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Hybrid UAVs have unique capabilities to take-off and land vertically. For these unique vehicles, there are several ways to achieve these phases of flight successfully. This paper proposes four strategies for a convertible hybrid unmanned aerial vehicle, to transition from forward flight to hover, and then land vertically. Strategy 1 and Strategy 2 suggest reducing forward airspeed gradually to zero while maintaining altitude by regulating the workload between the four motors and the main engine. The difference between these two strategies is the speed of reducing the forward airspeed to begin hovering. Strategy 3 proposes gradually losing altitude while reducing forward airspeed until transition airspeed is reached and hovering to commence. Strategy 4 suggests a way to drop the aircraft vertically by deep stalling in effort to lose altitude quickly but engage the four motors before the aircraft reach the ground. The paper concludes with a brief description of the role of the automatic flight control systems responsible for regulating this transition phase for convertible hybrid UAVs. [ABSTRACT FROM AUTHOR]

This paper proposes an original algorithm for automatic resolution of a multitude of conflicts in real airspace, the code and the calculation method being explained in detail in this paper. In this proposed new form, the generated algorithm also takes into account the problems that are previously detected and thus proposes a method to solve all these problems that inevitably appeared in the scientific research process. The problem of automating Air Traffic Control is an extremely important problem, which is continuously studied, because it offers a concrete solution in the conditions of exponential growth of air traffic, an increase that is estimated for the next 30 years as a pressing problem that requires early resolution. A fully automated solution will thus increase air efficiency while increasing air traffic safety, while certainly reducing the amount of effort for today's Air Traffic Controllers. The new form of implementation of this algorithm is expected to be much faster and more efficient in successfully resolving all the multitude of air conflicts. Also, the new algorithm can resolve existing conflicts between aircraft and if there is no solution that is strictly based on changing the flight speed of the aircraft considered. [ABSTRACT FROM AUTHOR]

The presented paper is dealing with the UHPC specimens, which have been reinforced by basalt fibres. Primarily, the experimentally investigated specimens were subjected to three-point bending test, in order to evaluate fracture properties, such as Fracture energy Gf and Stress Intensity Factor (SIF) KI. The bending tensile strength fcf was evaluated as well. Measured mechanical parameters were observed and evaluated after one month of curing process. The results, presented in the paper, are part of the extensive material research supported by Czech Science Foundation. [ABSTRACT FROM AUTHOR]

The paper presents a model of generation of the powder bed which is a part of the modeling platform for the simulation of the additive manufacturing (AM) technologies to study physical mechanisms and oriented firstly on selective laser melting (SLM) process. In the paper, several variants of the model developed and adopted for the platform are reviewed, compared, and analyzed in terms of possibilities. Some simulation results are presented. The powder deposition results are transferred from the model to another part of the platform for simulation of the SLM process, and the simulation results are also presented. The novelty of the presented platform, which contains the powder deposition model, is the creation and modeling of one layer with several tracks of laser movements during the SLM, the possibility to design the complex technology, and its optimization. [ABSTRACT FROM AUTHOR]

Based on kinematics theory, this paper proposes a computational tool that can rapidly assess the damage mechanism of aggregates in masonry structures. In this approach, some pre-assigned local mechanisms are assessed on a three-dimensional (3D) model of the whole aggregate, on which the shape of the involved macro-blocks is directly modelled. The method uses the principle of virtual work to calculate the horizontal load multiplier, judge the local failure mechanism, and carry out the reinforcement design. The method realizes coding in AutoLIS language function, uses AutoCAD software to model, and then realizes operation. The case analysed in the paper is an example from the 17 masonry aggregates located in the historical centre of Arsita. This aggregate is referred to as "Il Torrione". [ABSTRACT FROM AUTHOR]

The paper is devoted to development of the evolutionary modelling approach for solving project management problems in IT sectors in dynamic setting. The usage of an evolutionary model for the project management is determined by the advanced methodology, constructive software and effective visualization. The proposed approach is treating an IT project not as an indivisible elementary activity in an IT-company, but as internally organized structure, requiring resource allocation. Within the framework of the proposed approach, the paper presents three models that evolve from the basic model to the complex one and cover all necessary aspects of project management. The models take into account three dimensions: large-scale IT-company project management issues, small IT-company management with unified project team, and the most detailed personalized project team approach, allowing accounting each staff member individual contribution and productivity. The developed models are unified, scalable and invariant to the project complexity by their structure, so they can be easily adapted to the wide range of tasks. Simulation experiments conducting via the proposed evolutionary models enables visualization of the project dynamic process over the time horizon and provides analysis of related aspects along the entire management chain from the employees' appointment to the project personnel training. [ABSTRACT FROM AUTHOR]

The paper deals with the analysis of the economic growth model with CES-production function. The elasticity parameter of this function varies up to its limit value of one. In the limit case of the unit elasticity, the production function turns into Cobb-Douglas type. A special attention in the paper is devoted to this limit transformation and its impact on the stabilized solutions. Numerical examples finalize the paper. [ABSTRACT FROM AUTHOR]

In this paper, we show briefly outcomes of a pedagogical study using numerical methods, in particular the Arithmetic of Infinity, in teaching infinity for undergraduate level (for the detailed study, see [15]). This methodology, introduced by Yaroslav Sergeyev in 2003, provides a new way to deal with infinite quantities and infinitesimals. Though it is different from the methods used in traditional mathematics, those which are adopted in most school curriculums worldwide, yet it doesn't contradict those methods. The study presented in this paper highlights students' beliefs of mathematical infinity, as well as their ability to learn and use the new methodology. The results of evoking the Arithmetic of Infinity in school teaching seemed to be promising as it provides easy methods for computing infinite quantities and infinitesimals. In addition, students' beliefs of the mathematical infinity turned to be more confident and positive after being subject to the new method. [ABSTRACT FROM AUTHOR]

This paper is aimed at performing numerical simulations of the behavior of a planar model system consisting of a spherical absorber located in a supporting convex spherical cap. The derived system of nonlinear differential equations is subjected to a numerical solution. First, the time response of the system to harmonic excitation is analyzed. For this excitation, the frequency of the excitation was gradually changed, thus, resonance curves were created. This paper also examines the effect of initial conditions. For this purpose, numerical simulations of the system without an external excitation source have been performed. The results are phase portraits for selected pairs of initial conditions. [ABSTRACT FROM AUTHOR]

The paper is focused on the determination of mechanical fracture parameters of alkali-activated concrete (AAC) specimens of nominal dimensions 80 × 80 × 240 mm with central notches of the following types: straight-through notch, chevron notch with 90° notch angle and chevron notch with 120° notch angle. In accordance with the results of the experimental research, a numerical simulation of the fracture test of the specimens tested in three-point bending was carried out. The 3D FEM computational model is based on the configuration of the laboratory test and was developed in ATENA-GiD software. Artificial neural network (ANN)-based inverse analysis was used to identify the mechanical fracture parameters of studied composite. A neural network ensemble was created, with one robust network for each type of notch, covering the entire domain of identified parameters. The main goal of this paper is to present the results of the identification of the mechanical fracture parameters of the AAC and their comparison with the values obtained by direct evaluation of the experiments. Another objective is to investigate the influence of the notch type on the mechanical fracture parameters of the AAC. [ABSTRACT FROM AUTHOR]

This paper presents the evaluation of the fracture test of high-strength structural (HSS) steel grades S460 using a finite element (FEM) numerical model. Steels with better strength characteristics may exhibit different stress-strain diagram behavior and therefore material models need to be adequately prepared. The numerical model, which accurately simulates the experiments, was prepared using known information from tensile testing of high-strength steel. The aim is to determine the material parameters with high accuracy using inverse analysis so that complex numerical models of building structures such as steel halls and bridges can be prepared. The paper contains results from an experimental investigation compared with results from a numerical model of a tensile fracture test. Due to the good agreement, the derived material parameters can be applied in future research on high-strength structural steel in the construction industry. [ABSTRACT FROM AUTHOR]

This paper reviews an approach for formulation of an effective and accurate numerical model for description of brick firing processes in tunnel kilns. Within the paper, the key parts of the model are described and the motivation for introduction of those features given. The authors opinions are accompanied by preliminary results of a newly formulated model that is still being developed and will be published soon. [ABSTRACT FROM AUTHOR]

In this study, by implementing bosonic p-adic integral to some identities regarding the generalized and the non-central factorial coefficients, we derive some formulas that involves the first kind Stirling numbers and Bernoulli numbers, and also the Daehee numbers. Finally, we bring to an end of the paper by providing some concluding remarks with further observations on the findings of the current paper. [ABSTRACT FROM AUTHOR]

The rapid development of telecommunications technologies (ICT) and especially the internet has changed and continues to change the ways of teaching and learning. Educational organizations are becoming heavily dependent on ICT for the effective performance of daily tasks. Lately, the concept of "Bring your own device" (BYOD) has been implemented to support better education. In this paper the teachers' and students' opinions are analyzed and reasoned by generation characteristics. This paper adds to previous research on BYOD by highlighting key opinions of the users as well as providing a brief summary of research done between 2016–2021. [ABSTRACT FROM AUTHOR]

The document is a preface to the Proceedings of the International Conference on Numerical Analysis and Applied Mathematics 2022 (ICNAAM-2022). The conference aims to bring together leading scientists in the field of Numerical and Applied Mathematics and attract high-quality research papers. The selection of papers included in the volume was based on an international peer review process. The preface expresses gratitude to the Scientific Committee, organizers, invited speakers, and others involved in the conference. It also mentions the inclusion of the Proceedings in the AIP Conference Proceedings series. The document provides information about the conference details, the European Society of Computational Methods in Sciences and Engineering (ESCMSE), and the categories of membership in the society. [Extracted from the article]

In recent years, with the increase of online learning platforms, obtaining learning behavior data from students, are becoming easy. However, analyzing the data to extract meaningful information remains challenging due to the data volume and complexity. Here, we apply Self-organizing Maps (SOM) to visualize the learning characteristics of many elementary students over many online assignments in mathematics class. As a case study, this research used the data log of MONSAKUN, a digital learning environment that focuses on exercising arithmetic using story-based questions by using a problem-posing approach with the integration of mathematical sentences. Our primary objective is to give intuitive understanding to the teachers regarding the students' performance that subsequently allows the teachers to generate meaningful advices. Here, SOM generates a two-dimensional map that preserved the topological order of high-dimensional learning characteristics data, in which students with similar learning characteristics are located close to each other, while students with significantly different characteristics are distanced from each other. We are interested especially in locating low-performing students, as they are the most important to be given advice by the teachers. By locating the low-performing students and other students in their vicinity on the map, the teacher may be able to use other students as references for improving the low-performing students' performances. The idea is to mimic the learning characteristics of the students designated as references. Due to the learning characteristics similarity, the low-performing students do not need to make drastic changes in their learning styles. It can be expected that by iterating this process over many assignments, the students' performances will gradually be improved. In this paper, we utilized a digital learning platform MONSAKUN, for learning arithmetic used in Japan. In this paper, we present our preliminary results in the form a learning-visualization of characteristics students of analytical and advisory tools and described our future goals for building a more flexible and general tool that can be deployed in Indonesia. [ABSTRACT FROM AUTHOR]

The aim of this paper is to create/proposea new hybrid root finding algorithm to solve the given transcendental equations. The algorithm proposed in this paper is built on the trigonometrical algorithm using hyperbolic tangentfunction to find a root. Couples of numerical examples and one sample computations are presented to explain the proposed algorithms, efficiency and accuracy. Implementation of the proposed algorithms is presented in a mathematical software tool Maple. [ABSTRACT FROM AUTHOR]

This paper deals with distinct problems of a woman faced in the social hierarchical order. This paper finds the significance of the title "The Inheritance of Loss". The main focus of this paper is to see how a deserted woman is degraded by the husband and predicament status of a widow in the society. It also discusses the elements of terrorism and political issues and a subaltern treated by the judge. This paper discuses on various post-colonial issues like the issues of poverty and subalternity. This paper also discloses people's longing and losses which are essential part of loss. This paper focuses the ordinary life of poor people in the text. [ABSTRACT FROM AUTHOR]

In this paper, the reasons behind lack of communication skills of rural area students have been examined. The data for this study have been collected by observing English classrooms of rural schools, students of rural areas and also on the researcher's own experience of living with rural area students. The current study attempts to demonstrate the importance of English language and difficulties of rural area students in acquiring the second language. English language learning became compulsory for an individual to attain opportunities in today's world as it is a global language. The paper investigates the different factors influencing English language learning in rural areas and it examines English language education in rural Telangana. [ABSTRACT FROM AUTHOR]

This Paper deals with sufferings of lower-caste people. It brings out the logical consequence of an oppression and domination of a man. It finds the presentment of 'India's Darkness and India's Light'. It presents how a chauffeur breakdown the Rooster Coop. It shows the anticipation of Balram about his master. It presents how a poor man emerges as a successful entrepreneur. It describes the title's symbolization. This paper represents India as an emerging entrepreneurial power in the modern days. This paper employs that the class conflict and how the deprived one's struggle for achieving a right position in the world. It also explains that the oppressors change from place to place but the sufferings of the oppressed class never change. [ABSTRACT FROM AUTHOR]

This paper is a brief summary of some linguistic characteristics of Lambada language. Lambada is a nomadic tribal language spoken by many speakers in India. Most of the linguistic features of Lambada are similar to those of various Indo-Aryan Languages like Hindi, Marathi, Gujarati, and Rajasthani etc. In spite of the massive borrowing of lexical items, Lambada has retained several linguistic features that are not found in other Indo-Aryan Languages. This paper attempts to look at various basic linguistic features of Lambada language such as speech sounds of Lambada, phonological processes and grammatical features in a brief note. [ABSTRACT FROM AUTHOR]

A system which recognizes hand poses and gestures from the Indian Sign Language (ISL) in real time using grid-based features is presented in this paper. An attempt is made to minimize the gap between the hearing and speech impaired and the rest of the people in the society. The solutions that are existing now neither provide relatively high accuracy nor do good work in real time. Good results on both these parameters are provided in this paper. Some gestures and 33 hand poses from the ISL can be identified using grid-based features. A smart phone camera is used to capture the sign language and are transmitted to remotely placed server in the form of frames. It is user friendly and external hardware usage is thus avoided. For hand detection and tracking, techniques such as skin color segmentation, face detection and object stabilization are used. Further to represent the hand's pose in the form of feature vector, the image grid-feature extraction technique is implemented on the image. K-nearest neighbors' algorithm is used to classify the hand poses. Hidden Markov Model chain is fed with the motion and observation sequence of intermediate hand poses to classify the gestures in which 12 gestures are predefined in ILS. [ABSTRACT FROM AUTHOR]

Nowadays, Power Electronics is paying greater attention to the rapid advancement of power semiconductor devices. This paper examines the quantitative analysis of the Direct Matrix Converter using both MOSFET and IGBT for high efficiency converters. As a result, the IGBT has a substantially lower switching loss than the MOSFET. Additionally, switching loss for MOSFETs will significantly increase at high operating temperatures, whereas switching loss for IGBTs hardly varies with temperature. In this paper, by comparing switching power loss, temperature, volume, weight requirements, power quality, efficiency, and static characteristics, the performance of IGBT and MOSFET is assessed. It has been concluded through a comparison of the device parameters that IGBTs outperforms MOSFETs in terms of smaller loss, greater efficiency, and smaller size. [ABSTRACT FROM AUTHOR]

These days, the students are worried about their placement opportunities in this competitive world. Getting placed in a company with good package is what students dream. In this paper, a machine learning model to predict the package with which the students will get placed in a company. If they have less package then they can try to improve their skills. Based on the marks they have scored in some technical subjects are used to predict the package of the student using machine learning model. In this paper, linear regression model, regression tree and random forest classifier models are used for p rediction. Among all these three models, random forest model is performing well with least error while prediction. [ABSTRACT FROM AUTHOR]

In recent years, the multi-level dependency has been increasing. It has many convenient applications to conversion ability as well as to change in the improvement in the output voltage quality. Adding on, it has been providing the lowest total-harmonic-distortion(THD), the output power rating has also been increased by lower switching losses and conduction losses and also multi-level is providing higher staircase voltage levels. In this paper the H-Bridge cascaded-multiple-level inverter with different levels of output is studied using MATLAB. The role of multiple-level inverter is, it has to convert DC to good quality AC. In multi-level the transformation of power from DC to AC will be carried out in small steps which results in lower harmonics. This paper presents 3-level, 5-level and 7-level of H-Bridge cascaded-multiple-level inverters. The cascaded multiple-level inverter uses the notion of series connection means that, the output of one inverter stage is given as input to the following inverter stage. The number of voltage levels developed by the inverter depends on the number of individual inverter stages. Each inverter stage consists of four switching devices. For every inverter stage a separate DC source must be used. Here, we are using sinusoidal voltage pulse width modulation (SVPWM) technique to trigger the switching devices. Finally, the simulation results of 3-level, 5-level, 7-level are observed and compared. [ABSTRACT FROM AUTHOR]

Blockchain technology is one of the most sensational and under rated technology in current technological and financial sector. The great wave in blockchain technology for the banking sector is still unexplored to its depth, as the need for new technology in all the areas of life is a necessity nowadays. The study was conducted to identify different services that the financial sector can provide to its customer by accepting a unified blockchain technology. The fundamental inkling of blockchain technology is, its public and the same is shared in a tamperproof ledger which allows the heterogenous community to share the sensitive data over a distributed ledger. This paper gives an idea about how this tamperproof technology can be used to increase the efficiency, transparency and to lower the risk and expenditure associated with the highly sophisticated data of an individual in relation to banking sector. The technology has great potential to overcome the disadvantages of the current central server system in banking industry, which is highly prone to hacking and cracking. The blockchain technology is current meant to be a hack proof system which is still in its initial stage of development. As the technology is still in pilot testing stage on banking sector, once the same is found feasible to with stand the current market need, this will bring an economic and technological boom to different sectors. The most exciting premises about blockchain technology is, it makes banks pointless. Though, this paper contends that the advantages of block chain technology will be used by the financial institutions in a first mover place rather becoming outdated. [ABSTRACT FROM AUTHOR]

In this paper focused on SHA1 based OTP generated has alphanumeric string of characters that authenticates the user for a transaction and login into web as well as mobile application. Now a day's this kind of technology has developed rapidly for users using various types of applications and websites. But the major concern for users is secure logins into the application using SHA1. In the existing login system such as password authentication, QR authentication, biometric authentication not efficiently not working due to vulnerable from attacker. In such case lack of user privacy, confidentiality, also to avoid risk of password theft and memorization of passwords. In this paper proposed cryptographic SHA1based secure OTP authentication for application. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has been widely used across the oil and gas industries that elevate asset management efficiency. Nevertheless, as the industry produces hydrocarbons, reducing CO2 emissions becomes one of the challenges. Therefore, this paper illustrates the utilization of AI to enhance the gas lift operation using pattern recognition and optimization algorithms. Initially, the feature extractor was developed using self-supervised learning to learn features from data without manual labels. Then, the patterns are clustered to build a pattern recognition model using a supervised classification model. Afterward, an optimization algorithm is applied to optimize fluid production under allowable operational and CO2 emission limits. Then, a gas lift stable production model was developed using Machine Learning (ML), relying on controllable and reservoir parameters that will be used for optimization purposes. The study used synthetic data from eleven wells with similar wellbore and mandrel configurations with various depth and Productivity Index (PI) and constant reservoir pressure. An air compressor specification and specific CO2 emission were also determined. In addition, gas injection and adjustable choke are assumed as controllable parameters in the optimization process. This study shows a high prediction model accuracy of 0.99 for K-Nearest Neighbor classifier (KNN) and an R2 score of 0.99 for Multi Layers Perceptron (MLP) as a regressor. As regards the optimization algorithm, Simulated Annealing (SA) was used to achieve the optimum solution in a reasonable time, especially for a near real-time environment. Lastly, the workflow introduced in this paper could be implemented in a real case as the study used widely known information in gas lift operations. [ABSTRACT FROM AUTHOR]

For a long time, various farming activities are being performed precisely to fulfill food resource requirements. The farming activities are time and energy-consuming. With the increasing young population and the ageing of the old population, farming activities are being ignored. Further, with the increased industrial revolution, farmers have faced many problems such as complex working conditions, lack of skilled labor, less land size, and many more, which are causing less productivity and less profit. In such a case, the application of robotics is more effective. Over the past few years, there is a lot of research undertaken to develop smart farming with the help of agriculture robots and modern technology. The available review papers fail to highlight the contribution of robotics in the development of smart farming remarkably. The proposed work aims to review the significant impact and contribution of robotics in the development of smart farming. More than one hundred papers were reviewed to analyze the contribution of robotics to smart farming. From them, the fourth nine papers are taken out to cite in the proposed work. The contribution of robotics in smart farming is highlighted with the crop growth cycle phases such as cultivation, monitoring, and harvesting, followed by the tabular representation of review analysis and the comparative discussion. Robotics technology has replaced most of the major activities of crop growth phases. The contribution of wheel robotics is remarkable. The paper concludes with the various conclusions of the study and highlights future work. [ABSTRACT FROM AUTHOR]

Mobile robots are implemented in various fields for diverse applications. Mobile robots with wheeled, legged, and hybrid types are used in industrial and service sectors. Obstacle avoidance algorithms play an important role in mobile robot navigations. In this paper, comparative study of various hybrid path planning algorithms for avoiding static obstacles are carried out for determining the most efficient path planning algorithm for the given task. A modified Probablistic Road Map (PRM) approach is combined with variants of A star algorithm to create different hybrid path planning algorithms in this paper. The nodes and connections are created using PRM approach where as the optimum path is constructed with variants of A star algorithm. This paper compares the computational time, algorithm size, memory, path optimality, etc. The proposed hybrid algorithms are compared and evaluated by simulating the obstacle avoidance by the mobile robot in a structured environment. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) and Machine Learning (ML) transforming the Insurance industry by improving efficiency, reducing costs, and providing a better customer experience. As these technologies continue to evolve, more innovation can be expected in the Insurance industry. A Bibliographic analysis is conducted for scientific mapping based on 1,084 SCOPUS-indexed publications between the year 2000-2022 using VOSviewer Application. The Analysis was conducted based on Publications by year, Source, Author, Affiliation, Country, Type, Subject Area and Funding Sponsors. The research found the result, the year 2022 had the highest publication of 203, through documents per year by the source of Lecture Notes In Computer Science Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics at 43 publications, Bauder, R.A. author is the maximum contributor, Harvard Medical School has been the major affiliate, United States of America, has the maximum 341 publications, Conference paper has the majority participation at 412 documents at 38 percent and Keywords "Artificial intelligence", Machine Learning" and "Insurance" has the highest occurrence. The maximum number of publications inthe field of computer science at 28 percent. Overall, this bibliographic analysis provides a comprehensive overview of the current state of research in AI and Machine Learning in the Insurance industry and highlights the potential for further innovation and development in this field. [ABSTRACT FROM AUTHOR]

Animals suddenly obstructing roads and wild animals infiltrating human dwellings are involved in many of the world's worst road accidents. Aside from property damage, fatal deaths and permanent disabilities also occur. As a result, mitigation of such problems has become a prominent area of research, leading to the development of a wide range of detection techniques. This paper analyses ongoing research approaches to the prevention of animal-vehicle conflicts (AVC) and animal-human conflict (AHC). The primary goal of this study is to investigate the various image and video-based object detection approaches that are used to detect and solve image and video-based animal detection challenges. The various animal monitoring system, as well as some of the methods used to detect animals and collect their data sets, will be discussed in this paper. The challenges associated with animal identification are briefly discussed. [ABSTRACT FROM AUTHOR]

Various advantages of Multiple-Level Inverter (MLI) allow this technology to have numerous applications. In this paper, a topology for eleven level MLI setup for medium-voltage with superior performance has been proposed. This topology is capable to interface with a Solar Photovoltaic (SPV) module which ultimately generates power to connected grid. Thus, the system is designed to distribute solar energy to the grid. MLI topology consisting of twenty switches is interfaced with grid and a cascaded transformer is fed from a SPV as DC source. MATLAB simulations are conducted for the SPV grid and cascaded transformer connected grid to the eleven-level Cascaded H-bridge (CHB) MLI system. The paper examines various output characteristics at various coupling points of SPV, grid, and MLI. Finally, the outcomes from the simulation confirm the working of proposed MLI "design configuration" and "control technique" under different stochastic conditions. [ABSTRACT FROM AUTHOR]

The photo voltaic technology is one of an emergent technology, helping in the production of electrical energy. The demand for this technology has been increased globally due to the rapid increase in population growth. This rapid increase requires an emergent technology which helps in providing solution for the electric utilities. Solar Voltaic system helps in assisting the existing power system. This system is a kind of distributed power generation system. This is one of the best technologies to provide solution for present scenario. In this paper, the double stage three-phase grid-connected solar inverter is explained. The complete modelling is presented in MATLAB-Simulink environment for the switching model of a grid connected solar inverter. MPPT technique is also used to track the maximum power in the simulation. Phase lock loop technique is used to synchronize the PV system with a certain phase. The importance of the inverter modelling, outer voltage loop, inner current loop considering the connection requirements, the double stage controller is fabricated. The complete model is designed in the MATLAB environment. The present article thoroughly examines the two-stage three-phase grid-connected photovoltaic (PV) system. The paper describes the modeling of a single PV system's switching mechanism in phases. It emphasizes the importance of inverter control to meet future connectivity requirements. The double loop controller is used to regulate both the boost converter and inverter. Vector-oriented and feed-forward control techniques are employed to create the inverter controller. Additionally, the article discusses the significance of extracting positive and negative sequences. In the MATLAB environment, the entire model is created. Solar PV systems are classified as distributed generation since they aid existing power systems in meeting electricity demand for load changes. In this paper, a stand-alone PV system is connected to a three-phase grid, which includes a PV array, the Perturb and Observe (P and O) Maximum Power Point Tracking (MPPT) technique for tracking maximum power from the PV array, and the Duty Cycle adjustment for switching pulses to the Boost Converter's High-Level Switch. With Pulse-Width Modulation (PWM) control, the 2-level inverter converts DC to AC. The Phase Lock Loop approach is used to synchronize the Standalone PV system with the grid at a specific phase angle and frequency. According to load variations, the control circuit is designed to supply active and reactive electricity to the load from a standalone PV system and the grid. This study shows a three-phase dual-stage inverter-based grid-connected PV system in a centralized arrangement. The three-phase series resonant converter is chosen for the DC-DC stage because of its advantages. It is, however, insufficient for MPPT because its efficiency is highly dependent on the implemented deadtime and switching frequency. [ABSTRACT FROM AUTHOR]

In the present day, deep learning applications are widely used in every field of development. In this paper, such a type of application is discussed in real-time. Mura dataset is the largest abnormal dataset given by the University of Stanford. In this research paper, we will understand the pre-processing of the image dataset. Kera's and TensorFlow libraries are used to build this model. We are classifying images using different ML models where accuracy is compared to get the best model build. This paper gives us a clear understanding of building deep learning models, understanding pre-processing techniques, and working on heavy data. This research's main agenda is to create a model which can classify bone fracture images and also give a small path for further development in the deep learning area. In this project we are using Resnet50, InceptionV3, Mobile Net and DenseNet with optimizer Adam and comparing their accuracies graphically. [ABSTRACT FROM AUTHOR]

Generation of very fast transient over voltages (VFTOs) is very common during switching operations in gas insulated substations (GIS) and it is extremely harmful for substation equipment like transformers as it becomes a reason of insulation damage due to its less arising time. Sometimes, the VFTOs magnitude may be very near to the basic insulation level (BIL). Improvement and investigation of such transients in power transformer is of crucial importance in GIS as transformers are vital components of power system network. Generation of transient issues considers the generation and propagation of VFTOs while switching of circuit breakers or disconnector switches or earth faults. In this research, the investigation is on VFTO by putting intelligible models for a GIS of a capacity 400 KV. This paper presents a modeling guideline for VFTO analysis in GIS and, further mitigation techniques such as Nano-crystalline Rings, RC Filter, Ferrite Rings, Damping Resistance etc. have been studied using MATLAB simulation. Using an intelligent optimization technique like PSO, VFTO waveforms can be scaled down further to controllable limits so that substation components can be saved from impending failures. Further VFTO effect on GIS such as stress on substation Transformer leading to winding deformation has been discussed in this paper and localization of deformation and type of deformation in transformer winding is also carried out using intelligent classifier. [ABSTRACT FROM AUTHOR]

With the advancement of technology, computer network usage has significantly increased. Although everyone in today's world rely on the use of internet for the fulfillment of the day-to-day work Security issues are one of the concerns. Intrusion Detection System based on ML models are more structured and meticulous. In this paper we have discussed various datasets used in intrusion detection systems. i.e. (DARPA, KDD CUP 99, NSL-KDD, UNR-IDD, KYOTO, ADFA(LD), ADFA(WD) (Australian Defense Force Academy), CICIDS, LU-FLOW, UNSW-NB15, NF-UQ-NIDS-v2, etc.). Comparing UNSW-NB15 Machine learning models were used to Analyses the Dataset. The aim of this paper is to analysis all the datasets together to get the preformation of it. [ABSTRACT FROM AUTHOR]

The knowledge of current-voltage (I-V) characteristics of photovoltaic (PV) modules is essential for accurate estimation of solar energy production. The I-V characteristics of a PV module are frequently evaluated using models based on the equivalent circuit, whose parameters are determined from the information supplied in manufacturer's datasheet. The mathematical modeling of the I-V characteristics always presents a challenge when considering the scant information from datasheets (short-circuit current, open-circuit voltage and maximum power point). This study is rooted in our previous results (Sabadus and Paulescu, Energies 14 (2021) 3974), which highlight that for a given solar cell, different scientific papers report substantially different sets of equivalent circuit parameters for Standard Test Conditions (STC). Despite the differences, all the parameter sets replicate the I-V characteristics with high accuracy. This paper evaluates the impact of the parameters' magnitude at STC on estimating the performance of a PV module operating outdoor. The study deals with the five-parameter model. Firstly, for a commercial PV module, the accuracy in replication of the measured I-V characteristics is analyzed at STC considering different sets of parameters. Secondly, applying an algorithm for PV module performance estimation under real weather conditions, the output power is calculated and compared to measurements. Data recorded on the Solar Platform of the West University of Timisoara, Romania, are used in this stage. Finally, the impact of the estimated parameters at STC on the evaluation of PV module performance is assessed in real weather conditions. [ABSTRACT FROM AUTHOR]

The wildlife trading is the main driving factor that endangers the existence of wild species, in addition to potentially spread diseases and extend invasive species distribution. The nowadays perpetrators of wildlife trading take advantage of the advancement of communication technology, using online social media platforms as transaction media. In this paper, we report a monitoring on online insect trading activity commenced in a Facebook group between March to April 2022. Trading volume, traded insect taxa, role of trading perpetrators and locality of traded insects are among aspects monitored in this study. We recorded 236 posts during monitoring period with average 3.87±2.31 posts daily. These number was posted by 180 account holders that further defined as curious one-timer (126 accounts), occasional provider (33 accounts) and serious breeder/hunter/seller (21 accounts). There were more than 20 insect families offered during this period, with the members of Scarabaeidae (118 posts, 50.0%), Lucanidae (44 posts, 18.6%), Cerambycidae (17 posts, 7.2%) and Buprestidae (15 posts, 6.4%) became the most significant ones. Xylotrupes gideon (Lucanidae), Chalcosoma spp (Scarabaeidae) and Castiarina spp (Buprestidae) seemed to be adverted the most. West Java Province contributed the most in this group with 60 posts advertised 11 insect families, more than twice over what recorded from East Java (29 posts;>5 families), Central Java (21 posts;>8 families), Jambi (11 posts;>4 families) and Jakarta (10 posts; 4 families). This paper, despite covers only two months of online insect trading and on one single Facebook group, indicates a potential threat for the existence of Indonesian insects. Therefore, further systematic online survey is needed to assess the actual volume of online insect trading. [ABSTRACT FROM AUTHOR]

History shows how a war significantly affected the construction industry, including damage to infrastructure and buildings, disruption to the construction supply chain, price fluctuations, terminations of works, and post-conflict construction. This paper focuses on the impact of war on construction contracts by investigating clauses related to war as a force majeure event. The three most common types of standard forms of construction contracts namely FIDIC, NEC, and JCT are used as data to analyze the contractual implications of the war on on-going construction projects. A comparative analysis of contractual provisions related to war and its impact on the continuity of construction contracts is presented. This study found ten war issues being compared, including war as a force majeure event, notification procedure, contractor's obligations, and contract terminations. A systemic model illustrating the contractual implications of the war is developed based on these findings. This paper contributes by facilitating a better understanding of how war as a force majeure event has contractual implications on the on-going construction projects. Practically, the findings of this study can be used by the affected parties to consider the application of force majeure clauses and thus, implement best strategies to negotiate their contracts. [ABSTRACT FROM AUTHOR]

Finite difference technique has become a numerical tool that makes complex become easier for engineers to problems. The complex problems are difficult to solve in the normal way. In this paper, the application of a finite difference technique is used to solve the consolidation problem in the case of radial drainage to determining the reduction in pore water stress. Usually the application is on soils that are near to impermeable, but in this paper it is applied to semi-permeable soils that are silty sand and fine sand. In semi-permeable soils, increased pore water pressure is very shorter. In this study is the time of radial drain is discussed. The data used is taken from Air Tawar, Padang. The results shows that the 90% of increased 100unit pore pressure can be completed within about 126 seconds. The results also indicates this method can be used to solve the problem of a sudden increase in pore water in the soil. [ABSTRACT FROM AUTHOR]

Performance based design is believed to be the next important alternative design method for designing high rise building in Indonesia. This method can also be used to evaluate existing building in order to check the building's performance level. This paper will discuss HALIM High Speed Railway Station project, which is a train station consist of 3 stories with a 226,8 meters long railway on the third floor. Jakarta Building Authority/TABG (Tim Ahli Bangunan Gedung) considers HALIM Station also as a bridge infrastructure rather than just an ordinary building; and not to mention that HALIM Station is the first high-speed railway station in Indonesia. Therefore, in order to make sure the structural safety, TABG requested to do a Performance Based Design analysis to check the response modification factor (R) and its performance level. While there are several ways to perform performance based design, this paper will use non-linear static pushover analysis only. Pushover analysis will be applied on the model based on seismic parameters referred to Indonesian code SNI 1726:2012 and also SNI 1726:2019 even though HALIM Station have been designed before the SNI 1726:2019 is enforced thoroughly. The result shows that all the code methods used on pushover analysis give the same Immediate Occupancy (IO) performance level category. Furthermore, the response modification factor (R) obtained by pushover analysis is greater than the originally defined. Thus, the structural design using the original response modification factor of 8 is on the safe side. [ABSTRACT FROM AUTHOR]

This paper aims to examine the effectiveness of using mind maps as a tool to enhance students' conceptual understanding of photosynthesis. The study employed a one-group pretest-posttest design with a sample size of 27 students. The research instruments used in this study included a paper-pencil test to assess students' understanding of photosynthesis concepts before and after the intervention and the rubric to evaluate the quality of student mind maps. The data collected was analyzed using both descriptive and inferential statistics. The results indicate that students were able to increase their understanding of photosynthesis significantly. The intervention also has a large effect size (Cohen's d≥0.8), revealing that the mind maps can foster students' conceptions of the correct one. The VS-MPR in this research is very large (VS-MPR=1.271×10+13), so the probability of post-test>pre-test is also very high, and it also confirms that the intervention (mind maps) has a significant impact and is very effective in improving students' learning outcomes. The findings also found that student mind maps encompass six essential concepts regarding chloroplast, material for photosynthesis, reactions, electron transports, and photosynthesis products. In addition, the success of this research is also supported by the appearance of the hierarchical nature of mind map connecting the main topic and subtopic since the connection is clear and straightforward. Overall, this study provides empirical evidence supporting the use of mind maps as an effective learning strategy to enhance students' understanding of photosynthesis. [ABSTRACT FROM AUTHOR]

Currently, the documentation system for the professional education process is still paper-based. This system has several drawbacks, such as data manipulation, data similarity between students cannot be known, and cannot be monitored online. To overcome these problems, we need a system to monitor the activities of students who carry out professional education with an online system. The electronic documentation (e-doc) system was developed at Stikes Estu Utomo to produce an effective and efficient documentation system. This paper aimed to analyze and design an e-doc system for midwifery professional education at Stikes Estu Utomo Boyolali. The current system is analyzed to determine the system's functional requirements. System modeling using DFD (Data Flow Diagram) on the electronic documentation system (e-doc) for midwifery professional education is carried out to determine all system components. The system developed consists of 4 stakeholders: administrators, lecturers, field supervisors, and students. The data requirements of the information system were analyzed using entity relationship diagrams, and the user interface (UI) design of the e-doc system was developed using digital design software. The results of this study are the model and design of the e-doc system used to support the monitoring system for midwifery professional education activities for all students. [ABSTRACT FROM AUTHOR]

The purpose of this bibliometric study and literature review is to examine the connection between student sustainability committees and science education. The objective of this study is to methodically record the amount, trend, and intellectual framework of knowledge advancement. Information is gathered from the Scopus database and examined using Microsoft Excel and R Studio. A searchable database with 147 papers has been built by us. According to preliminary data, there has been a rise in the number of articles published about student sustainability committees and science education. R is used in bibliometric studies to find the most influential subjects' journals, authors, and papers. With the use of word clouds, trend themes, word dynamics, and tree maps, the analysis is done to examine how the themes have evolved. The terms "sustainable development," "education," "humans," and "students". This study explains the reasons behind the topic's rise to popularity in science classrooms and among student sustainability committees. This provides opportunities for further research in the relatively new and much-discussed field of sustainability as well as in the larger field of Science Education and Student Sustainability Committee. [ABSTRACT FROM AUTHOR]

In this paper a MPPT based impedance source solar powered inverter is designed to convert solar power to an alternating supply. First a boost converter is built to transform variable input voltage to a fixed DC voltage of desired magnitude and then it is fed to the impedance source inverter. MPPT algorithm is used to track the maximum power while controlling the duty cycle of the boost converter. The integration of MPPT with impedance source converter (ZSI) is primarily motivated by its efficiency in power conversion and reliability, making it a favorable choice for various distributed generation power applications compared to voltage source inverters. In this paper, an analysis is conducted on a three-phase impedance source inverter using a straightforward boost control method. The analysis focuses on key aspects such as the boosted output voltage, total harmonic distortion (THD) of line current, voltage stress on switches, generation of shoot-through states, and converter gain. Simulation is carried out in MATLAB Simulink environment and the results are presented to verify the theoretical findings [ABSTRACT FROM AUTHOR]

The automotive wheel is an indispensable part of a motor vehicle as it is the first part that receives loads in various forms from applications such as falls, heavy cargo and cornering, etc. This paper presents the effectiveness of the analysis process using a finite element method to simulate the dynamic cornering fatigue test by comparing the experimental results with the finite element analysis (FEA) results obtained from three methods: full transient, modal transient and static structural methods. The static structural method was found to have the highest accuracy, with less than 2% error, and also the least computational time. It takes 97% less computational time than the full transient method. Therefore, this paper demonstrates that the static structural method is most effective in using the fatigue life analysis to improve design prior to actual testing to help reduce the cost and time of launching new products in the alloy manufacturing industry. [ABSTRACT FROM AUTHOR]

This paper is proposed to numerically study effects of impact angle, impact position, posture, and height of pedestrian on kinematics and injury responses. A finite element human body model was employed to develop vehicle-pedestrian crash simulations. A 50th-percentile adult male (AM50) in standing and walking postures were considered. The human body model was set to impact a passenger car at its corner and at the centre of the bumper with 90° and 45° impact angles. Eight simulations were conducted. Since Asian pedestrians are usually smaller than their American counterpart, this paper also investigated the effect of pedestrian height by scaling down the AM50 model to a typical Asian height and weight. Four additional simulations were conducted. It was found that the impact position at the vehicle front-end affected the head impact location. Impacting at the corner position had high chance of head impacting the A-pillar which led to severe head injury. Impact angles also showed influence on the kinematics and injury response. Knee bending moment for the 45°impact angle was smaller than the 90°impact angle while bone bending was not much different. The 90° impact angle exhibited lower head injury criteria than the 45° impact angle. The results also revealed that different pedestrian postures led to some different kinematics with respect to the head impact location and speed. Pedestrian in walking posture exhibited more severe head and thorax injuries while the standing posture showed higher bending moment of the lower extremities. Finally, the human body model with Asian height exhibited higher risk of head injury than using AM50 data. The results of this study will be useful to vehicle manufacturers in designing a front structure of the vehicle and pedestrian protection systems. [ABSTRACT FROM AUTHOR]

Assignment problems have become much more challenging for academic institutions in terms of course assignments to lecturers. The challenges include assigning a lecturer to a course or subject that is within their area of expertise, level of preference, and teaching competency. This has led to time-consuming, inefficient, and biased or unbalanced lecturer-to-course assignments. The modified Hungarian method (MHM) optimally solves the unbalanced assignment problems, especially for the situation, for example, when the number of jobs is always greater than the number of available machines, given that the jobs are expected to be completed within a respective time interval. Analysis of the MHM, focusing on the structure of the problems and types of applications, is presented in this paper. Various types of applications of MHM are found, however, there are limited existing studies focused on course allocation and assignments for lecturers in higher-level education institutions, especially considering the preference level and teaching competencies. Moreover, assessing lecturers' teaching competency in course assignment problems has never been found within the area of interest. For this reason, a conceptual model using the MHM method is introduced in this paper. The model is expected to contribute to enhancing lecturers' well-being, the teaching satisfaction level, and the quality of teaching. [ABSTRACT FROM AUTHOR]

In this paper, we have obtained an upper estimate for the norm of the basis vectors of the lattice Λ in terms of the homogeneous minimum of the lattice μ. Such estimates are used to estimate and find the vector and closest vector problems on lattices. In this paper, we essentially use the geometric construction of the basis of an admissible lattice and some properties of matrix arithmetic. [ABSTRACT FROM AUTHOR]