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Widianto, Ilham Rizky, Wowon Priatna, and Hendarman Lubis. "Algoritma First in First Out (FIFO) Untuk Perancangan Aplikasi Pemesanan Kaos Sablon." Jurnal Kajian Ilmiah 23, no. 2 (2024): 135–46. http://dx.doi.org/10.31599/tva3pd96.
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The purpose of this study is to solve the problem of screen-printing T-shirt shops. For manual screen printing t-shirt shops, customers often have to visit the store in person or contact them via chat or phone, often encountering the following issues when ordering t-shirts: B. Irregular orders for those who have placed an order in advance or who have been waiting for a long time. One way to solve the queuing problem is the FIFO algorithm. FIFO algorithms are methods for organizing, processing, and manipulating basic data structures in computer systems. The FIFO algorithm phases in this study begin with the data preparation phase, the Gantt cart process, and finally his FIFO wait time. The result of the FIFO stage translates into creating applications using the Java programming language, Android Studio, and the FireBase database. The results of this study can be applied to his FIFO algorithm for customer queues in ordering T-shirts. A t-shirt ordering application was tested using the white box method by running the test case in four passes. All tests passed, so you can use the ordering application based on the FIFO algorithm.
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Nazri, Syania Aldila, M. Fakhriza, and Adnan Buyung Nasution. "Web-Based Inventory Management System Using First In First Out Algorithm." Jurnal Penelitian Medan Agama 15, no. 1 (2024): 104. http://dx.doi.org/10.58836/jpma.v15i1.21276.
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<p>PT. Agung Selaras Group is a property company that operates in the business of selling houses. With a good sales management system, the property company can support its work activities. The aim of this research is to develop a system that can simplify stock management and minimize the risk of loss in the sales process. The data source for this research was obtained from direct observation and interviews with PT. Agung Selaras Group. In this system the author will combine the First In First Out method in managing incoming and outgoing product stock. The results of this research are that the system that has been designed can make it easier for managers to collect data on incoming and outgoing goods so that the risk of managing product stock can be minimized, and with computerized reports it can provide more precise, accurate and fast information. From the results of black box testing, the percentage of this application system can run well.</p>
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Kumalasari, Ira, Dyah Lestari, and Febrianto Alqodri. "Penggunaan Algoritma First In First Out dalam Antrian Pembimbingan Mahasiswa." Belantika Pendidikan 7, no. 2 (2024): 60–72. https://doi.org/10.47213/bp.v7i2.376.
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Abstract: The student advising application that utilizes the First In First Out (FIFO) algorithm has been successfully integrated with the Thesis and Final Project Information System (SISINTA) and the Administrative Information System (SIADMIN). This application manages the advising process by following the laboratory room scheduling workflow, starting with schedule input by the room staff, time plotting by the faculty, and student reservations. The FIFO algorithm ensures a fair and transparent advising order. The waterfall development method includes requirements analysis, design, implementation, and testing. The application supports reservation, verification, monitoring, and scheduling features, and operates 100 percent as expected, enhancing efficiency and transparency. Abstrak: Aplikasi pembimbingan mahasiswa yang menggunakan algoritma First In First Out (FIFO) telah berhasil terintegrasi dengan Sistem Informasi Skripsi dan Tugas Akhir (SISINTA) serta Sistem Informasi Administrasi (SIADMIN). Aplikasi ini mengelola proses bimbingan dengan mengikuti alur penjadwalan ruang laboratorium yang dimulai dari input jadwal oleh petugas ruangan, plotting waktu oleh dosen, hingga reservasi oleh mahasiswa. Algoritma FIFO memastikan urutan bimbingan yang adil dan transparan. Metode pengembangan waterfall yang digunakan meliputi analisis kebutuhan, desain, implementasi, dan pengujian. Aplikasi ini mendukung fitur reservasi, verifikasi, monitoring, dan penjadwalan, serta berfungsi 100 persen sesuai harapan, meningkatkan efisiensi dan transparansi.
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Putra, Muhammad Taufik Dwi, Haryanto Hidayat, Naziva Septian, and Tiara Afriani. "Analisis Perbandingan Algoritma Penjadwalan CPU First Come First Serve (FCFS) Dan Round Robin." Building of Informatics, Technology and Science (BITS) 3, no. 3 (2021): 207–12. http://dx.doi.org/10.47065/bits.v3i3.1047.
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CPU scheduling is important in multitasking and multiprocessing an operating system because of the many processes that need to be run in a computer. This causes the operating system to need to divide resources for running processes. CPU scheduling has several algorithms in it such as First Come First Serve (FCFS), Shortest Job First (SJF), Priority Scheduling, and Round Robin (RR) algorithms. The writing of this study is intended to compare the First Come First Serve and Round Robin algorithms with four specified parameters namely Average Turn Around Time, Waiting Time, Throughput, and CPU Utilization. The experiment was conducted with the First Come First Serve algorithm and the Round Robin of three different Quantum Times. These calculations at different quantum times aim to find out if the differences affect the advantages of the Round Robin algorithm over the First Come First Serve algorithm. The conclusion is that the First Come First Serve (FCFS) algorithm is superior to the Round Robin (RR) algorithm. This is indicated by the average turn around time, waiting time, and throughput values of the First Come First Serve algorithm more effective in running the process
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Liliosa Julpartin, Yuliana, and Hendra Kurniawan. "Implementation of First In First Out Algorithm in Management Information System at Hade Laundry." Antivirus : Jurnal Ilmiah Teknik Informatika 18, no. 1 (2024): 163–76. http://dx.doi.org/10.35457/antivirus.v18i1.3542.
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Utilization of information technology can encourage business activities in a better direction, including the laundry business. This business is growing very rapidly in densely populated areas, especially in big cities. This was triggered by changes in people's lifestyles and busy lives, making laundry services a practical solution. Hade laundry is a business unit that concentrates on laundry services in the city of Makassar. This business unit still uses manual recording, so it is very vulnerable to data loss and irregularities. An inefficient queuing system causes conflicts between customers and the laundry. Therefore, to handle this problem you can use the management information system at Hade Laundry. This system is designed using the waterfall method. Customer queue data collection uses the FIFO (First-In, First-Out) algorithm to maintain queue stability or sequence. The programming language used in designing this system is PHP and the CodeIgniter framework, and uses a MySQL database. The results of the research are a website-based management information system with the application of the FIFO algorithm. The implementation of this algorithm is able to manage customer queues well (organized and structured), so as to minimize the occurrence of conflicts between customers and laundry parties.
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Candra Pamungkas, Angga Riyandi Saputra, Aditya Ramadhan, Alif Kurniawan, Naufal Abi Pratama, and Wishnu Rindra. "Pernerapan Algoritma Multilevel Feedback Queue (MFQ) & First In First Out (FIFO) pada Studi Kasus di Toko Bunga ARTHA PUSPA." JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital 2, no. 2 (2023): 192–98. http://dx.doi.org/10.55123/jumintal.v2i2.2402.
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Artha Puspa is a flower shop in Madiun which sells plant needs. This very rapid business development encourages every entrepreneur to create a form that is different from other businesses, one of which is the Arta Puspa Flower Shop, a common problem that is often experienced by Artha Puspa, namely direct purchase queues and orders. With that we use a combination of MFQ and FIFO. The application of a combination of Multilevel Feedback Queue (MFQ) and First In First Out (FIFO) algorithms is a strategy that can be used to manage processes that occur in computer systems. MFQ is a scheduling algorithm that uses several levels of queues, each of which has a different priority. Each process will be placed in a queue level according to its priority. Meanwhile, FIFO is a scheduling algorithm that manages processes by issuing processes that apply a combination of multilevel feedback queue (MFQ) & first in first out (FIFO) algorithms in the case study of the Bunga Artha Puspa store to enter the system for the first time. The combination of the two algorithms can provide a more effective solution in managing processes in computer systems. MFQ is a scheduling algorithm that uses several levels of queues, each of which has a different priority. Each process will be placed in a queue level according to its priority. Meanwhile, FIFO is a scheduling algorithm that manages processes by issuing processes that apply a combination of multilevel feedback queue (MFQ) & first in first out (FIFO) algorithms in the case study of the Bunga Artha Puspa store to enter the system for the first time. The combination of the two algorithms can provide a more effective solution in managing processes in computer systems. MFQ can be used to manage high priority processes, while FIFO can be used to manage low priority processes. Thus, processes that have high priority will always be processed first, thereby increasing system efficiency. In addition, the combination of MFQ and FIFO can also help reduce the waiting time for processes that have low priority, thereby increasing user satisfaction.
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Hertog, Maarten L. A. T. M., Ismail Uysal, Ultan McCarthy, Bert M. Verlinden, and Bart M. Nicolaï. "Shelf life modelling for first-expired-first-out warehouse management." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2017 (2014): 20130306. http://dx.doi.org/10.1098/rsta.2013.0306.
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In the supply chain of perishable food products, large losses are incurred between farm and fork. Given the limited land resources and an ever-growing population, the food supply chain is faced with the challenge of increasing its handling efficiency and minimizing post-harvest food losses. Huge value can be added by optimizing warehouse management systems, taking into account the estimated remaining shelf life of the product, and matching it to the requirements of the subsequent part of the handling chain. This contribution focuses on how model approaches estimating quality changes and remaining shelf life can be combined in optimizing first-expired-first-out cold chain management strategies for perishable products. To this end, shelf-life-related performance indicators are used to introduce remaining shelf life and product quality in the cost function when optimizing the supply chain. A combinatorial exhaustive-search algorithm is shown to be feasible as the complexity of the optimization problem is sufficiently low for the size and properties of a typical commercial cold chain. The estimated shelf life distances for a particular batch can thus be taken as a guide to optimize logistics.
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Nababan, Marlince NK, Windania Purba, and Evta Indra. "The Tuition Payment Queuing System Uses Android-Based First in First Out (FIFO) Algorithm." IOP Conference Series: Earth and Environmental Science 748, no. 1 (2021): 012038. http://dx.doi.org/10.1088/1755-1315/748/1/012038.
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Abstract Queuing is an important component of a process in service. Queues are formed in a company or institution due to customers. Disorderly queues are a big problem for all concerned. Where, disorderly queues occur at University Prima Indonesia at the time of tuition payment so that the campus has to carry out a crowded queue process and students have to stand waiting for the next call resulting in less effective and efficient even waste of energy for students and employees. This research designed a system of tuition payment queues using the First In First Out (FIFO) algorithm which aims to reduce the time students are queuing at the checkout at the time of tuition payment so as not to wait too long so that the time of students and campus employees is not wasted too much and reduce the crowded queue time. The result of this study is an android-based tuition payment system, which is useful for reducing student build up when paying tuition. Thus it can be said that the calculation result of P0 queue has a result of 0.25%, and the number of customers 3 people, the average customer in the queue has a value of 2.25, the total customer time is 20 minutes, and the average customer time in the row is 15 minutes, the server busy time is 0.75, and the server’s empty time is 0.25%.
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Yu, H., S. Ruepp, and M. S. Berger. "Enhanced first-in-first-out-based round-robin multicast scheduling algorithm for input-queued switches." IET Communications 5, no. 8 (2011): 1163–71. http://dx.doi.org/10.1049/iet-com.2010.0378.
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Sadiah, Halimah Tus, Delta Hadi Purnama, and Muhamad Saad Nurul Ishlah. "Implementation of the First In First Out (FIFO) Algorithm in the Sandal and Shoe Product Inventory (Stock) Application." International Journal of Quantitative Research and Modeling 5, no. 1 (2024): 31–39. http://dx.doi.org/10.46336/ijqrm.v5i1.552.
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This study addresses the optimization of inventory management for sandal and shoe products, at CV Diva Karya Mandiri Warehouse, which covers of five key features: a dashboard, master data management, transaction data, reporting, and user management. The First In First Out (FIFO) algorithm is specifically applied to the transaction feature, ensuring timely disbursement in line with the order of receipt. It is implemented using Rapid Application Development (RAD) methodology, which consists of Planning Requirements, User Design, Construction, and Cutover phases. The developed inventory application offers two access levels: administrators with comprehensive access and warehouse managers with limited access for viewing, searching, and filtering item data. This study successfully implementing the FIFO algorithm, with 95% Blackbox testing result achieved through boundary value analysis approach.Top of Form
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Maspaeni, Karina Nurwijayanti, Ahmad Yani, and Haikal Rosidi. "DESIGN AND BUILD AN OUTDOOR EQUIPMENT RENTAL INFORMATION SYSTEM BY APPLYING THE FIRST IN FIRST OUT ALGORITHM." JSiI (Jurnal Sistem Informasi) 10, no. 2 (2023): 103–8. http://dx.doi.org/10.30656/jsii.v10i2.7585.
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The rental system currently implemented at Mandala Outdoor Equipement requires customers who want to rent outdoor equipment to come directly or via telephone/WA communication to Mandala Outdoor Equipement. Rental of outdoor equipment sometimes causes problems, such as customers who are disappointed because they were previously confirmed to be able to rent outdoor equipment, after receiving information that they could not or that it was canceled by the provider because it turned out the stock had run out, even though this happens. After all, sometimes they prioritize renters with proximity factors because of the courage of new renters. with higher rental costs. Based on these existing problems, this research aims to build a website-based information system by applying the First in First Out (FIFO) algorithm for outdoor equipment rental at Mandala Outdoor Equipment. The method used in this research is the waterfall method. The result of this research is an outdoor equipment rental application by applying the FIFO algorithm to the web-based Mandala Outdoor Equipment so that rentals can be done via the website (anywhere and at any time) and rentals are served according to the rental time sequence (First in First Out). From the results of testing the application using a separate black box, seen from the functional aspect, both features and access rights, everything went well, successfully, and validly.
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Collins, Donald W., Tabut Torsiaa, and Robert Balgemann. "A simulation study to compare Minimum Inventory Variability Policies (MIVP ® ) and First-In-First-Out (FIFO) algorithm." IFAC Proceedings Volumes 32, no. 2 (1999): 461–66. http://dx.doi.org/10.1016/s1474-6670(17)56079-6.
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Kim, Seongjai. "3‐D eikonal solvers: First‐arrival traveltimes." GEOPHYSICS 67, no. 4 (2002): 1225–31. http://dx.doi.org/10.1190/1.1500384.
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The article is concerned with the development and comparison of three different algorithms for the computation of first‐arrival traveltimes: the fast marching method (FMM), the group marching method (GMM), and a second‐order finite‐difference eikonal solver. GMM is introduced as a variant of FMM. It proceeds the solution by advancing a selected group of grid points at a time, rather than sorting the solution in the narrow band to march forward a single grid point. The second‐order eikonal solver studied in the article is an expanding‐box, essentially nonoscillatory scheme for which the stability is enforced by the introduction of a down ‘n’ out marching and a post‐sweeping iteration. Techniques such as the maximum angle condition, the average normal velocity, and cache‐based implementation are introduced for the algorithms to improve the numerical accuracy and efficiency. The algorithms are implemented for solving the eikonal equation in 3‐D isotropic media, and their performances are compared. GMM is numerically verified to be faster than FMM. However, the second‐order algorithm turns out to be superior to these first‐order level‐set methods in both accuracy and efficiency; the incorporation of average normal velocity improves accuracy dramatically for the second‐order scheme.
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Bonifacius Vicky Indriyono and Widyatmoko. "Optimization of Breadth-First Search Algorithm for Path Solutions in Mazyin Games." International Journal of Artificial Intelligence & Robotics (IJAIR) 3, no. 2 (2021): 58–66. http://dx.doi.org/10.25139/ijair.v3i2.4256.
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A game containing elements of artificial intelligence, of course, requires an algorithm in its application. One example of a game that includes elements of artificial intelligence is the Labyrinth game. Maze is a simple educational game. This game is known as finding a way out of the maze to arrive at a predetermined goal. The labyrinth encounters numerous obstacles along the way, such as dead ends and parapets, to reach the target location. In this game, players are required to think logically about how to find the right maze path. The obstacle faced in this game is that sometimes players have difficulty finding a way out, especially if the game level has reached a high level in the process of finding a way out. To solve this problem, a graph tracing technique is needed. The Breadth-First Search (BFS) strategy can be used in conjunction with various graph search algorithms. An example of a broad search method is the Breadth-First Search Algorithm, which works by visiting nodes at level n first before moving on to nodes at level n+1. The advantage of the Breadth-First Search algorithm is that it can find a solution as the shortest path and find the minimum solution if there is more than one solution. This study will discuss how to find a path for the Labyrinth using the BFS algorithm. The result of applying this BFS algorithm is the shortest route solution raised so that the Labyrinth can arrive at the destination point through the route provided.
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Chaudhary, Kaylash, Avinesh Prasad, Vishal Chand, and Bibhya Sharma. "ACO-Kinematic: a hybrid first off the starting block." PeerJ Computer Science 8 (March 15, 2022): e905. http://dx.doi.org/10.7717/peerj-cs.905.
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The use of robots in carrying out various tasks is popular in many industries. In order to carry out a task, a robot has to move from one location to another using shorter, safer and smoother route. For movement, a robot has to know its destination, its previous location, a plan on the path it should take, a method for moving to the new location and a good understanding of its environment. Ultimately, the movement of the robot depends on motion planning and control algorithm. This paper considers a novel solution to the robot navigation problem by proposing a new hybrid algorithm. The hybrid algorithm is designed by combining the ant colony optimization algorithm and kinematic equations of the robot. The planning phase in the algorithm will find a route to the next step which is collision free and the control phase will move the robot to this new step. Ant colony optimization is used to plan a step for a robot and kinematic equations to control and move the robot to a location. By planning and controlling different steps, the hybrid algorithm will enable a robot to reach its destination. The proposed algorithm will be applied to multiple point-mass robot navigation in a multiple obstacle and line segment cluttered environment. In this paper, we are considering a priori known environments with static obstacles. The proposed motion planning and control algorithm is applied to the tractor-trailer robotic system. The results show a collision and obstacle free navigation to the target. This paper also measures the performance of the proposed algorithm using path length and convergence time, comparing it to a classical motion planning and control algorithm, Lyapunov based control scheme (LbCS). The results show that the proposed algorithm performs significantly better than LbCS including the avoidance of local minima.
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Zhang, Xiaoyu, Dong Zhang, Qiong Chen, and Yan Yang. "Second-order scalar wave field modeling with a first-order perfectly matched layer." Solid Earth 9, no. 6 (2018): 1277–98. http://dx.doi.org/10.5194/se-9-1277-2018.
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Abstract. The forward modeling of a scalar wave equation plays an important role in the numerical geophysical computations. The finite-difference algorithm in the form of a second-order wave equation is one of the commonly used forward numerical algorithms. This algorithm is simple and is easy to implement based on the conventional grid. In order to ensure the accuracy of the calculation, absorption layers should be introduced around the computational area to suppress the wave reflection caused by the artificial boundary. For boundary absorption conditions, a perfectly matched layer is one of the most effective algorithms. However, the traditional perfectly matched layer algorithm is calculated using a staggered grid based on the first-order wave equation, which is difficult to directly integrate into a conventional-grid finite-difference algorithm based on the second-order wave equation. Although a perfectly matched layer algorithm based on the second-order equation can be derived, the formula is rather complex and intermediate variables need to be introduced, which makes it hard to implement. In this paper, we present a simple and efficient algorithm to match the variables at the boundaries between the computational area and the absorbing boundary area. This new boundary-matched method can integrate the traditional staggered-grid perfectly matched layer algorithm and the conventional-grid finite-difference algorithm without formula transformations, and it can ensure the accuracy of finite-difference forward modeling in the computational area. In order to verify the validity of our method, we used several models to carry out numerical simulation experiments. The comparison between the simulation results of our new boundary-matched algorithm and other boundary absorption algorithms shows that our proposed method suppresses the reflection of the artificial boundaries better and has a higher computational efficiency.
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Li, Si-Chen, Bang-Ying Tang, Han Zhou, et al. "First Request First Service Entanglement Routing Scheme for Quantum Networks." Entropy 24, no. 10 (2022): 1404. http://dx.doi.org/10.3390/e24101404.
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Quantum networks enable many applications beyond the reach of classical networks by supporting the establishment of long-distance entanglement connections, and are already stepped into the entanglement distribution network stage. The entanglement routing with active wavelength multiplexing schemes is urgently required for satisfying the dynamic connection demands of paired users in large-scale quantum networks. In this article, the entanglement distribution network is modeled into a directed graph, where the internal connection loss among all ports within a node is considered for each supported wavelength channel, which is quite different to classical network graphs. Afterwards, we propose a novel first request first service (FRFS) entanglement routing scheme, which performs the modified Dijkstra algorithm to find out the lowest loss path from the entangled photon source to each paired user in order. Evaluation results show that the proposed FRFS entanglement routing scheme can be applied to large-scale and dynamic topology quantum networks.
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Rodríguez Maya, Cinthia, Carlos Gershenson García, and Helena Montserrat Gómez Adorno. "A similarity Based Algorithm for Predicting Academic Success in First-year Undergraduates." International Journal of Combinatorial Optimization Problems and Informatics 16, no. 1 (2025): 177–89. https://doi.org/10.61467/2007.1558.2025.v16i1.551.
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According to the European Commission, “Early school leaving is linked to unemployment, social exclusion, poverty, and poor health” (European Commission, 2024). Due to the importance of reducing school drop-out rates, several authors have analyzed this phenomenon. Before the boom of Artificial Intelligence, instead of using or implementing programming methods, researchers applied written formulas and rudimentary graphical visualizations to predict academic completion and the main factors behind it; besides, the development of Machine Learning (ML) algorithms has enhanced the precision and performance of an ample variety of investigations including the educational field. In this paper, we use a dataset of undergraduate-level students at the Universidad Nacional Autónoma de Mexico (UNAM) to predict timely academic completion. We use seven common ML algorithms and propose a novel algorithm based on students' similarities according to the most relevant features in common. This algorithm shows a higher precision than some traditional categorical ML algorithms. This innovative way to predict academic success can support educators, pedagogues, and policymakers make better decisions at UNAM.
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Indriyono, Bonifacius, and Widyatmoko. "Analysis of A* Algorithm Optimization and Breadth First Search in the Water Teapot Game." Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi 7, no. 2 (2022): 88–95. http://dx.doi.org/10.25139/inform.v7i2.4484.
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Artificial Intelligence (AI) is a branch of computer science that focuses on learning how computers can work or perform as well as humans or even better than humans. The development of artificial intelligence can be used as a benchmark for technological developments. Many problems can be solved using this artificial intelligence concept. One of them is a water jug logic game. The water jugs problem is a game requiring converting a situation into another desired situation using a certain set of operations. The objective of this game is for players to develop their deductive reasoning skills by figuring out how to move x litters of water from one teapot to another. To accomplish this, they will refer to the beginning value that has to be filled in each teapot and the end value that needs to be filled in each teapot. Using the A* algorithm and the Breadth-First Search (BFS) algorithm, which both fall under the umbrella of artificial intelligence, it is possible to find a solution to this issue. The A* algorithm is a Best First Search algorithm that combines Uniform Cost Search and Greedy Best-First Search, while the Breadth-First Search algorithm is a graph search algorithm that performs a wide search at each level. This study analyzed the effectiveness of the A* and BFS algorithms in solving the water jug logic problem, both from the number of steps and the time required for completion. The results of the tests were carried out, and it is known that the BFS algorithm is more effective than the A* algorithm because the BFS algorithm can provide a number of alternative solutions to the water jug logic problem with various conditions.
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Putri, Raissa Amanda. "Aplikasi Simulasi Algoritma Penjadwalan Sistem Operasi." Jurnal Teknologi Informasi 5, no. 1 (2021): 98–102. http://dx.doi.org/10.36294/jurti.v5i1.2215.
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Abstract - In the operating system course, various scheduling algorithms with complex calculations are studied. The scheduling algorithms that are often used are FIFO (First-in, first out) or FCFS (first come, first serve), SJF (Shortest Job First), RR (Round robin) and SRF (Shortest remaining first). Unfortunately, the scheduling algorithm learning method often only uses the Gantt Chart as a tool for its calculations. For this reason, the researcher intends to design and build a desktop-based operating system scheduling algorithm simulation application as a learning medium for operating system courses. The application built can simulate four types of queues, namely FIFO (First-in, first out) or FCFS (first come, first serve), SJF (Shortest Job First), RR (Round robin) and SRF (Shortest remaining first). This application performs a simulation by calculating the start time, completion time, response time and waiting time for each process. In addition, the system also produces the results of the average response time and average waiting time, as well as a gantt chart of the entire process.Keywords - Application, Simulation, Operating System, Scheduling Algorithm. Abstrak - Dalam mata kuliah sistem operasi, berbagai algoritma penjadwalan dengan perhitungan yang kompleks dipelajari. Algoritma penjadwalan yang sering digunakan adalah FIFO (First-in, first out) atau FCFS (first come, first serve), SJF (Shortest Job First), RR (Round robin) dan SRF (Shortest Remaining First). Sayangnya, metode pembelajaran algoritma penjadwalan seringkali hanya menggunakan Gantt Chart sebagai alat bantu perhitungannya. Untuk itu peneliti merancang dan membangun aplikasi simulasi algoritma penjadwalan sistem operasi berbasis desktop sebagai media pembelajaran mata kuliah sistem operasi. Aplikasi yang dibangun dapat mensimulasikan empat jenis antrian yaitu FIFO (First-in, first out) atau FCFS (first come, first serve), SJF (Shortest Job First), RR (Round robin) dan SRF (Shortest remaining first). Aplikasi ini melakukan simulasi dengan menghitung saat mulai, saat rampung, lama tanggap dan lama tunggu masing-masing proses. Selain itu, sistem juga mengeluarkan hasil rata-rata lama tanggap dan rata-rata waktu tunggu, serta gantt chart dari keseluruhan proses.Kata Kunci - Aplikasi, Simulasi, Sistem Operasi, Algoritma Penjadwalan.
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Birkun, A. A., L. I. Dezhurny, and A. A. Raevskiy. "Foreign Body Airway Obstruction: Modern Principles and Approaches to First Aid and Dispatcher Assistance on First Aid." Russian Sklifosovsky Journal "Emergency Medical Care" 12, no. 2 (2023): 299–308. http://dx.doi.org/10.23934/2223-9022-2023-12-2-299-308.
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Foreign body airway obstruction (FBAO) is one of the most common causes of accidental death in adults and children. Probability of saving a life in severe FBAO depends on the ability of the bystander to quickly recognize the problem and correctly provide first aid (FA) to the victim. However, due to the lack of knowledge and skills of the FA, bystanders rarely attempt to give necessary help. Along with mass FA training, provision of instructions on the FA to untrained bystanders over the telephone by emergency medical services (EMS) dispatchers can facilitate active involvement of the population in the process of providing FA. In this study, a detailed analysis of the modern principles and approaches to the provision of the FA in FBAO was carried out and a draft of a universal Russian-language algorithm for remote dispatch support of the FA was developed. The developed algorithm can become a component of the domestic program for remotely instructing the population on provision of FA in life-threatening conditions and is proposed for further testing and implementation in the practice of EMS dispatchers.
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Ahmadi, Abdeslam, Faissal El Bouanani, Hussain Ben-Azza, and Youssef Benghabrit. "Reduced Complexity Iterative Decoding of 3D-Product Block Codes Based on Genetic Algorithms." Journal of Electrical and Computer Engineering 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/609650.
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Two iterative decoding algorithms of 3D-product block codes (3D-PBC) based on genetic algorithms (GAs) are presented. The first algorithm uses the Chase-PyndiahSISO, and the second one uses the list-basedSISOdecoding algorithm (LBDA) based on order- reprocessing. We applied these algorithms overAWGNchannel to symmetric3D-PBCconstructed fromBCHcodes. The simulation results show that the first algorithm outperforms the Chase-Pyndiah one and is only 1.38 dB away from the Shannon capacity limit at BER of forBCH(31, 21, 5)3and 1.4 dB forBCH(16, 11, 4)3. The simulations of the LBDA-basedGAon theBCH(16, 11, 4)3show that its performances outperform the first algorithm and is about 1.33 dB from the Shannon limit. Furthermore, these algorithms can be applied to any arbitrary 3D binary product block codes, without the need of a hard-in hard-out decoder. We show also that the two proposed decoders are less complex than both Chase-Pyndiah algorithm for codes with large correction capacity and LBDA for large parameter. Those features make the decoders based on genetic algorithms efficient and attractive.
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Teng, Shaohua, Wei Zhang, Haibin Zhu, Xiufen Fu, Jiangyi Su, and Baoliang Cui. "A Least-Laxity-First Scheduling Algorithm of Variable Time Slice for Periodic Tasks." International Journal of Software Science and Computational Intelligence 2, no. 2 (2010): 86–104. http://dx.doi.org/10.4018/jssci.2010040105.
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The LLF (Least Laxity First) scheduling algorithm assigns a priority to a task according to its executing urgency. The smaller the laxity value of a task is, the sooner it needs to be executed. When two or more tasks have same or approximate laxity values, LLF scheduling algorithm leads to frequent switches among tasks, causes extra overhead in a system, and therefore, restricts its application. The least switch and laxity first scheduling algorithm is proposed in this paper by searching out an appropriate common divisor in order to improve the LLF algorithm for periodic tasks.
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Abbas, Safana Hyder, Wedad Abdul Khuder Naser, and Lamyaa Mohammed Kadhim. "Study and Comparison of Replacement Algorithms." International Journal of Engineering Research and Advanced Technology 08, no. 08 (2022): 01–06. http://dx.doi.org/10.31695/ijerat.2022.8.8.1.
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When a page fault occurs, the operating system has to choose a page to remove from memory to make room for the page that has to be brought in. The page replacement is done by swapping the required pages from backup storage to main memory and vice-versa. When a new page needs memory for allocation, page replacement algorithms decide which pages to swap out of the memory. In this paper, a comparison and analysis of five replacement algorithms: First in First out (FIFO), Least Recently Used (LRU), Clock, Most Recently Used algorithm (MRU), and Optimal Page Replacement (OPT) are made.
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Bernov, Muhammad Fahreal, Ani Dijah Rahajoe, and Budi Mukhamad Mulyo. "Route Optimization of Waste Carrier Truck using Breadth First Search (BFS) Algorithm." JEECS (Journal of Electrical Engineering and Computer Sciences) 7, no. 2 (2023): 1293–304. http://dx.doi.org/10.54732/jeecs.v7i2.23.
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Waste problems have always been the main focus which still occurs in cities and regencies in Indonesia, andalso Sidoarjo Regency is no exception. Increasingly rapid population growth is one of the factors in the increasingpiles of waste in Sidoarjo Regency. The large number of villages with long distances and a large area means that wastecollection cannot be carried out on time, causing accumulation of waste that disrupts residents' daily activities. Thewaste transportation system in Sidoarjo Regency has so far not been optimal because there are still several problemswith the accumulation of waste in several sub-districts.In this study, an optimal route search system was created using the Breadth First Search and Depth First SearchAlgorithms as a search comparison in order to make it easier for Sanitation Service officers to carry out the wastetransportation process by considering the optimal destination location route according to input from the user. Theresults of this study will display information on the comparison of the total distance traveled and the total volumetraveled by the Breadth First Search and Depth First Search algorithms with different differences.
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Ha, Seung-Yeal, Shi Jin, and Doheon Kim. "Convergence of a first-order consensus-based global optimization algorithm." Mathematical Models and Methods in Applied Sciences 30, no. 12 (2020): 2417–44. http://dx.doi.org/10.1142/s0218202520500463.
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Global optimization of a non-convex objective function often appears in large-scale machine learning and artificial intelligence applications. Recently, consensus-based optimization (CBO) methods have been introduced as one of the gradient-free optimization methods. In this paper, we provide a convergence analysis for the first-order CBO method in [J. A. Carrillo, S. Jin, L. Li and Y. Zhu, A consensus-based global optimization method for high dimensional machine learning problems, https://arxiv.org/abs/1909.09249v1 ]. Prior to this work, the convergence study was carried out for CBO methods on corresponding mean-field limit, a Fokker–Planck equation, which does not imply the convergence of the CBO method per se. Based on the consensus estimate directly on the first-order CBO model, we provide a convergence analysis of the first-order CBO method [J. A. Carrillo, S. Jin, L. Li and Y. Zhu, A consensus-based global optimization method for high dimensional machine learning problems, https://arxiv.org/abs/1909.09249v1 ] without resorting to the corresponding mean-field model. Our convergence analysis consists of two steps. In the first step, we show that the CBO model exhibits a global consensus time asymptotically for any initial data, and in the second step, we provide a sufficient condition on system parameters — which is dimension independent — and initial data which guarantee that the converged consensus state lies in a small neighborhood of the global minimum almost surely.
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Nugroho, Rizky Dwi, Anjik Sukmaaji, Endra Rahmawati, Arifin Pujiwidodo, and Teguh Sutanto. "New Selection Algorithm on Priority Service for Certification Queue Service Information System in BARISTRAND." JUITA : Jurnal Informatika 10, no. 2 (2022): 201. http://dx.doi.org/10.30595/juita.v10i2.13728.
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Queue management for product certification of perishable goods is a major problem faced by the Surabaya Industrial Standardization and Research Institute (BARISTAND). The purpose of this study is to combine the use of the First in first out (FIFO), First Expired First Out (FEFO) and Least Shelf Life First Out (LSFO) methods into an automatic queuing system that can ensure effective service performance in queue management. This research was conducted using qualitative methods with observations to collect data and processes about how the product certification queue process flow at the Surabaya Industrial Standardization and Research Institute (BARISTRAN). The results show that the service only requires an average service completion time of 0.14 products per minute, meaning that every hour it can serve approximately 8.4 products. The conclusion of the research system has succeeded in determining the queue based on the use of the First in first out (FIFO), First Expired First Out (FEFO) and Least Shelf Life First Out (LSFO) methods, and customers can perform the tracking process to find out the certification process for the registered products.
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Llorens, M., J. Oliver, J. Silva, and S. Tamarit. "Maximal and Minimal Dynamic Petri Net Slicing." Fundamenta Informaticae 188, no. 4 (2023): 239–67. http://dx.doi.org/10.3233/fi-222148.
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Context: Petri net slicing is a technique to reduce the size of a Petri net to ease the analysis or understanding of the original Petri net. Objective: Presenting two new Petri net slicing algorithms to isolate those places and transitions of a Petri net (the slice) that may contribute tokens to one or more places given (the slicing criterion). Method: The two algorithms proposed are formalized. The maximality of the first algorithm and the minimality of the second algorithm are formally proven. Both algorithms together with three other state-of-the-art algorithms have been implemented and integrated into a single tool so that we have been able to carry out a fair empirical evaluation. Results: Besides the two new Petri net slicing algorithms, a public, free, and open-source implementation of five algorithms is reported. The results of an empirical evaluation of the new algorithms and the slices they produce are also presented. Conclusions: The first algorithm collects all places and transitions that may contribute tokens (in any computation) to the slicing criterion, while the second algorithm collects the places and transitions needed to fire the shortest transition sequence that contributes tokens to some place in the slicing criterion. Therefore, the net computed by the first algorithm can reproduce any computation that contributes tokens to any place of interest. In contrast, the second algorithm loses this possibility, but it often produces a much more reduced subnet (which still can reproduce some computations that contribute tokens to some places of interest). The first algorithm is proven maximal, and the second one is proven minimal.
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Zhuang, Hongbin, Jou-Ming Chang, Xiao-Yan Li, Fangying Song, and Qinying Lin. "All-to-All Broadcast Algorithm in Galaxyfly Networks." Mathematics 11, no. 11 (2023): 2459. http://dx.doi.org/10.3390/math11112459.
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The design of interconnection networks is a fundamental aspect of high-performance computing (HPC) systems. Among the available topologies, the Galaxyfly network stands out as a low-diameter and flexible-radix network for HPC applications. Given the paramount importance of collective communication in HPC performance, in this paper, we present two different all-to-all broadcast algorithms for the Galaxyfly network, which adhere to the supernode-first rule and the router-first rule, respectively. Our performance evaluation validates their effectiveness and shows that the first algorithm has a higher degree of utilization of network channels, and that the second algorithm can significantly reduce the average time for routers to collect packets from the supernode.
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Yudaeva, Yu. "Role of simulation equipment in the formation process of cardiopulmonary resuscitation skills among the population in the volume of first aid." Bulletin of Science and Practice 4, no. 4 (2018): 30–38. https://doi.org/10.5281/zenodo.1218211.
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The aim of the study was to establish the role of simulation equipment in mastering the skills of cardiopulmonary resuscitation in the volume of first aid. Materials and methods: 2 groups of students formed CPR skills during traditional practical training and simulation trainings. Conclusion. For successful carrying out CPR requires a clear knowledge of the algorithm. The simulation form of the educational process, in which the student acts in a specially created simulated environment, is the most acceptable.
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DAESCU, OVIDIU, and JUN LUO. "CUTTING OUT POLYGONS WITH LINES AND RAYS." International Journal of Computational Geometry & Applications 16, no. 02n03 (2006): 227–48. http://dx.doi.org/10.1142/s0218195906002014.
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We present approximation algorithms for cutting out a polygon P with n vertices from another convex polygon Q with m vertices by line cuts and ray cuts. For line cuts we require both P and Q are convex while for ray cuts we require Q is convex and P is ray cuttable. Our results answer a number of open problems and are either the first solutions or significantly improve over previously known solutions. For the line cutting version, we prove a key property that leads to a simple, constant factor approximation algorithm. For the ray cutting version, we prove it is possible to compute in almost linear time a cutting sequence that is an O( log 2 n)-factor approximation of an optimal cutting sequence. No algorithms were previously known for the ray cutting version.
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K., Thamizhmaran. "Wireless Networks using Scheduling Techniques in Wireless MANET." Advancement and Research in Instrumentation Engineering 7, no. 3 (2024): 98–106. https://doi.org/10.5281/zenodo.14233852.
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<em>Mobile ad hoc networks are multi-hop wireless networks that are self-organizing and self-configuring, with a dynamically changing network structure. The primary cause of this is the nodes' mobility. Ad-hoc networking is becoming more and more significant due to the proliferation of portable devices and advancements in wireless communication, as well as the growing number of widely used applications. MANET has a wide range of applications, from tiny, static networks with power source constraints to large-scale, mobile, extremely dynamic networks. This study employs a Scheduling Algorithm to identify the rogue node. The primary goals of scheduling algorithms are to guarantee equity for all parties using the resources and to reduce resource famine. The issue of choosing which of the pending requests should receive resources is addressed by scheduling. The First In First Out (FIFO) algorithm is one of the useful algorithms that is employed. FIFO will prevent network path collisions and the sending of phony routes. The effectiveness of the First in First out (FIFO) scheduling method is examined in this article.</em> <strong><em> </em></strong>
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Arwan, Achmad, and Denny Sagita. "Automation Of Independent Path Searching using Depth First Search." Journal of Information Technology and Computer Science 3, no. 1 (2018): 104. http://dx.doi.org/10.25126/jitecs.20183162.
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In a basis path testing, there are independent paths that must be passed/tested at least once to make sure there are no errors in the code and ensure all pseudocode have implemented on the code. Previously, the independent path was generated using the Genetic Algorithm, but the number of iterations influenced the likelihood of the emergence of the corresponding the independent path. Besides, the pseudocode was also unable to be used directly since it must be implemented first, this makes finding an independent path longer because it has to implement the code. This research aims to find out how to find the independent path directly from pseudocode using a graph and how well the Depth First Search algorithm in finding the independent path. It was chosen because it was able to find the paths from a point to a particular point in a graph. The result of the system accuracy test was able to find the correct independent path as much as 52 from 76 test data, where the result of accuracy is 68.4% on average.
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Jeevitha, J. K., and Athisha G. "Energy-Efficient Virtualized Scheduling and Load Balancing Algorithm in Cloud Data Centers." International Journal of Information Retrieval Research 11, no. 3 (2021): 34–48. http://dx.doi.org/10.4018/ijirr.2021070103.
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To scale back the energy consumption, this paper proposed three algorithms: The first one is identifying the load balancing factors and redistribute the load. The second one is finding out the most suitable server to assigning the task to the server, achieved by most efficient first fit algorithm (MEFFA), and the third algorithm is processing the task in the server in an efficient way by energy efficient virtual round robin (EEVRR) scheduling algorithm with FAT tree topology architecture. This EEVRR algorithm improves the quality of service via sending the task scheduling performance and cutting the delay in cloud data centers. It increases the energy efficiency by achieving the quality of service (QOS).
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Muhimmatul Mahmuda, Anita Andriani, Reza Augusta Jannatul Firdaus, and Ahmad Heru Mujianto. "SISTEM INFORMASI PELAYANAN BANK SAMPAH LEBAK INDAH BERBASIS WEBSITE DENGAN MENGGUNAKAN ALGORITMA FIRST IN FIRST OUT (STUDI KASUS BANK SAMPAH DESA LEBAK)." Inovate : Jurnal Ilmiah Inovasi Teknologi Informasi 9, no. 2 (2025): 96–103. https://doi.org/10.33752/inovate.v9i2.8879.
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The lebak Indah waste bank server information system has several activities, including customer service, customer registration, queues as well as depositing and withdrawing balances. The purpose of creating a waste bank service information system is to help the performance of officers and customer queues at the beautiful waste bank. Queue can be interpreted as steps starting from the moment the customer arrives, waiting for service, and getting service. An unstructured queue system can interfere with the service well. However, together because of the current development of information technology, there have been many developments in the queue system. The purpose of this research is to design and develop data systems. Web-based beautiful lebak waste bank service with case studies found in Lebak Village garbage bank. The garbage bank service is on the object sometimes causing long and irregular queues, especially when the time of weighing waste causes customers to be crammed to queue. Based on the description of the problem, researchers are interested in developing and building a Web-Based Lebak Indah Waste Bank Service Information System with the Help of FIFO Algorithm (Case Study of Lebak Village Waste Bank). FIFO is a method to solve queue problems that may be applied as the first way to enter is considered as the first way to exit. Keywords: Information System, Service, Queue, Website, First In First Out
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Kim, JunSeong. "Feature-First Add-On for Trajectory Simplification in Lifelog Applications." Sensors 20, no. 7 (2020): 1852. http://dx.doi.org/10.3390/s20071852.
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Lifelog is a record of one’s personal experiences in daily lives. User’s location is one of the most common information for logging a human’s life. By understanding one’s spatial mobility we can figure out other pieces of context such as businesses and activities. With GPS technology we can collect accurate spatial and temporal details of a movement. However, most GPS receivers generate a huge amount of data making it difficult to process and store such data. In this paper, we develop a generic add-on algorithm, feature-first trajectory simplification, to simplify trajectory data in lifelog applications. It is based on a simple sliding window mechanism counting occurrence of certain conditions. By automatically identifying feature points such as signal lost and found, stall, and turn, the proposed scheme provides rich context more than spatio-temporal information of a trajectory. In experiments with a case study of commuting in personal vehicles, we evaluate the effectiveness of the scheme. We find the proposed scheme significantly enhances existing simplification algorithms preserving much richer context of a trajectory.
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Ismaeel, Ayad Zedo, and Ibarhim M. I. Zebari. "Comparing Traversal Strategies: Depth-first Search vs. Breadth-first Search in Complex Networks." Asian Journal of Research in Computer Science 18, no. 2 (2025): 60–73. https://doi.org/10.9734/ajrcos/2025/v18i2562.
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This article compares and contrasts two basic graph traversal algorithms that are commonly employed in computational problem-solving and network research. Common applications of these algorithms include pathfinding, optimisation of network flows, collaborative exploration, and classification tasks. To find out how well they function with different types of datasets, network topologies, and issue domains, researchers have systematically reviewed previous works. We measured the efficiency of each solution using performance indicators like execution time, memory utilisation, and path length. According to the results, one approach is more effective in memory-constrained settings and deep searches, while the other is better at discovering the shortest paths and providing comprehensive coverage. Furthermore, the paper emphasises the advantages of hybrid techniques, which merge the best features of both algorithms to provide better results in specific cases. This comparison helps fill gaps in our knowledge of graph-based problem-solving methods and sheds light on how to choose the best traversal algorithms for different types of applications.
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Biner, Daniel W., Jason S. Grosch, and Peter J. Ortoleva. "B-cell epitope discovery: The first protein flexibility-based algorithm–Zika virus conserved epitope demonstration." PLOS ONE 18, no. 3 (2023): e0262321. http://dx.doi.org/10.1371/journal.pone.0262321.
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Antibody-antigen interaction–at antigenic local environments called B-cell epitopes–is a prominent mechanism for neutralization of infection. Effective mimicry, and display, of B-cell epitopes is key to vaccine design. Here, a physical approach is evaluated for the discovery of epitopes which evolve slowly over closely related pathogens (conserved epitopes). The approach is 1) protein flexibility-based and 2) demonstrated with clinically relevant enveloped viruses, simulated via molecular dynamics. The approach is validated against 1) seven structurally characterized enveloped virus epitopes which evolved the least (out of thirty-nine enveloped virus-antibody structures), 2) two structurally characterized non-enveloped virus epitopes which evolved slowly (out of eight non-enveloped virus-antibody structures), and 3) eight preexisting epitope and peptide discovery algorithms. Rationale for a new benchmarking scheme is presented. A data-driven epitope clustering algorithm is introduced. The prediction of five Zika virus epitopes (for future exploration on recombinant vaccine technologies) is demonstrated. For the first time, protein flexibility is shown to outperform solvent accessible surface area as an epitope discovery metric.
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Toledo, Franklina Maria Bragion de, and André Luís Shiguemoto. "Lot-sizing problem with several production centers." Pesquisa Operacional 25, no. 3 (2005): 479–92. http://dx.doi.org/10.1590/s0101-74382005000300010.
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In this paper, a case study is carried out concerning the lot-sizing problem involving a single item production planning in several production centers that do not present capacity constraints. Demand can be met with backlogging or not. This problem results from simplifying practical problems, such as the material requirement planning (MRP) system and also lot-sizing problems with multiple items and limited production capacity. First we propose an efficient implementation of a forward dynamic programming algorithm for problems with one single production center. Although this does not reduce its complexity, it has shown to be rather effective, according to computational tests. Next, we studied the problem with a production environment composed of several production centers. For this problem two algorithms are implemented, the first one is an extension of the dynamic programming algorithm for one production center and the second one is an efficient implementation of the first algorithm. Their efficiency are shown by computational testing of the algorithms and proposals for future research are presented.
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Qi, Han. "Application of Fuzzy Control Algorithm in First-order Inverted Pendulum System." Journal of Physics: Conference Series 2417, no. 1 (2022): 012038. http://dx.doi.org/10.1088/1742-6596/2417/1/012038.
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The inverted pendulum system is widely used in the study of control theory. There are many advantages of the inverted pendulum: the equipment is cheap, and it features a simple structure and easy regulation. But since the inverted pendulum system is also a typical nonlinear, multivariable system, it’s a really difficult thing to keep it stable. Because of this, it’s important to figure out a way to stabilize the system. More importantly, new control methods will be discovered during the process, and these new methods can be used in many other different systems. The inverted pendulum system can reflect performances such as robustness, mobility and tracking performance. Its dynamic condition is similar to a human walk, and its steady state is similar to the launch system on a rocket’s motion attitude, so the study of the inverted pendulum system is also important to the robot and rocket area. This paper describes the construction of a mathematical model of a first-order inverted pendulum, and the process of designing the fuzzy controller based on the related fuzzy control rules. It also conducts the optimization of the fuzzy controller using a genetic algorithm. After using MATLAB’s Simulink module to simulate the inverted pendulum system and adjust the parameters of the controller, the system could finally reach a stable status within a short period of time, from all kinds of original status, and have anti-jamming performance.
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Li, Ding, and Xin Cheng. "A First-Out Alarm Detection Method via Association Rule Mining and Correlation Analysis." Entropy 26, no. 1 (2023): 30. http://dx.doi.org/10.3390/e26010030.
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Alarm systems are commonly deployed in complex industries to monitor the operation status of the production process in real time. Actual alarm systems generally have alarm overloading problems. One of the major factors leading to excessive alarms is the presence of many correlated or redundant alarms. Analyzing alarm correlations will not only be beneficial to the detection of and reduction in redundant alarm configurations, but also help to track the propagation of abnormalities among alarm variables. As a special problem in correlated alarm detection, the research on first-out alarm detection is very scarce. A first-out alarm is known as the first alarm that occurs in a series of alarms. Detection of first-out alarms aims at identifying the first alarm occurrence from a large number of alarms, thus ignoring the subsequent correlated alarms to effectively reduce the number of alarms and prevent alarm overloading. Accordingly, this paper proposes a new first-out alarm detection method based on association rule mining and correlation analysis. The contributions lie in the following aspects: (1) An association rule mining approach is presented to extract alarm association rules from historical sequences based on the FP-Growth algorithm and J-Measure; (2) a first-out alarm determination strategy is proposed to determine the first-out alarms and subsequent alarms through correlation analysis in the form of a hypothesis test on conditional probability; and (3) first-out rule screening criteria are proposed to judge whether the rules are redundant or not and then consolidated results of first-out rules are obtained. The effectiveness of the proposed method is tested based on the alarm data generated by a public simulation platform.
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Attar, Hani, Mohammad R. Khosravi, Shmatkov Sergiy Igorovich, Kuchuk Nina Georgievan, and Mohammad Alhihi. "Review and performance evaluation of FIFO, PQ, CQ, FQ, and WFQ algorithms in multimedia wireless sensor networks." International Journal of Distributed Sensor Networks 16, no. 6 (2020): 155014772091323. http://dx.doi.org/10.1177/1550147720913233.
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The best service mechanism in multimedia wireless sensor networks can be achieved based on the multimedia traffic flow by developing a proper simulation algorithm process model, to be a trustable indication for real implementations, which is proposed in this article, together with the algorithm model outcome analysis. The quality estimation of the proposed mechanism is investigated by simulating real data transmission and obtaining the integral criterion of the processed mechanism, to determine the queue formation and loading control. Accordingly, it was proved that the first-in first-out algorithm is not useful as a flow algorithm; however, it is regarded as suitable to be considered as the benchmark algorithm when compared with the other algorithms such as priority queue, custom queue, fair queuing, and weighted fair queuing algorithms. Finally, each algorithm’s advantages and disadvantages were verified and the best usage conditions according to certain parameters, such as packet loss probability, average time delay, and jitter, were declared.
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Luo, Hui, Zhifeng Bao, Gao Cong, J. Shane Culpepper, and Nguyen Lu Dang Khoa. "Let Trajectories Speak Out the Traffic Bottlenecks." ACM Transactions on Intelligent Systems and Technology 13, no. 1 (2022): 1–21. http://dx.doi.org/10.1145/3465058.
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Traffic bottlenecks are a set of road segments that have an unacceptable level of traffic caused by a poor balance between road capacity and traffic volume. A huge volume of trajectory data which captures realtime traffic conditions in road networks provides promising new opportunities to identify the traffic bottlenecks. In this paper, we define this problem as trajectory-driven traffic bottleneck identification : Given a road network R , a trajectory database T , find a representative set of seed edges of size K of traffic bottlenecks that influence the highest number of road segments not in the seed set. We show that this problem is NP-hard and propose a framework to find the traffic bottlenecks as follows. First, a traffic spread model is defined which represents changes in traffic volume for each road segment over time. Then, the traffic diffusion probability between two connected segments and the residual ratio of traffic volume for each segment can be computed using historical trajectory data. We then propose two different algorithmic approaches to solve the problem. The first one is a best-first algorithm BF , with an approximation ratio of 1-1/ e . To further accelerate the identification process in larger datasets, we also propose a sampling-based greedy algorithm SG . Finally, comprehensive experiments using three different datasets compare and contrast various solutions, and provide insights into important efficiency and effectiveness trade-offs among the respective methods.
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Layak Ali, Et al. "Grey Wolf Cuckoo Search Algorithm for Training Feedforward Neural Network and Logic Gates Design." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 722–32. http://dx.doi.org/10.17762/ijritcc.v11i9.8865.
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This paper presents a new hybrid Swarm Intelligence (SI) algorithm based on the Cuckoo Search Algorithm (CSA) and Grey Wolf Optimizer (GWO) called the Grey Wolf Cuckoo Search (GWCS) algorithm. The GWCS algorithm extracts and combines CSA and GWO features for efficient optimization. To carry out the comprehensive validation, the developed algorithm is applied to three different scenarios with their counterparts. The first validation is carried out on standard optimization benchmark problems. Further, they are used to train Feedforward Neural Networks and finally applied to design logic gates. The comprehensive results are presented and it is found that the proposed GWCS algorithms perform better compared to the state-of-the-art.
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Teso-Fz-Betoño, Adrian, Ekaitz Zulueta, Mireya Cabezas-Olivenza, Unai Fernandez-Gamiz, and Carlos Botana-M-Ibarreta. "Modification of Learning Ratio and Drop-Out for Stochastic Gradient Descendant Algorithm." Mathematics 11, no. 5 (2023): 1183. http://dx.doi.org/10.3390/math11051183.
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The stochastic gradient descendant algorithm is one of the most popular neural network training algorithms. Many authors have contributed to modifying or adapting its shape and parametrizations in order to improve its performance. In this paper, the authors propose two modifications on this algorithm that can result in a better performance without increasing significantly the computational and time resources needed. The first one is a dynamic learning ratio depending on the network layer where it is applied, and the second one is a dynamic drop-out that decreases through the epochs of training. These techniques have been tested against different benchmark function to see their effect on the learning process. The obtained results show that the application of these techniques improves the performance of the learning of the neural network, especially when they are used together.
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Begum, I. Parvin, and I. Shahina Begam. "Finding Optimal Algorithm in Artificial Intelligence." International Journal of Computer Science and Mobile Computing 10, no. 7 (2021): 84–90. http://dx.doi.org/10.47760/ijcsmc.2021.v10i07.012.
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Present days many artificial intelligence search algorithms are plays a important to figure out the problem of shortest path finding. The paper presents the detailed study of heuristic search and blind search techniques. The paper focus additional in the direction of blind search strategies such as Breadth First Search, Depth First Search, and Uniform Cost Search and informed explore strategies like A*, and Best First Search. The paper consist of effective of search procedure, their qualities, and demerits, where these algorithms are applicable, also at last comparison of search techniques based on complexity, optimality and completeness are presented in tabular structure.
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Sheng, Jiangcong, Dingxin He, Qiang Gu, and Dongjun Gong. "Dual-arm Robot Fast Pick-and-Place on a Moving Conveyor." Journal of Physics: Conference Series 2216, no. 1 (2022): 012025. http://dx.doi.org/10.1088/1742-6596/2216/1/012025.
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Abstract The pick-and-place (PNP) system of multi-robots on moving con- veyors have a wide range of industrial applications. In practice, the most used is first in first out (FIFO) algorithm. However, the efficiency of FIFO is low when the number of objects to be picked is large. To improve the PNP efficiency, we first build a kinematic model of the dual-arm robot and establish a PNP time lookup table based on the inverse kinematic algorithm. Then, we develop a PNP shortest time first out (STFO) algorithm to calculate the high-efficiency picking sequence. Dynamic experiments show that compared with FIFO, we improve the dual-arm robot PNP system efficiency by 20%.
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Pan, Renbo, and Caiming Zhong. "Fairness First Clustering: A Multi-Stage Approach for Mitigating Bias." Electronics 12, no. 13 (2023): 2969. http://dx.doi.org/10.3390/electronics12132969.
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Fair clustering aims to partition a dataset while mitigating bias in the original dataset. Developing fair clustering algorithms has gained increasing attention from the machine learning community. In this paper, we propose a fair k-means algorithm, fair first clustering (FFC), which consists of an initialization stage, a relaxation stage, and an improvement stage. In the initialization stage, k-means is employed to cluster each group. Then a combination step and a refinement step are applied to ensure clustering quality and guarantee almost fairness. In the relaxation stage, a commonly used fairness metric, balance, is utilized to assess fairness, and a threshold is set to allow for fairness relaxation while improving the clustering quality. In the improvement stage, a local search method is used to improve the clustering quality without changing the fairness. Comparisons of fairness and clustering quality are carried out between our method and other state-of-the-art fair clustering methods on 10 datasets, which include both synthetic and real-world datasets. The results show that compared to the method with the second highest balance value, FFC shares the same SSE value on one dataset and achieves lower SSE values on six datasets.
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Tang, Xiwei, Jianxin Wang, Min Li, Yiming He, and Yi Pan. "A Novel Algorithm for Detecting Protein Complexes with the Breadth First Search." BioMed Research International 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/354539.
Full textAbstract:
Most biological processes are carried out by protein complexes. A substantial number of false positives of the protein-protein interaction (PPI) data can compromise the utility of the datasets for complexes reconstruction. In order to reduce the impact of such discrepancies, a number of data integration and affinity scoring schemes have been devised. The methods encode the reliabilities (confidence) of physical interactions between pairs of proteins. The challenge now is to identify novel and meaningful protein complexes from the weighted PPI network. To address this problem, a novel protein complex mining algorithm ClusterBFS (Cluster with Breadth-First Search) is proposed. Based on the weighted density, ClusterBFS detects protein complexes of the weighted network by the breadth first search algorithm, which originates from a given seed protein used as starting-point. The experimental results show that ClusterBFS performs significantly better than the other computational approaches in terms of the identification of protein complexes.
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Sikelis, Konstantinos, and George E. Tsekouras. "Feature Selection with a Backtracking Search Optimization Algorithm." ITM Web of Conferences 43 (2022): 01018. http://dx.doi.org/10.1051/itmconf/20224301018.
Full textAbstract:
Feature selection carries significance in the outcome of any classification or regression task. Exercising evolutionary computation algorithms in feature selection has led to the construction of efficient discrete optimization algorithms. In this paper, a modified backtracking search algorithm is employed to perform wrapper-based feature selection, where two modifications of the standard backtracking search algorithm are adopted. The first one concentrates on utilizing a particle ranking operator regarding the current population. The second one focuses on removing the case of using a single particle on the mutation process. Then, the implementation of the above algorithm in feature selection is carried out in terms of two general frameworks, which originally were developed for the particle swarm optimization. The first framework is based on the binary and the second on the set-based particle swarm optimization. The experimental analysis shows that the above variants of the backtracking search algorithm perform equally well on the classification of several datasets.