Object-oriented Analysis Research Articles

A two-tier database architecture framework for combating cyber threats

The 21st century has witnessed a lot of advancements in science and technology. One may not be wrong to assert that the field of Information and Communications Technology (ICT) and its allied disciplines like Artificial Intelligence (AI) and Nanotechnology have taken the lead as we witness new developments in these areas year by year. The products and services we utilize and enjoy are evidence of the usefulness of this advancement in science and technology. It is worthy of note that the interest of many (both good and bad in the discipline of ICT), is being ignited by the fact that ICT finds its applicability virtually in every area of human endeavor. In this study, we propose a two tier database architecture that employs an Object-Oriented Analysis Design Methodology (OOADM) using the Unified Modelling Language (UML). The choice of this methodology is because we need to present every stage of the study from analysis to the design phases. With the help of the chosen methodology, we analyzed the existing frameworks, identified the weaknesses, and as a result, we further surveyed algorithms used for reliable data security. From the results obtained from the survey, we employed the SHA-256 algorithm because of its strength in data security, and the Argon2 hashing algorithm which is one of the best algorithms for securing database credentials. In the end, we provide an enhanced framework made up of the chosen algorithms and a two-dimensional database (2-DDb), which could be implemented to effectively combat attacks on important databases.

Convolutional neural networks method for folded naira currency denominations recognition and analysis

Sorting banknotes automatically in payment facilities or freewill donation boxes involves many tasks such as recognizing banknote denomination, fitness classification, and counterfeit detection. Different studies have addressed these problems using foreign currencies. In other words, very few researches have been conducted on naira banknote denomination recognition. A few studies did not consider folded naira banknote denomination recognition. To overcome this, we propose a Machine Learning Based Folded Banknote Denomination Recognition System. The proposed system automatically extracts relevant features and characteristics of the naira currency denomination in different positions, orientations, and folds. This automatic representation of the naira currency denomination enables the proposed system to reduce over-reliance on suggested characteristics, improve performance accuracy, and generalize the proposed system to new problems. Moreover, the proposed system was modeled using object-oriented analysis and design methodology, and implemented in the Keras framework interfaced with Tensorflow. Then, the Softmax classification algorithm was used to classify each Naira banknote denomination. The proposed machine learning-based folded banknote denomination recognition achieved an average accuracy of 95%, which shows the generalization ability of the proposed system to recognize folded banknote denominations in different orientations, positions, and folded forms.

An enhanced control solutions for efficient urban waste management using deep learning algorithms

This study focuses on developing an efficient urban waste management system using deep learning algorithms and Internet of Things (IoT) technology. The goal is to improve waste management in Ikot Ekpene municipality by enabling quick disposal responses to prevent environmental pollution. The researchers employed an Object-Oriented Analysis and Design (OOAD) methodology to develop a software system that integrates mobile GIS techniques and IoT sensors to monitor and manage waste. The system was trained using a dataset of 510 images of six classes of waste-related scenarios, with an 84% training set and 16% validation set. The results showed that the garbage bin half-full class had the highest F1 score (above 80%) at a confidence score of 0.4, indicating accurate detection. The average F1 score for all classes was 0.45 at a confidence score of 0.238. The system’s API was designed using Python, supporting both web-based and Android-based applications. The integration of IoT sensors and mobile GIS techniques enables real-time monitoring and efficient waste management. This study demonstrates the potential of deep learning algorithms and IoT technology in improving waste management services, contributing to a cleaner and healthier environment. The system’s effectiveness in detecting waste levels and triggering timely disposal responses can help prevent environmental pollution and enhance the well-being of citizens.

Object-Oriented Analysis in Software Engineering: A Systematic Review of the Literature

Object-Oriented Analysis in Software Engineering: A Systematic Review of the Literature

Improved Online Result Transcript Generation System

This study addresses the inefficiencies inherent in manual management of students’ academic records by proposing a robust online system for result processing and transcript generation. The aim of this study is to develop and implement an efficient online system for processing results and generating transcripts, to streamline the process and improve accessibility and accuracy. An in-depth analysis of the current manual processes reveals significant challenges and inefficiencies, which guide the design and development of a user-friendly, web-based application. The system employs the Object-Oriented Analysis and Design Methodology (OOADM) and integrates HTML5, CSS3, JavaScript, PHP, and MySQLi technologies to ensure scalability and effective handling of extensive student data. This research offers a substantial contribution to the modernization of academic administrative processes, demonstrating how an automated system can significantly improve result processing and transcript.

Development and execution of a notification system for lectures in universities

The aim of this work is design and implementation of a lecture alert system for Computer Science Department which makes use of Short Message Service (SMS) to enable lecturers to know when they have lectures and also deliver the venue, department, day, date and time to their phones. The motivation for this work is due to the challenges of the consistence report of errors in the process of filling and allocating the lectures on the time table, lack of effective record system or database system to store the record of time table and clashes of lecture because one venue can be allocated to different lecturers at the same time. The methodology that will be employed in this study is the object-oriented analysis and design methodology (OOADM) which will make use of the following programming languages; JavaScript for controls and flexibility, PHP for effective linking and communication with the database machine, HTML for browser communicator, a database machine, MySQL, and macromedia flash (11.0) for the video output display. The expected result that will be obtained is to a design a conventional lecture alert system using Short Messaging Service (SMS), also to provide a new method of checking lectures using mobile phone short messaging service work and to alert students ahead of their lectures and inform them of the venue of the lecture.

A Model for Detection of Malwares on Edge Devices

Abstract- Malware detection is a significant challenge in today's digital landscape. As new forms of malware are continuously being developed, traditional detection techniques often fall short due to their inability to detect these new strains. This paperintroduces meaningful features that effectively capture various types of malware, including viruses, worms, Trojans and Ransomware on Edge devices. The paper used a model that implemented Random forest classifier for feature selection and a support vector machine (SVM) model for Malware detection. Object-Oriented Analysis and Design (OOAD) methodology was used to as the design methodology, which involved identifying and modeling the different components of the system and their interactions. The system was developed using Python programming language, with an emphasis on model deployment via Python Flask for web-based testing and execution. The experimental results demonstrate the effectiveness of the proposed systems when compared with other existing system. The result gotten from proposed system is better than that of the existing system by achieving a detection accuracy of 99.98% which is better than existing techniques. This dissertation presents a promising direction for improving malware detection using support vector machine (SVM) model and highlights the potential for collaborative learning approaches to overcome the challenges of traditional centralized approaches. This result simulates edge device that performs malware detection. It measures the latency for each detection and prints whether the latency is high or low. After the simulation, it plots a graph to visualize the latency over multiple requests. Which shows that the proposed model had low latency between 0.25secs to 0.15 secs on multiple requests.

Application Of Vat Calculations, PPh Article 22, and PPh Article 23 On the Procurement of Goods/Services

The Lagadar Village Office still uses a manual approach to calculate taxes on acquiring goods and services. This condition involves using a calculator and recording the calculations in a notebook. Consequently, the Treasurer frequently made errors while performing computations, whether misclassifying the tax type or inaccurately incorporating the tax rate. Moreover, the requirement to input tax computation data again before printing creates a challenge for the Treasurer in locating the necessary information in the notebook for monthly reporting to the leadership. Hence, there is a requirement for a system that can simplify the Treasurer's task of calculating and summarizing the tax data. This project aims to develop apps that can accurately compute value-added tax, income tax 22, and income tax 23 for the acquisition of goods and services. The employed research methodology is the descriptive research method. The system development method employed is the Object-Oriented Analysis and Design (OOAD) model system development method. The system design employs a web programming language integrated with the Codeigniter framework, utilizes a MySQL database, and employs the Visual Studio Code text editor for development purposes. A research study has led to developing an application at the Lagadar Village Office. This application, designed to calculate Value Added Tax, Article 22 Income Tax, and Article 23 Income Tax for procuring goods and services, is a significant step towards more efficient tax calculations. Its purpose is to assist the Treasurer in efficiently calculating, collecting, recording, and reporting tax calculation data, ensuring accurate and organized records in the system. Research-based recommendations for further development of the application include the creation of an application landing page that provides information on taxation. This will enable application users to stay updated on the latest government regulations pertaining to taxation, particularly for Village Offices. This application not only simplifies the Treasurer's tasks but also ensures accurate and up-to-date tax calculations, instilling a sense of optimism for the future of tax management at the Lagadar Village Office.

PPH 21 Tax Calculation Application for Permanent Employees at The Bandung Regency Fire Service

This study aims to create a software application that can accurately compute PPh 21 (income tax) for full-time employees at the Bandung Regency Fire Department. The development process will utilize an Object-Oriented Analysis and Design (OOAD) System Development approach. The primary aim of this study is to mechanize the computation of PPh 21 in compliance with relevant tax statutes while streamlining tax and payroll administration at the organization. The development methodology comprises five primary phases: requirements analysis, system design, implementation, testing, and assessment. During the requirements analysis phase, data is gathered through interviews, observations, and literature research to comprehend the system's functional and non-functional requirements. The system design step entails developing a system architectural design that includes class, use case, and interaction diagrams to guarantee that the system fulfills the given requirements. Implementation involves creating program code based on the design and integrating system components. The testing phase encompasses unit, integration, system, and acceptance testing to verify that the system operates as intended and is error-free. The evaluation phase incorporates the participation of end users to gather input on the system's usability, efficiency, and precision and introduce enhancements prior to its complete implementation. The research findings demonstrate that using this internet-based application can enhance the effectiveness and precision of tax computations, mitigate the likelihood of data loss, and facilitate heightened job efficiency at the Bandung Regency Fire Department. This application is anticipated to favorably impact tax and payroll management at the agency while also enhancing the quality of public services through digitalization and technological innovation.

A Critique on the Role of Object-Oriented Finite Element Analysis (OOF2) in Predicting Thermal and Mechanical Properties in Thermal Sprayed Coatings

A Critique on the Role of Object-Oriented Finite Element Analysis (OOF2) in Predicting Thermal and Mechanical Properties in Thermal Sprayed Coatings

The Limits of Object-Oriented Literary Analysis in Rereading Emily Dickinson’s “My Life had stood—a Loaded Gun”

The Limits of Object-Oriented Literary Analysis in Rereading Emily Dickinson’s “My Life had stood—a Loaded Gun”

Rural And Urban Land And Building Tax Calculation Application (PBB-P2)

The PBB-P2 application, which focuses on the case study of Cangkuang Wetan Village, is specifically created to streamline and enhance the inputting and managing of rural and urban land and building taxes. The data-gathering methods employed, including thorough observation, comprehensive interviews, and extensive literature review, ensure the accuracy and reliability of the system. The system design was created with descriptive techniques and the object-oriented analysis and design (OOAD) development methodology, employing, which involves a process of analysis, system design, and object-oriented implementation outlinas ed by the Unified Modeling Language (UML). This design aims to provide benefits to Cangkuang Wetan Village by automating the tax computation process, managing citizen data, and generating time-saving reports.

Waterlogged Area Identification Models Based on Object-Oriented Image Analysis and Deep Learning Methods in Sloping Croplands of Northeast China

Drainage difficulties in the waterlogged areas of sloping cropland not only impede crop development but also facilitate the formation of erosion gullies, resulting in significant soil and water loss. Investigating the distribution of these waterlogged areas is crucial for comprehending the erosion patterns of sloping cropland and preserving black soil resource. In this study, we built varied models based on two stages (one using only deep learning methods and the other combining object-based image analysis (OBIA) with deep learning methods) to identify waterlogged areas using high-resolution remote sensing data. The results showed that the five deep learning models using original remote sensing imagery achieved precision rates varying from 54.6% to 60.9%. Among these models, the DeepLabV3+-Xception model achieved the highest accuracy, as indicated by an F1-score of 53.4%. The identified imagery demonstrated a significant distinction in the two categories of waterlogged areas: sloping cropland erosion zones and erosion risk areas. The former had obvious borders and fewer misclassifications, exceeding the latter in terms of identification accuracy. Furthermore, the accuracy of the deep learning models was significantly improved when combined with object-oriented image analysis. The DeepLabV3+-MobileNetV2 model achieved the maximum accuracy, with an F1-score of 59%, which was 6% higher than that of the model using only original imagery. Moreover, this advancement mitigated issues related to boundary blurriness and image noise in the identification process. These results will provide scientific assistance in managing and reducing the impact in these places.

Object-oriented analysis as a foundation for building climate storylines of compounding short-term drought and crop heat stress

IntroductionCrops are vulnerable to precipitation and heat extremes during late spring through summer.MethodsWe analyzed for a north-central U.S. region short-term drought and agricultural heat stress during April-May-June-July. We used the 4-km Parameter Elevation Regression on Independent Slopes Model (PRISM) for observations, aggregated to a 25-km grid, and two 25-km Regional Climate Model version 4 (RegCM4) simulns used either GFDL- or MPI-GCM boundary conditions. We chose 1981-2000 as our contemporary time period, and 2041-2060 as our scenario time period, which used the Representative Concentration Pathway 8.5 emissions scenario. We used object-oriented analysis to identify events of interest in observations and simulations by identifying objects in a space-time domain that meet specified criteria, such as exceeding a heat-stress temperature threshold. The event diagnosis allowed analysis of compound events, occurring when temperature and drought objects overlap.ResultsIdentified objects yielded events that can undermine agricultural productivity and which are thus relevant to decision makers, making them building blocks for possible climate storylines. The observations and simulations showed similar spatial distributions of event frequencies across the analysis region. However, the simulations attained this distribution by having fewer events that tend to cover larger areas compared to observed events, suggesting that the effective resolution of the simulations was coarser than their 25-km grids. Short-term drought frequency increased and heat-stress frequency decreased in transitioning to the scenario climate. When compounding occurred heat-stress events generally preceded the short-term drought events. The overlapping, compound events tended to be more extreme compared to non-overlapping events of either type.DiscussionThe information yielded projected changes in these agriculturally motivated events. One prominent conditional behavior emerging from the work was that a heat-stress event should be a warning to watch for potential drought, as both could compound each other to more intense levels.

A Pixel Texture Index Algorithm and Its Application

Image segmentation is essential for object-oriented analysis, and classification is a critical parameter influencing analysis accuracy. However, image classification and segmentation based on spectral features are easily perturbed by the high-frequency information of a high spatial resolution remotely sensed (HSRRS) image, degrading its classification and segmentation quality. This article first presents a pixel texture index (PTI) by describing the texture and edge in a local area surrounding a pixel. Indeed.. The experimental results highlight that the HSRRS image classification and segmentation quality can be effectively improved by combining it with the PTI image. Indeed, the overall accuracy improved from 7% to 14%, and the kappa can be increased from 11% to 24%, respectively.

A novel hybrid database security management technique

Since the advent of the internet and the digitization of information, more individuals and organizations have gained access to the internet, leading to a significant expansion in the size of our database systems. These databases are relied upon for day-to-day activities by individuals and organizations. Furthermore, the advancements in technology have increased the vulnerability of database management systems and enforcing adequate database security measures is of paramount importance to individuals and organizations. In this study, we deployed a hybrid approach to database security system that integrates two techniques: dynamic time-warping algorithm and voice recognition methods. The implementation follows Object-Oriented Analysis and Design procedures, utilizing SQL Management Studio 2014 for the backend and ASP.NET C# for the frontend. Our hybrid approach demonstrates enhanced database security compared to previously employed authentication measures.

Potential of Lightweight Drones and Object-Oriented Image Segmentation in Forest Plantation Assessment

Forests play a vital role in maintaining ecological balance and provide numerous benefits. The monitoring and managing of large-scale forest plantations can be challenging and expensive. In recent years, advancements in remote sensing technologies, such as lightweight drones and object-oriented image analysis, have opened up new possibilities for efficient and accurate forest plantation monitoring. This study aimed to explore the utility of lightweight drones as a cost-effective and accurate method for mapping plantation characteristics in two 50 ha forest plots in the Nayla Range, Jaipur. By combining aerial photographs collected by the drone with photogrammetry and limited ground survey data, as well as topography and edaphic variables, this study examined the relative contribution of drone-derived plantation canopy information. The results demonstrate the immense potential of lightweight drones and object-oriented image analysis in providing valuable insights for optimizing silvicultural operations and planting trees in complex forest environments.

Aplikasi Perhitungan Pajak Pensiun Pegawai dengan PPH 21 Sebagai Variabel Moderating

Along with the times, technology is experiencing rapid development. This advances company performance through the Tax Information System as a tool to help companies manage and process tax information more efficiently, accurately and in accordance with applicable regulations. PT Bio Farma (Persero) adalah BUMN (Badan Usaha Milik Negara) whose share ownership is fully owned by the government. PT Bio Farma (Persero) as the only producer of vaccines for humans in Indonesia. Currently there is no application that specifically helps employees calculate their pension tax easily because it is possible for errors to occur in calculating pension tax. Given these problems, to minimize errors in pension tax calculations, an application was created using the PHP framework as the programming language and MySQL as the database. The research method used in this research is the Descriptive Method. The development method used is OOAD (Object-Oriented Analysis and Design) with system design techniques using UML (Unified Modeling Language). The results showed that pension tax calculation application in PT Bio Farma (Persero) makes it easier to calculate pensions and minimizes calculation errors or delays in pension tax calculation reports.

Wildfire risk assessment and mapping – an approach for Natura 2000 forest sites

Over the last ten years, Bulgaria's forest areas have been under almost year-round fire activity, severely impacting the Natura 2000 sites: Managing forests and maintaining traditional links between people and nature in mountain sites is becoming increasingly challenging. However, the National Methodology for determining the risk of forest fires (proposed in 2016) is applicable only at the regional administrative level (NUTS 3). This study is motivated by the actual need for an approach and a toolbox that can accurately assess the risk of wildfires, considering the unique characteristics of each location. An object-oriented vulnerability analysis is necessary to ensure that all parties involved in wildfire risk management can respond effectively. The main objective of this study is to suggest a flexible and scalable approach for spatial assessment and mapping of wildfire risk in geographic units relevant to natural heritage maintenance and resource management. A single register of potential fire risk factors is proposed, integrating 29 indicators into five thematic groups reflecting up-to-date data on hazards, vulnerability, and emergency response capacity. The factors are assessed and overlayed to come out with an integrated evaluation of the fire risk within a forestry subdivision - the smallest unit of forest management and inventory. The evaluation process involved geospatial technologies for analyzing the data and mapping the results. The methodology is tested on two Natura 2000 sites - BG0000496 “Rilski Manastir” (includes UNESCO’ World Heritage Site and symbol of Bulgarian identity – Rila Monastery) and BG0001011 “Osogovska Planina”, for which a conservation concern has been identified under the influence of wildfire risk. It has been confirmed that risk maps have the potential to support response teams, as demonstrated during a fire event that occurred on October 30th, 2022. The results from the study were used to identify suitable locations for the construction of fire towers and a visitor information system at BG0000496 “Rilski Manastir”.

A Health Mobile Application for Self-Care of Colostomy Patients

Abstract Introduction and Objective In most cases, due to the failure of nonsurgical methods in the treatment of diseases related to the colon, it is necessary to perform colostomy as the main treatment method. However, this surgery can cause a wide range of physical, social, and psychological problems in patients. Therefore, in order to prevent and treat the complications of colostomy, it is necessary to adopt measures in the field of self-care and continuous education for patients to control the complications of the disease, seek treatment, and experience improvements in their quality of life . Additionally, considering the role of mobile health (mHealth) applications in facilitating continuous and effective training, and improving self-care for these patients, the aim of the present study was to design and evaluate an mHealth application for self-care of colostomy patients. Materials and Methods In the present applied research, first the functional requirements of the software were determined considering the self-care requirements of colostomy patients. Then, the software was designed based on object-oriented analysis, and according to it, the application was coded in Java and developed in the Android Studio environment. Finally, to evaluate the software, the opinions and comments of 5 gastroenterologists and 10 adult colostomy patients in the age range between 27 and 64 years who had at least a high school diploma were used as the basis of judgment at this stage. The instruments used in the evaluation included a checklist, derived from three standard questionnaires (the System Usability Scale [SUS], the mHealth App Usability Questionnaire [MAUQ], and the User Version of the Mobile Application Rating Scale [uMARS]) to measure the user-friendliness indicator, and a researcher-made checklist to measure the performance indicator of the various services provided. Results The services of the software developed include the provision of medical information and self-care instructions regarding colostomy surgery, as well as alerts for the user to schedule an appointment with a doctor and the time to take medications. Based on the results of the evaluation stage, the users were generally satisfied with the interface, services, and general features of the software. In general, the software was evaluated at the “acceptable” level, with a rate of 85%. Discussion and Conclusion Based on the findings of the current research, the software developed can be significantly effective in facilitating the education of colostomy patients and improving their self-care. Proper and continuous self-care and education for colostomy patients is necessary to prevent and control complications resulting from surgery and to improve their quality of life. Therefore, in addition to patients, all health care staff, organizations, and associations which support colostomy patients can also use this software to educate patients and improve the care provided to them.