In this paper, we propose an optimization approach based on an improved Moth Flame optimization (MFO) algorithm for solving emergency operating room scheduling problems. The purpose of the MFO is to minimize the maximum span of operations, ensuring patients receive their surgeries in a timely manner. This nature-inspired algorithm stimulates the moth’s special navigation method at night called transverse orientation. The moth uses the moonlight to sustain a fixed angle to the moon, therefore, guaranteeing a straight line. However, a light source can cause a useless or deadly spiral fly path for moths. The results show that MFO has advantages over Grey Wolf optimization (GWO) and Genetic Algorithm (GA), particularly when comparing the performance of the algorithms under different spiral curves when considering the unrestricted use of surgical beds between different procedures and the optimization of algorithm speed.
Cuiting Huang, Sicong Ye, Shi Shuai, Mengdi Wei, Yehong Zhou
Healthcare provider
Algorithms and theory, cloud computing
September 2022
The rapid increase in bandwidth demand has driven the development of flexible, efficient, and scalable optical networks. One of the technologies that allows for much more flexible resource utilization is Elastic Optical Network. However, there is a need to solve the Routing, Modulation and Spectrum Assignment (RMSA) problem. In this paper, we use reinforcement learning to improve the efficiency of the routing algorithm. More specifically, we implement an off-policy Q-learning and compare it with the state-of-the-art algorithms. The results confirm that Q-learning is highly effective when optimal results need to be found in a large search space.
Nolen B. Bryant; Kwok K. Chung; Jie Feng; Sommer Harris;
Internet service provider
Networking, artificial intelligence
September 2022
In this survey, we look at the overall idea of Remotely Piloted Aircraft Systems (RPAS) and autonomous control, as well as RPAS infrastructure, levels of autonomy, and current benefits and difficulties in the field when utilizing Artificial Intelligence. While current remotely piloted aircraft systems have a manual pilot operator to provide double-layer security and safety, studies show that having RPAS with a fully autonomous vehicle at its centre could significantly improve decision-making and overall mission precision, accuracy, safety, and efficiency.
Ruchi Bhavsar; Mino Reyes
InDro Robotics, Aerometrix
Robotics, artificial intelligence
September 2022
With the growing demand for e-Commerce and remote working applications, it has become more important than ever to design applications with high availability and fault tolerance. This research proposes a push-based mechanism with persistent connection to reduce the “time to detect” such that the overall service level agreement for applications can be improved.
Norman Kong Koon Kit
Amazon
Systems and networking, cloud computing
May 2022
Usage of Artificial Intelligence (AI) technology to aid the Remotely Piloted Aircraft System (RPAS) helps to get accurate imagery along with vital ground details, which as a result boosts the Search and Rescue operations. Since the search must be done quickly, real-time video processing is essential for survival. Our solution attempts to integrate image processing, more specifically, the You Only Look Once (YOLO) algorithm to detect humans in all environmental conditions. Moreover, traditional methods of AI use Graphics Processing Units (GPU) instead of Central Processing Units (CPU). We solved the issue of low frame-per-second processing on the CPU with a newly designed frame-skipping algorithm. This improved method results in accurate and quick detection of humans and allows real-time detection.
Rohan Sharma
InDro Robotics
Robotics, artificial intelligence
January 2022
Object detection is a fundamental part of computer vision, with a wide range of real-world applications. It involves the detection of various objects in digital images or video. In this paper, we propose a proof of concept usage of computer vision algorithms to improve the maintenance of railway tracks operated by Via Rail Canada. Via Rail operates about 500 trains running on 12,500 km of tracks. These tracks pass through long stretches of sparsely populated lands. Maintaining these tracks is challenging due to the sheer amount of resources required to identify the points of interest (POI), such as growing vegetation, missing or broken ties, and water pooling around the tracks. We aim to use the YOLO algorithm to identify these points of interest with the help of aerial footage. The solution shows promising results in detecting the POI based on unmanned aerial vehicle (UAV) images. Overall, we achieved a precision of 74% across all POI and a mean average precision @ 0.5 (mAP @ 0.5) of 70.7%. The most successful detection was the one related to missing ties, vegetation, and water pooling, with an average accuracy of 85% across all three POI.
Rohan Sharma, Kishan Patel, Sanyami Shah
Via Rail Canada/spexiGeo
Computer vision, machine learning
September 2021
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Capstone projects are crucial for computer science students because they provide hands-on experience tackling an open-ended problem similar to what you’ll face professionally. It helps you develop technical abilities like coding and system design and important skills like project planning, problem-solving, and teamwork.
Are you ready to write your CS capstone project? Read our list with awesome 100 computer science capstone project ideas!
The capstone project options range from AI and web development to cybersecurity and blockchain, offering something for every computer science enthusiast. Choose a capstone project that matches your hobbies and professional ambitions.
Computer Science Capstone Project Ideas 1) In what ways does social media influence current developments in information systems and marketing? 2) What recent developments have we seen in natural language processing?
2021 Capstone Projects To wrap up their undergraduate experience at CU Boulder, computer science students participate in a year-long senior capstone project that gives them a chance to put their skills into practice on real-world projects, as well as to make important professional connections.
Computer Science and Data Science AI-Powered Language Translation: Build a language translation tool that uses AI to enhance accuracy. Machine Learning for Healthcare Diagnostics: Develop ML models for early disease detection.
Capstone are senior-level project courses that allow you to solve a substantial problem with knowledge gained from many areas in computer science and engineering. Students work in teams to define a problem, develop a solution, produce and demonstrate an artifact that solves the problem, and present their work.
Computer Science Capstone Projects. This page provides a summary of past projects that have been completed as part of the Computer Science capstone at SLU. Graphical Modeling of Biological Systems in Education. Monitoring Patients' Cardiovascular Health via Common Wearable Fitness Devices.
Unlock complex problems through important research. Looking for in-depth research support? A capstone is an end-of-program applied research project where students will spend twenty hours per week, for fifteen weeks, investigating a research problem alongside an industry stakeholder.
Recent Undergraduate Capstone Project Abstracts. Systems of a Racing Game (43.3 KB) Abstract_Final Project (785.1 KB) Mongodog: Eliminating orphaned data for MongoDB deletion (20.2 KB) Startup Scraper: Unveiling the secrets of the startup/VC industry through publicly accessible data (335.6 KB)