Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.

In the environment of 450mm wafers production known as the next-generation semiconductor production process, one of the most significant features is the full automation over the whole manufacturing processes involved. The full automation system for 450mm

  Recent advances in mobile computing technologies and platform-independent information systems have enabled to realize a ubiquitous environment. Community computing has been developed as a useful tool for realizing collaborative services in a ubiquitous

  In mobile ad-hoc networks(MANETs), nodes are mobile and network topology changes very frequently. The mobility of nodes does affect the system performance. There has been considerable attention on the mobility models, however, most work is confined to t

Slotted ALOHA(S-ALOHA) is widely used in local wireless network. We analyze the performance of contention-based model in wireless LAN using S-ALOHA protocol. We analyze the performance of binary exponential backoff (BEB) algorithm under the slotted ALOHA

As for the performance estimation of the AS/RS(Automated Storage/Retrieval System) most research assumes the AS/RS machine performs only either single command (SC) or dual command (DC) at each operation, and in addition, the type of requests is known in advance, which are not adequate in the real system. In this paper, we propose a stochastic approach for the performance estimation of a unit-load AS/RS. We assume that the service time when the AS/RS performs single command is differently distributed from that of dual command. Especially, we obtain the steady state probability distribution of the numbers of storage and retrieval commands waiting in the queues at each service completion epoch.

A proper performance evaluation of ATM (Asynchronous Transfer Mode) multiplexer is essential for stable management of ATM networks. We model the on/off traffics entering to the ATM switch as a Markov renewal process (MRP) and propose a performance evaluation method of ATM multiplexer by modeling the system as a discrete time MR/D/1/B queueing system, whose input process is the superposed MRP and present a performance analysis by finding CLP(Cell Loss Probability).

This paper presents an approach to derive likelihood models for use in engineering design problems. One main point is made. It is that incorporating engineering knowledge into a likelihood model is possible. The work is foundational in nature, but is developed with an explicit example taken from fatigue failure problem of a structural component, the Paris crack-propagation criterion, and a modified truncated Gaussian distribution.

In hepatobiliary organs, cases of neuroendocrine neoplasm are extremely rare, comprising less than 1% of all neuroendocrine tumor. Mixed adenoneuroendocrine carcinoma is even more rarer. Since neuroendocrine tumor component of mixed adenoneuroendocrine carcinoma defines the prognosis, it is of great importance to identify them for the practical point of view. Here, we report a case of 83 year-old female with mixed adenoneuroendocrine carcinoma in common bile duct. This lesion showed lymphovascular invasion of tumor cells.