Search results for: Basà

Authors: Imoh Philip

Abstract:

Basà language is classified as belonging to Kainji family, under the sub-phylum Western-Kainji known as Rubasa (Basa Benue) (Croizier & Blench, 1992:32). Basà is an under-described language spoken in the North-Central Nigeria. The language is characterized by subject-verb-object (henceforth SVO) as its canonical word order. Data for this work is sourced from the researcher’s native intuition of the language corroborated with a careful observation of native speakers. This paper investigates the syntactic derivational strategy of information-structure encoding in Basà language. It emphasizes on a negative operator, as a strategy for focusing a constituent or clause that follows it and negativizes a whole proposition. For items that are not nouns, they have to undergo an obligatory nominalization process, either by affixation, modification or conversion before they are moved to the pre verbal position for these operations. The study discovers and provides evidence of the fact showing that deferent constituents in the sentence such as the subject, direct, indirect object, genitive, verb phrase, prepositional phrase, clause and idiophone, etc. can be focused with the same negativizing operator. The process is characterized by focusing the pre verbal NP constituent alone, whereas the whole proposition is negated. The study can stimulate similar study or be replicated in other languages.

Keywords: negation, focus, Basà, nominalization

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Authors: Imoh Philip

Abstract:

This work investigates four verbal extensions; two in each set resulting in two opposite effects of the valency of verbs in Basà language. Basà language is an indigenous language spoken in Kogi, Nasarawa, Benue, Niger states and all the Federal Capital Territory (FCT) councils. Crozier & Blench (1992) and Blench & Williamson (1988) classify Basà as belonging to Proto–Kru, under the sub-phylum Western –Kru. It studies the effects of such morphosyntactic operations in Basà language with special focus on ‘reflexives’ ‘reciprocals’ versus ‘causativization’ and ‘applicativization’ both sets are characterized by polar syntactic processes of either decreasing or increasing the verb’s valency by one argument vis-à-vis the basic number of arguments, but by the similar morphological processes. In addition to my native intuitions as a native speaker of Basà language, data elicited for this work include discourse observation, staged and elicited spoken data from fluent native speakers. The paper argues that affixes attached to the verb root, result in either deriving an intransitive verb from a transitive one or a transitive verb from a bi/ditransitive verb and equally increase the verb’s valence deriving either a bitransitive verb from a transitive verb or a transitive verb from a intransitive one. Where the operation increases the verb’s valency, it triggers a transformation of arguments in the derived structure. In this case, the applied arguments displace the inherent ones. This investigation can stimulate further study on other transformations that are either syntactic or morphosyntactic in Basà and can also be replicated in other African and non-African languages.

Keywords: verbal extension, valency, reflexive, reciprocal, causativization, applicativization, Basà

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Authors: Frankie Burgos, Emely Munar, Conrado Basa

Abstract:

This paper aimed at developing an artificial neural network (ANN) model specifically for the Philippine Stock Exchange index closing value. The inputs to the ANN are US Dollar and Philippine Peso(USD-PHP) exchange rate, GDP growth of the country, quarterly inflation rate, 10-year bond yield, credit rating of the country, previous open, high, low, close values and volume of trade of the Philippine Stock Exchange Index (PSEi), gold price of the previous day, National Association of Securities Dealers Automated Quotations (NASDAQ), Standard and Poor’s 500 (S & P 500) and the iShares MSCI Philippines ETF (EPHE) previous closing value. The target is composed of the closing value of the PSEi during the 627 trading days from November 3, 2011, to May 30, 2014. MATLAB’s Neural Network toolbox was employed to create, train and simulate the network using multi-layer feed forward neural network with back-propagation algorithm. The results satisfactorily show that the neural network developed has the ability to model the PSEi, which is affected by both internal and external economic factors. It was found out that the inputs used are the main factors that influence the movement of the PSEi closing value.

Keywords: artificial neural networks, artificial intelligence, philippine stocks exchange index, stocks trading

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Authors: Thelma Palaoag, Melanie Basa, Jezreel Mark Panilo

Abstract:

Checking short-answer questions and essays, whether it may be paper or electronic in form, is a tiring and tedious task for teachers. Evaluating a student’s output require wide array of domains. Scoring the work is often a critical task. Several attempts in the past few years to create an automated writing assessment software but only have received negative results from teachers and students alike due to unreliability in scoring, does not provide feedback and others. The study aims to create an application that will be able to check short-answer questions which incorporate information extraction. Information extraction is a subfield of Natural Language Processing (NLP) where a chunk of text (technically known as unstructured text) is being broken down to gather necessary bits of data and/or keywords (structured text) to be further analyzed or rather be utilized by query tools. The proposed system shall be able to extract keywords or phrases from the individual’s answers to match it into a corpora of words (as defined by the instructor), which shall be the basis of evaluation of the individual’s answer. The proposed system shall also enable the teacher to provide feedback and re-evaluate the output of the student for some writing elements in which the computer cannot fully evaluate such as creativity and logic. Teachers can formulate, design, and check short answer questions efficiently by defining keywords or phrases as parameters by assigning weights for checking answers. With the proposed system, teacher’s time in checking and evaluating students output shall be lessened, thus, making the teacher more productive and easier.

Keywords: information extraction, short-answer question, natural language processing, application

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