising according to the technology process. It is one of the major applications which is used in various domains such as business and digital signal process etc. The way of general multiplication is much more time taking process. So, mainly as to remove this time delay in this paper the concept of Vedic mathematics is introduced. This paper introduced about Indian ancient Vedic mathematics is involved to clear those problems. Sixteen sutras among the Vedic mathematics the one sutra that is widely used and implemented is “URDHVA-TIRYAGBHYAM” is proposed. The multiplication process of two 4 bit and two 3 bit and also two 2-bit multiplications are gone through this paper. This process ultimately leads to the consumption of less time and faster implementation. But, with respect to the order of multiplication, the complexity will also increase. When compared to other multipliers it takes less area.
Ultra Low Power Compressor Based Multiplier Circuits for Robots
Authors: Kajla Tushar , Jhamb Mansi
Published: November 2022

As today’s modern autonomous robots consist of many sensors, multiple processors and artificial intelligence software. For this, it draws data from the input sensor and process them into meaningful information with the help of an on board microcontroller unit, MCU otherwise known as the processor. It is also responsible for taking decisions based on the information provided by the sensors and therefore, tells the output devices how to function and do a task. Processors are the main thinking and evaluating part of any of the robot. Main purpose of the processors and the CPU is performing of functions out of which most of them are performed using multipliers in the processor. Compressor are mainly used for designing different type of power efficient multipliers. In this work, a 3:2 And 4:2 compressor are designed using XOR-XNOR circuit. This innovative design structure of 3:2 and 4:2 compressor helps in power consumption and delays as compared to todays existing designs. The simulated results shows improvement in the performance parameters. It indicates decrement in the power consumption by 13.46% for 3:2 compressor and 25.29% for 4:2 compressor at 2.5v obtained from the comparison with the existing state of art.
Analysis of Delamination Damage and Eigenvalue Buckling of Lap Joint in CFRP Laminates Using Finite Element Method
Authors: Acharya Aniket , Singh Anant Kumar , Agarwal Aayaam , Rastogi Vikas
Published: November 2022

Delamination damage is a characteristic damage which is observed in composite laminates. Delamination damage can be very disastrous, hence delamination analysis for any CFRP structure is necessary. In this paper epoxy carbon woven (230 GPa) Prepreg laminates was used as the adherend and FM-300K was used as adhesive to form a lap shear joint. The model was created using ANSYS ACP and analysis of delamination damage was done using 3D non-linear finite element method. Longitudinal buckling load was applied to study the eigenvalue buckling and deformation in different modes. Adhesive bonded lap shear joint made of fibre reinforced polymer (FRP) considering flat geometry subjected to longitudinal load has been investigated. The results were obtained for 10 modes in this analysis. Interpretation of the results shows that deformation decreases with increase in modes. It was also inferred that deformation is much smaller in modes where buckling occurs in two planes. Tsai-Wu failure criterion was used to observe the failure layers in the composite laminate structure. Crack Closure Technique was used to find out the strain energy release rates. It was observed that peel stress and shear stress in the inter laminar region was three dimensional in nature.
Torque modeling of reluctance spherical motors using the virtual work method
Authors: Zhang Tao , Li Guoli , Zhou Rui , Wang Qunjing , Wang Lei
Published: November 2022

Compared to traditional single-axis motors, reluctance spherical motors (RSMs) can generate rotational torque in three spatial latitudes on a single motor, thus enabling three degrees-of-freedom (DOF) motion. Due to the complexity of their structure, the finite element method (FEM) is usually used to calculate the torque, but this method has the problem of consuming huge computational resources and long computation time. To address the problem that the FEM for calculating the torque of RSM consumes a lot of computation time, the torque model of RSM is developed by using the virtual work method considering the nonlinear cases of the magnetic circuit in this paper. Firstly, the inductance simulation of a single stator coil of a RSMs is carried out using finite element simulation software to obtain its inductance model. When the magnetic circuit is linear, the torque is obtained by partial differential calculation of the inductance surface. When the magnetic circuit is nonlinear, the distribution of flux linkage is first solved. Then, the electromagnetic torque is obtained by partial differential calculation of the magnetic co-energy. The calculated results are then projected to the global coordinate system to convert the two-DOF torque to the three-DOF torque. Finally, the experimental torque measurement platform is built, and the torque is measured and compared with the analytical calculation results. The results show that this method greatly reduces the amount of computing and simulation work with accurate modeling and provides a theoretical basis for the study of energization strategies and real-time control of the reluctance spherical motors.
A hybrid dynamic hysteresis model based on the Preisach model and stacked auto-encoder
Authors: Ma Yangyang , Li Yongjian , Chen Ruiying , Yue Shuaichao , Sun He
Published: November 2022

With the increase in power electronic equipment in power system, the excitation of ferromagnetic materials often involves a large number of harmonics. Therefore, it is necessary to construct an accurate dynamic hysteresis model to adapt to this complicated operating state of electrical equipment. In this paper, a Hybrid Dynamic Hysteresis Model (HDHM), which can effectively characterize the harmonic excitation of materials is studied based on the Preisach model and Stacked Auto-Encoder (SAE) model. The static part of this model takes the form of the inverse Preisach model. And the Multiple Dynamic Hysteresis Model Set (MDHMS) is constructed by multiple dynamic models of eddy currents and excess characteristics of the ferromagnetic materials. The dynamic part of the HDHM takes the form of the model structure combining the Stacked Auto-encoder and the MDHMS. The calculation results of the hysteresis loop and ferromagnetic loss in the harmonic condition of silicon steel sheet proves the validity of this model. Moreover, compared with the conventional dynamic hysteresis model, the HDHM has better accuracy and generalization ability.
Signal enhancement of vehicle wireless sensor network based on adaptive filter
Authors: Wang Yubao , Guo Shaocui
Published: November 2022

A signal enhancement method of vehicle wireless sensor network (WSN) based on adaptive filter is designed in this paper. By analyzing the vehicle WSN structure and node deployment mode, the signal operation process of WSN in the vehicle is determined, the relationship between Received Signal Strength Indication (RSSI) and distance is analyzed, and the signal of vehicle WSN is acquired. In order to reduce the workload of signal enhancement, set the signal strength judgment conditions of vehicle WSN, among the collected signals, the signal with poor intensity is taken as the research object. On this basis, the adaptive filter is used to remove the signal noise of vehicle WSN and enhance the signal strength. The signal enhanced by the proposed method has less noise and good stability.
Operating efficiency of the innovation ecosystem of college students’ start-ups based on three-stage DEA model
Authors: Wang Hong
Published: November 2022

Taking 20 innovation and entrepreneurship bases (college students’ start-ups) in Liaoning Province as the research object, an evaluation indicator system of the operating efficiency of the innovation ecosystem of college students’ start-ups was constructed. The innovation incubation ability and the operating efficiency of the innovation ecosystem of these bases were evaluated using the three-stage DEA model, and the factors affecting the operating efficiency were analyzed. Then, the effects of five environment variables (including the per capita GDP, the business volume of telecommunications service, the number of graduates, the local financial expenditure on science and technology, and the Internet penetration rate, as the explanatory variables) on the operating efficiency of the innovation ecosystem of college students’ start-ups were studied by using efficiency values excluding environment variables and random factors as the explained variables, and five environment variables as the explanatory variables.
IoT-enabled smart healthcare data and health monitoring based machine learning algorithms
Authors: Deepa S. , Sridhar K.P. , Baskar S. , Mythili K.B. , Reethika A. , Hariharan P.R.
Published: November 2022

A smart healthcare network can use sensors and the Internet of Things (IoT) to enhance patient care while decreasing healthcare expenditures. It has become more difficult for healthcare providers to keep track and analyze the massive amounts of data it generates. Health care data created by IoT devices and e-health systems must be handled more efficiently. A wide range of healthcare industries can benefit from machine learning (ML) algorithms in the digital world. However, each of these algorithms has to be taught to anticipate or solve a certain problem. IoT-enabled healthcare data and health monitoring-based machine learning algorithms (IoT-HDHM-MLA) have been proposed to solve the difficulties faced by healthcare providers. Sensors and IoT devices are vital for monitoring an individual’s health. The proposed IoT-HDHM-MLA aims to deliver healthcare services via remote monitoring with experts and machine learning algorithms. In this system, patients are monitored in real-time for various key characteristics using a collection of small wireless wearable nodes. The health care business benefits from systematic data collection and efficient data mining. Thus, the experimental findings demonstrate that IoT-HDHM-MLA enhances efficiency in patient health surveillance.
Development of an Intelligent Software System to Ensure Cyber Security Through Ontology
Authors: Mahmudova Shafagat
Published: November 2022

This study reviews software security, etc. It studies the methods for the analysis of software security. The problems of software protection are identified. The risks for software projects, their management, determination and categories are studied. The article describes the ontology of cybersecurity based on standards. The main concepts related to cybersecurity problem and their relationships are reviewed. It studies basic structure, concept, etc. of intelligent software system to ensure cybersecurity.
Methods of Detecting Cyber-Attacks on Unmanned Aerial Vehicles: A Survey
Authors: Valikhanli Orkhan
Published: November 2022

This paper covers a wide range of issues related to the cyber security of unmanned aerial vehicles (UAVs). It highlights the most common attacks which target UAVs. Moreover, it examines and compares the methods for detecting these types of attacks. As a result of the comparison, the advantages and disadvantages of such methods are discussed.
Problems and Methods of Information Security in Electronic Education
Authors: Aghayev Firudin , Mamedova Gulara , Zeynalova Lala , Melikova Rena
Published: November 2022

The popularity of e-education has been growing in recent years. Because of it, the problem of ensuring its security arises, which must be carried out using security methods and internationally recognized standards. This article identifies various problems of personal data security in e-education and proposes solutions to ensure the protection of educational information.
Analysis and Research of the Impact of Industry 4.0: Challenges on Demographic Processes
Authors: Nabibayova Gulnara
Published: November 2022

In order to solve the problem posed in the article, the characteristics of Industry 4.0 (Fourth Industrial Revolution) are considered. In addition, the possibility of threats to the data security of an electronic demographic (e-demographic) decision support system (DSS) from intruders in the context of Industry 4.0 is considered, due to the attack risks for them is very high. It is found out that the damage to these data will affect the decision-making in the field of demography, and, consequently, on the course of demographic processes in the region. Solution ways of arisen problems are indicated.
Is neuro-symbolic AI meeting its promises in natural language processing? A structured review
Authors: Hamilton Kyle , Nayak Aparna , Božić Bojan , Longo Luca
Published: November 2022

Advocates for Neuro-Symbolic Artificial Intelligence (NeSy) assert that combining deep learning with symbolic reasoning will lead to stronger AI than either paradigm on its own. As successful as deep learning has been, it is generally accepted that even our best deep learning systems are not very good at abstract reasoning. And since reasoning is inextricably linked to language, it makes intuitive sense that Natural Language Processing (NLP), would be a particularly well-suited candidate for NeSy. We conduct a structured review of studies implementing NeSy for NLP, with the aim of answering the question of whether NeSy is indeed meeting its promises: reasoning, out-of-distribution generalization, interpretability, learning and reasoning from small data, and transferability to new domains. We examine the impact of knowledge representation, such as rules and semantic networks, language structure and relational structure, and whether implicit or explicit reasoning contributes to higher promise scores. We find that systems where logic is compiled into the neural network lead to the most NeSy goals being satisfied, while other factors such as knowledge representation, or type of neural architecture do not exhibit a clear correlation with goals being met. We find many discrepancies in how reasoning is defined, specifically in relation to human level reasoning, which impact decisions about model architectures and drive conclusions which are not always consistent across studies. Hence we advocate for a more methodical approach to the application of theories of human reasoning as well as the development of appropriate benchmarks, which we hope can lead to a better understanding of progress in the field. We make our data and code available on github for further analysis.11 https://github.com/kyleiwaniec/neuro-symbolic-ai-systematic-review
An Innovative Low-dose CT Inpainting Algorithm based on Limited-angle Imaging Inpainting Model
Authors: Zhang Ziheng , Yang Minghan , Li Huijuan , Chen Shuai , Wang Jianye , Xu Lei
Published: November 2022

Background:

With the popularity of computed tomography (CT) technique, an increasing number of patients are receiving CT scans. Simultaneously, the public’s attention to CT radiation dose is also increasing. How to obtain CT images suitable for clinical diagnosis while reducing the radiation dose has become the focus of researchers.

Objective:

To demonstrate that limited-angle CT imaging technique can be used to acquire lower dose CT images, we propose a generative adversarial network-based image inpainting model—Low-dose imaging and Limited-angle imaging inpainting Model (LDLAIM), this method can effectively restore low-dose CT images with limited-angle imaging, which verifies that limited-angle CT imaging technique can be used to acquire low-dose CT images.

Methods:

In this work, we used three datasets, including chest and abdomen dataset, head dataset and phantom dataset. They are used to synthesize low-dose and limited-angle CT images for network training. During training stage, we divide each dataset into training set, validation set and testing set according to the ratio of 8:1:1, and use the validation set to validate after finishing an epoch training, and use the testing set to test after finishing all the training. The proposed method is based on generative adversarial networks(GANs), which consists of a generator and a discriminator. The generator consists of residual blocks and encoder-decoder, and uses skip connection.

Results:

We use SSIM, PSNR and RMSE to evaluate the performance of the proposed method. In the chest and abdomen dataset, the mean SSIM, PSNR and RMSE of the testing set are 0.984, 35.385 and 0.017, respectively. In the head dataset, the mean SSIM, PSNR and RMSE of the testing set are 0.981, 38.664 and 0.011, respectively. In the phantom dataset, the mean SSIM, PSNR and RMSE of the testing set are 0.977, 33.468 and 0.022, respectively. By comparing the experimental results of other algorithms in these three datasets, it can be found that the proposed method is superior to other algorithms in these indicators. Meanwhile, the proposed method also achieved the highest score in the subjective quality score.

Conclusions:

Experimental results show that the proposed method can effectively restore CT images when both low-dose CT imaging techniques and limited-angle CT imaging techniques are used simultaneously. This work proves that the limited-angle CT imaging technique can be used to reduce the CT radiation dose, and also provides a new idea for the research of low-dose CT imaging.
FAKTOR–FAKTOR YANG MEMPENGARUHI PEMBIAYAAN MUDHARABAH DI BANK MUAMALAT INDONESIA
Authors: Adni Bella , Rafidah Rafidah , Mubyarto Novi
Published: November 2022

Raising funds from third parties of Islamic banks is an indicator of the number of Islamic banks disbursing financing, if more Islamic banks channel financing, the more profit margin returns. This study aims to analyze the factors that influence mudharabah financing at Bank Muamalat Indonesia in 2015-2020. Mudharabah financing will be viewed from Third Party Funds, Return on Assets, Capital Adequacy Ratio, Non Performing Financing and Total Assets. Bank Muamalat Indonesia financial report data for 6 years from 2015-2020 on a quarterly basis so that there are 24 samples. The data were analyzed using multiple linear regression. Partially, the Third Party Fund variable has a negative and significant influence on mudharabah financing. The ROA, NPF and Total Assets variables have a positive influence in distributing mudharabah financing, while the CAR variable has no effect on the distribution of mudharabah financing. However, simultaneously the variables of TPF, ROA, CAR, NPF, and Total Assets affect the distribution of mudhaarabah financing.
THE FUNCTION OF TRANSPORT NETWORKS IN THE ECONOMIC DEVELOPMENT OF RURAL SETTLEMENTS
Authors: Hnes Liudmyla
Published: November 2022

Developing market economy and European values in Ukraine, there are principles which are aimed at resolving social and economic requirements in areas that are designed to promote their efficient development. One of the principles of balanced development is the creation of a transport network, which will contribute to the development of the economic sphere of "peripheral territories" as well as social development. The transport network prompts investment attraction and, thanks to this, the territories get impetus for further development.

Nowadays, rural settlements in Ukraine are mostly concentrated along the roads at a distance between 5 and 15 km. Beside this, there is an interconnection between the type of transport network and the settlement pattern. Transport provides the migration mobility of the population, the intensity of land settlement, areas of reconstruction and new development. The transport system is closely interconnected with the development of cities and urban agglomeration, it provides interconnection between cities and rural settlements, and the lack of roads causes the collapse of the whole rural infrastructure.

Comparing the main components of the impact on the development of rural areas, they should be considered from the standpoint of the theory of O. Gutnov, "skeleton and fabric", which are an integral part of the cyclical development and evolutionary dynamics of urban systems, while acting as a forming urban space, with the main components:

– communication framework (network of various categories of roads and their junctions); areas of social activity development fabric filled with a variety of spatially localized functions.

It has been determined that based on the theoretical model of O. Gutnov it could be possible to predict the dynamics of the impact of transport networks on the environment and on the development of existing settlements, to outline the modern system model of rural areas, as integration of subsystems:

On the basis of systematic research, the author analyzes the areas of Zhovkva district, Lviv region which are under the influence of highways and local roads, and notes their more intensive, more diverse development and their greater occupancy within 10-15 km of roads than more distant territories.