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Deep learning is a powerful means to classify and thus optimize Energy management in Buildings. Deep learning is effective especially when the training dataset has a reduced volume or when the test set changes at a higher frequency than the training ...
In this paper, we simulated a distributed, cooperative path planning technique for multiple drones (~200) to explore an unknown region (~10,000 connected units) in the presence of obstacles. The map of an unknown region is dynamically created based on ...
The unmanned aerial vehicle (UAV) swarm has developed rapidly in recent years, especially the UAV swarm with sensors which is becoming common means of achieving situational awareness. In this paper, we develop a scalable, online and myopic algorithm for ...
Support Vector Machine (SVM) learning algorithm is considered as the most popular classification algorithm. It is a supervised learning technique that is mainly based on the conception of decision planes. These decision planes define decision boundaries ...
Analyzing thermostat data together with outdoor weather to predict indoor temperature can help smart thermostats optimize the operation of a residential building's HVAC system and make buildings more comfortable. Using weather forecasts, these smart ...
Earthquake and seismic hazards are natural disasters which are very difficult to predict. Researchers are working hard to predict these disasters for minimizing loss of life and property. Proposed research used data mining algorithms on seismic bumps ...
A fully autonomous quadrotor is an aerial drone that utilizes four propellers to achieve stable flight through the use of obstacle avoidance, attitude control, and altitude control algorithms. In this research we created a simulator for a group of ...
In this paper, we use several supervised classification algorithms to predict musical preference of a person. From psychological point of view, although personal emotion is an important feature that has an influence on selecting music, there are some ...
The proposed paper describes Artificial Neural Network (ANN) application developed for the Model of Advanced pLanner for Interoperable Computer Interactive Simulation (MALICIA) project. It deals with stochastic discrete event simulator customization as ...
Accurate detection of juxtapleural lung cancer, which are nodules on the chest wall, has great importance in the early detection of lung cancer. To acquire a good performance of Computer Aided Detection (CAD), both positive (nodule) detection and false ...
This paper proposes a real-time, image-based training scenario comprehension method. This method aims to support the visual and haptic guidance system for laparoscopic surgery skill training. The target task of the proposed approach is a simulation ...
Cryptosystems, even after recent algorithmic improvements, can be vulnerable to side-channel attacks (SCA). In this paper, we investigate one of the powerful class of SCAs based on machine learning techniques in the forms of Principal Component Analysis ...
When it comes to road traffic, there seems to be no parameter more essential than the driver himself. Currently, there are many models available, which can be used to describe a driver's behavior for a traffic simulation. Nevertheless, despite the rich ...
This paper presents research on the development of multi-agent systems (MAS) for integrated and performance driven architectural design. It presents the development of a simulation framework that bridges architecture and engineering, through a series of ...
This paper describes a process of using local interactions to generate intricate global patterns and emergent urban forms. Starting with network topology optimization, agent-based model (ABM) is used to construct the micro-level complexity within a ...
Current Computer-Aided Architectural Design (CAAD) systems fail to represent buildings in-use before their realization. This failure prevents testing the extent to which a proposed setting supports the activities of its intended users. We present a ...
This paper presents a framework for the distributed recommender system that can process the huge amount of social data of Web 2.0 sites in online manner. To evaluate this idea a multi-agent simulator is built to exploit user profile together with ...
This paper describes a haptic guidance system developed to assist in model-based training of minimally invasive, laparoscopic procedures. The key factor motivating the development of the device called CAST (Computer-Assisted Surgical Trainer) is the ...
Single-linkage hierarchical clustering is one of the prominent and widely-used data mining techniques for its informative representation of clustering results. However, the parallelization of this algorithm is challenging as it exhibits inherent data ...
With the growing interest in high altitude balloon experiments for Science, Technology, Engineering, and Math (STEM) outreach, the desire for more capable data links, to include 802.11-based solutions, has also increased. This paper addresses the ...