Proposed Research Method Research Articles

Optimization of accurate estimation of single diode solar photovoltaic parameters and extraction of maximum power point under different conditions

Introduction. With the snowballing requirement of renewable resources of energy, solar energy has been an area of key concern to the increasing demand for electricity. Solar photovoltaic has gotten a considerable amount of consideration from researchers in recent years. Purpose. For generating nearly realistic curves for the solar cell model it is needed to estimate unknown parameters with utmost precision. The five unknown parameters include diode-ideality factor, shunt-resistance, photon-current, diode dark saturation current, and series-resistance. Novelty. The proposed research method hybridizes flower pollination algorithm with least square method to better estimate the unknown parameters, and produce more realistic curves. Methodology. The proposed method shows many promising results that are more realistic in nature, as compared to other methods. Shunt-resistance and series-resistance are considered and diode constant is not neglected in this approach that previously has been in practice. The values of series-resistance and diode-ideality factor are found using flower pollination algorithm while shunt-resistance, diode dark saturation current and photon-current are found through least square method. Results. The combination of these techniques has achieved better results compared to other techniques. The simulation studies are carried on MATLAB/Simulink.

Digital models of parametric structures

Formation of parametric structure digital model are considered. Investigation was based on the analysis of the shaping evolution of the analytical surface in the form of a hyperboloid of rotation. Finite element frame represents a spatial plate-rod system has been developed during creation of the digital model. This scheme allows to study the effectiveness of constructive solutions under dynamic influence at the design stage. Dynamic characteristics of various design solutions are considered in process of choosing a rational variant of the building frame. The influence of the inclusion of outrigger floor in the model of the frame at various levels of the building are investigated. The proposed method of research and application of the possibilities of the shaping evolution allows to proceed to the modernization of BIM technologies in the design of unique buildings. Recommendations for refining the algorithm for studying parametric object digital models were developed.

Institutional Review Board (IRB) Shopping- Accessible for Public Comment

Context: IRB Forum Shopping is an under-researched yet highly-relevant ethical issue in the context of clinical research. IRB members review the proposed research methods to ensure the ethical principles. The IRB has the authority to approve or disapprove the research proposals that fall within the institutional policy and adheres to SOP (Standard Operating Procedures). When the research project has obtained an unfavorable or conditional IRB review, the researcher bypass the process of addressing the IRB’s decision by deserting the IRB and selecting another forum that will provide favorable review. Currently, proposed regulations to prohibit IRB shopping are available for public comment. The FDA report made clear that no empirical evidence exists to support the widespread of IRB shopping.

Computer Aided Teaching System Based on Artificial Intelligence in Football Teaching and Training

As the world's largest sport, football has affected a wide area and a large number of participants and had a great impact on political economy and culture, which has become the best embodiment of the social function of football. Throughout the experience of football in developed countries in the world, the stable development of youth football is the best way to improve the level of football in a country, and the Chinese Football Association has invested more energy in professional leagues and national teams. The development of youth campus football is basically in a state of no management. Therefore, people gradually realize the concept that “football should serve education.” In order to solve the problem of football players' lack of exercise in multiple subjects, it is particularly important to design systems and make plans for their respective physical characteristics. After the failure of various important competitions, the Chinese national football team reflected on the specific factors of backwardness. Under today's system, no one manages the specific development of youth campus football. Especially for young people, training programs that adapt to their individual characteristics should be formulated according to their growth stage and physical characteristics. It can effectively improve the efficiency of football teaching and training (FTT) by managing football players' training information and coaches' teaching information in an intelligent and informatized way. The different sports in which athletes participate in training are identified through the motion recognition layer. The data generated during the entire exercise process, including exercise time, number of exercises, score settlement, and other data, are stored, and the data are finally uploaded to the server, to carry out scientific analysis and management and generate sports training prescriptions in line with their own characteristics. This paper proposes research methods based on the intelligent integrated system of FTT, including literature retrieval, questionnaire survey, training empirical method, comparative analysis method, interview method, and support vector machine model for action recognition, which are used in football teaching and the design experiment of the intelligent integrated system for training; the overall architecture design of the football teaching intelligent integration system and the specific design of the football teaching intelligent integration system are proposed. The experimental results of this article show that 90.70% of players like the teaching mode of intelligent FTT, and the intelligent FTT system can help improve the enthusiasm of players in training and learning.

Mono-Material 4D Printing of Digital Shape-Memory Components.

Dynamic shading systems in buildings help reduce solar gain. Actuated systems, which depend on renewable energy with reduced mechanical parts, further reduce building energy consumption compared to traditional interactive systems. This paper investigates stimuli-responsive polymer application in architectural products for sustainable energy consumption, complying with sustainable development goals (SDGs). The proposed research method posits that, by varying the infill percentage in a pre-determined manner inside a 3D-printed mono-material component, directionally controlled shape change can be detected due to thermal stimuli application. Thus, motion behavior can be engineered into a material. In this study, PLA+, PETG, TPU and PA 6 printed components are investigated under a thermal cycle test to identify a thermally responsive shape-memory polymer candidate that actuates within the built environment temperature range. A differential scanning calorimetry (DSC) test is carried out on TPU 95A and PA 6 to interpret the material shape response in terms of transitional temperatures. All materials tested show an anisotropic shape-change reaction in a pre-programmed manner, complying with the behavior engineered into the matter. Four-dimensional (4D)-printed PA6 shows shape-shifting behavior and total recovery to initial position within the built environment temperature range.

Multi Objective Concerned Network Coding Technique for Optimal Data Transmission

The Internet of Things (IoT) seems to developed in the real-world scenario due to increased utilization of sensor driven technologies. There are various research works has been proposed earlier for the network coding to ensure the reliable data transmission. However, existing research techniques doesn’t focus on the reliable route path selection which might affect the rate of data transmission. These issues are focused in the proposed research method by introducing the method namely Multi-Objective concerned Network Coding Technique (MO-NCT). In this work initially multicast tree construction is performed using Particle Swarm Optimization method. The main goal of this research work is ensuring the reliable and successful data transmission. Here the optimal network nodes will be chosen for constructing the multi cast tree. The multiple objectives considered in this work for the selection of the nodes are residual energy, remaining bandwidth level and throughput of nodes. To ensure the reliable data transmission even with the presence of larger coverage area, this work attempted to select the backup forwarder nodes which will act as intermediate hop relay nodes. The overall analysis of the research work is done in the NS2 simulation environment from which it is proved that the proposed method MO-MRP tends to achieve the optimal data transmission rate.

DATA-driven shock impact of COVID-19 on the market financial system

The Corona Virus Disease 2019(COVID-19) has a dramatic effect on my country's market and financial system. Although China has controlled the deterioration of the epidemic, this global epidemic will inevitably have an impact on the global economy including China. In order to study the shock effect of the COVID-19 on the market financial system, this paper builds a data model processing system based on the event analysis method, and analyzes the shock effect from three aspects of supply chain finance, financial securities, and corporate financial systems. Moreover, this paper uses crawler technology to obtain valid data from major websites, analyzes model data with mathematical statistics combined with event models, and outputs the results and compares them with the actual situation. Through data analysis, it can be seen that the model constructed in this paper can effectively reflect the shock effect of the COVID-19 on the market financial system. Finally, the comparison method is used to compare the research results with the actual situation. The results show that the two are basically the same. Therefore, it can be seen that the proposed research method has significant effects and has certain reference value for studying the shock effect of the epidemic on the financial system.

Study of a novel rotational speed amplified dual turbine wheel wave energy converter

In this study, a novel wave energy converter is proposed, which features a dual turbine wheel to provide an amplified rotational speed to the generator. The design novelty of the system is that the counter-rotational turbine wheels are connected to the generator stator and rotor respectively through a belt-drive transmission system for amplification of the rotational speed of the generator. This arrangement enables the power take-off system to be placed inside the buoy which is above the waterline. Furthermore, the belt-drive transmission system can effectively absorb the load fluctuations or vibrations caused by sea waves. A lumped parameter analytical model of the system has been developed where the Lagrange principle is applied to analyze the motion of the system and the computational fluid dynamics simulation is employed to determine the drag coefficients of the system. The results obtained from the lumped parameter analytical model have been verified by experimental test results. The developed lumped parameter analytical model allows accurate performance prediction without the high computational cost of the detailed simulations. The proposed research method could be applied as an effective tool to explore the science of wave energy conversion and to optimize the power absorption capacity and the efficiency of the power take-off system, which is the originality of this paper and contributes to the new knowledge in this area. For this prototype of the dual turbine wheel wave energy converter with an overall underwater volume of 0.002 m3, the maximum harvested efficiency and harvested power at the wave excitation condition of 80 mm in amplitude and 0.3 Hz in frequency are 11.57%, and 26.4mW, respectively.

A New Strategy for Improving the Accuracy of Aircraft Positioning Using DGPS Technique in Aerial Navigation

In this paper a new mathematical algorithm is proposed to improve the accuracy of DGPS (Differential GPS) positioning using several GNSS (Global Navigation Satellites System) reference stations. The new mathematical algorithm is based on a weighting scheme for the following three criteria: weighting in function of baseline (vector) length, weighting in function of vector length error and weighting in function of the number of tracked GPS (Global Positioning System) satellites for a single baseline. The algorithm of the test method takes into account the linear combination of the weighting coefficients and relates the position errors determined for single baselines. The calculation uses a weighting scheme for three independent baselines denoted as (1A,2A,3A). The proposed research method makes it possible to determine the resultant position errors for ellipsoidal BLh coordinates of the aircraft and significantly improves the accuracy of DGPS positioning. The analysis and evaluation of the new research methodology was checked for data from two flight experiments carried out in Mielec and Dęblin. Based on the calculations performed, it was found that in the flight experiment in Mielec, due to the application of the new research methodology, DGPS positioning accuracy improved from 55 to 94% for all the BLh components. In turn, in the flight experiment in Dęblin, the accuracy of DGPS positioning improved by 63–91%. The study shows that the highest DGPS positioning accuracy is seen when using weighting criterion II, the inverse of the square of the vector length error.

Regional measurement of the hotel sector development of a tourist destination (on the example of Odessa region, Ukraine)


 
 
 In the conditions of transformation of the national economy and intensification of competition in the regional tourist markets, Ukrainian hotel business enterprises have an important problem related to increasing the efficiency of filling hotel places and attracting tourist flows. One of the ways to solve this problem is to form a management measures based on forecasting the length of stay of tourists in accommodation facilities, load levels of hotel enterprises in tourist destinations of Ukraine, planning the production of competitive hotel services that can meet the needs of foreign and domestic consumers, market demand. This problem is especially important in the context of overcoming the effects of the global COVID-19 pandemic. The purpose of the article is to identify trends in the hotel business in the tourist regions of Ukraine and outline the prospects that can be realized in post-crisis conditions. The study used a statistical method of trend analysis of the dynamics of the duration of tourists in hotels, which aims at the establishing patterns of changes in the levels of the studied indicators over time, to identify the main trend of this phenomenon. The example of Odessa region proved that the evaluation of the hotel business areas are the basis for predicting spatial and temporal relationships in the regional economy for the development of hotel business in other tourist destinations, increase their competitiveness and improve the marketing of tourist flows. According to the calculations, the annual decrease in the length of stay of tourists for the period 2021-2022 in hotel establishments of the Odessa region is forecasted. The experience of experimental verification of the proposed approach to forecasting the length of stay of tourists in hotel establishments shows that the proposed research methods can form modern tools for diagnosing the current state of regional markets for hotel services and making management decisions.
 
 

머신러닝을 이용한 누적 로그 기반 온라인 게임 봇 탐지 시스템

The online game market is steadily growing, and as such, there are active financial transactions to buy and sell game items. This paper focuses on developing an intelligent game bot detection system based on machine learning to detect game bots that collect game experience values and items illegally in online games. The proposed research method was constructed by reducing the learning data dimension using big data log information from RPG, AION games provided by KISA"s “K-Cyber Security Challenge” for intelligent game bot detection, and experiments were conducted using XgBoost and Random Forest models. Experiments show that the game bot detection performance of the proposed method with 97.7% of the results using a total of 3,761 account logs through visualization through correlation coefficient analysis of the data set accumulated with log information. The proposed research is currently applicable to the RPG (Role Playing Game) game bot detection field as a game bot detection method using machine learning technology.

Risk Evaluation Method of Import and Export Goods Based on Fuzzy Reasoning and DeepFM

At present, the inspection mode of China's import ports is generally manual based on experience, or random inspection by the document review system according to a preset random inspection ratio. In order to improve the detection rate of unqualified goods and realize the best allocation of limited human and material resources of inspection and quarantine institutions, a method composed of fuzzy reasoning, deep neural network, and factorization machine (DeepFM) was proposed for the intelligent evaluation of risk sources of imported goods. Fuzzy reasoning is used to realize the fuzzy normalization of the dataset samples, the DeepFM deep neural network is finally used for training and learning to classify and evaluate the risks of goods. Results of experimental tests on a specific customs import and export dataset verify the effectiveness of the proposed research method.

Hybrid Crypto Techniques for Secured Multimedia Big Data Content Protection System (SMBDCPS)

Most of the existing work does not ensure the optimal and secured storage maintenance of big data. This is resolved in the proposed research method name called secured multimedia big data content protection system (SMBDCPS). The proposed scheme has using AES and SHA-256 hybrid mechanism for securing the keys of encryption and decryption. This method has integrated the key value of AES and SHA-256 together to generate the new key value for increasing the security level. The main advantage of the proposed scheme has required only small storage which is computation efficient. The overall performance of the proposed scheme has carried out on MATLAB simulation environment over the medical health care datasets. The performance proves the proposed scheme has yield better results than the existing scheme.

Determination of the class of steel by small samples

Introduction. The data of the results of the inspection of steel structures are given, based on the analysis of which strength classes of structural steels are established. The goal has been solved by determining the chemical composition of metal structures and full-scale tests of the mechanical characteristics of steel structures, followed by a calculated conversion of the hardness index HB to the value of temporary tensile strength σv.
 
 Materials and methods. Strength indicators of metal structures are determined by non-destructive express method by means of a portable hardness tester of the dynamic principle of action. For the calculated determination of the breaking strength σv adopted the average lengthening coefficient kδ. By its value, the indicators of elongation and contraction are established, as well as the yield strength of the metal. Based on the calculated standard indicators of plasticity (δ, ψ) and strength (σv, σt), the complex criterion C equation is compiled. Using it, calculated the uniform elongation δр and the transverse narrowing ψр, which were used to assess the tensile strength (Sv, Sk) and fatigue (σ–1, τ–1).
 
 The chemical composition of small-sized samples in the form of metal shavings was determined by x-ray fluorescence. Additionally, the chemical composition of the steel was monitored using a scanning microscope with an attachment for determi­ning the chemical composition by energy dispersive x-ray spectroscopy.
 
 Results. The proposed research method makes it possible to conduct full-scale tests of metal structures and reduces the complexity of the selection and delivery of samples for laboratory research. The results obtained by both methods are correlated with the source data (design documentation for the object of the survey).
 
 Conclusions. An integrated method of sampling and direct measurement of hardness on site allows one to determine the chemical composition of metal structures, the grade and type of structural steel and its mechanical properties. At the same time, the scientific novelty is the given technique as a whole, which is characterized by a significant reduction in labor costs and minimization of damage to the objects under study.

Data Sharing in Biomedical Sciences: A Systematic Review of Incentives.

Background: The lack of incentives has been described as the rate-limiting step for data sharing. Currently, the evaluation of scientific productivity by academic institutions and funders has been heavily reliant upon the number of publications and citations, raising questions about the adequacy of such mechanisms to reward data generation and sharing. This article provides a systematic review of the current and proposed incentive mechanisms for researchers in biomedical sciences and discusses their strengths and weaknesses. Methods: PubMed, Web of Science, and Google Scholar were queried for original research articles, editorials, and opinion articles on incentives for data sharing. Articles were included if they discussed incentive mechanisms for data sharing, were applicable to biomedical sciences, and were written in English. Results: Although coauthorship in return for the sharing of data is common, this might be incompatible with authorship guidelines and raise concerns over the ability of secondary analysts to contest the proposed research methods or conclusions that are drawn. Data publication, citation, and altmetrics have been proposed as alternative routes to credit data generators, which could address these disadvantages. Their primary downsides are that they are not well-established, it is difficult to acquire evidence to support their implementation, and that they could be gamed or give rise to novel forms of research misconduct. Conclusions: Alternative recognition mechanisms need to be more commonly used to generate evidence on their power to stimulate data sharing, and to assess where they fall short. There is ample discussion in policy documents on alternative crediting systems to work toward Open Science, which indicates that that there is an interest in working out more elaborate metascience programs.

Separation and extraction of non-thermal effects of strong microwave electric field on dielectric properties of materials based on time modulation and cavity perturbation method

The influence of strong microwave electric field (SMEF) on the dielectric properties of materials is the result of the joint action of microwave thermal effect and microwave non-thermal effect. Generally, the thermal effect of SMEF is stronger than the non-thermal effect, which makes the non-thermal effect of SMEF difficult to detect. Moreover, it is difficult to distinguish the influence of these two factors from each other. Therefore, the formation mechanism and characteristics of the non-thermal effect of SMEF have not been elucidated so far. In this paper, a separation and extraction model of the non-thermal effect of SMEF on the dielectric property of material is proposed based on the time modulation method and cavity perturbation method. By adjusting the interaction time between SMEF and materials, reducing the influence of microwave thermal effect, and strengthening the proportion of microwave non-thermal effect, the separation and extraction of the non-thermal effect of SMEF is realized. Through the designed re-entrant coaxial cavity, the corresponding test system is constructed and the typical materials are tested. Experimental results show that the proposed research method is feasible. The research method proposed in this paper provides an effective way for the follow-up study on the formation mechanism and characteristics of the non-thermal effect of SMEF on the dielectric properties of materials.

Integral assessment of anti-corrosion materials‘ quality

In modern conditions, protective paint and varnish coatings are used everywhere to ensure the safety of metal structures and include the materials of various composition and application. The paints and varnishes market offers conventional hard and thixotropic anticorrosive coatings applied by the devices using airless spray technology. The article describes the experiment results, which consists in conducting a comparative analysis of protective materials in the framework of laboratory studies. The main physical and mechanical properties are determined. Modeling of anticorrosive coatings‘ indicators, which determine the degree of change in material properties in terms of adhesion, thickness, uniformity, flexibility and weather resistance of the treated surface of a metal structure, has been carried out. The values of the indicators were formed within the framework of the existing database, created and replenished using the real data obtained during the maintenance and repair of the existing facilities. The considered method is applicable for any number of analyzed surfaces and parameters of anticorrosive materials. As a result, it was found that the traditional coatings within the considered sufficiency indicators meet the specified requirements by 85-90=. However, the primer “Tectyl BT Coat” is the best option for using anticorrosive materials to protect the steel structures exposed to aggressive environmental influences. The sufficiency level for this primer is 92=, which determines its first place in the rating. The proposed method of experimental research and subsequent integral assessment of satisfying the requirements adequacy is versatile and is a tool that can be used when solving the problems of multi-criteria selection or ranking of a finite number of different anti-corrosion coatings or other objects.

Application the SBAS/EGNOS Corrections in UAV Positioning

The paper presents a new concept of determining the resultant position of a UAV (Unmanned Aerial Vehicle) based on individual SBAS (Satellite-Based Augmentation System) determinations from all available EGNOS (European Geostationary Navigation Overlay Service) satellites for the SPP (Single Point Positioning) code method. To achieve this, the authors propose a weighted mean model to integrate EGNOS data. The weighted model was based on the inverse of the square of the mean position error along the component axes of the BLh ellipsoidal frame. The calculations included navigation data from the EGNOS S123, S126, S136 satellites. In turn, the resultant UAV position model was determined using the Scilab v.6.0.0 software. Based on the proposed computational strategy, the mean values of the UAV BLh coordinates’ standard deviation were better than 0.2 m (e.g., 0.0000018° = 0.01″ in angular measurement). Additionally, the numerical solution used made it possible to increase the UAV’s position accuracy by about 29% for Latitude, 46% for Longitude and 72% for ellipsoidal height compared to the standard SPP positioning in the GPS receiver. It is also worth noting that the standard deviation of the UAV position calculated from the weighted mean model improved by about 21 ÷ 50% compared to the arithmetic mean model’s solution. It can be concluded that the proposed research method allows for a significant improvement in the accuracy of UAV positioning with the use of EGNOS augmentation systems.

Stability of a nonlinear discrete-time model of information dissemination under stochastic perturbations

A nonlinear discrete-time model of information dissemination is considered and conditions for existence of a positive equilibrium of this system are obtained. It is shown that asymptotically stable positive equilibrium saves his stability under the influence of stochastic perturbations of the different types: small multiplicative perturbations, quickly fading multiplicative perturbations and quickly fading additive perturbations. Stability conditions are obtained using Lyapunov functions, are formulated in the terms of linear matrix inequalities (LMIs) and are illustrated by numerical simulations of solutions of the considered system. As an unsolved problem it is proposed to investigate the situation when stochastic perturbations fade on the infinity, but not very quickly. The proposed research method can be applied to investigate many other nonlinear mathematical models in various applications.

Accurate and reliable detection of DDoS attacks based on ARIMA-SWGARCH model

DDoS attack detection is the process of finding the attacks happening on a network that causes continues packet drops or losses. Accurate detection of DDoS is the most complex task due to varying network traffic traces and patterns. This is resolved in our previous work by introducing the method namely bandwidth flooding attack detection method. However, this method failed to perform better with varying traffic patterns and traces. This is resolved in this research work by introducing the method namely hybrid ARIMA-SWGARCH model whose main goal is to detection DDoS attacks by analysing the varying measured network traffic. Here initially normalisation of measure network patterns is done by using the Box-Cox transformation. And then the white test is performed to finding the heteroscedasticity characteristics of time series of traffic patterns. And then the hybrid ARIMA-SWAGARCH model is applied to efficiently detect the DDoS attacks happening on the network. The overall evaluation of this method is conducted in the MATLAB simulation environment from which it is proved that the proposed research method can ensure the optimal and reliable detection of DDoS attacks happening on the network.