A Case Study of Dholuo Anaphors using Relevance Theory | Chapter 6 | Progress in Language, Literature and Education Research Vol. 9

 

This paper aims to investigate the interpretation of anaphors in Dholuo in different contexts to ascertain their relevance in utterances. A number of studies on languages all over the world indicate the presence of anaphors such as reflexives and reciprocals. These anaphors occupy different positions with regard to their occurrence, hence determining their varied interpretations. This could probably be due to anaphors deriving reference from the antecedent that occurs before them in an utterance. These anaphors are also marked as morphemes or lexically marked. Dholuo an African language, for instance, marks the reflexive and the reciprocal by the same morpheme, which poses some ambiguity in their interpretation. A descriptive design was employed to describe the anaphors using Relevance Theory (RT) as the tool for analysis. The corpus of primary data used in this paper consists of a string of sentences with anaphors elicited through the researcher’s intuition as a native speaker, and also from the participants through semi-structured interviews. In order to ensure validity, data was verified by six adult native speakers selected through a purposeful sampling technique. Data collected was presented systematically and then analyzed procedurally. RT Cognitive and Communicative Principles were employed to describe the relevance of the anaphoric utterances in the utterance. To guarantee a clear interpretation of the utterance in various situations, a Relevance Comprehension Procedure (RCP) was added. The outcome shows that when context is added, Dholuo anaphors can be distinguished between reflexives and reciprocals. Because the anaphora is used so frequently, it is clear that both the speaker and the listener understand the utterance's inferred meaning.  However, RT may fail to provide an immediate interpretation of the utterance with the prevailing context. This led to violation of the RCP as more contexts are presented to ensure the right interpretation is reached. This calls for the theory to accommodate utterances that require a lot of effort to interpret.

 

Author(s)details:-

 

Janet Achieng’ Onyango
Department of Literature, Linguistics and Foreign Languages, Kenyatta University, Box 43844-00100, Nairobi, Kenya.

 

Henry Simiyu Nandelenga
Department of English, Literature and Journalism, Kibabii University, 1699-50200, Bungoma, Kenya.

 

Please See the book here :- https://doi.org/10.9734/bpi/pller/v9/12324F

Contextual Complexities and Second Language Acquisition in Cameroon | Chapter 5 | Progress in Language, Literature and Education Research Vol. 5

The complexity of the linguistic environment in Cameroon raises the question of context and its role in the acquisition of another language. While examining progress in English language learning in Cameroon, this chapter draws a dichotomy between learners in such contexts considered rural and those regarded as urban or cosmopolitan with its inherent complexities. Using the irregular verb as a yardstick, an evaluation of the acquisition of irregular verb patterns by 80 final year primary school learners from two contexts in the Northwest Region of Cameroon serves as a guide. Oral and written tests are used to check learners’ acquisition of verb inflectional categories, verb tenses and general written and oral productions within the mixed method design. The findings reveal similar trends in the acquisition of inflectional categories and verb tenses by learners in both contexts and divergent trends in general oral and written productions. For instance, learners in both contexts exhibit similar challenges using the Vs, Ved and Ven inflections with a very low average frequency of 26% and with a high frequency of 67.2% for the Ving and Vo inflections. Though learners in the urban centres have higher degrees of efficiency in oral productions, their counterparts in the rural areas exhibit more challenges in verbal as against written productions. The chapter concludes that second language acquisition is not a consequence of a unilateral context but a result of a plethora of other factors both within and without the learning environment with evident pedagogic implications for stakeholders in the second language acquisition industry. While context is noted to have impending implications in language learning as highlighted in the chapter, the finality of SLA is also dependent on other linguistic factors like innate capabilities inherent in all learners.

Author(s) Details:

Louis Mbibeh,
The University of Bamenda, Cameroon.

Please see the link here: https://stm.bookpi.org/PLLER-V5/article/view/13349

Self and Other-Presentation in Arabic & English Political Discourse: An Overview | Chapter 6 | Research Highlights in Language, Literature and Education Vol. 7

 This unit discusses in what way or manner political leaders use Self/Other-Presentation methods to convince their hearing with their beliefs. politics has become one of ultimate important pieces of the functioning of modern people, designed to regulate the friendship of people inside the society, to guarantee the sustainability of social processes. The distinguishing physiognomy of political ideas are publicity, individual-direction (from a communicator to a receiver), unstable and various character of the hearing. Despite recent significant progresses in political discourse research and studies, Arabic governmental discourse deserves more focus, at least taking everything in mind the region's current acceleration of governmental events.  Therefore, this study investigates how governmental leaders in the Arab-Islamic-American Summit grasped in Riyadh in May 2017 use Self/Other-Presentation to send ideas to their allies and opponents, in two together Arabic and English. significant happenings have been realized in political discourse research and studies. Due to the accelerated pace of governmental events in the Arab globe in the last decade, Arabic governmental discourse deserves more attention. The study likewise aims at investigating the ruling devices secondhand within self and other performance model in both Arabic and English governmental discourse. The findings concerning this study should be cautiously elucidated as the analysis is used to one talk in Arabic and one in English. Therefore, further research on the topic is heartened on other Arabic and English sorts.

Author(s) Details:

Sameh Salah Youssef,
Faculty of Arts, Helwan University, Egypt and King Abdulaziz University, Kingdom of Saudi Arabia.

Mohammed A. Albarakati,
King Abdulaziz University, Kingdom of Saudi Arabia.

Please see the link here: https://stm.bookpi.org/RHLLE-V7/article/view/11156

Research Issues on Datamining | Book Publisher International

 Data mining is a set of techniques for removing randomness from large and complicated databases and uncovering hidden patterns. The extraction of new knowledge from large databases is known as datamining (DM), sometimes known as knowledge discovery from databases (KDD). Data mining is the process of discovering previously undiscovered, valid patterns and relationships in big data sets using advanced data analysis techniques. Data mining techniques can estimate future trends and actions to help individuals make better decisions. Datamining has a range of applications. Identifying trends and patterns is a powerful tool for businesses across all sectors and industries.

Modern intrusion detection systems must deal with a number of difficulties. These applications must be dependable, expandable, controllable, and cost-effective to maintain. In recent years, data mining-based intrusion detection systems (IDSs) have demonstrated high accuracy, good generalisation to novel types of intrusion, and consistent behaviour in a changing environment. In order to find the optimum neural network, the number of hidden layers in various neural network topologies is compared. Misuse detection is a method of attempting to detect instances of network attacks by comparing current behaviour to the expected activities of an intruder. Artificial neural networks can detect and classify network activity even when the input is sparse, imperfect, and nonlinear.

The major goal of this research is to investigate privacy and security concerns among cloud computing users and consumers in a dispersed setting. Machine learning, natural language processing (NLP), and data mining techniques are used in conjunction to automatically detect and uncover patterns in a variety of sources. Both continuous and discontinuous changes can be dealt with using predictive analytics. Predictive analytics uses classification, prediction, and, to some extent, affinity analysis as analytical tools.

The semantic context and syntactic components are the focus of current text or document mining research. We investigated a mining model to categorise documents based on the Order of Context, Concept, and Semantic Relations in order to accomplish this, and with the inspiration garnered from our previous research efforts (OCCSR). Users will be able to get valuable information from virtually connected data warehouses using data mining techniques based on Cloud computing, cutting infrastructure and storage expenses. From the cloud, data mining can extract useful and potentially helpful information. The 3Vs are three features that are commonly used to define big data (Volume, Velocity and Variety). The report examines Big Data analytics methodologies, settings, and technologies in critical domains, as well as how they contribute in the creation of analytics solutions for Clouds.

 

Clustering is a type of unsupervised learning approach that is used to find a new set of categories. The processing time for grid-based clustering is typically determined by the size of the grid rather than the data. Three clustering algorithms are compared: hierarchical clustering, density-based clustering, and K Means clustering.

The majority of current approaches to identifying misuse rely on rule-based expert systems to identify indicators of previously detected attacks. We give a quick review of the numerous Artificial Intelligence techniques used in the design, development, and deployment of Intrusion Detection Systems (IDS) for defending computer and communication networks from intruders, as well as their improvements. Knowledge Discovery in Data (KDD) aims to extract information that isn't immediately apparent through meticulous and detailed analysis and interpretation. Analytics uses KDD, data mining, text mining, statistical and quantitative analysis, explanatory and predictive models, and advanced and interactive visualisation tools to drive choices and actions.

Author(s) Details

E. Kesavulu Reddy
Department of Computer Science, S. V. University College of CM & CS, Tirupati, Andhra Pradesh-517502, India.

View Book:- https://stm.bookpi.org/RID/article/view/5216