• Journal of Power Electronics
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• v.18 no.6
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• pp.1791-1804
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• 2018

To achieve a fast dynamic response and to solve the multi-objective control problems of the output currents, capacitor voltages and system constraints, this paper proposes a deadbeat and hierarchical predictive control with space-vector modulation (DB-HPC-SVM) for five-level nested neutral point piloted (NNPP) converters. First, deadbeat control (DBC) is adopted to track the reference currents by calculating the deadbeat reference voltage vector (DB-RVV). After that, all of the candidate switching sequences that synthesize the DB-RVV are obtained by using the fast SVM principle. Furthermore, according to the redundancies of the switch combination and switching sequence, a hierarchical model predictive control (MPC) is presented to select the optimal switch combination (OSC) and optimal switching sequence (OSS). The proposed DB-HPC-SVM maintains the advantages of DBC and SVM, such as fast dynamic response, zero steady-state error and fixed switching frequency, and combines the characteristics of MPC, such as multi-objective control and simple inclusion of constraints. Finally, comparative simulation and experimental results of a five-level NNPP converter verify the correctness of the proposed DB-HPC-SVM.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.1-13
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• 2006

In this paper, we introduce a novel key management scheme that is based on the key pre-distribution but provides the key re-distribution method, in order to manage keys for message encryption and authentication of lower-layer sensor nodes on hierarchical mobile sensor networks. The characteristics of our key management are as follows: First, the role of key management is distributed to aggregator nodes as well as a sink node, to overcome the weakness of centralized management. Second, a sink node generates keys using regression model, thus it stores only the information for calculating the keys using the key information received from nodes, but does not store the relationship between a node and a key, and the keys themselves. As the disadvantage of existing key pre-distributions, they do not support the key re-distribution after the deployment of nodes, and it is hard to extend the key information in the case that sensor nodes in the network enlarge. Thirdly, our mechanism provides the resilience to node capture(${\lambda}$-security), also provided by the existing key pre-distributions, and fourth offers the key freshness through key re-distribution, key distribution to mobile nodes, and scalability to make up for the weak points in the existing key pre-distributions. Fifth, our mechanism does not fix the relationship between a node and a key, thus supports the anonymity and untraceability of mobile nodes. Lastly, we compare ours with existing mechanisms, and verify our performance through the overhead analysis of communication, computation, and memory.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.561-581
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• 2017

Bayesian statistics can play a key role in the design and analysis of clinical trials and this has been demonstrated for medical device trials. By 1995 Bayesian statistics had been well developed and the revolution in computing powers and Markov chain Monte Carlo development made calculation of posterior distributions within computational reach. The Food and Drug Administration (FDA) initiative of Bayesian statistics in medical device clinical trials, which began almost 20 years ago, is reviewed in detail along with some of the key decisions that were made along the way. Both Bayesian hierarchical modeling using data from previous studies and Bayesian adaptive designs, usually with a non-informative prior, are discussed. The leveraging of prior study data has been accomplished through Bayesian hierarchical modeling. An enormous advantage of Bayesian adaptive designs is achieved when it is accompanied by modeling of the primary endpoint to produce the predictive posterior distribution. Simulations are crucial to providing the operating characteristics of the Bayesian design, especially for a complex adaptive design. The 2010 FDA Bayesian guidance for medical device trials addressed both approaches as well as exchangeability, Type I error, and sample size. Treatment response adaptive randomization using the famous extracorporeal membrane oxygenation example is discussed. An interesting real example of a Bayesian analysis using a failed trial with an interesting subgroup as prior information is presented. The implications of the likelihood principle are considered. A recent exciting area using Bayesian hierarchical modeling has been the pediatric extrapolation using adult data in clinical trials. Historical control information from previous trials is an underused area that lends itself easily to Bayesian methods. The future including recent trends, decision theoretic trials, Bayesian benefit-risk, virtual patients, and the appalling lack of penetration of Bayesian clinical trials in the medical literature are discussed.

• Journal of Communications and Networks
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• v.6 no.2
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• pp.156-162
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• 2004

In recent years, mobile ad-hoc networks have received a great deal of attention in both academia and industry to provide anytime-anywhere networking services. As wireless networks are rapidly deployed, the security of wireless environment will be mandatory. In this paper, we describe a group key management architecture and key agreement protocols for secure communication in mobile ad-hoc wireless networks (MANETs) overseen by unmanned aerial vehicles (UAVs). We use implicitly certified public keys method, which alleviates the certificate overhead and improves computational efficiency. The architecture uses a two-layered key management approach where the group of nodes is divided into: 1) Cell groups consisting of ground nodes and 2) control groups consisting of cell group managers. The chief benefit of this approach is that the effects of a membership change are restricted to the single cell group.

• Korean System Dynamics Review
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• v.8 no.2
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• pp.253-273
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• 2007

To measure the effect of school zone on housing cost, Linear Regression Model is widely used, and school zone is known as a key determinant of housing cost in Korea. However, when the Hierarchical Linear Model (HLM) is applied with the same data, school effect on housing cost becomes statistically non-significant. It is because HLM effectively separates the effect of individual housing's attributes from the group effect. In sum, the housing cost of Kangnam, where good public schools are located, is apparently is higher than that of Kangbuk. However, the school effect on housing cost (Level 2) becomes non-significant when individual housing's attributes (Level 1) are controlled with HLM.

• Journal of Information Science Theory and Practice
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• v.5 no.3
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• pp.31-47
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• 2017

The narrow-down approach, separately composed of search and classification stages, is an effective way of dealing with large-scale hierarchical text classification. Recent approaches introduce methods of incorporating global, local, and path information extracted from web taxonomies in the classification stage. Meanwhile, in the case of utilizing path information, there have been few efforts to address existing limitations and develop more sophisticated methods. In this paper, we propose an expansion method to effectively exploit category path information based on the observation that the existing method is exposed to a term mismatch problem and low discrimination power due to insufficient path information. The key idea of our method is to utilize relevant information not presented on category paths by adding more useful words. We evaluate the effectiveness of our method on state-of-the art narrow-down methods and report the results with in-depth analysis.

• International Journal of Contents
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• v.5 no.4
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• pp.88-93
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• 2009

It is important for communication networks to possess the capability to overcome failures and provide survivable services. We address modeling and analysis of performability affected by both performance and availability of system components for a token ring network under failure and repair conditions. Stochastic reward nets (SRN) is an extension of stochastic Petri nets and provides compact modeling facilities for system analysis. In this paper, hierarchical SRN modeling techniques are used to overcome state largeness problem. The upper level model is used to compute availability and the lower level model captures the performance. And Normalized Throughput Loss (NTL) is obtained for the composite ring network for each node failures occurrence as a performability measure. One of the key contributions of this paper constitutes the Petri nets modeling techniques instead of complicate numerical analysis of Markov chains and easy way of performability analysis for a token ring network under SRN reward concepts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3641-3655
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• 2016

Wireless sensor networks (WSNs) provide a promising approach to monitor the physical environments, to prolong the network lifetime by exploiting the mutual correlation among sensor readings has become a research focus. In this paper, we design a hierarchical network framework which guarantees layered-compression. Meanwhile, a data sorting-based adaptive spatial compression scheme (DS-ASCS) is proposed to explore the spatial correlation among signals. The proposed scheme reduces the amount of data transmissions and alleviates the network congestion. It also obtains high compression performance by sorting original sensor readings and selectively discarding the small coefficients in transformed matrix. Moreover, the compression ratio of this scheme varies according to the correlation among signals and the value of adaptive threshold, so the proposed scheme is adaptive to various deploying environments. Finally, the simulation results show that the energy of sorted data is more concentrated than the unsorted data, and the proposed scheme achieves higher reconstruction precision and compression ratio as compared with other spatial compression schemes.

• Convergence Security Journal
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• v.9 no.2
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• pp.71-78
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• 2009

It is very difficult to apply previous security protocols to WSNs(Wireless Sensor Networks) directly because WNSs have resource constrained characteristics such as a low computing ability, power, and a low communication band width. In order to overcome the problem, we proposes a secure group communication scheme applicable to WSNs. The proposed scheme is a combined form of the TEEN(Threshold sensitive Energy Efficient sensor Network protocol) clustering based hierarchical routing protocol and security mechanism, and we assume that WSNs are composed of sensor nodes, cluster headers, and base stations. We use both private key and public key cryptographic algorithms to achieve an enhanced security and an efficient key management. In addition, communications among sensor nodes, cluster headers, and base stations are accomplished by a hierarchical tree architecture to reduce power consumption. Therefore, the proposed scheme in this paper is well suited for WSNs since our design can provide not only a more enhanced security but also a lower power consumption in communications.

• The KIPS Transactions:PartC
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• v.16C no.3
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• pp.285-298
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• 2009

According to the development of ubiquitous technologies, sensor networks is used in various area. In particular, medical field is one of the significant application areas using sensor networks, and recently it has come to be more important according to standardization of the body sensor networks technology. There are special characteristics of their own for medical sensor networks, which are different from the one of sensor networks for general application or environment. In this paper, we propose a hierarchical medical sensor networks structure considering own properties of medical applications, and also introduce transmission mechanism based on hierarchical structure. Our mechanism uses the priority and threshold value for medical sensor nodes considering patient's needs and health condition. Through this way Cluster head can transmit emergency data to the Base station rapidly. We also present the new key establishment mechanism based on key management mechanism which is proposed by L. Eschenauer and V. Gligor for our proposed structure and transmission mechanism. We use key provisioning for emergency nodes that have high priority based on patients' health condition. This mechanism guarantees the emergency nodes to establish the key and transmit the urgent message to the new cluster head more rapidly through preparing key establishment with key provisioning. We analyze the efficiency of our mechanism through comparing the amount of traffic and energy consumption with analysis and simulation with QualNet simulator. We also implemented our key management mechanism on TmoteSKY sensor board using TinyOS 2.0 and through this experiments we proved that the new mechanism could be actually utilized in network design.