The National Agency for Language Development and Cultivation (henceforth, Badan Bahasa) has published many dictionaries as a government agency under the Ministry of Education and Culture of ...Indonesia. More than 100 dictionaries have been published since 1977. Some dictionaries have been revised by adding new entries and senses. In alignment with technological developments, Badan Bahasa has started an integration project that aims to provide an online application for their language products. In 2015, it started Program Pengayaan Kosakata (Word proposal application program), and this was followed by the launch of the online version of the Kamus Besar Bahasa Indonesia (KBBI; Comprehensive dictionary of Indonesian), Tesaurus Tematis Bahasa Indonesia (Thematic thesaurus of Indonesian), and Ensiklopedia Sastra Indonesia (Encyclopedia of Indonesian literature) in 2016. In 2020, Badan Bahasa started the development of Aplikasi Pangkalan Data Kamus, also called Aplikasi Kompilasi Kamus (AKK; Dictionary compilation application). This online application accommodates at least three kinds of dictionary – a local language dictionary, specialized dictionary, and bilingual dictionary – published by Badan Bahasa. The process has continued by developing a digitalization project targeting the digitalization of print versions of specialized dictionaries, Indonesian-local language dictionaries, and local language-Indonesian dictionaries. This article aims to discuss some challenges regarding the digitalization of dictionaries arising from the print versions, the dictionary structure, and the dictionary interface, and puts forward some solutions to deal with the issues. The research method uses qualitative methods for observing dictionary files and examining microstructure issues throughout the whole process. The results of this study are expected to support the digitalization process and dictionary development in Indonesia.
English as an international language plays an important role in the lives of Balinese people since Bali is a world tourism destination. In general Balinese people use English when they ...communicate with tourists because most of the Balinese work at tourism. Therefore, it is inevitable that English is one of the most popular languages ??for the younger Balinese generation to learn. However, the difference in the pronunciation system between English and Balinese, which is the mother tongue of the Balinese people, is often a problem. One of the most common types of pronunciation difficulties is the pronunciation of diphthongs in English. Pronunciation errors will certainly have an impact on misunderstandings in English communication.
Based on this phenomenon, this community service is carried out with the aim of providing one solution to improve the ability to pronounce diphthongs in English, namely by utilizing various online dictionaries that are equipped with audio features. This solution is believed to be one of the options that can be done considering that currently, Balinese people are very close to technology, but some still are not able to fully utilize the dictionary in the network. The target of this community service activity was the students of SMK PGRI Payangan Gianyar. The selection of Payangan Gianyar area is due to it has the potency to become a new tourist destination in Gianyar District.
Keywords: diphthong, online dictionary, community service
With the advancement of educational technologies, computer-assisted language learning (CALL) tools, like online dictionaries, are essential for acquiring a second language, especially new vocabulary. ...There has been no empirical focus on the usage of Ġabra online dictionary in learning Maltese, with a specific focus on international adults learning Maltese as a second language (ML2) and a lack of research in the pedagogy of e-dictionaries. This study aims to contribute to this research gap by exploring teachers' perspectives and pedagogy of Ġabra for adults learning ML2, which could refer to any other second language. Unstructured interviews were conducted to obtain qualitative data from eleven teachers of ML2 adult learners including refugee learners. According to the study's findings, Ġabra helps students learn new words, it is simple to use, it is a great resource and reference for ML2 learning, and it is convenient. The research also offers various pedagogical activities that illustrate how Ġabra is implemented in class. Another significant characteristic of Ġabra identified in this study is that students do not need to know the basic verb/noun/adjective to seek for a word, as they would in a traditional dictionary. Ġabra's shortcomings were its incompleteness, no pronunciation feature, lack of sentence examples and its dependency on internet access. Although Ġabra's benefits exceeded its disadvantages, it was recommended that Ġabra should continue to be corrected and to use artificial intelligence applications.
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Data transmission is crucial in the process of equipment monitoring. The compression algorithms are adopted to reduce the amount of data transmission. When sparse encoding algorithms are used for ...this purpose, despite extensive attempts to improve their performance, some problems still remain. The main issues pertain to: (1) Dictionary construction − As practical dictionary better matches the input signal, such a dictionary must be efficiently established; 2) The setting of sparsity value − It is difficult to determine the size of sparsity values when prior knowledge is insufficient (when the parameter settings are too large, the cost of data transmission increases considerably, while excessively small values can result in poor reconstruction accuracy); and (3) How to implement engineering applications of data compression based on sparse encoding. To address these issues, in this work, an optimized sparse encoding algorithm is proposed by combining the non-negative Online Dictionary Learning (ODL) with the optimized Orthogonal Matching Pursuit (OMP) algorithm. First, a non-negative ODL algorithm is adopted for dictionary learning based on the training dataset to obtain an effective dictionary. Next, the optimized OMP algorithm is used to obtain the sparsity and the sparse coefficient matrix. Further analyses confirm that the reconstructed signal has a small reconstruction error. Finally, A lossy compression framework is proposed for the compressing equipment condition monitoring data using sparse encoding algorithms. Compared with the compression algorithms based on compressive sensing and DCT, the average compression ratio can reach 42.7 when the reconstruction accuracy is similar. In terms of comprehensive compression performance, the quality score is also higher compared to other algorithms.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
Online dictionaries provide unique possibilities to both dictionary makers and users, in particular in the following areas (cf. Granger 2012: 4ff): Accessibility of data, multimedia ...functions, customization, hybridization, user-input and storage space. This article investigates the extent to which these opportunities have been exhausted in current online learner’s dictionaries. It demonstrates that the vast technological opportunities of the internet are only beginning to be fully exploited. While storage space, for example, is already being used effectively to provide additional example sentences and collocations, the dictionaries under investigation offer partly unsatisfactory functionality in terms of data accessibility and several other areas.
In a big data environment, the data from long-term monitoring are of great importance in intelligent diagnoses, prognostic and health management of industrial components. However, in practice, it is ...difficult to ensure high reconstructive accuracy making the preservation performance of low-frequency information (e.g., periodic fault impulses) stable. To address this issue, this article proposes a new data reconstruction method that combines a smoothing sparse low-rank matrix (SSLRM) with online dictionary learning. This article first presents the design of SSLRM model for decomposing the raw data into a low resonance component (LRC) and a high resonance component (HRC), such that the periodic fault impulse can be isolated and preserved in advance. Then, both LRC and HRC are, respectively, reconstructed using an online dictionary learning algorithm, i.e., Hankel K-singular value decomposition; thus, the reconstructed data can be obtained accordingly. Both simulation case and engineering case are applied to show the effectiveness and practicality of the proposed approach.
•The physical meaning of the L1 norm is given in the paper.•The method can deal with pseudo-color medical image fusion, the color information in the fusion image is least distorted, and the spatial ...details remain well.•The geometrical direction of the patch is used as the criteria for patch classification, which produces the directional sub-dictionary and ensures a more accurate sparse representation for the directional patch.
Medical image fusion is one of the hot research in the field of medical imaging and radiation medicine, and is widely recognized by medical and engineering fields. In this paper, a new fusion scheme for medical images based on sparse representation of classified image patches is proposed. In this method, first, the registered source images are divided into classified patches according to the patch geometrical direction, from which the corresponding sub-dictionary is trained via the online dictionary learning (ODL) algorithm, and the least angle regression (LARS) algorithm is used to sparsely code each patch; second, the sparse coefficients are combined with the “choose-max” fusion rule; Finally, the fused image is reconstructed from the combined sparse coefficients and the corresponding sub-dictionary. The experimental results showed that the proposed method outperforms other methods in terms of both visual perception and objective evaluation metrics.
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Abstract
Naming emotions may pose a serious problem for foreign language learners as emotion words constitute a complex semantic field. Here is where monolingual learners’ dictionaries turn out to be ...useful. The paper reports on a comparative analysis of dictionary representation of the semantics of adjectives signifying emotions. To investigate the treatment of this semantic field, twenty-four adjectives are looked up in the five British pedagogical dictionaries published by Oxford, Cambridge, Longman, Macmillan and Collins. The qualitative analysis concentrates on definitions as primary carriers of meaning. Yet, examples, grammatical information and additional sources of information within a dictionary entry are also given attention. The study demonstrates that some inconsistencies in defining emotion words in individual dictionaries can be spotted. The value of examples is limited: some focus merely on presenting a word’s syntactic properties. Thus, the combination of the definition and the examples both clarifying meaning and illustrating the typical use of the words is judged to best represent meaning. The paper suggests model definitions of adjectives signifying emotions and offers recommendations aiming at improving the representation of their meaning in dictionaries.
