• Journal of Communications and Networks
• /
• v.17 no.5
• /
• pp.473-481
• /
• 2015

In this study, we propose a clustering algorithm to enhance the performance of wireless sensor and actuator networks (WSANs). In each cluster, a multi-level hierarchical structure can be applied to reduce energy consumption. In addition to the cluster head, some nodes can be selected as intermediate nodes (INs). Each IN manages a subcluster that includes its neighbors. INs aggregate data from members in its subcluster, then send them to the cluster head. The selection of intermediate nodes aiming to optimize energy consumption can be considered high computational complexity mixed-integer linear programming. Therefore, a heuristic lowest energy path searching algorithm is proposed to reduce computational time. Moreover, a channel assignment scheme for subclusters is proposed to minimize interference between neighboring subclusters, thereby increasing aggregated throughput. Simulation results confirm that the proposed scheme can prolong network lifetime in WSANs.

• Journal of Communications and Networks
• /
• v.13 no.6
• /
• pp.612-620
• /
• 2011

Recently, one of the problems with the Internet is the issue of scalability. To this end, locator/identifier separation protocol (LISP), which separates end-system identifiers and routing locators, has been proposed as a solution. In the LISP deployed network, the ingress and egress nodes of inter-AS traffic is determined by edge router selection (ERS) and endpoint identifier-routing locator mapping assignment (ERMA). In this paper, joint optimizations of ERS and ERMA for stub networks with and without predetermined link weights are studied and the mixed integer linear programming (MILP) formulations for the problems are given. To make the problem with optimizable link weights tractable, a revised local search algorithm is also proposed. Simulation results show that joint optimization of ERS and ERMA enables better network performance.

• ETRI Journal
• /
• v.30 no.4
• /
• pp.546-554
• /
• 2008

Phase-locked loops (PLLs) are among the most important mixed-signal building blocks of modern communication and control circuits, where they are used for frequency and phase synchronization, modulation, and demodulation as well as frequency synthesis. The growing popularity of PLLs has increased the need to test these devices during prototyping and production. The problem of distinguishing and classifying the responses of analog integrated circuits containing catastrophic faults has aroused recent interest. This is because most analog and mixed signal circuits are tested by their functionality, which is both time consuming and expensive. The problem is made more difficult when parametric variations are taken into account. Hence, statistical methods and techniques can be employed to automate fault classification. As a possible solution, we use the back propagation neural network (BPNN) to classify the faults in the designed charge-pump PLL. In order to classify the faults, the BPNN was trained with various training algorithms and their performance for the test structure was analyzed. The proposed method of fault classification gave fault coverage of 99.58%.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2007.06a
• /
• pp.336-337
• /
• 2007

The energy conversion characteristics of $TiO_2$ paste of dye-sensitized solar cell (DSSC) was investigated. In the case of DSSC without a binder, the current density increased due to the development of porosity. As for DSSC with a binder, the fill factor increased due to the development of network among the particles. The energy conversion efficiency of 7.2% was obtained due to the porosity and the network as for DSSC with the mixed binder (Vol. 50:50).

• International Journal of Advanced Culture Technology
• /
• v.11 no.1
• /
• pp.325-331
• /
• 2023

In this paper, we propose a mixed neural network structure of CNN and LSTM that can be used to detect or predict odor occurrence, which is most required in manufacturing industry or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data such as hydrogen sulfide, ammonia, benzene, and toluene in real time, and applies this data to an inference model to detect and predict odor conditions. The proposed model evaluated the prediction accuracy of the learning model through performance indicators according to accuracy, and the evaluation result showed an average performance of 94% or more.

• Macromolecular Research
• /
• v.17 no.2
• /
• pp.110-115
• /
• 2009

The electrical, morphological and rheological properties of melt and dry mixed composites of poly ethylene (PE)/graphite (Gr), polypropylene (PP)/Gr and PP/nickel-coated carbon fiber (NCCF) were investigated as a function of filler type, filler content and processing temperature. The electrical conductivities of dry mixed PP/NCCF composites were increased with decreasing processing temperature. For the melt mixed PP/NCCF composites, the electrical conductivities were higher than those of the melt mixed PE/Gr and PP/Gr composites, which was attributed to the effect of the higher NCCF aspect ratio in allowing the composites to form a more conductive network in the polymer matrix than the graphite does. From the results of morphological studies, the fillers in the dry mixed PP/NCCF composites were more randomly dispersed compared to those in the melt mixed PP/NCCF composites. The increased electrical conductivities of the dry mixed composites were attributed to the more random dispersion of NCCF compared to that of the melt mixed PP/NCCF composites. The complex viscosities of the PP/Gr composites were higher than those of the PP/NCCF composites, which was attributed to the larger diameter of the graphite particles than that of the NCCF. Furthermore, the fiber orientation in the 'along the flow' direction during melt mixing was attributed to the decreased complex viscosities of the melt mixed PP/NCCF composites compared those of the melt mixed PP/Gr composites.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.8
• /
• pp.3384-3398
• /
• 2020

In recent years, as the environment has become an important issue in dealing with food, energy, and urban development, diverse environment-related applications such as environmental monitoring and ecosystem management have emerged. In such applications, automatic classification of animals using video or sound is very useful in terms of cost and convenience. So far, many works have been done for animal sounds classification using artificial intelligence techniques such as a convolutional neural network. However, most of them have dealt only with the sound of a specific class of animals such as bird sounds or insect sounds. Due to this, they are not suitable for classifying various types of animal sounds. In this paper, we propose a sound classification scheme based on a multi-feature network for classifying sounds of multiple species of animals. To do that, we first collected multiple animal sound datasets and grouped them into classes. Then, we extracted their audio features by generating mixed records and used those features for training. To evaluate the effectiveness of our scheme, we constructed an animal sound classification model and performed various experiments. We report some of the results.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.5
• /
• pp.1618-1637
• /
• 2014

Clustering wireless sensor network is an efficient way to reduce the energy consumption of individual nodes in a cluster. In clustering, multihop routing techniques increase the load of the Cluster head near the sink. This unbalanced load on the Cluster head increases its energy consumption, thereby Cluster heads die faster and create an energy hole problem. In this paper, we propose an Energy Balancing Cluster Head (EBCH) in wireless sensor network. At First, we balance the intra cluster load among the cluster heads, which results in nonuniform distribution of nodes over an unequal cluster size. The load received by the Cluster head in the cluster distributes their traffic towards direct and multihop transmission based on the load distribution ratio. Also, we balance the energy consumption among the cluster heads to design an optimum load distribution ratio. Simulation result shows that this approach guarantees to increase the network lifetime, thereby balancing cluster head energy.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.25 no.2
• /
• pp.87-100
• /
• 2000

As a result of rapid advances in communication technology, fiber optics have begun to be adopted in most telecommunication systems 3s an economic choice Due to the trend of evolution toward broadband communication network with fiber optics and electronic devices. the network design problem for broadband communication has been received a great deal of research attention recently. In this paper, we address a topological design problem for broadband local access network with uncertain demands, which has received surprisingly little attention so far. in our problem, we select a set of hubs and links for constructing network expected penalty cost for the amount of undersupplied In addition to the usual cost terms of the fixed demand problem Our problem can be approximated as a mixed 0-1 integer programming problem by using Szwarc’s linear approximation technique. Then the problem is transformed successfully into a version of classical network design model. Some computational experiments for the model and concluding remarks are described.

• ETRI Journal
• /
• v.41 no.2
• /
• pp.207-223
• /
• 2019

Network function virtualization can significantly improve the flexibility and effectiveness of network appliances via a mapping process called service function chaining. However, the failure of any single virtualized network function causes the breakdown of the entire chain, which results in resource wastage, delays, and significant data loss. Redundancy can be used to protect network appliances; however, when failures occur, it may significantly degrade network efficiency. In addition, it is difficult to efficiently map the primary and backups to optimize the management cost and service reliability without violating the capacity, delay, and reliability constraints, which is referred to as the reliability-aware service chaining mapping problem. In this paper, a mixed integer linear programming formulation is provided to address this problem along with a novel online algorithm that adopts the joint protection redundancy model and novel backup selection scheme. The results show that the proposed algorithm can significantly improve the request acceptance ratio and reduce the consumption of physical resources compared to existing backup algorithms.