Question Answering Model in Thai by using Squad Thai Wikipedia dataset

Nowadays, Question Answering is one of the challenge applications in the Natural language processing domain. There are plenty of English language Question Answering model distributed on the model sharing website such as Hugging face hub. Unlike Thai language, there is on a few Thai language Question Answering model distributed on the model sharing website. So, we decided to fine-tune a multilingual Question Answering model to a specify language which is Thai language. The datasets that we will use for training is a Thai Wikipedia dataset from iApp Technology. We have tried to fine-tune on two multilingual model. We also create another dataset to evaluate adaptivity of the model. The result came out to be as satisfy. Both fine-tuned models perform better than base model on evaluation score. We have published Question Answering model to Hugging face hub that will allow people to using these models for others application later.

Question Answering Model in Thai by using Squad Thai Wikipedia dataset

Nowadays, Question Answering is one of the challenge applications in the Natural language processing domain. There are plenty of English language Question Answering model distributed on the model sharing website such as Hugging face hub. Unlike Thai language, there is on a few Thai language Question Answering model distributed on the model sharing website. So, we decided to fine-tune a multilingual Question Answering model to a specify language which is Thai language. The datasets that we will use for training is a Thai Wikipedia dataset from iApp Technology. We have tried to fine-tune on two multilingual model. We also create another dataset to evaluate adaptivity of the model. The result came out to be as satisfy. Both fine-tuned models perform better than base model on evaluation score. We have published Question Answering model to Hugging face hub that will allow people to using these models for others application later.

A systematic study of independently-tuned room-specific PBS beam model in a beam-matched multiroom proton therapy system

Background In the existing application of beam-matched multiroom proton therapy system, the model based on the commissioning data from the leading treatment room was used as the shared model. The purpose of this study is to investigate the ability of independently-tuned room-specific beam models of beam-matched gantries to reproduce the agreement between gantries’ performance when considering the errors introduced by the modeling process. Methods Raw measurements of two gantries’ dosimetric characteristics were quantitatively compared to ensure their agreement after initially beam-matched. Two gantries’ beam model parameters, as well as the model-based computed dosimetric characteristics, were analyzed to study the introduced errors and gantries’ post-modeling consistency. We forced two gantries to share the same beam model. The model-sharing patient-specific quality assurance (QA) tasks were retrospectively performed with 36 cancer patients to study the clinical impact of beam model discrepancies. Results Intra-gantry comparisons demonstrate that the modeling process introduced the errors to a certain extent indeed, which made the model-based reproduced results deviate from the raw measurements. Among them, the deviation introduced to the IDD curves was generally larger than that to the beam spots during modeling. Cross-gantry comparisons show that, from the beam model perspective, the introduced deviations deteriorated the high agreement of the dosimetric characteristics originally shown between two beam-matched gantries, but the cross-gantry discrepancy was still within the clinically acceptable tolerance. In model-sharing patient-specific QA, for the particular gantry, the beam model usage for intensity-modulated proton therapy (IMPT) QA plan generation had no significant effect on the actual delivering performance. All reached a high level of 95.0% passing rate with a 3 mm/3% criterion. Conclusions It was preliminary recognized that among beam-matched gantries, the independently-tuned room-specific beam model from any gantry is reasonable to be chosen as the shared beam model without affecting the treatment efficacy.

GO-DEVS: Storage and Retrieval System for DEVS Models Using Graph and Ontology Representation

DEVS is a powerful formal language to describe discrete event systems in modeling and simulation areas and useful for component-based design. One of the advantages of component-based design is reusability. To reuse or share DEVS models developed by many other modelers, a system to systematically store and retrieve many DEVS models should be supported. However, to the best of our knowledge, there does not exist such a system. In this paper, we propose GO-DEVS (Graph/Ontology-represented DEVS storage and retrieval system) to store and retrieve DEVS models using graph and ontology representation. For effective model sharing, an ontology is introduced when a DEVS model is developed. To search for DEVS models in an effective and efficient way, we propose two types of queries, IO query and structure query, and provide a method to store and query DEVS models on an RDBMS. Finally, we experimentally show GO-DEVS can process the queries efficiently.

Mobile Edge Computing for Beyond 5G/6G

This chapter first introduces the mobile edge computing (MEC) paradigm in beyond 5G and 6G networks. The motivations, applications, and challenges of integrating MEC into 6G are discussed in detail. We then present a new paradigm, MEC-empowered edge model sharing, as a use case for 6G. Furthermore, the architecture and processes of the MEC-empowered edge model sharing system are provided to show the integration angles of MEC and 6G networks.

HARMONISASI POLA ASUH ORANG TUA DENGAN PENGAJARAN SEKOLAH MINGGU TERHADAP PEMBENTUKAN KARAKTER ANAK USIA DINI BERDASARKAN NILAI-NILAI SPIRITUAL DI GKPB JEMAAT GALANG NING SABDA CICA BALI

Pertumbuhanan dan perkembangan karakter anak tidak terlepas dari tanggunjgawab orang tua dalam menerapkan pola asuh dalam keluarga dan juga pengajaran yang diberikan disekolah, termasuk sekolah minggu. Orang tua sebagai penanggungjawab utama dari pertumbuhan dan karakter anak, maupun guru-guru sekolah minggu, sama berperan penting dalam pembentukan karakter anak. Tetapi kenyataan yang terjadi adalah tidak adanya harmoni (Dishamorni) antara orang tua dan guru sekolah minggu. Tidak adanya harmoni ini terlihat dari sikap acuhnya orang tua terhadap pengajaran sekolah minggu yang diterima oleh anak-anak mereka. Disisi lain, kurangnya komunikasi guru-guru sekolah minggu dengan orang tua juga menjadi salah satu satu penyebab disharmoni. Tujuan penulisan penelitian ini adalah untuk mengetahui pola asuh orang tua dengan pengajaran sekolah minggu, menentukan karakter anak usia dini berdasarkan nilai-nilai spiritual, menghasilkan model harmonisasi pola asuh orang tua dengan pembelajaran sekolah minggu pada pembentukan karakter anak usia dini berdasarkan nilai-nilai spiritual yang ada di GKPB Jemaat Galang Ning Sabda Cica Bali. Metode penelitian yang digunakan peneliti dalam penelitian ini adalah penelitian kualitatif, yaitu penelitian yang bertujuan untuk memperoleh pemahaman yang lebih luas dan mendalam tentang Model Harmonisasi Pola Asuh Orang Tua dan Pengajaran Sekolah Minggu Terhadap Pembentukan Karakter Anak Usia Dini Berdasarkan Nilai Spiritual di GKPB Galang Ning Jemaat Sabda Cica Bali. Hasil dari penelitian ini memperlihatkan bahwa Model Harmonisasi antara Pola Asuh Orang Tua di rumah dengan Pengajaran sekolah minggu yang dapat diterapkan adalah model komunikasi, model kerja sama, model sharing of life dan model pertemuan rutin.