Software Functions Research Articles

A study of teeth generation for arbitrary-shaped sprockets

ABSTRACT In the noncircular sprocket designing process, drawing the teeth cannot be automatically performed using any function in the drawing software, and it needs complicated manual operations and adjustments. The accuracy and time waste are big problems here. This paper proposes a procedure to automatically generate a complete 3D sprocket design from a set of sprocket pitch coordinates. Japanese standard tooth profile (JIS B 1801) is used as an example model in the procedure development. First, the tooth profile equation is derived using the theory of gearing in a particular coordinate system. Subsequently, the coordinate transformation matrix is built to attach the tooth profile on every sprocket pitch coordinate in the correct direction, remove some coordinates surpassing the outer diameter limit, and build the complete 3D sprocket profile. The proposed procedure can be implemented into programming languages with the sprocket pitch coordinate file as the input and the set of sprocket teeth coordinate as the output. With the proposed procedure, a 3D design of any shape sprocket can be generated quickly and accurately.

Comparative investigations of Ag/H2O nanofluid and Ag-CuO/H2O hybrid nanofluid with Darcy-Forchheimer flow over a curved surface

Abstract Nanofluid performed well and produced good results in heat transport phenomena, attracting scientists to suspend other combinations of nanoparticles, called “hybrid nanofluid. Hybrid nanofluids are superior than nanofluids due to their thermal capabilities and emerging benefits that contribute to the boost in the rate of heat transmission. Applications for these nanoparticles, including sophisticated lubricants, are increasing in the fields of bioengineering and electricity. The main prospective of this research is to inquire about the water-based dual nature nanofluid stream numerical simulation through the irregular stretched sheet with heat transfer. In this perspective, silver with base fluid water is used as nanoparticles for nanofluid, and for making hybrid nanofluid, copper oxide and silver particles are used with water-based fluid. Modified Fourier and Fick’s model for heat flux utilized the above phenomenon and observed the heat and mass transport. Similarity variables are needed to transform the partial differential equations into associated nonlinear ordinary differential equations, which are then computationally resolved by the technique of bvp4c which is a built-in function in MATLAB mathematical software. Based on the concurrent approximations, reformations are performed to determine the impact of various quantities on flow variables. The predicted outcomes are depicted in velocity, temperature, and concentration profiles through graphical depiction. The factors indicate that the hybrid nanofluid is more powerful in the transfer of heat than a basic nanofluid because of its superior thermal characteristics. The velocity profile decays for the increasing values of Darcy-Forchheimer parameter. The thermal profile increases for the higher magnitude of Darcy-Forchheimer parameter. The velocity distribution profile increases for the higher values of curvature parameter, while the thermal profile decreases. This unique work might benefit nanotechnology and related nanocomponents. This safe size-controlled biosynthesis of Ag and CuO nanoparticles has resulted in a low-cost nanotechnology that may be used in a variety of applications. Biosynthesized Ag and CuO particles have been used successfully in a variety of applications, including biomedical, antibacterial agents, biological, food safety, and biosensing, to mention a few.

Exploration of entropy analysis and viscous dissipation on radially convective flow of (Cu‐Al2O3:H2O) hybrid nanofluid over a stretching disk

AbstractThe current research work deals with the impact of suction/injection on the thermally radiating convective flow generated by a nonlinear stretched disk. The energy equation is addressed by the presence of thermal radiation and the energy dissipative function. This work was carried out with the help of the Das and Tiwari (single‐phase nanofluid) models and the Maxwell Garnett and Brinkman nanofluid models for the analysis of entropy generation. In the present model, nanoparticles of copper (Cu) and alumina (Al2O3) are being used with water (H2O) as the base fluid. The governing nonlinear partial differential equations are transformed into ordinary differential equations with the assistance of appropriate similarity variables. These transformed equations are then solved using the bvp4c function, a built‐in function in MATLAB software. The investigation examines the influence of various factors on the velocity and temperature fields, entropy generation, skin friction, and heat transfer rate. The findings show that suction decreases velocity and temperature by 6.59%, while injection has the opposite effect. Viscous dissipation increases velocity by 5.13% and temperature by 17.94% in hybrid nanofluids. Higher Prandtl numbers reduce velocity and temperature by 6% in nanofluids but boost them by 5.45% and 18.81% in hybrid nanofluids with radiation growth. As volume fraction rises, Al2O3/H2O nanofluid speed falls by 5.37%, but Cu‐Al2O3/H2O hybrid nanofluid temperature increases by 13.09% and surface drag force increases by 12%. The entropy of the hybrid nanofluid increases by 5.84%, 8.19%, and 14.04% with Eckert number, suction, and Prandtl number but decreases by 10.08% with temperature difference. The Nusselt number of nanofluid decreases by 10.58% and 12.40% with Eckert number and radiation, but hybrid particles increase it by 10.31% with intensified Prandtl number. These findings offer valuable insights for potential applications of hybrid nanofluids in heat transfer and cooling systems.

Numerical analysis of impingement characteristics of supercooled large droplets on the surface of a rotating hood

The authors of this study numerically analyze the characteristics of impingement of supercooled large droplets on the surface of the rotating hood of an aircraft. We use the secondary development function of Fluent software to first compare the prevalent models of impinging supercooled large droplets and then develop a modified model to numerically simulate their characteristics of impingement on the surface of a rotating hood in order to examine the effects of the diameter of the droplets, the speed of rotation, and the corresponding velocity of inflow on them. The results showed that the efficiency of the loss of mass of the droplets caused by their splashing and rebounding was low on the top of the cone, while the efficiency of local droplet collection was the highest. The efficiency of mass loss quickly increased, while that of droplet collection sharply decreased in the area of transition from the top to the side. The efficiencies of mass loss and droplet collection were nearly constant on the side of the cone, while that of the latter decreased to zero on the tail of the cone. When the median volumetric diameter of the droplets was increased from 79 to 250 µm, the efficiency of the loss of mass increased by about 15% on the side of the cone, but that of local droplet collection changed only slightly. The efficiency of the loss of mass decreased by about 20%, while that of local droplet collection increased by about 2.6% on the top of the cone under this condition. When the speed of rotation was increased from 1200 to 4300 r/min and the corresponding velocity of inflow was increased from 30 to 140 m/s, the efficiency of mass loss increased by about 15% on the side of the cone, while that of local droplet collection changed little. The efficiency of mass loss on the top of the cone decreased by about 37.5%, while that of local droplet collection increased by about 8% in this case.

Evaluation of the effectiveness of the functioning of production and consumption waste management systems in the Arctic regions of Russia based on Data Envelopment Analysis

Subject of research: is the functioning of the production and consumption waste management systems of the regions (RSOO) of the Arctic zone of the Russian Federation for the period from 2016 to 2020.
 Purpose of research: is to quantify production efficiency production efficiency coefficients (СEP) of the functioning of these systems based on shell data analysis (Data Envelopment Analysis, DEA). This method is based on the repeated application of linear programming to a set of input and output indicators recorded by the current system of state statistics and characterizing the activities of sets of similar specialized enterprises in the regions for waste management (production facility, software).
 Methods and objects of research: to assess the СEP of the software functioning by the DEA method, the "time slice" and "time window" schemes were used. Based on the calculated СEP values, stable subgroups of software with low, medium and high СEP values were identified. For insufficiently effective software, target values of input indicators were calculated, the achievement of which allows them to maximize СEP values. At the same time, for these software, a recommendatory choice of a leader/landmark object was carried out, which can be considered as a carrier of best practices and successful experience in organizing work, which is relevant for the development of the RSOO.
 Main results of research: the formed classification of RSOO was compared with the normative indicators of waste processing given in the State Program of the Russian Federation "Environmental Protection" for 20122020.

Heat transfer analysis of Maxwell tri-hybridized nanofluid through Riga wedge with fuzzy volume fraction

This contribution aims to optimize nonlinear thermal flow for Darcy-Forchheimer Maxwell fuzzy left( {{text{Al}}_{{2}} {text{O}}_{{3}} + {text{Cu }} + {text{TiO}}_{{2}} {text{/EO}}} right) tri-hybrid nanofluid flow across a Riga wedge in the context of boundary slip. Three types of nanomaterials, {text{Al}}_{{2}} {text{O}}_{{3}} , Cu and {text{TiO}}_{2} have been mixed into the basic fluid known as engine oil. Thermal properties with the effects of porous surface and nonlinear convection have been established for the particular combination left( {{text{Al}}_{{2}} {text{O}}_{{3}} + {text{Cu}} + {text{TiO}}_{{2}} {text{/EO}}} right){.} Applying a set of appropriate variables, the set of equations that evaluated the energy and flow equations was transferred to the dimensionless form. For numerical computing, the MATLAB software's bvp4c function is used. The graphical display is used to demonstrate the influence of several influential parameters. It has been observed that flow rate decay with expansion in porosity parameter and nanoparticles volumetric fractions. In contrast, it rises with wedge angle, Grashof numbers, Darcy-Forchheimer, nonlinear Grashof numbers, and Maxwell fluid parameter. Thermal profiles increase with progress in the heat source, nanoparticles volumetric fractions, viscous dissipation, and nonlinear thermal radiation. The percentage increases in drag force for ternary hybrid nanofluid are 13.2 and 8.44 when the Modified Hartmann number takes input in the range 0.1 le {text{Mh}} le 0.3 and wedge angle parameters 0.1 le m le 0.3. For fuzzy analysis, dimensionless ODEs transformed into fuzzy differential equations and employed symmetrical triangular fuzzy numbers (TFNs). The TFN makes a triangular membership function (M.F.) that describes the fuzziness and comparison. This study compared nanofluids, hybrid nanofluids, and ternary nanofluids through triangular M.F. The boundary layer flow caused by a wedge surface plays a crucial role in heat exchanger systems and geothermal.

Development and validation of web software to support prenatal care management

Objective To describe the development and validation process of a web software to support the management of prenatal care. Methods Technological development research, carried out between March and August 2022, based on principles and techniques of the Scrum method. The functionalities of the web software, with access and specific functions for three different users (Administrator, Manager and Visitor), were developed jointly by developers, researchers, managers and health professionals, based on practical needs related to the management of prenatal care. Results The web software is a tool to support the management of prenatal care, with the potential to generate infographics that denote gestational intercurrences and that allow, in an agile and safe way, the making of local-regional strategic decisions. Conclusion The process of development and validation of the web software to support the management of prenatal care was carried out jointly by developers, researchers, managers and health professionals, based on practical needs related to the management of prenatal care. The tool was developed in order to allow access and specific functions to three different users (Administrator, Manager and Visitor), with a view to making quick and safe decisions.

Research on the Application of Information Management System in the Laboratory of Power Generation Enterprises

Information management systems have achieved many application results in the management of metrological calibration and chemical testing laboratories facing society, but there are few research and application cases that combine the two information systems. The power generation enterprise is equipped with both a metrological calibration laboratory and a chemical testing laboratory. Huadian Laizhou Power Generation Co., Ltd. and Huadian Electric Power Research Institute Co., Ltd. have jointly developed an information system that can manage both laboratory businesses simultaneously. Starting from practical cases, this article discusses the development feasibility of this information system, its differences from conventional laboratory information systems, and the innovation points implemented in the project from the perspectives of information technology and software function settings.

Modeling and exploring the evolution of the mobile software ecosystem: How far are we?

AbstractThe health of mobile software ecosystems is closely related to the interests of software developers, end‐users, and stakeholders. Therefore, it is crucial to maintain the mobile software ecosystem healthy and functioning. Researchers have done considerable research on mobile software ecosystems like Android and iOS. However, the evolution laws implicit in mobile software ecosystems have not attracted widespread attention. This paper proposes a research framework for investigating the evolution process and influencing factors of mobile software ecosystems based on community mining. Firstly, we mine the evolving ecosystem from many mobile software projects based on a community detection algorithm. Then we analyze the evolution process of the ecosystem by identifying evolution events in different periods. Furthermore, we utilize the multinomial logistics regression model to analyze the relevant indicators and summarize the crucial factors affecting the evolution. Meanwhile, by training the long short term memory (LSTM) model to predict evolution events, our prediction accuracy can reach 75%. This work can be used to maintain and improve the healthy operations of mobile software ecosystems.

Experimental validation of sensor fault estimation for vehicle dynamics with a nonlinear tire model

Sensor fault estimation in an automotive application is crucial for the safe execution and availability of software functions controlling the vehicle. Especially, in situations at the grip limits of the tires the safety of the passengers is most critical and a nonlinear tire model is required for accurate predictions. However, the influence of a nonlinear tire model for sensor fault estimation in an automotive application is not sufficiently analyzed in the literature.In this paper, the influence of a nonlinear tire model on sensor fault estimation during highly dynamic cornering maneuvers is demonstrated. A two-stage Extended Kalman Filter (TSEKF) based on a simple state transformation is used for the estimation of additive and multiplicative faults in longitudinal/lateral acceleration and yaw rate. The proposed estimation algorithm was implemented in real-time on a dSPACE MicroAutoBox II and experimental results with multiple measurements of an Audi S8 (D5) are used for validation of the results. The estimation performance during the measurements, using a linear and a nonlinear tire model, is analyzed and the influence of the state transformation on the accuracy of the filter is investigated.Using a simple nonlinear tire model the state estimation performance under nonlinear operating conditions can be improved by up to 79%, thereby reducing false positive detections significantly. Furthermore, the results show that for the considered system without the use of a state transformation, i.e., neglecting the state-fault cross-covariance, degrades the estimation performance by less than 1%.

Resolving Misconception Challenges in the Teaching and Learning of Computer Science Amongst First-Year Undergraduate Students

Misconceptions in the field of computer science can lead to confusion and loss of confidence for students. These misconceptions are based on students' concepts that are not scientifically accurate interpretations. One of the major reasons why students find certain computing and scientific concepts so tough to acquire is because they suffer an inequality or gap between their early classification of a concept and the new learning framework. Resolving misconception challenges in the teaching and learning of sciences is not new because according to the past studies, it is believed to manifest throughout the life of individuals where students are greatly involved when it comes to teaching and learning sciences. The study aims to resolve and correct students’ misconceptions using a practical approach and its impact on students’ gender differences. To address these misconceptions, an experimental design study was conducted in order to examine the effects of practical approach correcting misconceptions among students in computing. The study compared students' scores on Pre-Test and Post-Test, comparing their perceptions of computing and the effectiveness of practical methods to address them. The population of the study consisted of all undergraduate students in higher education institutions in Lagos State. Through the use of random sampling method, 75 undergraduate students from Lagos State University of Education were selected. The instrument was subjected to reliability index after it was validated by experts in computing. An index of .887 results showed significant highly reliable instrument. The results of findings established significant differences between the pre-and post-test scores, but only a slight difference between male and female scores observed. The study recommends that students should be given the opportunity to investigate and test their own findings of computer science components and software functions in order to build a deeper understanding without preconceptions from their prior experiences.

Spatial–temporal distribution of global production–living–ecological space during the period 2000–2020

Global production-living-ecology space closely corresponds with sustainable development’s economic, social and ecological elements. The dataset of global production–living–ecological space in this paper was generated by combining the global land cover obtained using GlobeLand30 and the population density supplied by NASA’s Socioeconomic Data and Applications Center in 2000, 2010, and 2020. The verification was carried out using the random sampling function of ArcGIS software on the basis of Google Earth sample images. The overall accuracy of the global production–living–ecological space data in 2020 was 83.94% and the Kappa coefficient was 0.81. The overall accuracy of the global production–living–ecological space data in 2010 was 87.00% and the Kappa coefficient was 0.84. The overall accuracy of the spatial data in 2000 was 86.06% and the Kappa coefficient was 0.83. The dataset fills a gap in the global production-living-ecology space database and will be an essential reference for assessing the coordinated development of sustainable development goals.

Hepatobiliary surgery based on intelligent image segmentation technology.

Liver disease is an important disease that seriously threatens human health. It accounts for the highest proportion in various malignant tumors, and its incidence rate and mortality are on the rise, seriously affecting human health. Modern imaging has developed rapidly, but the application of image segmentation in liver tumor surgery is still rare. The application of image processing technology represented by artificial intelligence (AI) in surgery can greatly improve the efficiency of surgery, reduce surgical complications, and reduce the cost of surgery. Hepatocellular carcinoma is the most common malignant tumor in the world, and its mortality is second only to lung cancer. The resection rate of liver cancer surgery is high, and it is a multidisciplinary surgery, so it is necessary to explore the possibility of effective switching between different disciplines. Resection of hepatobiliary and pancreatic tumors is one of the most challenging and lethal surgical procedures. The operation requires a high level of doctors' experience and understanding of anatomical structures. The surgical segmentation is slow and there may be obvious complications. Therefore, the surgical system needs to make full use of the relevant functions of AI technology and computer vision analysis software, and combine the processing strategy based on image processing algorithm and computer vision analysis model. Intelligent optimization algorithm, also known as modern heuristic algorithm, is an algorithm with global optimization performance, strong universality, and suitable for parallel processing. This algorithm generally has a strict theoretical basis, rather than relying solely on expert experience. In theory, the optimal solution or approximate optimal solution can be found in a certain time. This work studies the hepatobiliary surgery through intelligent image segmentation technology, and analyzes them through intelligent optimization algorithm. The research results showed that when other conditions were the same, there were three patients who had adverse reactions in hepatobiliary surgery through intelligent image segmentation technology, accounting for 10%. The number of patients with adverse reactions in hepatobiliary surgery by conventional methods was nine, accounting for 30%, which was significantly higher than the former, indicating a positive relationship between intelligent image segmentation technology and hepatobiliary surgery.

Analytical input-output modelling of surface dielectric barrier discharge plasma actuator

Surface dielectric barrier discharge (SDBD) actuators are a type of asymmetric dielectric barrier discharge (DBD) actuator that can be used to generate ions and produce thrust for near-space vehicles. In this paper, a physics-based model for SDBD produced thrust is developed that accounts for geometric and environmental variation between SDBDs. The presented SDBD analytical model (SDBD-AM) is based on models for parallel-plate DBDs but accounts for the ‘virtual electrode’ resulting from changing plasma length that is particular to SDBDs. To validate the model, thrust measurements from 12 different configurations from previous studies were used, and the mean absolute percentage error (MAPE) between each configuration and SDBD-AM was determined. The observed effects on the model were attributed to structural effects including electrode width, electrode spacing, dielectric, and environmental effects including pressure, and the apparent uncertainties are different for each effect. As a result, it was obtained that the MAPE between SDBD-AM and the experimental data for different structures is 11%, and for different pressures, it is 12%. The body force field has been simulated using SDBD-AM and a distribution function in COMSOL software, and the body force profile near the exposed electrode has been validated with a previous numerical model. This model can be used for the design and optimization of SDBD actuators and also in the design of control systems such as spacecraft attitude control in order to increase the accuracy and performance of the controller.

Deformation-Failure Characteristics of Coal with Liquid CO2 Cryogenic-Freezing Process: An Experimental and Digital Study

The aim of this paper is to analyze the deformation-failure degree and microstructure variations in coal under the cryogenic-freezing effect of liquid CO2. In this paper, X-ray CT scanning technology is adopted to measure the microscopic-morphological parameters of coal. Drawing support from the image processing and three-dimensional (3D) visualization functions of Avizo software, 3D spatial structure variation rules, as well as the deformation and permeability parameters, are quantitatively calculated. Under the effect of LCO2 cryogenic freezing, the macroscopic mechanical properties and deformation-failure degree of coal are thoroughly analyzed. The results show that fracture-scale parameters of treated coal are significantly increased, resulting in spatial structure parameters including the coal plug total volume (Vt), fracture network volume (V0), and proportion of fracture network (μ0) to increase by 17.11%, 56.57%, and 55.59%, respectively. A comparison analysis indicates that the coverage area of a single value function from the percolation theoretical model for treated coal plugs becomes larger, and its percolation curves are more intensive; the quantitative coal permeability coefficients are increased to more than 40% on average, which further proves that the permeability of coal by using LCO2 cryogenic freezing is significantly improved. Under the same uniaxial stress loading rate, the peak stress threshold value required by treated coal in the compaction and elastoplastic deformation stage is decreased. The corresponding output acoustic emission energy is apparently increased, owing to the increased brittleness of coal, and deformation failure of coal occurs more easily. Simultaneously, the fracture network and matrix surface of treated coal are more complex, and the corresponding fractal characteristic is obvious. It could be thus concluded that the coal plugs have deformation-failure changes under cryogenic freezing by using LCO2, increasing the proportion of coal microstructure and enhancing coal permeability. Therefore, the capability of gas migration through the coal microstructure becomes easier, which is favorable for coalbed methane recovery.

Ellipsoidal seed modeling and simulation parameter selection based on the discrete element method

At present, there are still some issues in the discrete element modeling of non-spherical agricultural materials. For example, it is still necessary to enrich and optimize the particle model of non-spherical granular materials and study their simulation parameters. Therefore, in this paper, ellipsoidal seeds, such as those of soybeans, red beans, and kidney beans, were taken as the research object, and their dimensions and shapes were analyzed. The results showed that the dispersion in size could be approximated by a normal distribution. An approach for modeling ellipsoidal seeds as particles based on the multi-sphere (MS) method was proposed. Moreover, the Plackett–Burman (PB) test and the path of the steepest ascent method were both adopted to calibrate the simulation parameters, which were obtained with difficulty through experiments, and simulations of the piling test and the rotating hub test for calibration to ensure the rationality of the parameter selection. In addition, to improve the reliability of the calibration test, the automatic filling function in EDEM software was adopted for particle modeling, where the smoothness was 2. A 122-sphere model for the soybean seed, a 114-sphere model for the red bean seed, and a 242-sphere model for the kidney bean seed were established, and the three models were applied for the calibration of the simulations of the tests. The results showed that the coefficients of rolling friction between seeds had a significant influence on the simulation results for the three varieties of seeds. Finally, the manual filling models and the automatic filling models were further verified by using simulations of bulk density tests. Comparing the simulation and experiment results showed that when the number of filling spheres increased, the simulation results were closer to those obtained experimentally. Better simulation accuracy could be obtained with fewer filling spheres. These results could provide a reasonable discrete element model and simulation parameters for further simulation and optimization of designs of seeding machinery for ellipsoidal seeds.

Automated hospital management system: A study of Kogi State Specialist Hospital, Idah

Automatic Hospital Management System (AHMS) is health care service software which is built to digitalize the various services rendered by a hospital. In this paper, the Kogi State Specialist Hospital, Idah, is used as the case study for the hospital management system. The software functions are divided into three modules: administrative, medical and security modules. The aim of the AHMS is to save, retrieve, update and control the numerous activities that play out in the hospital on a daily basis. It is a web application which runs on the App Platform of Digital Ocean server, and built based on the agile software methodology. It is made of frontend, middleware and backend. Various programming languages were employed in the implementation of this work. Data transmission on the system is secured by a Cross Site Request Forgery (CSRF) token for each stream of data. Demonstrations carried out with the system showed high efficiency.

A primer on Variational Laplace (VL)

This article details a scheme for approximate Bayesian inference, which has underpinned thousands of neuroimaging studies since its introduction 15 years ago. Variational Laplace (VL) provides a generic approach to fitting linear or non-linear models, which may be static or dynamic, returning a posterior probability density over the model parameters and an approximation of log model evidence, which enables Bayesian model comparison. VL applies variational Bayesian inference in conjunction with quadratic or Laplace approximations of the evidence lower bound (free energy). Importantly, update equations do not need to be derived for each model under consideration, providing a general method for fitting a broad class of models. This primer is intended for experimenters and modellers who may wish to fit models to data using variational Bayesian methods, without assuming previous experience of variational Bayes or machine learning. Accompanying code demonstrates how to fit different kinds of model using the reference implementation of the VL scheme in the open-source Statistical Parametric Mapping (SPM) software package. In addition, we provide a standalone software function that does not require SPM, in order to ease translation to other fields, together with detailed pseudocode. Finally, the supplementary materials provide worked derivations of the key equations.

Image segmentation and feature extraction method for lung lesion detection in computed tomography images

Lung cancer is a form of cancer that causes uncontrollable cell growth in the lungs. Patients with lung cancer frequently miss a treatment, face higher health care costs, and get the worst outcomes. The detection of the existence of lung cancer can be performed in a variety of ways, such as computed tomography (CT), magnetic resonance imaging (MRI), and radiography. Many researchers have developed ways of automating lung cancer diagnosis using image processing techniques because of the noise and low image quality between the cancer cells, the lung, and the background. This study develops an image processing technique that uses image segmentation algorithms to segment lung nodules in computed tomography images using feature extraction. In the initial phase, it is essential to establish a rigorous image processing framework with the following sequential steps: (i) object edge identification and (ii) lesion boundary recognition. The architecture includes image processing techniques, thresholding, and morphological detections (erosion and dilation). Lesions can have various sizes and shapes, both regular and irregular. The new method has been applied to find the lesions using their roundness size. In addition to learning purely from CT scans, the previously studied lesion characteristics are also integrated. Data was collected from the Advanced Medical and Dental Institute (AMDI), Universiti Sains Malaysia, Penang. The manual segmentation was used image segmented in the MATLAB software function to remove the background of the images. The perimeter evaluates such as accuracy, recall, and F-score. Based on the analysis the performance of lung lesion segmentation of accuracy is 99.95, recall at 45.76%, and the F-score is 60.67%. For lung lesion detection, the results shows it consist of 3-5 slices with the value of roundness. Besides, lesion detection also have continuity for the roundness value. The experiment results found clear support for the next step of this research for classifications of lesions.

Earthquakes time series visualization in cilacap earthquake zone using QGIS and USGS data sets

Cilacap region earthquakes often occur with more than 5 Richter Scale. With these seismic conditions, earthquake studies in the Cilacap region will always be needed. These studies usually only have output in form of map visualization spatially, however, they have not been compiled in a time series. This study attempts to include visualization of spatial data in the form of a time-series. The data visualization was presented in form of graphs and maps. Graphical visualization using line bar graph type by applying descriptive statistics tries to determine the earthquake’s magnitude fluctuation. The other visualization in form of Heatmap map analysis applying the Kernel Density method is interpolated earthquake magnitude spatial data. The data used in this research was retrieved from the USGS datasets between 1918 to 2021. The spatial boundaries were taken from -7.324 ˚S, 107.941˚E to -10.407˚S, 111.116˚E. The results of spatial data visualization using the heatmap techniques were then analyzed temporally using the Temporal function in the QGIS software. The results of temporal analysis within a year are then sequenced into a video which is displayed on the following link https://youtu.be/m3B7HkfI8qY. The descriptive statistical analysis shows that Earthquakes have magnitudes ranging from 3.3 to 7.58 with a mean of 4.58 and a mode of 4.4. Heatmap analysis shows the results of earthquake magnitude interpolation with high density, located in the south of Cilacap and south of Yogyakarta. Also, the spatiotemporal analysis results show that there is a change in location trends that have high earthquake magnitude density values