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Recently, Deep Learning has been applied in the techniques of artificial intelligence. Especially, Deep Learning performed good results in the field of image recognition. Most new Deep Learning architectures are naturally developed in image recognition. For this reason, not only the numerical data and text data but also the time-series data are transformed to the image data format. Multi-modal data...
We employ an individual pool to increase the precision of the estimated convergence points of a population by using individual information from past generations. Better individuals from past generations are kept in the pool, and poorer individuals are replaced with new better individuals when the pool becomes full; convergence points for the population are thus estimated using those individuals from...
Speech is natural verbal form of communication in human beings. Each spoken word consists of phonetic combinations of vowels and consonants. Speech recognition is an application of the field of study in pattern recognition, applying pattern matching to phonetic patterns for identification of various linguistic objects including parts of speech. The various techniques to approach the model of this...
With the development of science and technology, robots have gradually come into our life from industry. Tennis ball collection robot is one of the more prominent representatives. How to find the position of tennis ball accurately is the key. In order to improve the speed and accuracy, we use deep learning and divide the image recognition into two steps. Using AlexNet network model to test whether...
In this work, we propose a novel adaptive control on digital Doherty Power Amplifier (DPA) for efficiency and gain enhancement. Unlike traditional DPA design, we propose Simultaneously Perturbated Stochastic Approximation (SPSA) optimization algorithm by considering phase difference, power distribution and gate voltage parameters of main and peak amplifiers in order to achieve optimal performance...
The quantum-inspired evolutionary algorithm (QEA) and QEA with a pair-swap strategy (QEAPS), where each gene is represented by a quantum bit (qubit), and the qubit is updated by a unitary transformation in both algorithms. QEA and QEAPS can automatically shift from a global search to a local search and have shown superior search performance to the classical genetic algorithm. However, it is important...
This paper proposes a system that recommends tourist spots around the current location relating with the sentiment selected by the user. This system collects tweets and comments about tourist spots from Twitter1 and Yelp2, and calculates 10 kinds of emotional scores such as “joy” and “angry” for each spot. Those scores are stored in a RDF (Resource Description Framework) database and used for spot...
Reinforcement learning which is applied to multiobjective optimization problem is called multi-objective reinforcement learning. Related works in the study field of the multiobjective Reinforcement Learning indicate that multi-objective reinforcement learning with a choice procedure based on Hypervolume is effective for finding Pareto optimal solution of multiobjective optimization problems. However,...
Indisposition behavior of lecturers to work across university departments is still common in some developing countries. That condition makes little information is known about their preferences of research collaboration. It creates inter-departmental recommendation process similar to a cold-start problem where there is no ground-truth dataset for validating the recommended topics. We propose a recommender...
This paper proposes an estimation method of missing data of showcase using Artificial Neural Networks (ANN). When various abnormal conditions such as frost formation in the refrigerators and refrigerant leakage happen, vendors of showcases have to treat the abnormal conditions as quickly as possible. Therefore, various measured data of showcases such as temperatures or pressures of some portions of...
Recently, the number of elderly persons with dementia has been increasing, and this is one of the severe social problems in Japan. In the field of geriatrics, it is usually said that detecting dementia in the early stage is quite important and currently, there are many dementia evaluation methods. For instance, Hasegawa's Dementia Scale for Revised (HDS-R) and Mini-Mental State Examination (MMSE)...
This paper presents an automatic segmentation method used to detect cotton wool spots in the retinal images for diabetic retinopathy disease. An early detection of cotton wool is important to prevent the dangerous damage which may cause blindness and vision loss. A preprocessing is applied to enhance image quality followed by optic disc removal. A feature extraction method is used to take useful elements...
Conference proceedings front matter may contain various advertisements, welcome messages, committee or program information, and other miscellaneous conference information. This may in some cases also include the cover art, table of contents, copyright statements, title-page or half title-pages, blank pages, venue maps or other general information relating to the conference that was part of the original...
Neural Network system for SoC is one topic in the world. Recently, SoC began to combine AI technique by Python. When developers consider Intelligent system on SoC, the co-design software and hardware are significant. In this case, small devices and embedded system are target system. For IoT, those techniques will grow up in the world. Those cases, avoiding premature convergence while keeping performance...
We constructed a multi-agent simulation model to replicate the results of an evacuation study in a field experiment [4]. Four or two leaders instructed 16 evacuees in the follow-me method. The results of the simulation, however, were not close to the results obtained in the experimental study. Therefore, we introduced a rule that evacuees follow a leader if the evacuee happens to see a leader instructing...
This paper presents reactive tabu search for job shop scheduling problems considering energy management. Production scheduling of factories should be minimized in order to keep customer delivery time. Since reduction of energy costs is important, operational planning of energy plants in factories should be optimized as well. However, the scheduling in factories and optimization of energy plants have...
This paper proposes a matrix-based collaborative filtering based on users' personal values. On many online shopping sites, hotel booking sites, etc, a huge amount of items are available, from witch it becomes difficult for users to find items of interest. Recommender systems help users by suggesting items expected to be preferred by them. One of the common and successful recommendation methods is...
This paper proposes generation methods of neighborhood schedules for crew scheduling problems (CSPs) in order to apply to practical problems. The proposed methods can give diversification to neighborhood schedules and generate an appropriate schedule. The results indicate that the proposed methods can drastically reduce the objective function values for the actual timetable than the conventional method.
The pure pursuit algorithm is one of the hottest research fields of autonomous driving advanced system as well as a major means for realizing intelligent operating of autonomous driving advanced system in future. This paper presents a thorough research on GPS automatic navigation technology of autonomous driving advanced system considering that working conditions and field conditions for the vehicle...
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