Design of a ROIC for scanning type HgCdTe LWIR focal plane arrays

Design of a silicon readout integrated circuit (ROIC) for LWIR HgCdTe Focal Plane is presented. ROIC incorporates time delay integration (TDI) functionality over seven elements with a supersampling rate of three, increasing SNR and the spatial resolution. Novelty of this topology is inside TDI stage; integration of charges in TDI stage implemented in current domain by using switched current structures that reduces required area for chip and improves linearity performance. ROIC, in terms of functionality, is capable of bidirectional scan, programmable integration time and 5 gain settings at the input. Programming can be done parallel or serially with digital interface. ROIC can handle up to 3.5V dynamic range with the input stage to be direct injection (DI) type. With the load being 10pF capacitive in parallel with 1MΩ resistance, output settling time is less than 250nsec enabling the clock frequency up to 4MHz. The manufacturing technology is 0.35μm, double poly-Si, four-metal (3 metals and 1 top metal) 5V CMOS process

Towards Knowledge-Intensive Software Engineering

Postprin

Parsing Thai Social Data: A New Challenge for Thai NLP

Dependency parsing (DP) is a task that analyzes text for syntactic structure and relationship between words. DP is widely used to improve natural language processing (NLP) applications in many languages such as English. Previous works on DP are generally applicable to formally written languages. However, they do not apply to informal languages such as the ones used in social networks. Therefore, DP has to be researched and explored with such social network data. In this paper, we explore and identify a DP model that is suitable for Thai social network data. After that, we will identify the appropriate linguistic unit as an input. The result showed that, the transition based model called, improve Elkared dependency parser outperform the others at UAS of 81.42%.Comment: 7 Pages, 8 figures, to be published in The 14th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP 2019

Reify Your Collection Queries for Modularity and Speed!

Modularity and efficiency are often contradicting requirements, such that programers have to trade one for the other. We analyze this dilemma in the context of programs operating on collections. Performance-critical code using collections need often to be hand-optimized, leading to non-modular, brittle, and redundant code. In principle, this dilemma could be avoided by automatic collection-specific optimizations, such as fusion of collection traversals, usage of indexing, or reordering of filters. Unfortunately, it is not obvious how to encode such optimizations in terms of ordinary collection APIs, because the program operating on the collections is not reified and hence cannot be analyzed. We propose SQuOpt, the Scala Query Optimizer--a deep embedding of the Scala collections API that allows such analyses and optimizations to be defined and executed within Scala, without relying on external tools or compiler extensions. SQuOpt provides the same "look and feel" (syntax and static typing guarantees) as the standard collections API. We evaluate SQuOpt by re-implementing several code analyses of the Findbugs tool using SQuOpt, show average speedups of 12x with a maximum of 12800x and hence demonstrate that SQuOpt can reconcile modularity and efficiency in real-world applications.Comment: 20 page

Towards OWL-based Knowledge Representation in Petrology

This paper presents our work on development of OWL-driven systems for formal representation and reasoning about terminological knowledge and facts in petrology. The long-term aim of our project is to provide solid foundations for a large-scale integration of various kinds of knowledge, including basic terms, rock classification algorithms, findings and reports. We describe three steps we have taken towards that goal here. First, we develop a semi-automated procedure for transforming a database of igneous rock samples to texts in a controlled natural language (CNL), and then a collection of OWL ontologies. Second, we create an OWL ontology of important petrology terms currently described in natural language thesauri. We describe a prototype of a tool for collecting definitions from domain experts. Third, we present an approach to formalization of current industrial standards for classification of rock samples, which requires linear equations in OWL 2. In conclusion, we discuss a range of opportunities arising from the use of semantic technologies in petrology and outline the future work in this area.Comment: 10 pages. The paper has been accepted by OWLED2011 as a long presentatio