Open Application Programming Interface Research Articles

Optimal design of steel exoskeleton for the retrofitting of RC buildings via genetic algorithm

In recent decades, steel exoskeletons have gathered significant attention as a seismic retrofitting technique for existing structures. The design methods proposed so far are focused on the identification of the system's overall parameters through simplified models. Although these methodologies provide helpful guidance at the preliminary design stage, they do not consider aspects such as the distribution of the exoskeletons and sizing of their components. To overcome these limitations, an optimization process based on the Genetic Algorithm is proposed in this paper to identify the optimal exoskeleton number and spatial arrangement, and to determine the optimal size of their constituent elements. The algorithm aims to minimize the weight of the retrofit solution while keeping the whole existing structure in the elastic field and ensuring the structural verification of the exoskeleton's elements. The analyses have been conducted using a finite-element code with an Open Application Programming Interface, which allows the models to be handled through automatic routines. The proposed optimization tool has been applied to several case studies, considering two different layouts for the exoskeletons. Finally, the effectiveness of the retrofit method has been demonstrated, and the proposed optimization tool has been able to significantly reduce the weight and cost of the intervention.

Development of a BIM Platform for the Design of Single-Story Steel Structure Factories

Traditional design methods for single-story steel structure factories are characterized by low levels of digitalization and high error rates. To deal with these problems, a building information modeling (BIM) platform for the design of single-story steel structure factories was developed in this paper, which aimed to improve the design process for such structures. Firstly, the components of the factory were categorized, and the Revit API was employed to automate the generation of the BIM model. Load applications and combinations were then established using the Revit API, which relied on a set of predefined parameters. Secondly, this paper proposed the creation of a dedicated database for data exchange between BIM software and finite element analysis software. Additionally, the SAP2000 Open Application Programming Interface (OAPI) was employed for the automated construction and analysis of the SAP2000 structural model. Finally, the innovative use of Dynamo–Revit API hybrid programming allowed for the visualization of internal forces directly within the Revit environment, significantly diminishing the dependency on standalone FEA software. The application results obtained on a project demonstrated that the developed platform markedly improves the efficiency of design single-story steel structure factories and ensures the accuracy of the structural analysis. This confirms that the developed platform can transform the traditional design process by integrating advanced digital tools, thereby providing a novel approach to the design of single-story steel structure factories.

THE URGENCY OF STANDARDIZING THE OPEN APPLICATION PROGRAMMING INTERFACE IN IMPLEMENTATION OF OPEN BANKING FOR CUSTOMER PROTECTION

Open banking with Open Application Programming Interface (open API) technology is an initiative aimed at streamlining the payment system in Indonesia. The open API allows banks to integrate their systems with digital financial service providers (fintech) and bold trade (e-commerce) providers by disclosing customer transaction data. This study investigates the urgency of open API standardization in implementing open banking in Indonesia. This study uses a normative juridical approach to secondary data. The data includes primary, secondary, and tertiary legal materials. In addition, it also uses qualitative normative data analysis methods. It was concluded that before the National Open API Payment Standard (SNAP) stipulation, the process of sharing data between banks and fintech and/or e-commerce still needed to be standardized but was only based on an agreement between the parties. Banking in Indonesia has various open API standards that can affect the protection of customer data. According to the Financial Services Authority Regulation Number 12/POJK.03/2018, the relationship between banks, fintech, and/or e-commerce in providing digital banking services based on agreements between parties needs to be stronger. OJK is indeed present as a supervisory agency. However, the parties will eventually come back to a deal between themselves. Unlike the Regulations of the Financial Services Authority, the Regulations of the Members of the Board of Governors, which form the legal basis for SNAP, provide standards that must be complied with by both service providers and service users. However, implementing SNAP-based open APIs still requires personal data protection regulations.

Analysis of the global level of the banking system readiness for the implementation of the open banking concept.

This research main goal is to give an a vision of current state of Electronic Banking with analysis of the modern state of Open Banking and Open application programming interface (API) initiative. The tectonic shifts in regulation from Central banks and governments digitalisation strategy required from financial institutions to became more technologically ready to comply with licensing. This face banks and financial institutions with a new type of technological challenges which recently wasn't part of regular banks routine and now banks should adopt. Different regions and countries have own regulations and strategies how banking and payments sector should adopt. For example, in Europe each bank must apply a numbers of new software services which was never available for third party companies before. It gives a boost to overall banking and payments software industry to meet the demand of the market. Many other developed countries also have own initiatives for the banking sector similar to PSD2 but with own perspective, timing for implementation and features lists. Standardization and unifications of API’s and messaging between financial organization represented in ISO 20022 and main browsers integrated payments API also a huge step forward for integrators, service providers and software development teams. The results of this research represent current stage of readiness of banking and payment industry to new regulations requirements. Banks and Financial institutions must dramatically change their current business model and initiate completely new departments which makes bank more open from technological point of as never before. World wide size companies and organizations promote new financial messaging standards and API implementation on browser levels. With all of this, banks will become more “digital friendly” and new products and services from third party companies, in collaboration with banks, will fill in the market. Inside this research discovered different aspects of the current problems which banks usually faced during implementation and conclusions what they need to expect when such projects is initiated. The information inside this research gives readers detailed information about the most important aspects of the technical side of implementation and review of new standards and tools.

LAMPPrimerBank, a manually curated database of experimentally validated loop-mediated isothermal amplification primers for detection of respiratory pathogens.

The emergence of coronavirus disease 2019 (COVID-19) has once again affirmed the significant threat of respiratory infections to global public health and the utmost importance of prompt diagnosis in managing and mitigating any pandemic. The nucleic acid amplification test (NAAT) is the primary detection method for most pathogens. Loop-mediated isothermal amplification (LAMP) is a rapid, simple, sensitive, and specific epitome of isothermal NAAT performed using a set of four to six primers. Primer design is a fundamental step in LAMP assays, with several complexities and experimental screening requirements. To address this challenge, an online database is presented here. Its workflow comprises three steps: literature aggregation, data curation, and database and website implementation. LAMPPrimerBank ( https://lampprimerbank.mathematik.uni-marburg.de ) is a manually curated database dedicated to experimentally validated LAMP primers, their peculiarities of assays, and accompanying literature, with a primary emphasis on respiratory pathogens. LAMPPrimerBank, with its user-friendly web interface and an open application programming interface, enables the accelerated and facile exploration, comparison, and exportation of LAMP primer sequences and their respective information from the massively scattered literature. LAMPPrimerBank currently comprises LAMP primers for diagnosing viral, bacterial, and fungal respiratory pathogens. Additionally, to address the challenge of false-positive results generated by nonspecific amplifications, LAMPPrimerBank computationally predicted and visualized the sizes of LAMP products for recorded primer sets in the database. LAMPPrimerBank, as a pioneering database in the rapidly expanding field of isothermal NAAT, endeavors to confront the two challenges of the LAMP: primer design and discrimination of false-positive results.

The use of professional audio external USB sound cards for building acoustics measurements

CSIRO purchased an open application programming interface for hardware with an ethernet connection from a major acoustical instrument manufacturer. Using this interface, the author developed software for fractional octave band filtering with linear and exponential averaging. He then extended this software to automatically measure reverberation time. Fast Fourier Transform and Stepped Sine software was also developed. He then realized that CSIRO also owned two professional audio external USB sound cards. One of these had eight analogue inputs and ten analogue outputs. The other had two analogue inputs and two analogue outputs. Both could supply 48 V phantom power on their analogue inputs. It is possible to purchase phantom power preamplifiers for professional measurement microphones, but CSIRO decided to purchase phantom power to IEPE pre-amplifier adaptors. This enabled the use of professional pre-polarized microphones with IEPE microphone preamplifiers and accelerometers with built-in IEPE preamplifiers. CSIRO also had external USB hardware from another acoustical instrument manufacturer. Upon opening this instrument, it consisted of a professional audio external USB sound card and an IEPE front end for the two analogue input channels. The author decided to produce a version of his software that could be used with these three external USB sound cards.

Reconfigure and evaluate consumer satisfaction for Open API in advancing FinTech

With the rise of FinTech, Open API (application programming interface) is essential in advancing FinTech applications in the future, but its customer satisfaction is a concern. Therefore, this study uses the technology acceptance model (TAM) to reconfigure and evaluate customer satisfaction of Open API in advancing FinTech by applying extended variables. This study initially applies the decision making trial and evaluation laboratory (DEMATEL) approach with the analytic network process (ANP) technique to reconfigure the modified TAM. Finally, we use Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) analysis to evaluate customer satisfaction for examining the acceptance of Open API.The results of DANP point out ‘perceived privacy’ (0.179), ‘customer use intention’ (0.158) and ‘perceived usefulness’ (0.147) are the three most influential variables for Open API in advancing FinTech. Furthermore, VIKOR analysis indicates online security or cryptocurrency trading (0.536) performs best in which Open API can satisfy customers in advancing FinTech and online banking (0.438) has the most space for improvement. This study also indicates that privacy protection plays a very important role in consumer satisfaction of Open API. The influences of the variables demonstrate that Open API compared to conventional APIs, is more convenient and relatively beneficial in advancing FinTech.

Open Geospatial Data Integration in Game Engine for Urban Digital Twin Applications

Increasing interest has recently been shown towards the digital twins of cities. These urban digital twins utilize 3D city models together with other data sources, such as open data, which can be accessed, e.g., through application programming interfaces (APIs). A large amount of open geospatial data is already available through various open data portals and APIs, such as REST and MQTT. Game engines, on the other hand, have been seen as highly potential platforms for urban digital twins, with recent development increasing the useability of geospatial data in game engines. This study explores the possibilities of game engines for urban digital twins by integrating and visualizing API-based open geospatial datasets with a 3D city model data set in a game engine environment. Three open data integration approaches are demonstrated, and the performance of these approaches is tested for urban digital twins. Based on the results, modern game engines offer a great platform for creating urban digital twin applications; however, some problems and limitations must be overcome before the use of geospatial data in game engines becomes feasible on a larger scale.

Automated minimum-weight sizing design framework for tall self-standing modular buildings subjected to multiple performance constraints under static and dynamic wind loads

In recent decades, the shortage of affordable housing has become an endemic issue in many cities worldwide due to the ongoing urban population growth. Against this backdrop, volumetric steel modular building systems (MBSs) are becoming an increasingly compelling solution to the above challenge owing to their rapid construction speed and reduced upfront costs. Notwithstanding their success in low- to mid-rise projects, these assembled structures generally rely on a separate lateral load-resisting system (LLRS) for lateral stiffness and resistance to increased wind loads as the building altitude increases. However, additional LLRSs require on-site construction, thereby compromising the productivity boost offered by the MBSs. To this end, this paper proposes a novel optimisation-driven sizing design framework for tall self-standing modular buildings subjected to concurrent drift, floor acceleration, and member strength constraints under static and dynamic wind loads. A computationally efficient solution strategy is devised to facilitate a meaningful sizing solution by decomposing the constrained discrete sizing problem into a convex serviceability limit stage (SLS) and a non-convex ultimate limit stage (ULS), which can be then solved using preferred local and global optimisation methods, separately. The framework is implemented by integrating SAP2000 (for structural analysis) and MATLAB (for optimisation) through SAP2000′s open Application Programming Interface (API), and demonstrated using a 15-storey self-standing steel modular building exposed to three different levels of wind intensity. A comprehensive performance assessment is conducted on the optimally designed case-study building to investigate its elastic instability behaviour, geometric nonlinear effects on wind-induced response, and impacts of global sway imperfections on member utilisation ratios under wind effects. It is concluded that tall self-standing modular buildings can be achieved economically using ordinary corner-supported modules without ad hoc structural provisions, while consuming steel at similar rates to conventional building structural systems. Furthermore, the proposed sizing framework and solution strategy have proven to be useful design tools for reconciling the structural resilience and material efficiency in wind-sensitive self-standing modular buildings.

Thai Commercial Banks on Twitter

Twitter is a social media (SM) platform that rapidly generates electronic word of mouth (e-WOM). Marketer-generated content (MGC) is controllable and could enhance the positive e-WOM. Hence, in this study, the author examined the characteristics of MGC and reactions from followers based on Thai banks' Twitter accounts. The author collected a total of 10,000 tweets from nine banks in Thailand—both high- and low-performing banks. The author conducted research with natural language processing (NLP) to uncover intents using an open application programming interface (API). The author used three data-mining techniques—association, clustering, and classification. The Twitter strategies of banks with high and low performances are quite similar. The sentiment is the intent type that dominates Thai banks' intent strategies. Several intents could be combined to draw e-WOM in terms of favorites (FAV) and retweets (RT). Six intent patterns (clusters) were extracted. Some of these clusters are classifiers for FAV and non-FAV tweets. This study guides the application of data mining in business research and suggests MGC strategies for marketers.

ANN-based optimization framework for the design of wind load resisting system of tall buildings

Conventional design methodology for tall buildings is a time-consuming and repetitive trial-and-error procedure with a limited probability of yielding an optimal solution that satisfies architectural, structural and serviceability requirements. Tall buildings are typically slender structures and mainly depend on lateral load resisting systems (LLRS) (e.g., shear walls, cores, and bracing systems) to withstand the lateral load of earthquakes and wind events, where a minor change in their layout, size, or shape will affect the cost tremendously. Consequently, an automated layout optimization procedure will result in a more economic and sustainable design. This paper develops a novel structure-wind optimization framework (SWOF) to find the optimal shear wall layout of tall buildings subjected to wind loads. SWOF is considered a genetic algorithmbased framework that uses an Artificial Neural Network (ANN) surrogate model to evaluate its constraints and objective function. These surrogate models rely on a training dataset prepared using the Finite Element Method (FEM), which has been created using an open application program interface (OAPI) MATLAB code. An optimization problem; is presented to show SWOF's efficiency. SWOF showed significant capabilities in recognizing load direction, critical load cases and inertia concepts without explicitly defining them through the developed code.

Teaching-learning-based optimization of unbraced steel frames with semi-rigid connections and column bases

The teaching-learning optimization (TLBO) technique is applied to unbraced steel frames with semi-rigid beam-to-column connections and semi-rigid column-to-base connections. The algorithm for design produces optimized steel frames by choosing appropriate sections from a set of standard steel sections. These standard steel sections, including wide-flange profiles (W), are provided by the American Institute of Steel Construction (AISC). The first example is subjected to the displacement, inter-story drift, and stress constraints of AISC-Load and Resistance Factor Design (LRFD) regulations. In addition, the displacement and stress limitations of the AISC-Allowable Stress Design (ASD) standard and the geometric (size) requirements are implemented in the last two examples. In finite element analysis, optimal designs of three alternative unbraced frames are performed with and without semi-rigid beam-to-column and column-to-base plate connections. All optimization techniques are encoded in the high-level programming language C# version 17.4.4 to integrate with SAP2000 version 22's Open Application Programming Interface (OAPI). The analysis results indicate that the rigidity of connections is determining parameter in the weight optimization of unbraced steel frames.

Evaluating robustness of a generalized linear model when applied to electronic health record data accessed using an Open API.

The Integrated Clinical and Environmental Exposures Service (ICEES) provides open regulatory-compliant access to clinical data, including electronic health record data, that have been integrated with environmental exposures data. While ICEES has been validated in the context of an asthma use case and several other use cases, the regulatory constraints on the ICEES open application programming interface (OpenAPI) result in data loss when using the service for multivariate analysis. In this study, we investigated the robustness of the ICEES OpenAPI through a comparative analysis, in which we applied a generalized linear model (GLM) to the OpenAPI data and the constraint-free source data to examine factors predictive of asthma exacerbations. Consistent with previous studies, we found that the main predictors identified by both analyses were sex, prednisone, race, obesity, and airborne particulate exposure. Comparison of GLM model fit revealed that data loss impacts model quality, but only with select interaction terms. We conclude that the ICEES OpenAPI supports multivariate analysis, albeit with potential data loss that users should be aware of.

Integration of Excel VBA with professional software for the structural analysis and design of civil structures

AbstractA feasible combined approach between structural analysis program (SAP) 2000 and Excel software is proposed in this article to develop customized numerical tools for the analysis of civil engineering structures. For such scope, the Open Application Programming Interface from SAP 2000 software is linked to the Visual Basic for Application (VBA) environment embedded within Excel. Three computer applications resembling industrial situations related to size optimization of trusses, soil−structure interaction in buildings, and automatic design of reinforced concrete slabs are presented. As the tools are parameterized, students can observe the effects of the various parameters on the output response of the structures because geometry, loading, and material properties can be easily varied. As the main concern is the educational aspect, the novelty of this research is to present the proposed combined approach in a stepwise manner with explained codes. The source codes of the developed tools are made freely available so that the applicants can modify them according to their priorities. The tools present a friendly user interface that made them attractive to use in daily design tasks at the office, but certainly, they are the result of the integration of student knowledge as part of a bachelor's dissertation in an undergraduate civil engineering educational program. The tools have been preliminarily introduced into a reinforced concrete course at the Federal University of Rio Grande do Sul (Brazil), searching for a better understanding of theoretical concepts, while integrating technology into the classroom and reducing time constraints as new configurations for the studied structures can be easily explored during class.

Using open infrastructures for alternative quality assessment of research outputs

Decision-makers are not able to follow all the changes in the open science (OS) on the policy level as fast as needed. This affects the way how research outputs are assessed. Due to this, not all research outputs are recognised, and there are no mechanisms to trace and appraise all outputs. This paper presents open infrastructures and supporting methods which are capable of overcoming these deficiencies. The Scopus and Web of Science citation indexes have a significant impact on the quality assessment of research outputs, especially when it comes to research promotion and career development. At the same time, researchers produce scientific outputs that cannot be assessed using traditional approaches (Pravilnik o sticanju istraživačkih i naučnih zvanja, 2020).Open infrastructures can support research communities by providing methods which are verifiable and available for integration with institutional infrastructures (such as repositories and CRIS systems). There are also some services that do not fall into the category of open infrastructure but support the concept by providing technical solutions that can be open access. Also, there is a tendency to make open infrastructures as compliant with OS principles as possible. Some of these infrastructures implement other closely related principles such as the FAIR data principles (GO FAIR initiative, 2022). When an institutional infrastructure adopts these principles and integrates services provided by open infrastructures, then benefits are seen by both researches and decision-makers. Dimensions is an alternative to and more open and inclusive than a traditional citation database. Also, Dimensions is integrated with other infrastructures that embrace the concept of openness (Dimensions, 2019). Thanks to functionalities available through various open application programming interfaces (APIs), Dimensions has played an important part in technical adoption of OS principles in Serbia.Alternative metrics like Altmetric could serve as another solution (Altmetric, 2018). Like Dimensons, Altmetric is not an open infrastructure, but it contributes to open infrastructures through open APIs that can track the impact of research outputs across the Internet. The main focus is on tracking research papers on social media (Facebook, Twitter) and multimedia platforms (YouTube) or their mentions in Internet communities. An important issue for each country is how to assess research outputs in humanities. Knowing that research outputs in this area focus mainly on locally relevant topics, it is difficult to track the impact of such results by relying on traditional citation databases.Unlike Dimensions and Altmetric, OpenCitations is an open infrastructure which fully embraces the concept of OS and is compliant with the FAIR data principles inasmuch as the data it collects are findable, accessible, interoperable, and re-usable. Furthermore, OpenCitations has adopted the Principles of Open Scholarly Infrastructure (POSI) (Bilder, Lin and Neylon, 2020) and its infrastructure has been upgraded with a system that provides persistent identifiers (PIDs) (Peroni, Shotton, 2019). All these solutions are mostly dealing with citations. However, there are research outputs like peerreview reports and editorial work that cannot be assessed only by the number of citations and require other metrics. Publons is far from an open infrastructure but at least provides some open access services for researchers. More relevant in this context is the recently launched OpenAlex, an open infrastructure that can serve as a search engine, research output monitor, and assessment tool. OpenAlex aggregates data from sources like Crossref and ORCID and seeks to present data in a standardised way

Optimum sizing design of steel frame structures through maximum energy dissipation of friction dampers under seismic excitations

This paper focuses on optimum sizing design of steel frame structures equipped with friction dampers (FDs) in order to prevent the vulnerable effect of an earthquake. The fundamental concept is to maximize the energy dissipation of implemented FDs under different seismic excitations. The FDs utilized as passive energy dissipation devices in a steel structure increase the energy dissipation capacity of the structure by decreasing the seismic demand during an earthquake. In this context, the Pall friction dampers (PFDs) are implemented as diagonal damped brace members in investigated structures. Three different earthquake records (Kobe, Kocaeli-Duzce, Erzincan) are utilized to acquire nonlinear dynamic responses of the steel frame structures through time-history analyses. The open application programming interface (OAPI) functions are used to integrate a finite element modelling based structural analysis program, SAP2000, with a design optimization algorithm encoded in MATLAB for achieving the exact structural behaviours by synchronously data transferring. As an optimizer, one of the recent nature-inspired metaheuristic techniques, so-called Grey Wolf (GW) algorithm is used. Initially, under effect of seismic excitations, the steel frame structures are optimally sized for attaining minimum design weights without implementing the PFD elements by subjecting only strength, displacement, drift, and geometric structural design constraints taken from AISC-LRFD practice code provisions. Afterward, in order for optimally modelling the PFD elements, the frames are equipped with PFDs to calculate optimum yield strengths that is defined as slip load of a PFD. To do so, the GW algorithm ensures the maximizing of the dissipated energy and controls the yield strengths between the stories since the shear force due to the earthquake increases towards the base of the structure. Eventually, the provisions-based sizing design optimizations of the steel frame structures equipped with optimally modelled PFD elements are conducted under seismic excitations for conclusive evaluations.

Structural damage identification in thin-shell structures using a new technique combining finite element model updating and improved Cuckoo search algorithm

In this paper, the powerful advantages of Open Application Programming Interface (OAPI) in SAP2000 software, known as an excellent tool to solve structural engineering problems, are exploited to establish a new technique of finite element (FE) model updating. This technique is based on the development of a successful sub-program, which can link programming language of MATLAB with SAP2000 through the OAPI library. Therefore, the two-way data exchange between MATLAB and SAP2000 can be continuously secured, and the process of modification of the initial FE model in SAP2000 is implemented by coding instead of using the standard point-and-click procedure in SAP2000′s interface. The damage identification process in structures is then done using an optimization algorithm, named a modified version Cuckoo search (CS) algorithm, and called new balance of Cuckoo search (NB-CS). The key factor in NB-CS is to create a balance between two values: the best global and the worst global. To achieve this balance, NB-CS proposes two main contributions. The first is based on the modification of the concept of a random walk whose step lengths obey Lévy distribution. Whereas, the second is to establish a new balance vector, which is presented based on the global optimal and the worse optimal exploited at each iteration. This vector is combined with each step length to establish a new movement strategy, which is more flexible and more intelligent than that of the original CS. To examine NB-CS's reliability, the first 23 classical benchmark functions are selected to illustrate the convergence rate and level of accuracy of NB-CS compared to the original CS. To authenticate the efficiency of the proposed method, three models, including square shell structure, parabolic domes, and partial sphere shell structure, are investigated for different damage cases. NB-CS is then employed to minimize the objective function with design variables related to the extent and location of damage in thin-shell elements in the structures. The statistical results show the feasible performance of NB-CS in a widespread class of optimization problems and its great potential for application to structural damage identification.

A new metaheuristic optimization based on K-means clustering algorithm and its application to structural damage identification

This paper develops a new metaheuristic optimization algorithm named K-means Optimizer (KO) to solve a wide range of optimization problems from numerical functions to real-design challenges. First, the centroid vectors of clustering regions are established at each iteration using K-means algorithm, then KO proposes two movement strategies to create a balance between the ability of exploitation and exploration. The decision on the movement strategy for exploration or exploitation at each iteration depends on a parameter that will be designed to recognize if each search agent is too long in the region visited with no self-improvement. To demonstrate the effectiveness and reliability of KO, twenty-three classical benchmark functions, CEC2005 and CEC2014 benchmark functions, are employed as a first example and compared with other algorithms. Then, three well-known engineering problems are also considered and their results are compared to the results obtained by the other algorithms. Finally, KO is applied to structural damage identification (SDI) problem of a complex 3D concrete structure including seven stories building having a 25.2 m total height. For this purpose, SAP2000 is used to solve the finite element (FE) model of this structure. Then, for the first time, we successfully developed a sub-program that allows two-way data exchange between SAP2000 and MATLAB through the Open Application Programming Interface (OAPI) library to update the FE model. From the results, we found that KO has the best performance for the considered benchmark functions based on the Wilcoxon rank-sum test and Friedman ranking test. The results obtained in this work have proved the effectiveness and reliability of KO in solving optimization problems, especially for SDI. Source codes of KO is publicly available at http://goldensolutionrs.com/codes.html.

How Safe You Are on Social Networks?

Millions of individuals use Twitter, one of the most prominent social media sites, to exchange information, broadcast tweets, and follow other users. Twitter being an open application programming interface is vulnerable to attacks from fake accounts. Fake accounts are primarily used for advertising and marketing, defamation of an individual, consumer data acquisition, increasing fake blog or website traffic, sharing wrong information, online fraud, and control. Fake accounts are disruptive to both users and service providers, thus it's critical to recognize and filter out such information on social media. This paper presents a technique for detecting fake Twitter accounts using the feature set mapped to Twitter’s rules and policies to flag suspicious accounts. To choose the apt subset of features from the original feature space, feature selection techniques such as information gain and correlation were used. Users have been classified using a Logistic Regression classifier with the detection accuracy of 93.5 percent after being trained on the data of about 1,00,000 Twitter users. Furthermore, an algorithm for classifying suspicious users as Fake profiles has been presented. The results of the experiments show that the suggested model outperforms competitive state-of-the-art research in the majority of circumstances.

Size and Shape Optimization of a Guyed Mast Structure under Wind, Ice and Seismic Loading

This paper discusses the size and shape optimization of a guyed radio mast for radiocommunications. The considered structure represents a widely industrial solution due to the recent spread of 5G and 6G mobile networks. The guyed radio mast was modeled with the finite element software SAP2000 and optimized through a genetic optimization algorithm (GA). The optimization exploits the open application programming interfaces (OAPI) SAP2000-Matlab. Static and dynamic analyses were carried out to provide realistic design scenarios of the mast structure. The authors considered the action of wind, ice, and seismic loads as variable loads. A parametric study on the most critical design variables includes several optimization scenarios to minimize the structure’s total self-weight by varying the most relevant parameters selected by a preliminary sensitivity analysis. In conclusion, final design considerations are discussed by highlighting the best optimization scenario in terms of the objective function and the number of parameters involved in the analysis.