• Journal of Communications and Networks
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• v.16 no.4
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• pp.465-474
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• 2014

Wireless sensor network (WSN) is considered to be one of the most important research fields for ubiquitous healthcare (u-healthcare) applications. Healthcare systems combined with WSNs have only been introduced by several pioneering researchers. However, most researchers collect physiological data from medical nodes located at static locations and transmit them within a limited communication range between a base station and the medical nodes. In these healthcare systems, the network link can be easily broken owing to the movement of the object nodes. To overcome this issue, in this study, the fast link exchange minimum cost forwarding (FLE-MCF) routing protocol is proposed. This protocol allows real-time multi-hop communication in a healthcare system based on WSN. The protocol is designed for a multi-hop sensor network to rapidly restore the network link when it is broken. The performance of the proposed FLE-MCF protocol is compared with that of a modified minimum cost forwarding (MMCF) protocol. The FLE-MCF protocol shows a good packet delivery rate from/to a fast moving object in a WSN. The designed wearable platform utilizes an adaptive linear prediction filter to reduce the motion artifacts in the original electrocardiogram (ECG) signal. Two filter algorithms used for baseline drift removal are evaluated to check whether real-time execution is possible on our wearable platform. The experiment results shows that the ECG signal filtered by adaptive linear prediction filter recovers from the distorted ECG signal efficiently.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.26-51
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• 2003

Large scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in thePDB. PSIMAP incorporates both functional and evolutionary information into a single network. It makes it possible to age protein domains in terms of taxonomic diversity, interaction and function. One consequence of it is to predict the most important protein domain structure in evolution. We present a global analysis of PSIMAP using several distinct network measures relating to centrality, interactivity, fault-tolerance, and taxonomic diversity. We found the following results: ${\bullet}$ Centrality: we show that the center and barycenter of PSIMAP do not coincide, and that the superfamilies forming the barycenter relate to very general functions, while those constituting the center relate to enzymatic activity. ${\bullet}$ Interactivity: we identify the P-loop and immunoglobulin superfamilies as the most highly interactive. We successfully use connectivity and cluster index, which characterise the connectivity of a superfamily's neighbourhood, to discover superfamilies of complex I and II. This is particularly significant as the structure of complex I is not yet solved. ${\bullet}$ Taxonomic diversity: we found that highly interactive superfamilies are in general taxonomically very diverse and are thus amongst the oldest. This led to the prediction of the oldest and most important protein domain in evolution of lift. ${\bullet}$ Fault-tolerance: we found that the network is very robust as for the majority of superfamilies removal from the network will not break up the network. Overall, we can single out the P-loop containing nucleotide triphosphate hydrolases superfamily as it is the most highly connected and has the highest taxonomic diversity. In addition, this superfamily has the highest interaction rank, is the barycenter of the network (it has the shortest average path to every other superfamily in the network), and is an articulation vertex, whose removal will disconnect the network. More generally, we conclude that the graph-theoretic and taxonomic analysis of PSIMAP is an important step towards the understanding of protein function and could be an important tool for tracing the evolution of life at the molecular level.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.263-269
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• 1996

The most vital arc in the maximum flow problem is that arc whose removal results in the greatest reduction in the value of the maximal flow between a source node and a sink node. This paper develops an algorithm to determine such a most vital arc(MVA) in the maximum flow problem. We first define the transformed network corresponding In a given network in order to compute the minimal capacity for each candidate arc. The set of candidate arcs for a MVA consists of the arcs whose flow is at least as greate as the flow over every arc in a minimal cut As a result, we present a method in which the MVA is determined more easily by computing the minimal capacity in the transformed network. The proposed method is demonstrated by numerical example.

• Current Optics and Photonics
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• v.1 no.5
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• pp.456-467
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• 2017

The benefits of network coding in all-optical multicast networks have been widely demonstrated. In this paper, we mainly discuss the multicast service efficiently provisioning problem in the network coding enabled elastic optical networks (EONs). Although most research on routing and spectrum allocation (RSA) has been widely studied in the elastic optical networks (EONs), rare research studies RSA for multicast in the network coding enabled EON, especially considering the time delay constraint. We propose an efficient heuristic algorithm, called Network Coding based Multicast Capable-Multipath Routing and Spectrum Allocation (NCMC-MRSA) to solve the multipath RSA for multicast services in the network coding enabled EON. The well-known layered graph approach is utilized for NCMC-MRSA, and two request ordering strategies are utilized for multiple multicast requests. From the simulation results, we observe that the proposed algorithm NCMC-MRSA performs more efficient spectrum utilization compared with the benchmark algorithms. NCMC-MRSA utilizing the spectrum request balancing (SRB) ordering strategy shows the most efficient spectrum utilization performance among other algorithms in most test networks. Note that we also observe that the efficiency of NCMC-MRSA shows more obvious than the benchmark algorithm in large networks. We also conduct the performance comparisons of two request ordering strategies for NCMC-MRSA. Besides, we also evaluate the impact of the number of the linkdisjoint parallel w paths on the spectrum utilization performance of the proposed algorithm NCMC-MRSA. It is interesting to find that the change of the parameter w in a certain range has a significant impact on the performance of NCMC-MRSA. As the parameter w increases to a certain value, the performances of NCMC-MRSA cannot be affected by the change of w any more.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.151-160
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• 2023

Breast cancer is the most dangerous and deadly form of cancer. Initial detection of breast cancer can significantly improve treatment effectiveness. The second most common cancer among Indian women in rural areas. Early detection of symptoms and signs is the most important technique to effectively treat breast cancer, as it enhances the odds of receiving an earlier, more specialist care. As a result, it has the possible to significantly improve survival odds by delaying or entirely eliminating cancer. Mammography is a high-resolution radiography technique that is an important factor in avoiding and diagnosing cancer at an early stage. Automatic segmentation of the breast part using Mammography pictures can help reduce the area available for cancer search while also saving time and effort compared to manual segmentation. Autoencoder-like convolutional and deconvolutional neural networks (CN-DCNN) were utilised in previous studies to automatically segment the breast area in Mammography pictures. We present Automatic SegmenAN, a unique end-to-end adversarial neural network for the job of medical image segmentation, in this paper. Because image segmentation necessitates extensive, pixel-level labelling, a standard GAN's discriminator's single scalar real/fake output may be inefficient in providing steady and appropriate gradient feedback to the networks. Instead of utilising a fully convolutional neural network as the segmentor, we suggested a new adversarial critic network with a multi-scale L1 loss function to force the critic and segmentor to learn both global and local attributes that collect long- and short-range spatial relations among pixels. We demonstrate that an Automatic SegmenAN perspective is more up to date and reliable for segmentation tasks than the state-of-the-art U-net segmentation technique.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.1
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• pp.133-138
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• 1986

In this paper, we are modeling the problem of the reliability evaluation in the network with delay. The triconnected decomposition and factoring algorithm for the network reliability, known as the most efficient algorithm, does not work in this constrained problem. So, we propose some ideas that reduce the above constrained problem to the general network reliability problem. We also present an algorithm for the reliability evaluation in the network with delay based on these ideas.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.53-56
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• 2003

Ethernet is one of the most successful LAN technologies. Now gigabit ethernet is available in real network and some network interface cards(NIC) supports TCP segment offloading (TSO), IP checksum offloading(ICO), Jumbo frame and interrupt moderation. If we use this features appropriately, we obtain high throughput with low CPU utilization. This paper represents the network performance by varying above features.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.3
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• pp.65-77
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• 2001

Survivability of a network is one of the most important issues in designing present-day communication networks. the k-edge survivability of a given network is defined as the percentage of total traffic surviving the worst case failure of k edges. Although several researches calculated k-edge survivability on small networks by enumeration, prior research has considered how to calculate k-edge survivability on large networks. In this paper, we develop an efficient procedure to obtain lower and upper bounds on the k-edge survivability of a network.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.497-498
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• 2007

The most of important thing when we design a Wireless Sensor Network is resources. You have to consider energy efficient operation When you design Wireless Sensor Network. Because Sensor devices have a limited resources. In this paper, we proposed energy efficiency localization technique in Wireless Sensor Network. We used Cell ID technique for location search. This method can reduce power consumption and the network life time will be extension.

• Science of Emotion and Sensibility
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• v.26 no.1
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• pp.101-114
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• 2023

This research aimed to recognize the determinant characteristics affecting consumers' clothing fit evaluation by employing text mining and social network analysis. For this aim, we first extracted text data linked to clothing fit from 2,000 consumer reviews collected from social network services and conducted semantic network examination and CONCOR analysis. As a result, we reported that "pants" and "skirts" were the most commonly associated clothing items with consumers' clothing fit evaluation. And the length of clothing was most commonly investigated. Then, the "waist" and "hip" were the most critical body parts affecting consumers' perception of clothing fit. Further, the four keywords including "wide," "large," "short," and "long" were the most employed ones in consumer reviews when evaluating clothing fit. This study is meaningful in that it specifically recognized the structural relationship and semantic meanings of keywords relevant to consumers' evaluation of clothing fit, which could bring empirical reference information for advanced clothing fit.