Optimal Prefix Codes with Fewer Distinct Codeword Lengths are Faster to Construct

A new method for constructing minimum-redundancy binary prefix codes is described. Our method does not explicitly build a Huffman tree; instead it uses a property of optimal prefix codes to compute the codeword lengths corresponding to the input weights. Let $n$ be the number of weights and $k$ be the number of distinct codeword lengths as produced by the algorithm for the optimum codes. The running time of our algorithm is $O(k \cdot n)$. Following our previous work in \cite{be}, no algorithm can possibly construct optimal prefix codes in $o(k \cdot n)$ time. When the given weights are presorted our algorithm performs $O(9^k \cdot \log^{2k}{n})$ comparisons.Comment: 23 pages, a preliminary version appeared in STACS 200

冗長性を活かしたへビ型ロボットの物体操りと関節故障リカバリー制御

京都大学新制・課程博士博士(工学)甲第24322号工博第5071号新制||工||1972(附属図書館)京都大学大学院工学研究科機械理工学専攻(主査)教授 松野 文俊, 教授 藤本 健治, 教授 東 俊一学位規則第4条第1項該当Doctor of Philosophy (Engineering)Kyoto UniversityDGA

単一運動性微生物の刺激応答計測のためのマイクロロボティックプラットホーム

九州工業大学博士学位論文 学位記番号:生工博甲第355号 学位授与年月日:令和元年9月20日1 Introduction|2 Observation Platform|3 Stimulation Platform|4 Application to Actual Motile Microorganisms|5 Conclusion九州工業大学令和元年

A unified ontology-based data integration approach for the internet of things

Data integration enables combining data from various data sources in a standard format. Internet of things (IoT) applications use ontology approaches to provide a machine-understandable conceptualization of a domain. We propose a unified ontology schema approach to solve all IoT integration problems at once. The data unification layer maps data from different formats to data patterns based on the unified ontology model. This paper proposes a middleware consisting of an ontology-based approach that collects data from different devices. IoT middleware requires an additional semantic layer for cloud-based IoT platforms to build a schema for data generated from diverse sources. We tested the proposed model on real data consisting of approximately 160,000 readings from various sources in different formats like CSV, JSON, raw data, and XML. The data were collected through the file transfer protocol (FTP) and generated 960,000 resource description framework (RDF) triples. We evaluated the proposed approach by running different queries on different machines on SPARQL protocol and RDF query language (SPARQL) endpoints to check query processing time, validation of integration, and performance of the unified ontology model. The average response time for query execution on generated RDF triples on the three servers were approximately 0.144 seconds, 0.070 seconds, 0.062 seconds, respectively

Improved DC-Link Voltage Controller for Photo Voltaic ON-Grid Systems

The DC-link voltage is an essential intermediate stage between the DC/DC and DC/AC converters in solar energy system. Due to the voltage fluctuations and current disturbances, a controller should be suitably designed to maintain the DC-link voltage well stabilized. In this paper, a variant of an adaptive DC-link voltage controller is proposed, namely PI-Fuzzy controller. The proposed controller has a fixed integral gain, while the proportional gain is determined based on a set of Fuzzy logic inference rules. Moreover, an anti-windup mechanism is added to the proposed controller to overcome integrator windup when the actuator saturates. Simulation results show that the proposed controller provides better rejection of current disturbances and fastest rise-time comparing to recently proposed PI-controllers for the DC-link voltage control