Computational methods for Traditional Chinese Medicine: a survey

Traditional Chinese Medicine (TCM) has been actively researched through various approaches, including computational techniques. A review on basic elements of TCM is provided to illuminate various challenges and progresses in its study using computational methods. Information on various TCM formulations, in particular resources on databases of TCM formulations and their integration to Western medicine, are analyzed in several facets, such as TCM classifications, types of databases, and mining tools. Aspects of computational TCM diagnosis, namely inspection, auscultation, pulse analysis as well as TCM expert systems are reviewed in term of their benefits and drawbacks. Various approaches on exploring relationships among TCM components and finding genes/proteins relating to TCM symptom complex are also studied. This survey provides a summary on the advance of computational approaches for TCM and will be useful for future knowledge discovery in this area.     

Computational methods for modeling facial aging: A survey

Facial aging, a new dimension that has recently been added to the problem of face recognition, poses interesting theoretical and practical challenges to the research community. The problem which originally generated interest in the psychophysics and human perception community has recently found enhanced interest in the computer vision community. How do humans perceive age? What constitutes an age-invariant signature that can be derived from faces? How compactly can the facial growth event be described? How does facial aging impact recognition performance? In this paper, we give a thorough analysis on the problem of facial aging and further provide a complete account of the many interesting studies that have been performed on this topic from different fields. We offer a comparative analysis of various approaches that have been proposed for problems such as age estimation, appearance prediction, face verification, etc. and offer insights into future research on this topic.     

Computational methods for parametric LQ problems--A survey

Iterative methods for finding the optimal constant feedback gains for parametric LQ problems, notably for optimal constant output feedback problems, are surveyed. The connections of several methods to loss function expansions are discussed with important implications to the understanding of their convergence properties. Especially, the descent Anderson-Moore method, Levine-Athans like methods, and the Newton method are considered. Convergence results are also included. The initialization problem and the output feedback stabilization problem are also discussed. Furthermore, it is shown that the concepts and methods surveyed in this paper are useful in solving many realistic generalized parametric LQ problems as well, notably so-called robust parametric LQ problems.     

Urdu language processing: a survey

Extensive work has been done on different activities of natural language processing for Western languages as compared to its Eastern counterparts particularly South Asian Languages. Western languages are termed as resource-rich languages. Core linguistic resources e.g. corpora, WordNet, dictionaries, gazetteers and associated tools being developed for Western languages are customarily available. Most South Asian Languages are low resource languages e.g. Urdu is a South Asian Language, which is among the widely spoken languages of sub-continent. Due to resources scarcity not enough work has been conducted for Urdu. The core objective of this paper is to present a survey regarding different linguistic resources that exist for Urdu language processing, to highlight different tasks in Urdu language processing and to discuss different state of the art available techniques. Conclusively, this paper attempts to describe in detail the recent increase in interest and progress made in Urdu language processing research. Initially, the available datasets for Urdu language are discussed. Characteristic, resource sharing between Hindi and Urdu, orthography, and morphology of Urdu language are provided. The aspects of the pre-processing activities such as stop words removal, Diacritics removal, Normalization and Stemming are illustrated. A review of state of the art research for the tasks such as Tokenization, Sentence Boundary Detection, Part of Speech tagging, Named Entity Recognition, Parsing and development of WordNet tasks are discussed. In addition, impact of ULP on application areas, such as, Information Retrieval, Classification and plagiarism detection is investigated. Finally, open issues and future directions for this new and dynamic area of research are provided. The goal of this paper is to organize the ULP work in a way that it can provide a platform for ULP research activities in future.     

Using slots and modifiers in logic grammars for natural language

In this paper, ideas are presented for the expression of natural language grammars in clausal logic, following the work of Colmerauer, Kowalski, Dahl, Warren, and F. Pereira. A uniform format for syntactic structures is proposed, in which every syntactic item consists of a central predication, a cluster of modifiers, a list of features, and a determiner. The modifiers of a syntactic item are again syntactic items (of the same format), and a modifier's determiner shows its function in the semantic structure. Rules for semantic interpretation are given which include the determination of scoping of modifiers (with quantifier scoping as a special case). In the rules for syntax, the notions of slots and slot-filling play an important role, based on previous work by the author. The ideas have been tested in an English data base query system, implemented in Prolog.     

Reversible logic grammars for natural language parsing and generation

The use of a single grammar in natural language parsing and generation is most desirable for a variety of reasons, including efficiency, perspicuity, integrity, robustness, and a certain amount of elegance. These characteristics have been noted before by several researchers, but it was only recently that more serious attention started to be paid to the problem of creating a bidirectional system for natural language processing. In this paper we discuss a somewhat more radical version of the problem: given a parser for a language, can we reverse it so that it becomes an efficient generator for the same language? Furthermore, since both the parser and the generator are based upon the same grammar, are there any normalization conditions upon the form of the grammar that must be met in order to assure the maximum efficiency of the reversed program? Can other grammars be transformed into the normal form? We describe the results of an experiment with PROLOG-based logic grammar which has been derived from a substantial-coverage string grammar for English. We present an alogorithm for automated inversion of a unification parser into an efficient unification generator, using the collections of minimal sets of essential arguments for predicates. We discuss the scope of the present version of the algorithm and then point out several possible avenues for extension. We also outline a preliminary solution to the question of grammar's “normal form” and suggest a handful of normalizing transformations that can be used to enhance the efficiency of the generator. This research interacts closely with a Japanese-English machine translation project at New York University, for which the first implementation of the inversion algorithm has been prepared.     

Natural language based financial forecasting: a survey

Natural language processing (NLP), or the pragmatic research perspective of computational linguistics, has become increasingly powerful due to data availability and various techniques developed in the past decade. This increasing capability makes it possible to capture sentiments more accurately and semantics in a more nuanced way. Naturally, many applications are starting to seek improvements by adopting cutting-edge NLP techniques. Financial forecasting is no exception. As a result, articles that leverage NLP techniques to predict financial markets are fast accumulating, gradually establishing the research field of natural language based financial forecasting (NLFF), or from the application perspective, stock market prediction. This review article clarifies the scope of NLFF research by ordering and structuring techniques and applications from related work. The survey also aims to increase the understanding of progress and hotspots in NLFF, and bring about discussions across many different disciplines.     

A survey of grammatical inference methods for natural language learning

The high complexity of natural language and the huge amount of human and temporal resources necessary for producing the grammars lead several researchers in the area of Natural Language Processing to investigate various solutions for automating grammar generation and updating processes. Many algorithms for Context-Free Grammar inference have been developed in the literature. This paper provides a survey of the methodologies for inferring context-free grammars from examples, developed by researchers in the last decade. After introducing some preliminary definitions and notations concerning learning and inductive inference, some of the most relevant existing grammatical inference methods for Natural Language are described and classified according to the kind of presentation (if text or informant) and the type of information (if supervised, unsupervised, or semi-supervised). Moreover, the state of the art of the strategies for evaluation and comparison of different grammar inference methods is presented. The goal of the paper is to provide a reader with introduction to major concepts and current approaches in Natural Language Learning research.     

Computational algorithms for linear control systems: a brief survey

This paper presents a brief survey of computational algorithms for the analysis and synthesis of linear control systems described in the state space. An attempt is made to select the most efficient methods for analysis of the stability, controllability and observability, the reduction into canonical forms, the pole assignment synthesis and the synthesis of optimal systems with quadratic cost. Some aspects of the development of mathematical software for solving these problems are also discussed.     

The role of native grammars in correcting errors in second language learning

This paper describes VP², a system that has been implemented to tutor nonnative speakers in English. This system differs from many tutoring systems by employing an explicit grammar of its user's native language. This grammar enables VP² to customize its responses by addressing problems due to interference of the native language. The system focuses on the acquisition of English verb-particle and verb-prepositional phrase constructions. Its correction strategy is based upon comparison of the native language grammar with an English grammar. VP² is a modular system: its grammar of a user's native language can easily be replaced by a grammar of another language. The problems and solutions presented in this paper are related to the more general question of how modelling previous knowledge facilitates instruction in a new skill.     

Data dimensionality estimation methods: a survey

In this paper, data dimensionality estimation methods are reviewed. The estimation of the dimensionality of a data set is a classical problem of pattern recognition. There are some good reviews (Algorithms for Clustering Data, Prentice-Hall, Englewood Cliffs, NJ, 1988) in literature but they do not include more recent developments based on fractal techniques and neural autoassociators. The aim of this paper is to provide an up-to-date survey of the dimensionality estimation methods of a data set, paying special attention to the fractal-based methods.     

Computational complexity of manipulation: A survey

In situations when a group of people has to make a decision based on the set of individual preferences, they use a certain aggregation method, in particular, voting. One of the main problems for any non-dictatorial social choice rule is the possibility for the voters to achieve a more preferable outcome of the voting by misrepresenting their preferences. Such actions on behalf of the voters are called manipulation, or strategic voting. One approach used to compare social choice rules in terms of how hard they are to manipulate is to find the complexity classes of manipulation problems for a given aggregation method. In this work, we present a survey of the studies of complexity classes of manipulation problems under various model assumptions and constraints.     

Adding classes to the C language: An exercise in language evolution

The C language is a fine tool for writing compact and efficient programs. It is relatively easy to produce good compilers for, and the number of tools available for supporting program- ming in C is large, especially in its ‘home environment’, the UNM system. However, C'S facilities for structuring programs were, until recently, rather limited. To remedy this situation, a data abstraction facility, called classes, was added. The class concept described here has benefitted from the experience gained through a year's use. It is now in use at close to a hundred installations. The guiding principles of the design of C classes were simplicity both in concept and in implementation. Smooth blending of the new facilities into the existing C programming environment was considered essential. Classes can be used without sacrificing the run-time efficiency expected from C. This paper presents some of the reasons why C classes are what they are.     

Lexicalization in natural language generation: A survey

In natural language generation, a meaning representation of some kind is successively transformed into a sentence or a text. Naturally, a central subtask of this problem is the choice of words, orlexicalization. In this paper, we propose four major issues that determine how a generator tackles lexicalization, and survey the contributions that researchers have made to them. Open problems are identified, and a possible direction for future research is sketched.