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Community Question Answering (CQA) has emerged as a popular type of service enabling users to ask and answer questions, and access the existing knowledgebase. CQA archives contain a lot of useful user-generated content and have been recognized as important information resources for the web. To improve accessibility to this body of knowledge in CQA archives, effective and efficient question retrieval is required. Question retrieval in a CQA archive aims to identify and retrieve existing questions that are relevant to new user questions. The objective of this study is to develop a question retrieval system that can sift through such forums and identify existing questions which are most similar to the user-provided question. We focus on health forums, and propose a CQA system using weighted TF-IDF, relevance heuristics, and term expansion. We compare our proposed algorithm against other well-known methods, and demonstrate that our method outperforms the Latent Dirichlet allocation (LDA) topic model, Latent Semantic Indexing (LSI), language modelbased information retrieval, BM25, vector space, Word2Vec, and semantic similarity approaches. Our initial experiments use datasets from the IEEE Healthcare Data Analytics Challenge 2015, and we also present our efforts towards development of a Bronze Standard for question similarity evaluation using self-annotations and annotations provided by affiliates of Mayo Clinic.

Duplicate questions get posted on QaA online forums because users may not be aware of similar questions. Our proposed system, Golden Retriever, can recommend existing questions that are semantically related to incoming questions. Compared with other existing techniques such as Latent Semantic Indexing, Language Model and Semantic Similarity, our approach shows good results for the ICHI Healthcare Data Analytics Challenge dataset using normalized TF-IDF, relevance heuristics, and semantic relatedness.

To transmit and to store digital video sequences, compression is necessary. Motion Estimation (ME) Technique is used to redundant data in video sequences. ME which limits the performance of image quality, generated bitrates and encoding time requires huge complexity. To reduce the computational complexity, a Hierarchical motion estimation scheme in Multi-view Video Coding (MVC) is proposed. The proposed method exploits the characteristics of the distribution of motion vectors to terminate the motion estimation early and to place the search points in the search area. Experiment results show that the complexity reduction of the proposed method over FS and TZ can be up to 98.9% and 42∼78% respectively while maintaining image quality and bitrates. This electronic document is a “live” template and already

We explore methods for effectively extracting information from clinical narratives, which are captured in a public health consulting phone service called HealthLink. The currently available data consists of dialogues constructed by nurses while consulting patients on the phone. Since the data are interviews transcribed by nurses during phone conversations, they include a significant volume and variety of noise: First is explicit noise, which includes spelling errors, unfinished sentences, omission of sentence delimiters, variants of terms, etc. Second is implicit noise, which includes non-patient's information and negation of patient's information. To filter explicit noise, we propose our biomedical term detection/normalization method: it resolves misspelling, term variations, and arbitrary abbreviation of terms by nurses. In detecting temporal terms and other types of named entities (which show patients' personal information such as age, and sex), we propose a bootstrapping-based pattern learning to detect all kinds of arbitrary variations of the named entities. To address implicit noise, we propose a dependency path-based filtering method. The result of our denoising is the extraction of normalized patient information. The experimental results show that we achieve reasonable performance with our noise reduction methods.

A versatile 30V analog CMOS process in a 0.18 μm technology node has been developed by using cost-effective and modular fashion. To reduce the thermal budget deep NWELL isolation is formed after CMOS well formation. The drain-extended (DE) CMOS from 7V to 30V shows very competitive trade-off performance between the breakdown voltage and the specific on-resistance. In addition, low 1/f noise of 5V CMOS can be obtained by pure gate oxide process.

As the volume of clinic notes written in natural language is rapidly increasing, physicians need a tool to automatically extract information about diseases/treatments. The main problem in extracting medical information is that physicians use variant words to describe the same disease/treatment. In order to help physicians interpret and share disease/treatment information in clinic notes, we need to reliably and effectively detect and normalize the medical terms. In this study, we perform detection/normalization of medical terms using a UMLS meta-thesaurus combined with a document retrieval technique. We regard a medical sentence as a query, and a UMLS ontology entry as a document, and try to apply a language modeling-based information retrieval method as currently used in the document retrieval field. Because the term frequency in the UMLS dictionary is uniform, we employ a domain-specific term frequency instead of traditional term frequency. To retrieve only the relevant terms in 900,000 UMLS entries, we also propose an adaptive ranking method which dynamically determines the relevant documents for each query without using static cut-off threshold. The experimental results outperform the previous methods in detecting and normalizing medical terms in Medline clinical trials, and our approach can be used in normalizing the real diagnosis list in the patient charts of physicians.

This paper explores a method for Korean text watermarking based on a linguistic analysis scheme using morphemic and syntactic analysis. In this scheme, a predicate nominal is separated into its nominal and its predicate, and syntactic adverbial is displaced. Korean, as an agglutinative language, provides a good basis for this morpheme-based natural language watermarking because a word consists of several morphemes. A Korean word usually consists of a content morpheme and a function morpheme. However, a predicate nominal is an exception, having two content morphemes—nominal and predicate--and one function morpheme. So, we can divide a predicate nominal into a nominal and a predicate. In addition, we also perform syntax-based watermarking. We displace syntactic adverbials using the characteristic that most languages permit displacement of syntactic adverbials within its clause. Combining these morphemic and syntactic characteristics, we propose a method of language watermarking based on syntactic displacement and morphological division. To make our system more secure, we also include a sentence weight value and encode the weight value with a watermark bit. Our watermarking method doesn’t change the meaning of the most marked sentences, and it also ensures the naturalness of the sentences. From the experimental results, we show that the rate of unnatural sentences of marked text is reasonable, and the watermarking capacity is better than previous systems. The coverage of marked sentences is also reasonable. Experimental results also show that the marked text retains the same style, and also has the same information without semantic distortion.

We experimentally demonstrate a Super-Junction LDMOS transistor in a 0.18 µm BCD technology. The buffered Super-Junction structure is implemented by the use of existing N- and P-drift layer, which are optimized for conventional 20V to 30V LDMOS transistors. The breakdown voltage and the specific on-resistance of the fabricated Super-Junction LDMOS are 98.6 V and 1.01 mΩ⋅cm2, respectively. The TLP measurement results show fairly good electrical SOA characteristics up to 78V for all gate voltages.

A proteinpsilas subcellular localization is considered an essential part of the description of its associated biomolecular phenomena. As the volume of biomolecular reports has increased, there has been a great deal of research on text mining to detect protein subcellular localization information in documents. It has been argued that linguistic information, especially syntactic information, is useful for identifying the subcellular localizations of proteins of interest. However, previous systems for detecting protein subcellular localization information used only shallow syntactic parsers, and showed poor performance. Thus, there remains a need to use a full syntactic parser and to apply deep linguistic knowledge to the analysis of text for protein subcellular localization information. In addition, we have attempted to use semantic information from the WordNet thesaurus. To improve performance in detecting protein subcellular localization information, this paper proposes a three-step method based on a full syntactic dependency parser and semantic information. In the first step, we construct syntactic dependency paths from each protein to its location candidate. In the second step, we retrieve root information of the syntactic dependency paths. In the final step, we extract syn-semantic patterns of protein subtrees and location subtrees. From the root and subtree nodes, we extract syntactic category and syntactic direction as syntactic information, and synset offset of the WordNet thesaurus as semantic information. According to the root information and syn-semantic patterns of subtrees, we extract (protein, localization) pairs. Even with no biomolecular knowledge, our method shows reasonable performance in experimental results using Medline abstract data. In fact, our proposed method gave an F-measure of 74.53% for training data and 58.90% for test data, significantly outperforming previous methods, by 12-25%.

Motion estimation (ME) plays an important role in digital video compression, since it can significantly affect the image quality, the encoding speed and the compression ratio. ME is very computationally demanding part of the encoder. To reduce computational complexity and to maintain the good image quality, integer pixel and fractional pixel ME methods are proposed in this paper. For integer pixel ME, a hierarchical search strategy is proposed. This strategy method consists of symmetrical cross search pattern, multi square grid pattern, large and small diamond search patterns. To reduce the computational time and not to fall into the local minimum, these search patterns place search points symmetrically and evenly in the overall search area. After integer pixel ME, the adaptive fractional pixel ME method is performed. This fractional pixel ME method decides the search pattern adaptively according to the block size. Experimental results show that the speedup improvement of the proposed method over unsymmetrical cross multi hexagon grid search (UMHexagonS) and full search (FS) can be about 1.2~ 5.2 times faster. Compared to image quality of FS, the proposed method shows an average PSNR drop of 0.01 dB while showing an average PSNR gain of 0.02 dB in comparison to that of UMHexagonS.

Mobile IP ensures the seamless IP connectivity while roaming but it also introduce deficiencies in terms of processing overhead. Proxy mobile IP (PMIP) has been proposed to solve the challenge of IP mobility. Network-based mobility support removes the involvement of mobile node (MN) by introducing new mobility entities, local management anchor (LMA) and mobility access gateway (MAG). This paper presents authentication scheme for exchanging mobility signaling between Home Agent and new enmities.

We present a new BCD technology in a 0.18 μm technology platforms with a capability of 7 to 60V high-voltage devices such as DEMOS and LDMOS. The developed 0.18 mum BCD process provides various kinds of high voltage LDMOS such as 7, 12, 20, 50, 60 V LDMOS transistors for variety of applications. The power LDMOS transistors in the process have very competitive specific on-resistance compared to previous results.

This paper explores the method for Korean text watermarking and develops a syntactic tree-based adverbial displacement scheme. Korean, as an agglutinative language, provides a good ground for the syntactic tree-based natural language watermarking because syntactic constituent order is relatively free -especially syntactic adverbial. Our proposed natural language watermarking method consists of six procedures. First, we construct a syntactic dependency tree of unmarked text. Next, we perform clausal segmentation from the syntactic tree. Third, we choose a target adverbial constituent, which will be displaced within its clause. Then, we embed a watermark bit. Fifth, if the watermark bit does not coincide with the direction of the target adverbial displacement, we displace the target adverbial constituent in the syntactic tree. Finally, from the modified syntactic tree, we obtain a marked text. From the experimental results, we show that the coverage of our method outperforms that of previous systems, and the rate of unnatural sentences of marked text is better than that of previous systems. Experimental results also show that the marked text keeps the same style, and it also has the same information without semantic distortion.

The relative velocity of the vehicle ad hoc network that has high mobility can affect network topology. This can affect the efficiency of those networks, so a suitable mechanism is necessary for effective management of them. This paper analyzes MAC throughputs in according with relative velocity in vehicle ad hoc environment. The vehicle ad hoc network has serious a topological variation because of high-mobility of a vehicle. So each station has a MAC-overhead to avoid collision. The RTS-CTS frame is the biggest overhead between them. In this paper, we evaluate basic mechanism and RTS-CTS mechanism about sent frame length. The result shows that RTS-CTS mechanism exhibits superior efficiency in low relative velocity and basic mechanism appears better efficiency than that in high relative velocity. Therefore, we confirm that relative velocity is an import factor in vehicle ad hoc network, and propose requirement of suitable mechanism.

Motion estimation (ME) limits the performance of the encoder in terms of encoding speed and image quality. However, its complexity is too high to be applied in real time applications. To reduce its complexity and maintain the image quality, the proposed method uses a hierarchical search strategy for integer pel ME. This strategy consists of symmetrical cross search pattern, multi-square grid search pattern and diamond search patterns. This hybrid search strategy places search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum and to reduce the complexity. Experiment results show that the speedup improvement of the proposed method over unsymmetrical-cross multi-hexagon grid search (UMHexagonS) and full search (FS) can be up to 1.2 square 6.6 times faster respectively. Compared to FS, the proposed method shows an average PSNR drop of 0.01 dB while showing an average PSNR gain 0.01 dB in comparison to UMHexagonS.