International Journal on Advanced Science, Engineering and Information Technology
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2006 research outputs found
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Enhanced Artificial Bee Colony, Square Root Raised Cosine Precoding, and Mu law Compandor for Optimization of MIMO-OFDM System
Get PDFThe efficiency and high-speed data transfer rate of the communication system are increased based on Orthogonal Frequency Division Multiplexing (OFDM). The existing research in OFDM involves applying optimization methods to improve the system's efficiency. The high Peak Average Power Ratio (PAPR) value is a major limitation in the OFDM system, and this provides distortion due to the non-linear High-Power Amplifier (HPA). Local optima trap and lower convergence are two main limitations in existing optimization methods. This research proposes Enhanced Artificial Bee Colony (ABC) optimization method with a precoding-compandor technique to increase the efficiency of the OFDM system. Enhanced ABC method is applied with Boltzmann search to increase the exploitation capacity of the optimization efficiency. The selective mapping technique is applied to transform the candidate signal in the system. The ABC method increases exploration, and Boltzmann search increases exploitation. The enhanced ABC method increases the exploitation process that helps to overcome local optima traps and lower convergence. Square Root Raised Cosine (SRRC) precoding and Mu law compandor techniques were applied to reduce the PAPR. The Discrete Cosine Transform (DCT) technique is applied for domain conversion in the OFDM system. The proposed method has a convergence rate of 6.4069, and the existing one has a 6.4033 convergence rate. The enhanced ABC method provides higher efficiency in the MIMO-OFDM system regarding Symbol Error Rate (SER), PAPR, and Bit Error Rate (BER)
Integrated Solid Waste Management System Using Distributed System Architecture for Indonesia: An IT Blueprint
Get PDFIndonesia is in the top 5 country that generates solid waste. It is the 14th largest country in the world in managing waste, but unfortunately, Indonesia is not known for its diligence to waste management. In 2019, the coordinating minister for Maritime Affairs and Investment of the Republic of Indonesia, Luhut Binsar Pandjaitan, stated that it is a top priority in the national agenda to keep improving solid waste management due to the growing number of people living in the urban areas and the estimated 105.000 tons of solid waste a day. This paper aims to create an IT blueprint for this waste management through a distributed system that allows an optimum flow of waste out of dense urban centers and into the proper waste disposal facilities. It involves smarter waste surveillance, a consolidated fleet of collection agents of varying mobility and capacity and includes people participation to control unnecessary waste generation. The system should be scalable while using existing resources and systems to manage the problem in the long term. It should maintain the three principles of Integrated Solid Waste Management (ISWM): waste prevention, recycling, and disposal. New technologies, such as a sensor network to monitor waste generation close to the source, can help burgeon localized SWM techniques such as community composting. The country can take the steps necessary to mitigate the problem
Hybrid Centralized Peer to Peer Architecture for Resource Discovery and Secure Communication in Internet of Things
Get PDFThe Internet of Things (IoT) made communication between people and objects easy. It helps to build smart cities, homes, manufacturing systems, health monitoring systems, etc., for mankind. The increased adoption of IoT applications enabled many smart devices on the Internet platform. These devices deployed across the globe may have varying computational and communication capabilities. It is a great challenge to manage IoT resources efficiently. Some of well-known protocols are defined to identify and access IoT resources locally in a real-world environment. Many authors have adopted the Distributed Hash Table (D.H.T.) based Peer to Peer (P2P) model for global and massive resource management. However, D.H.T. based solutions have many shortcomings and are not perfectly suitable for the IoT domain. In this paper, it has been proposed a novel Hybrid Centralized Peer to Peer (HCP2P) architecture for efficient resource discovery and access mechanism. The proposed solution builds a secure communication channel among trusted peer devices with the aid of an HCP2P server. The trusted devices can discover and access the required resource efficiently and securely with reduced load on the central server. The proposed HCP2P solutions are evaluated on both hardware prototypes and simulations. The proposed model gives almost constant resource registration, discovery, and access time. This evaluation showed that HCP2P architecture performance is superior to traditional DHT-based P2P architecture. Finally, the performance parameters of the proposed scheme are evaluated in terms of resource registration time, discovery time, and hop-count
Design and Implementation of a Programming Automatic Assessment System in Jupyter Notebook
Get PDFLearning programming is challenging. So, computer educators have developed various tools to help students. In this paper, we have developed a tool that combines the advantages of a Programming Automatic Assessment (PAA) system and Jupyter Notebook (JN) to support learning programming. The design direction of this system is free to use, easy to set up, and supports interactive computing. The Programming Automatic Assessment in Jupyter Notebook (PAAinJN) is available free of charge using the assessment module released on Git and the personal JN. The initialization is completed by executing in a code cell with two lines of code that downloads and executes the assessment module. In an interactive computing environment, presenting problems, writing code to be evaluated, and evaluating code can be executed in the code cells, and the problems and the results of the assessment are presented in the code cell outputs. The performance was verified by the examples presented in a high school informatics textbook using the programming automatic assessment system as teaching learning material. In addition, we propose a way to develop teaching-learning materials using PAAinJN in consideration of teachers and students and a way of distributing and collecting teaching-learning materials using the free Learning Management System. PAAinJN is expected to help students learn programming by eliminating assessment and feedback delays through PAA while learning to program in an interactive computing environment
The Impact of Real Traffic from Twitter for 5G Network Deployment
Get PDFThe utilization of technology, particularly cellular networks, is continuously expanding. This is evident through the increasing number of mobile network operators (MNOs) users, especially in the current era where most things are accomplished online. Consequently, mobile network operators must furnish a comprehensive array of cellular network access services, not just for smartphones but also for other smart devices, to guarantee maximum coverage. With the growing interest in 5G deployment based on low band and millimeter wave communication (mmWave) for outdoor use scenarios, such as tourist destinations, site design experts are looking for sophisticated real-time traffic data from social media like Twitter to simulate and calculate outdoor radio coverage using 3GPP 38.901 prediction models. This study used the frequencies of 700 MHz and 26 GHz, utilizing Inter-band Carrier Aggregation (CA) to increase data rates while maintaining a wide range and optimizing the number of gNodeBs. This research is intended to monitor the Borobudur Temple area, Indonesia, which serves as a tourist destination and one of the world's wonders, thus making it a densely populated area and, inevitably requiring good network connectivity. The parameters used are Synchronization Signal Reference Signal Received Power (SS-RSRP), Synchronization Signal Signal to Interference plus Noise Ratio (SS-SINR) and data rate. The simulation revealed that CA SS-RSRP with traffic map increased by 38.88%, SS-SINR increased by 45.05%, and the peak data rate increased from 5884.12 Mbps to 6199.88 Mbps
Comparative Study of 3D Assets Optimization of Virtual Reality Application on VR Standalone Device
Get PDFThe progress of VR technology is undeniably rapid and reaches many sectors unrelated to what it first came out of entertainment. Today, many educational, health care, company training, etc., use and utilize VR in one way or another as their first step to familiarize a concept or procedure with their members or workers. The advantages of implementing educational content with VR are ease of development, cheap operational cost, and safety. This kind of approach is a good step considering the impact of VR technology on those cases. However, because the leading device for VR is a standalone VR, some things to consider are performance and visualization. Some early adaptations have these problems, performance issues, and the realism of visualization shown on the VR application. We can minimize those problems by meticulously optimizing 3D assets used in VR applications. The optimization method improved the average FPS on CBIVT by 14.02% on Quest 1 and 8.99% on Quest 2. The GPU utilization level percentage of Quest 1 decreased by 6.73%, and the Quest 2 GPU utilization level percentage decreased by 11.72%. On the other metrics, the user's comfortability also increases because of the enhancement of performance on the CBIVT application. These changes are marked by the increase in Important and Satisfactory levels to 4.26 and 4.16, respectively
An Analysis of Several Optimizers on CNNSVM and CNNRF for COVID–19 Chest X–ray Images
Get PDFCOVID–19 is a new type of ailment caused by the strenuous acute respiratory syndrome, namely SARS–CoV-2, also frequently well–known as the Coronavirus. An early tendency of COVID–19 for some sufferers can cause no symptoms at all as no experience is referred to as asymptomatic confirmation cases, yet these sufferers can still transmit COVID–19 to other people. Therefore, the authors developed a program using Machine Learning that sustains data to be analyzed based on the input served under the proposed methods of Convolutional Neural Network–Support Vector Machine (CNNSVM) and Convolutional Neural Network–Random Forest(CNNRF), along with several optimizers to be compared. Convolutional Neural Networks is a deep learning algorithm that can train large data sets with millions of parameters and has attracted attention in various fields that are commonly used for the classification and detection of Convolution in Neural Networks. In amalgamation with Support Vector Machines, a technique that uses two vectors to form a dividing line or side and fairly high accuracy,y random forests classification. In the manner of image data obtained from ChestX–ray images of people with COVID–19 from the Italian Society of Medical and Interventional Radiology (SIRM), a total of 1750 observations consisting of 1000 data for COVID¬–19 images and 750 data for non-COVID–19 images. This research aims to determine which optimizer is better for analyzing COVID–19 ChestX–ray images by evaluating both methods. Hopefully, both methods can provide higher accuracy for future studies with wider databases to provide better results for analyzing different ailments
Development of AI Liberal Arts Curriculum for the General Public
Get PDFExtending beyond technology, artificial intelligence (AI) is fundamentally changing how people live. It plays a key role in determining the competitiveness of countries and companies and is expected to change the competitive landscape of existing industries fundamentally. The better people understand AI, the better they can utilize it effectively and safely. Therefore, preparing a strategy to ensure that all citizens have access to AI education is important. This study aims to develop an AI liberal arts curriculum to improve the general public’s ability to utilize and understand AI. Through literature analysis, AI core competencies for the general public were derived. The core competencies are Adaptability, Public Interest Consideration, Creative and Convergent Thinking, Collaboration, Computational Thinking, and Artificial Intelligence Literacy. The AI curriculum was designed considering AI core competencies, and the validity of the experts was verified for AI technology and education experts. We also conducted a comparative analysis of the content and level of AI curriculum for the general public based on the results of word frequency and topic modeling analysis of AI education-related papers collected from the Web of Science. The areas of the AI curriculum consisted of understanding artificial intelligence, application of artificial intelligence, and artificial intelligence. This study is significant in that the topics discovered are based on the frequency of words extracted from many AI education-related documents, and the results of topic modeling are considered in the curriculum development process
Smart Greenhouse Technology for Hydroponic Farming: Is it Viable and Profitable Business?
Get PDFThis study aims to analyze the profitability and sustainability of horticulture agribusiness using hydroponics with a smart greenhouse (SGH) technology. This study also evaluates the acceptability of SGH technology. This study investigates the impact of the COVID-19 pandemic on the supply chain of horticulture vegetables produced using SGH, semi-smart greenhouse (SSGH), and conventional technologies. The methods used in this study are a dynamic model, i.e., the causal loop diagram (CLD), the benefit-cost ratio (B/C), the revenue-cost ratio (R/C), and descriptive analysis. The results show that the feedback structure was complex and dynamic. The determinants of SGH-based agribusinesses were cost, income, and sustainability. The findings showed that business profitability and sustainability proxied by B/C and R/C were higher in SSGH than SGH and were the lowest in conventional. The regulated use of the technology in SSGH is more profitable and applicable in Indonesia. The acceptability of SGH technology was determined by profits, investment and operational costs, market segmentation, price factors, maintenance, and farmers’ skills. Meanwhile, the impacts of the COVID-19 pandemic on the supply chain of vegetable commodities vary in SGH, SSGH, and conventional farming. The differences were influenced by business scale, partnerships, production locations, markets, logistics (transportation), and digital marketing. The findings of this study contribute to the literature on smart farming technology, especially the regulated application of SSGH
Scenario Planning and Simulation in Disaster Response
Get PDFThis study examines disaster response effectiveness. This workshop was preceded by a case scenario featuring an explosion in a heavily populated Kuala Lumpur City, Malaysia, produced by the researchers. The agencies involved used this case scenario as a storyline to implement the response. The coordination efforts undertaken by each agency can be seen. It is plain to see the efforts of collaboration that each agency has been putting forth. Focus group discussion served as one forum for debating the course of action taken; at the same time, the action taken by each agency involved should align with the roles and responsibilities outlined. During the workshop, it was revealed that it assisted researchers in better understanding agencies' disaster response process in identifying shortcomings, determining gaps, and improving on the processes already in place for disaster response. However, it was noted that the success of implementing SP&S lies in the involvement and participation of each agency. Therefore, it can be concluded that communication and coordination between agencies are very important in the success of an operation, not only during SP&S but also during disaster response