International Journal of Engineering Research and Advanced Technology (ijerat) (E-ISSN 2454-6135)
International Journal of Engineering Research and Advanced Technology (IJERAT) with e-ISSN: 2454-6135, and DOI: 10.31695/IJERAT, is an international open access peer-reviewed monthly published engineering online journal with an aim to disseminate knowledge and provide visibility to quality research work to the international peer community. IJERAT aims to provide the best possible quality and reliable source of information on the recent developments in the field of applied research in engineering. The emphasis will be on publishing peer-reviewed quality research articles periodically and making them immediately open access to researchers worldwide. International Journal of Engineering Research and Advanced Technology (IJERAT) provides free of charge access to all published research papers on the website of the journal for open access and use under the creative commons license, meant for open access publishing practices.
Integrating Macro Indicators into Block chain Forecasting Systems
Blockchain forecasting has matured from early price-oriented models into broad analytical frameworks capable of integrating behavioral, structural, and transactional data. Despite this progress, most existing systems struggle to incorporate macroeconomic indicators, even though digital assets increasingly respond to global liquidity, monetary policy, fiscal conditions, and cross-market volatility. The absence of macro inputs limits both predictive accuracy and the ability of forecasting systems to identify regime shifts. This article explores methods for integrating macro indicators into blockchain forecasting models and introduces an architecture developed by the author, originally designed for multi-domain risk assessment and adapted here to macro-driven forecasting. The model incorporates interest-rate cycles, inflation expectations, global liquidity measures, capital flows, and geopolitical risk, fusing these signals with blockchain-level activity through a multi-modal attention mechanism. The article concludes with recommendations for designing next-generation forecasting systems capable of capturing the macroeconomic forces shaping digital-asset behavior.
Copyright (c) 2026 Tatiana Krestnikova https://creativecommons.org/licenses/by-nc/4.0
Today’s Internet is a global communications network used to transfer, process, and store classical information. The quantum Internet is a hypothetical high-speed Internet that provides ultra-secure connectivity to quantum devices across the globe. It is a network of quantum computers that will someday send, compute, and receive information encoded in quantum states. It is a communications network that will transform industries, increase security, and alter the way we transmit information. While quantum computers exist in the physical world, the concept of quantum Internet is currently theoretical. In its infant form, the quantum Internet promises to make the digital domain safer, more productive, and more powerful than ever before. In this study, we provide a primer on quantum Internet, which provides a large-scale application of advanced quantum communication technologies and protocols.
Copyright (c) 2025 Matthew N. O. Sadiku, David Padi, Janet O. Sadiku https://creativecommons.org/licenses/by-nc/4.0
Artificial intelligence (AI) is a field of computer science that creates systems capable of simulating human intelligence. It means any technology that seeks to mimic human intelligence, which covers a huge range of capabilities such as voice and image recognition, machine learning techniques, and semantic search. It involves the development of algorithms and computational models that allow machines to learn, reason, make decisions, and solve complex problems autonomously. AI in marketing is the application of AI technologies like machine learning, natural language processing, and data analytics to optimize and automate marketing tasks. This allows marketers to create more efficient, personalized, and data-driven campaigns. AI in marketing is synonymous with precision, personalization, and efficiency. Marketing AI works by processing data with algorithms and pattern recognition to simulate human intelligence. From chatbots to social media management to full-scale marketing campaigns and automation, artificial intelligence is changing the way marketers do their jobs. In this paper, we will explain various uses of AI in marketing.
Deep Learning Models to Identify and Classify Malware Variants
Witthe ever-growing threat of cyber-attacks, proactive malware detection and remediation are of utmost importance in securing the digital world. Our research investigates using advanced deep learning techniques to detect and classify malware strains such as worms, viruses, and ransomware based on a multitude of characteristics including code signatures, behavior patterns, and structural elements. Deep neural network architectures including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformer models, among others, are used to create a powerful and reliable malware detection machine learning framework. By studying tens of thousands of malwares, specimens and the characteristics that make them up, our models can differentiate between good and bad programs and learn how to quickly identify new malware threats. The suggested approach continuously learns new malware samples and adapts to attack vectors in real time to ensure a proactive security posture. The suggested model experiments significantly improve the performance of malware detection models and certify that they have a high detection rate in the new environment. This work shows how deep learning techniques could largely improve the detection of different malware viruses. Also, the quality of known detection improved steadily by analyzing the results of our models on a test set
Copyright (c) 2025 Mohammed Ali Majeed Hammed, Taha Bahaa Khaleel, Mohammed Najah Shakir https://creativecommons.org/licenses/by-nc/4.0
Elastic Deflection of Beams and frames Using Dream Method
This paper presents a new graphical method for the analysis of linear elastic structures called Dream Method. The method states that the strain energy of a linear elastic multi-member structure undergoing small deformation is the sum of moment of area of the bending moment diagrams of the individual members each about its own diagram base divided by the flexural rigidity of the member. The displacement at any point on the structure is equal to the partial derivative of the total strain energy with respect to the load at that point. The method is applied successfully in the analysis of a built-in stepped beam, a beam on three supports, and a four-member frame.
Copyright (c) 2025 Mahmoud Yassin Osman https://creativecommons.org/licenses/by-nc/4.0
Hazardous Effects of Fluoride and Its Removal Techniques: A Review
Fluorine (F) is highly electronegative in nature and reactive non-metal element. It is rarely found in pure form. It is found in combined form with other elements except oxygen and noble gases. An inorganic monoatomic F anion is called fluoride (F⎺). Although F⎺ is the reason for healthy teeth and bones, excess F⎺ can be detrimental to human and animal health. The rising prevalence of F⎺ related problems with human, animal, and plant health is mostly due to natural geological sources and expanding industrialization. The main source of daily F⎺ consumption in human is potable water. Dental and skeletal fluorosis is caused by F⎺ concentrations that are above the recommended limits. Some other effects include programmed cell-death, endocytosis, metabolic disorders, osteoporosis, joint pain, weakness of muscles, non-ulcer dyspepsia, polydipsia, anaemia, etc. For human safety and control, removal of F⎺ is necessary. Therefore, it is important to gather knowledge on the fundamental problems related to F⎺ contamination, such as origin of F⎺ disclosure, negative impact on health, along with the viability of F⎺ removal techniques. This review provides a comprehensive summary of the F⎺ removal techniques in recent use along with their benefits and drawbacks.
Copyright (c) 2025 Saiswapna Rautaray, Anup Kumar Swain, Nikhil Ranjan Dash, Hemalata Patra, Abanti Sahoo https://creativecommons.org/licenses/by-nc/4.0
Subject Review : Application of Nanotechnology in Computer Science
Nanotechnology refers to engineered structures, devices, and systems. It is the manipulation of matter on a near-atomic scale to produce new structures, materials and devices. Nanomaterials have a length scale between 1 and 100 nanometers. By controlling atoms and molecules, companies can develop nanomaterials no more than 100 nanometers thick and apply these materials to industries like healthcare, sports and electronics. In this paper, we explore the development of nanotechnology which provides good chance to develop a smaller, faster and reliable computer. This paper tells about the advantages of nanotechnology using nano tubes in place of silicon chip that is to be used in the CPU’s of computer.
Copyright (c) 2025 Safana Hyder Abbas, Wedad Abdul Khuder Naser, Amal Abbas Kadhim https://creativecommons.org/licenses/by-nc/4.0
Subject Review: AI-Driven Security in Quantum Machine Learning:Vulnerabilities, Threats, and Defenses
Quantum Machine Learning (QML) has advanced significantly thanks to the combination of Quantum Computing (QC) with Artificial Intelligence (AI), hence releasing computational benefits over conventional methods. This synergy does, however, also bring fresh security flaws like adversarial attacks, quantum noise manipulation, and cryptographic weaknesses. This work offers a thorough investigation of QML security along with an examination of its special vulnerabilities resulting from hardware-induced faults, quantum variational circuits, and quantum data encoding. We methodically investigate adversarial attack techniques using the probabilistic character of quantum states including side-channel assaults, quantum noise injection, and algorithmic perturbations. We also assess innovative defensive strategies such differential privacy, quantum adversarial training, quantum error correction (QEC), cryptographic techniques include Quantum Homomorphic Encryption (QHE), We offer a hybrid AI-driven method for protecting QML models against developing threats by linking artificial intelligence and quantum security frameworks. This work emphasizes the importance of developing quantum-safe AI systems and consistent adversarial robustness standards. The results help to advance AI-enhanced quantum security, thereby guaranteeing the future of QML applications is efficient, strong, and resistant to adversarial attack.
Copyright (c) 2025 Farah Neamah Abbas, Mohanad Ridha Ghanim, Rafal Naser Saleh https://creativecommons.org/licenses/by-nc/4.0
Matching Medical Images with Deep Learning Networks: A Survey
Many patients' lives are being saved by image-guided interventions, and the image registration issue must be regarded as the most difficult and complex problem to solve. However, the latest enormous advancements in machine learning (ML), which include the potential to deploy deep neural networks (DNNs) on modern many-core GPUs, have created a promising opportunity for tackling a variety of medical applications, including registration. The most recent research on medical image registration with DNNs is reviewed in detail in the presented work. All of the relevant papers that have already been published in the subject are included in the systematic review. This thorough overview includes a detailed discussion as well as survey of important ideas, statistical analysis from many perspectives, novelties and key contributions, confiding challenges, future directions, key-enabling approaches, and prospective trends. For readers who are actively involved in the subject, researching state-of-the-art and hoping to present a contribution to future publications, the presented study offers a deep grasp and insight.
Copyright (c) 2025 Ikhlas Watan Ghindawi, Lamyaa Mohammed Kadhim https://creativecommons.org/licenses/by-nc/4.0
Development of Deep Learning Models for Analysis of Network Traffic to Detect and Classify an Cyber-attack
Security in network infrastructures, especially in current times, takes top priority. Techniques to detect and mitigate malicious activities pose a serious challenge. This research work is defined as developing deep learning models to analyze network traffic data for detecting and classifying abnormal behavior that could lead to cybersecurity threats. Using artificial neural networks, deep learning algorithms help to find anomalies such as DoS attacks, malware presence, and data exfiltration in real-time. The proposed models have been trained with different datasets of various attack vectors to detect anomalies with high precision. The research work demonstrates that deep learning models effectively differentiate between normal and abnormal network traffic. Hence, it provides a foundation for real-time network security monitoring and threat mitigation. The study signifies the role of AI in securing networks against cyber-attacks and opens doors for future research in the development of automated threat detection systems.
Copyright (c) 2025 Ahmed Hasan khanjar, Mohammed Ali majeed hammed https://creativecommons.org/licenses/by-nc/4.0
AI for Sustainable Development: Applying Machine Learning to Optimize Energy Efficiency in Smart Cities
A number of challenges, opportunities towards the increasing use of Artificial Intelligence (AI) for energy efficiency sector in smart cities Our work focuses on three challenges for these models: 1) the scalability and integration of AI in a wide range of urban contexts,2), long-term sustainability and assessment of the impact driven by an energy system based on AI solutions;3), ethical concern to society that is required due respect. Current research calls for resilient AI solutions capable of being tailored to each city differently based on the infrastructure and technological advancements they have invested in. As a solution, modular AI frameworks and simple models can be used for scalability and interoperability. Furthermore, because most studies consider only short-term benefits this study calls attention to the need of Life Cycle Impact Assessment (LCA) type tools for continuous monitoring and evaluation with respect long term sustainability aspects. This is further exacerbated by the larger surface area of ethical issues, such as biases and social impacts — that can be surfaced only through building rigorous ethical AI frameworks and engaging with stakeholders. In this study, a multi-methods approach involving pilot testing, scenario analysis and real-time monitoring evaluates AI-powered energy management systems. S-curves and scenario analysis graphs visualize the evolution of energy savings, CO2 emissions reductions as well as forecasting accuracy improvements. The research aims to integrate these approaches for a comprehensive view of AI in contributing sustainable energy management, particularly smart cities.
Copyright (c) 2025 Mohammed Nsaif Mustafa https://creativecommons.org/licenses/by-nc/4.0
Enhancing Image Processing with CNNs: A Comparative Analysis with other Research and Current Sources
The development of convolutional neural networks (CNNs) has been a major factor in the tremendous progress made in the field of image processing in recent decades. CNNs were first created for simple image identification tasks, but they have now matured into sophisticated models that can handle challenging computer vision problems. By contrasting the efficacy of these contemporary neural network architectures with more conventional approaches reported in earlier research, this essay aims to investigate the revolutionary influence of CNNs on image processing techniques. The conversation will emphasize the critical role CNNs play in improving accuracy, efficiency, and utility in image processing applications by examining both historical methods and contemporary advancements. This analysis will also take into account the effects of these developments on a number of fields, such as digital media, driverless cars, and medical imaging.
Copyright (c) 2025 Muntaha Abood Jassim https://creativecommons.org/licenses/by-nc/4.0
Public Health Innovations Through Network Systems and Internet Technologies: A Review
The Internet of Network Systems (IoNS) is a groundbreaking integration of networked devices, digital platforms, and powerful data analytics that is transforming the provision, monitoring and administration of health care. This research target is to assess IoNS effects on the health industry, focusing on its application in disease surveillance, telemedicine, remote patient monitoring, and data-driven decision-making. In the same context, we discuss the theoretical frameworks, methods, benefits of IoNS, and the problems and limitations concerning its adoption. Such problems and limitations involve data privacy, interoperability, and the digital divide. Last but not least, we highlight directions for further investigations and actions, especially regarding the introduction of modern technologies such as 5G, blockchain, and artificial intelligence IoT devices that can improve IoNS capabilities in the health sector. The review aims to explain in detail how IoNS is transforming the health sector and for better patient outcomes by collating existing literature.
Copyright (c) 2025 Ahmed Hasan Khanjar Al- Behadili https://creativecommons.org/licenses/by-nc/4.0
Machine Learning-Driven Crime Risk Modelling and Prediction
Effective law enforcement and public safety strategies are essential for accurate crime analysis, and forecasting. This situation is a global challenge, especially in the region where diverse socioeconomic factors can influence complex crime patterns. This study presents a novel machine learning-based approach to address this critical issue. By leveraging publicly available historical crime data and relevant socio-demographic variables, we develop a predictive model to identify crimes in the area with high rates. The methodology involves data preprocessing, feature selection, model training, and validation using advanced machine learning techniques. Our proposed method attains a prediction accuracy of 0.52 over other competitive methods. These empirical results demonstrate the efficacy of the approach in forecasting crime hotspots, providing actionable insights for law enforcement agencies and policymakers. This research contributes to enhancing proactive measures for crime prevention and resource allocation in regions with diverse social economic factors.
Copyright (c) 2025 Mwita Isaac Makene, Stanley Leonard Tito https://creativecommons.org/licenses/by-nc/4.0
The Performance of SRAM Cell Topologies with 6 T, 7 T, 8 T And 9 T Technologies at 45 Nm Technology node
Numerous SRAM cell architectures employing 45nm technology were simulated in the Tanner tool used for this inquiry. In every arrangement, variables like read latency, write delay, power read, power write consumption, read static noise margin (RSNM), and write static noise margin (WSNM) were examined. Of all the designs, the 7T SRAM cell stands out for having the lowest power read utilization. Nevertheless, compared to the 6T SRAM cell, the 8T SRAM cell displayed a 44.15% reduction in power write power. The 9T SRAM cell exhibited the lowest write latency of all the cells tested. Among all the simulated devices, the traditional 6T SRAM cell also showed the highest RSNM value. There was discovered the 8T SRAM cell's WSNM.
Copyright (c) 2024 S. Jagan Mohan Rao, K.Yesurani, B. Raghavaiah, K. Raju, B. Ashok, Ch. Lakshmi https://creativecommons.org/licenses/by-nc/4.0
Low power 7T SRAM cell optimization with 45nm Technology
A new low power SRAM cell introduced that promises improved performance by adding extra circuitry to a 6T-SRAM cell. This new design features a 7T(seven-transistors) cell at 45nm size CMOS technology, aiming to enhance power efficiency, stability, overall performance compared to older designs for low power memory operations. By optimize the size and implementing a novel write circuitry scheme, new (seven transistor) 7T SRAM cell full fill a significant 45% reduction in power consumption during memory operations when compared to the traditional 6T SRAM-based design. Furthermore, through CADENCE simulations, it is shown that this 7T SRAM cell is highly resistant to process variations, highlighting its robustness and reliability in real-world applications.
Copyright (c) 2024 S. Jagan Mohan Rao, B. N. V. Sathish, J. Prasanth Kumar, M. L. S. N. S Lakshmi, Yakkla Lavanya, Ch. Lakshmi https://creativecommons.org/licenses/by-nc/4.0
IoT based Anti-Theft System for Enhanced Protection
The advancement of Internet of Things (IoT) technology has led to the development of innovative solutions for enhancing security measures. This project proposes an IoT-based anti-theft system leveraging Raspberry Pi, Raspberry Camera, IR sensor, RTC module, Wi-Fi connectivity, and a buzzer. The system aims to provide heightened protection against theft and unauthorized access to valuable assets by integrating various hardware components with smart detection and alerting mechanisms. At its core, the system utilizes Raspberry Pi as the central processing unit, coordinating the functionalities of the interconnected components. The Raspberry Camera serves as the primary sensor for capturing images and videos of the surrounding environment. Integrated IR sensors enable the detection of motion or presence within designated areas, triggering the system to activate security measures. Additionally, the RTC module ensures accurate timekeeping, facilitating event logging and scheduling of security protocols.
Copyright (c) 2024 Y. Lavanya, B. Bhanuprasad, K. Vishnukanth, B. Naresh, M. Divakar https://creativecommons.org/licenses/by-nc/4.0
Design and Development of Biometric and Keypad Based Smart Door Security System for Residential Building
A door access system's development involves many characteristics, from the most basic a keypad to the most sophisticated using smart cards and biometrics. The Arduino-Based Door Access System was created to address the problems of maintaining and upgrading the current system. This study covers using an Arduino microcontroller in a door entry system. One kind of microcontroller that has its programming language is Arduino. It may be used for experiments because it contains an electrical prototyping platform of its own. The keypad and fingerprint scanner are the two inputs for this project. The outputs consist of an LCD display, a siren, an indicator, and a magnetic switch. Based on the accuracy results of testing five people, each with four distinct fingerprints, connecting all inputs and outputs with Arduino led to accurate results in opening the door. The result that appears on the LCD display is the output, and the inputs are the password that is entered via the keypad and the details that are retrieved by scanning a fingerprint. This project is trustworthy because it uses an Arduino Microcontroller and a straightforward technique to raise the security level of the door access mechanism.
Copyright (c) 2024 Y. Lavanya, M. Rajitha Lakshmi, Vasamsetti Tarun, Putta Suma, Pandi Rakesh https://creativecommons.org/licenses/by-nc/4.0
Analysis of Implementation Plans for the ACR - PCR System on Flexible Pavement Runways at Utilization Cooperation Airport
ICAO determined that the ACR–PCR system will take effect in July 2020 and be effective in November 2024. It is very important for airports in Indonesia to make adjustments to optimize the use of pavement assets. The research aims to calculate ACR-PCR, compare it with ACN-PCN, evaluating the airside pavement structure of airport through the application of the ACR-PCR system. Case study analysis of calculations with ICAO–ACR1.32 and FAARFIELD2.0. ACN/PCN and ACR/PCR ratios are classified against pavement strength limitation criteria. Evaluation based on the criteria for permanent deformation of the subgrade layer and fatigue cracking of the asphalt layer. Tjilik Riwut airport runway PCR value 542FBXT, Radin Inten II 850FCXT, Fatmawati Soekarno 712FCXT and H. AS. Hanandjoeddin 643FCXT. Comparison of the ACR/PCR and ACN/PCN ratios shows an increase in pavement capacity of 1.4746. Based on the criteria for fatigue cracking of the asphalt layer and permanent deformation of the PCR subgrade layer at Tjilik Riwut airport 668 and 575 FBXT, Radin Inten II 1027 dan 629FCXT, Fatmawati Soekarno 862 and 629 FCXT, H. AS. Hanandjoeddin 675 and 560 FCXT. The structural pavement capacity of PT Angkasa Pura Indonesia airport has the opportunity to be increased in terms of flight frequency
Copyright (c) 2024 Edy Arif Nugroho, Nunung Widyaningsih, Hermanto Dwiatmoko https://creativecommons.org/licenses/by-nc/4.0
Travel Behavior Changes during the COVID-19 Pandemic in Indonesia: Present, Past and Future
COVID-19 (Coronavirus disease 2019) brought major changes to the behavior and mobility of people all over the world. This change is mainly a consequence of the lockdown and social distancing taken by governments in most countries around the world. This article presents an analysis of a survey conducted in major cities from 6 big islands in Indonesia (Java, Bali, Sumatera, Kalimantan, Maluku, Papua) where citizens were asked about their mobility preferences before, during, and after the lockdown due to the virus and about factors that influence the decision in choosing a mode. The surveyors distributed the closed questionnaire using Google forms to reduce the contact time with the respondents. The data is processed through a comparative test with the Friedman Test revealed that there is an average difference in the choice of transportation mode before, during, and after the pandemic and there is also a difference about the main travel purpose of the community before, during, and after the pandemic. The main purpose of respondents' travel before the pandemic was work/school, during the pandemic it was shopping the daily needs (except those working in the essential sector) and after the pandemic returning to work/school as the main purpose of travel. The results of the influence test on nine socio-demographic conditions revealed that before the pandemic there were 6 factors that influenced the mode choice, which is: gender, type of job, working in the essential sector or not, the number of people in the family, vehicle ownership and marital status influenced the modal choice, during pandemic COVID-19 there was 5 influential factors, which is: age, occupation, working in the essential sector/not, number of family members and vehicle ownership after the pandemic are the same as before the pandemic except working in the essential sector/not.
Copyright (c) 2024 Nunung Widyaningsih, Reni Karno Kinasih, Nabila, Sakti Adji Adisasmita, Mukhlisya Dewi Ratna Putri, Maya Fricilia https://creativecommons.org/licenses/by-nc/4.0
Strategic Network Expansion: Geospatial Data Visualization in Telecom Planning for GSM Operators in Iraq (Asia Cell, Zain, and Korek)
The fast growth of the phone and internet world in recent years has made planning for infrastructure and market study more difficult. Many cell towers have grown and there is a big struggle between network managers. They need new ideas to learn about the ever-changing field of wireless phone connections. In this study, we look at how to best show and understand data about where cell towers are located on a map. We suggest using some tools from Python programming language which will help solve the issue. We show how these libraries, not giving them a name, can help solve the problem. We also give useful tips for planning telecommunications networks and infrastructure management. The Study Case is Mobile Phone Companies in Iraq (Asia Cell, Zain and Korek). The phone and internet business is changing really fast. With 5G technology growing, more data use and need for connection in far-off places coming up. It's now more important than ever to have a good plan with efficient infrastructure setup that works well all around. But, the huge amount of data from cell towers and their complicated location make it very hard. Showing information about the world on maps is a useful way to understand and share details with others. In this article, we will start a trip through many code examples that demonstrate different ways to see geographical data. We will learn to use Python tools like Matplotlib, Seaborn, Folium and Selenium for making interesting maps and pictures. Pygal can also be helpful in this area. Every piece of code will be talked about deeply. We'll focus on what it does, its features and the knowledge we can get from it. By the end of this article, you will know more about different ways to show data on a map and how they can be used in real life.
Copyright (c) 2026 Intisar Mohsin Saadoon https://creativecommons.org/licenses/by-nc/4.0
Analysis of the influence of Management Planning, Organizing, Actuating and Controlling on the Time Performance of Construction Implementation Tower Telecommunications
The discovery of the phenomenon of delays in the Bakti Kominfo telecommunications tower construction project is a major problem that is currently being widely discussed by the public, just as researchers have found to occur in projects already run by PT. ABC consists of 51 village locations divided into regions (Sumatra, Kalimantan, Maluku). After conducting further analysis of the Detail Summary Sitelist PT. ABC with the construction of telecommunications towers in 51 village locations. As for the results of the site list analysis that has completed the construction stage with the final result achieved, it can be seen that 13 village locations were built faster with a maximum duration of 26 days than the target given by the client. Furthermore, the results of the site list analysis that have completed the construction stage with the final result Delayed can shows, 38 village locations have development delays with a maximum duration of -199 days from the target given by the client. There are average performance or productivity results of PT. ABC completed the construction of the target determined by the client in 60 days with average construction productivity results ranging from -50 days. It can be concluded that the performance productivity and implementation of management are carried out by the PT Resource Team. ABC is still not optimal and is considered late in completing the construction of the BTS tower. By conducting this research it is intended to find out the delay factors that most influence time performance, with elements of implementing POAC (Planning, Organizing, Actuating, and Controlling) management systematically and measurably.
Copyright (c) 2023 Tengku Alfian Rafsanjani, Agus Suroso, Mawardi Amin https://creativecommons.org/licenses/by-nc/4.0
Computer Vision Matcher for Extracting and Detection Objects
The research examines the issue of feature matching and object recognition in two images with the use of brute-force matches. The suggested framework utilized several concurrent algorithms, including BRISK (Binary Robust Invariant Scalable key points), SURF (Speeded-Up Robust Features), ORB (Oriented FAST and Rotated BRIEF), and SIFT (Scale Invariant Feature Transform), for descriptor extraction and feature detection. K-Nearest Neighbors (KNN) algorithm in conjunction with the brute-force approach allows for feature matching. The robust Random Sample Consensus (RANSAC) approach calculates the transformation between two successive images using the found matches. As a result, the RANSAC approach is used to enhance the removal of outliers. With the use of the OpenCV library, the suggested technique was developed and put into practice. Analyses of the speed at which it executes commands and the precision of the feature matching serve as proof of the system's quality and efficacy.
Copyright (c) 2023 Ikhlas Watan Ghindawi, Lamyaa Mohammed Kadhim https://creativecommons.org/licenses/by-nc/4.0
Analysis of Building Information Modeling (BIM) 4D-5D Method to Minimize the Occurrence of Variation Orders in Design and Build Contract Models
Reducing VO in the Design and Build contract model requires increased coordination, communication, and change management between the design team, project implementers, and service providers. This study aims to analyze the effect of BIM 4D and BIM 5D on the Order of Variations in the Design and Building contract model, as well as the effect of their combinations. This study examines the effectiveness of applying the 4D and 5D BIM methods to mitigate work changes in projects. Data was collected through questionnaires and analyzed with SPSS for Windows. The results showed that the BIM 4D variable had a significant effect on the use of Variation Order to reduce post-construction changes. The X1 BIM 4D coefficient (β1) is 0.937 indicating that an increase in X1 BIM 4D by 1 increases the Y1 Variation Order by 0.937. Regression analysis showed a tcount of 4.343 which is significant at the 0.05 level (p<0.05). The 5D BIM variable has a significant effect on Variation Order in reducing post-construction-growth changes. The coefficient value of β2 X2 BIM 5D is 0.120 and is positive, which means that every 1-time increase in X2 BIM 5D will increase Y1 Financial Performance by 0.120. The results of the regression analysis showed an F - count value of 3.764 and a significance of 0.041. The results of data processing show a Fcount value of 83.893 and a significance of 0.000. H0 and Ha are accepted. BIM 4D and BIM 5D have a significant effect on Variation Order as a tool for minimizing post-construction growth changes. The application of 4D and 5D BIM technologies helps mitigate construction project risks through simulating project steps, training project teams, visualizing changes/requests using BIM, and storing material specification information in BIM models. BIM technology reduces risks and increases the effectiveness of construction projects.
Copyright (c) 2023 Mulyo, Mawardi Amin https://creativecommons.org/licenses/by-nc/4.0
City Bus Inter-City and Inter-Provincial Traveller Safety Analysis in Jakarta until Solo Province
Safety is one of the main goals in reducing and minimizing traffic accident victims. The factors that cause accidents are humans, vehicles, and the environment/nature. Buses, which have their own prestige, play a role in moving from the place of origin to the destination. This study is decisive in analyzing travel safety for bus users, especially on inter-city buses between provinces with the route Jakarta - Solo. The approach used in this research was quantitative by collecting data using a closed questionnaire which was distributed to 92 respondents using the Jakarta - Solo buses, observing and interviewing respondents using Inter-City Inter-Provincial (AKAP) buses traveling from Jakarta to Solo. The distribution of questionnaires was carried out at the Pondok Cabe Type A Terminal, where later the data was processed using Structural Equation Modeling or SEM. In this research, it was used as a data analysis technique with the SPSS and AMOS 24.00 programs to determine the determinants of safety behavior. Data processing resulting from the goodness of fit test output functions to process and analyze data that has statistical analysis capabilities as well as a data management system with a graphical environment. Apart from that, the benefit of testing AMOS SEM data is to see the relationship between variables simultaneously and take into account direct and indirect effects between variables and this test explains the significant influence on safety behavior. Implementation of a ramp check within the fleet departure time has an important factor in determining travel safety which originates from vehicle factors. Handling accidents in order to minimize casualties by checking and handling (maintaining) vehicles, getting adequate rest for drivers, providing adequate space and equipment if passengers have an accident, and the need to establish related agency skills by providing education to passengers and buses, as well as accident handlers.
Copyright (c) 2023 Natalia Reza Kusumawati, Nunung Widyaningsih https://creativecommons.org/licenses/by-nc/4.0
The Combined Effects of Intense THz Laser Field and Applied Electric Field on Binding Energy of Exciton in GaAs/ GaAlAs Finite Spherical Quantum Dot
In this paper,we study the combined effects of intense THz laser field and electric field on the ground state binding energy of heavy hole excitons confined in GaAs/ GaAlAs spherical finite quantum dots. The formulation is based on the model of “laser dressed potential” which combines Coulomb interaction and field effect in only one potential as reported in the literature. The calculation is performed by using the variational method in the framework of the single band effective mass theory. Our results show that (i) The laser field increases the electron and hole confinement energy that form the exciton in the QD until they reach a maximum, then they become almost constant for a intense laser field., (ii)the electric field and the laser field lowers the binding energy for all quantum dot radii making the exciton stabilized and clustered near the center of the dot,iii)the laser field increases the spatial extention of exciton but the electric field deacreses it linearly.
Copyright (c) 2023 J.Diouri, A.Ouadgui, J.Khamkhami, A. El Rhalami https://creativecommons.org/licenses/by-nc/4.0
Exploring the role of artificial intelligence in the advancement of e-governance
E-governance is one of the applications of information and communication technology. Therefore, it represents the interaction of government, business, electronic employee, and citizen with each other, and these interactions produce homogeneous and heterogeneous databases. Heterogeneous databases are sloppy, unprocessed, and bulky. Dealing with and analyzing these types of data sets takes time, effort, cost, and a clear strategy for data analysis. The aim of this research is to find out the impact of artificial intelligence technology on improving the performance and productivity of organizations by automating processes and its effective role in improving services in e-government. The data entered into smart systems is generally classified into six types: a set of recorded data, a set of text data, images, audio, video clips and other data. This classification shows that each type of data set can be analyzed by appropriate mining techniques such as core data mining, text mining, image, audio and video data mining, etc. which helps identify the needs of citizens and services in the form of multimedia (text, image, audio, video, etc.). In this research, the virtual library was taken as a model for digital governance.
Copyright (c) 2023 Intisar Saadoon, Rasha Thamer Shawe, Farah Neamah Abbas, Muntaha shokah https://creativecommons.org/licenses/by-nc/4.0
Improved Blowfish Algorithm for Text Encryption Using DNA and Linear Feedback Shift Registers (LFSR)
The Blowfish algorithm is a popular way to protect information by scrambling it. It is known for being strong and fast. The strength and randomness of the encryption key are very important for the security of Blowfish. This paper suggests a new way to make the key generation process better in the Blowfish algorithm by using Linear Feedback Shift Registers (LFSRs) and DNA Algorithm. LFSRs are basic but effective machines that create sequences that look random but are not truly random. The DNA algorithm is used to make it harder for others to guess the correct key. To make the Blowfish algorithm better, we are combining the LFSR and DNA Algorithms in the key generation stage. This will make it more secure and efficient. The security of Blowfish greatly depends on how strong and random the encryption key is. It also explains the benefits and things to think about when using these methods. The paper includes experiments to test if this approach works well.
Copyright (c) 2023 Raghda Sattar Jabbar, Israa Shihab Ahmed , Saadi Mohammed Saadi https://creativecommons.org/licenses/by-nc/4.0
Comparison and Analysis of Wireless Sensor Networks Routing Protocols
In Wireless Sensor Networks (WSNs), the data transmission might be specified as a major challenge. Various protocols of routing were suggested for saving energy throughout the transmission of data in WSNs. The protocols of routing which are on the basis of data centric method were adequate in such regard which are performing data’s in-network aggregations for yielding energy- saving data disseminations, such sensor nodes have a few of limitations because of their limited, computing power, storage capacity, and limited energy. The data have been routed between nodes with the use of various routing protocols. In addition, there are a few routing protocols for WSNs, all such protocols attempted on eliminating a few of such limitations. In this paper, a comparison and analysis is presented for Wireless Sensor Networks Routing Protocols according to estimated time.
Copyright (c) 2023 Salam Ayad Hussein https://creativecommons.org/licenses/by-nc/4.0
Lean Six Sigma Implementation to Reduce Rubber Sole Waste in the Manufacturing Company
This study aim to research about the waste of rubber sole in the one of the rubber sole company in Tangerang. The company has a problem due to the amount of rubber sole waste is 5.5% over the company's standard, namely max.3.0%. There are 5 (five) largest type of rubber sole defect. They are dents, contamination, colour bleeding, lack of material and bubbles. To find out the factors that cause defects and how to provide suggestions for improvements to the problem. This research using the Lean Six Sigma method with the DMAIC approach (define, measure, action, improve, control). Furthermore, to find out the root cause of the problem will be using fishbone diagram tool and proposed improvements using the 5W+1H and FMEA. The purpose of the research is to find out the factors that cause of rubber sole waste over than company standards. The results of the research after making some improvements using 5W+1H and FMEA. The waste of the rubber sole to be 1.1%.
Define, Measure, Action, Improve, Control ( DMAIC)
Copyright (c) 2023 Meike Elsye Beatrix https://creativecommons.org/licenses/by-nc/4.0