LEXICAL DEVIATIONS OF THE TRANSLATED VERSION OF THE FAIRY TALE ENTITLED “THE ORIGIN OF GOOSES HAVE LONG NECK†(BILINGUAL VERSION: INDONESIAN-ENGLISH) SERI I

Abstract-Translation becomes the basic requirement in exchanging process of information in the world. Fairy tale is a kind of learning media in the form of books for children which is written in Indonesia and is translated into English. In this case, the translators sometimes make deviations in translated work such as a fairy tale. Fairy tales are rarely considered as the data research to be analyzed. Some researchers pay more attention to analyze novels, poems, and films as the sample of data than fairy tale, perhaps, because the style of fairy tale is more imaginative, literal, and more simple than another literary text.The researcher is intended to find out the types of lexical errors in this study by using Peter Newmark theory and Nida theory. The study applies the descriptive qualitative research method in textual or document analysis. The data of the research are the sentences and utterances that contain errors in lexical type.This research concludes that errors or deviations can cause or create different meaning from the original text which is read by the reader. The greatest errors occur when the structure in the sentence of target text is not complete. It can be said that English language must notice grammar, and it must be natural

Modeling Large Time Series for Efficient Approximate Query Processing

Evolving customer requirements and increasing competition force business organizations to store increasing amounts of data and query them for information at any given time. Due to the current growth of data volumes, timely extraction of relevant information becomes more and more difficult with traditional methods. In addition, contemporary Decision Support Systems (DSS) favor faster approximations over slower exact results. Generally speaking, processes that require exchange of data become inefficient when connection bandwidth does not increase as fast as the volume of data. In order to tackle these issues, compression techniques have been introduced in many areas of data processing. In this paper, we outline a new system that does not query complete datasets but instead utilizes models to extract the requested information. For time series data we use Fourier and Cosine transformations and piece-wise aggregation to derive the models. These models are initially created from the original data and are kept in the database along with it. Subsequent queries are answered using the stored models rather than scanning and processing the original datasets. In order to support model query processing, we maintain query statistics derived from experiments and when running the system. Our approach can also reduce communication load by exchanging models instead of data. To allow seamless integration of model-based querying into traditional data warehouses, we introduce a SQL compatible query terminology. Our experiments show that querying models is up to 80 % faster than querying over the raw data while retaining a high accuracy

Performance analysis of a novel decentralised MAC protocol for cognitive radio networks

Due to the demand of emerging Cognitive Radio (CR) technology to permits using the unused licensed spectrum parts by cognitive users (CUs) to provide opportunistic and efficient utilisation of the white spaces. This requires deploying a CR MAC with the required characteristics to coordinate the spectrum access among CUs. Therefore, this paper presents the design and implementation of a novel Medium Access Control (MAC) protocol for decentralised CRNs (MCRN). The protocol provides efficient utilisations of the unused licensed channels and enables CUs to exchange data successfully over licensed channels. This is based on the observation procedure of sensing the status of the Licensed Users (LUs) are ON or OFF over the licensed channels. The protocol is validated with the comparison procedure against two different benchmark protocols in terms of the network performance; communication time and throughput. Therefore, performance analysis demonstrated that the proposed MCRN perform better and achieve higher throughput and time benefits than the benchmarks protocols