The Prehistoric Maritime Frontier of Southeast China

This open access book presents multidisciplinary research on the cultural history, ethnic connectivity, and oceanic transportation of the ancient Indigenous Bai Yue (百越) in the prehistoric maritime region of southeast China and southeast Asia. In this maritime Frontier of China, historical documents demonstrate the development of the “barbarian” Bai Yue and Island Yi (岛夷) and their cultural interaction with the northern Huaxia (华夏) in early Chinese civilization within the geopolitical order of the “Central State-Four Peripheries Barbarians-Four Seas”. Archaeological typologies of the prehistoric remains reveal a unique cultural tradition dominantly originating from the local Paleolithic age and continuing to early Neolithization across this border region. Further analysis of material culture from the Neolithic to the Early Iron Age proves the stability and resilience of the indigenous cultures even with the migratory expansion of Huaxia and Han (汉) from north to south. Ethnographical investigations of aboriginal heritage highlight their native cultural context, seafaring technology and navigation techniques, and their interaction with Austronesian and other foreign maritime ethnicities. In a word, this manuscript presents a new perspective on the unique cultural landscape of indigenous ethnicities in southeast China with thousands of years’ stable tradition, a remarkable maritime orientation and overseas cultural hybridization in the coastal region of southeast China

Anomaly Identification Model for Telecom Users Based on Machine Learning Model Fusion

With the development of economic globalization and modern information and communication technology, the situation of communication fraud is becoming more and more serious. How to identify fraudulent calls accurately and effectively has become an urgent task in current telecommunications operations. Affected by the sample set and the current state of the art, the current machine learning methods used to identify the imbalanced distribution dataset of positive and negative samples have low recognition accuracy. Therefore, in this paper, we propose a new hybrid model solution that uses feature construction, feature selection and imbalanced classes handling. A stacking model fusion algorithm composed of a two-layer stacking framework with several state-of-the-art machine learning classifiers is adopted. The results show that the risk user identification model based on mobile network communication behavior established by our stacking model fusion algorithm can accurately predict the category labels of telecom users and improve the risk of telecom users. The generalization performance of the identification is high, which provides a certain reference for the telecommunications industry to identify risk users based on mobile network communication behaviors

Verb Serialization in Kanakanavu

[[abstract]]Abstract: This paper aims to study the morphosyntax of verb sequences in Kanakanavu, a Formosan language spoken in Southern Taiwan. It shows that verbs sequences in Kanakanavu can be divided into SVCs (Serial Verb Constructions) and Non-SVCs due to the differences in their grammatical behaviors. Verb sequences formed by the category of motion, manner, resultative, instrumental, ability, frequency and directional verbs truly serialize, while those formed by the category of aspectual, purposive, stance/postural, control, implicative, deontic/epistemic, perception and factive verbs do not involve verb serialization. Both SVCs and Non-SVCs in Kanakanavu form a spectrum from ‘non-finite’to ‘finite’with respect to grammatical restrictedness on V2 complements. The research indicates that (i) the syntax of “finiteness”may vary from language to language; (ii) typology of serializability can be diverse, and verb serialization can be cognitively motivated; (iii) verb serialization in Kanakanavu behaves similarly to that in Kavalan, where SVCs display AF-only Restriction, but differently from Tsou, where SVCs are characterized by Focus Harmony Restriction.[[fileno]]204_JA07_2006_v2_p109[[department]]語言學研究