• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.480-497
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• 2012

As a new business concept, machine-to-machine (M2M) communications are born from original telemetry technology with the intrinsic features of automatic data transmissions and measurement from remote sources typically by cable or radio. M2M includes a number of technologies that need to be combined in a compatible manner to enable its deployment over a broad market of consumer electronics. In order to provide better understanding for this emerging concept, the correlations among M2M, wireless sensor networks, cyber-physical systems (CPS), and internet of things are first analyzed in this paper. Then, the basic M2M architecture is introduced and the key elements of the architecture are presented. Furthermore, the progress of global M2M standardization is reviewed, and some representative applications (i.e., smart home, smart grid and health care) are given to show that the M2M technologies are gradually utilized to benefit people's life. Finally, a novel M2M system integrating intelligent road with unmanned vehicle is proposed in the form of CPS, and an example of cyber-transportation systems for improving road safety and efficiency are introduced.

• Acta Via Serica
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• v.7 no.2
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• pp.133-152
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• 2022

Both in popular perception and specialized literature, the Achaemenid Empire, for over two centuries the most important player from the Aegean to the Indus, is rarely evoked in correlation with the complex of socio-cultural dynamics which shaped the spaces of what has become known as the Silk Road(s). Building on the case study of the Pazyryk carpet on the one hand (King 2021, 353-361, Linduff and Rubinson 2021, 88-97), and of the spread of an artistic motive such as the quatrefoil on the other (Kim 2021), this paper explores the rich and complex nature of the commercial networks that flourished across Central Asia under the aegis of Achaemenid Great Kings. Both archaeological and literary evidence shall be discussed (especially the Aramaic Documents from Ancient Bactria: Naveh and Shaked 2012, and now King 2021, 315-320). If taken together and read against the grain, such material is significant for the following reasons. First, it suggests the existence - and the scale - of commercial activities directly fostered or indirectly promoted by the imperial administration in Central Asia, an area of crucial importance within the Achaemenid domains, but for which our evidence is rather scanty and difficult to assess. Second, it shows how the Achaemenid "Imperial Paradigm" (Henkelman 2017) affected the social and economic landscape of Central Asia even after the demise of the Empire itself, thus considerably shaping the world of the Silk Road(s) a century before the Ancient Sogdian Letters (de la Vaissière 2005, 43-70) or Zhāng Quiān's famous report.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.437-438
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• 2023

This paper takes the Pingjiang historical and cultural district of Suzhou city as an example, collects 1439 visitor review data from Ctrip.com with the help of Python technology, and uses web text analysis to conduct research on high-frequency words, semantic networks and emotional tendencies to comprehensively assess the tourist perception of the Grand Canal heritage. The study found that: natural and humanistic landscape, historical and cultural accumulation, and the style of Jiangnan Canal are fully reflected in the tourists' perception of Pingjiang historical and cultural district; tourists hold strong positive emotion towards Pingjiang Road, however, there is still more room for renovation and improvement of the historical and cultural district. Finally, countermeasure suggestions for improving the tourist perception of the Grand Canal heritage are given in terms of protection first, cultural integration and innovative utilization.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.944-953
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• 2020

Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.

• The Journal of the Korea Contents Association
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• v.12 no.9
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• pp.489-499
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• 2012

Most roads in Korea are constructed through a riverside or among the mountains due to geographical characteristics, and composed of various connection roads and complex networks, which makes it susceptible to a fog, rainfall and snowfall and causes serious negligent accidents due to misperception of network while driving. This study amis at securing original technology to provide traffic information, utilizing the road surface by grafting LED and optical technology highly recognized in terms of energy efficiency recently onto ITS, thereby developing next-generation ITS service. To support the research development, H/W was developed and field test was conducted. In addition, the customer satisfaction survey towards equipment, an end product of this research development was also carried out to find out what it means to customers potentially.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.103-118
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• 2014

Over the last couple of years, traditional VANET (Vehicular Ad Hoc NETwork) evolved into VANET-based clouds. From the VANET standpoint, applications became richer by virtue of the boom in automotive telematics and infotainment technologies. Nevertheless, the research community and industries are concerned about the under-utilization of rich computation, communication, and storage resources in middle and high-end vehicles. This phenomenon became the driving force for the birth of VANET-based clouds. In this paper, we envision a novel application layer of VANET-based clouds based on the cooperation of the moving cars on the road, called CaaS (Cooperation as a Service). CaaS is divided into TIaaS (Traffic Information as a Service), WaaS (Warning as a Service), and IfaaS (Infotainment as a Service). Note, however, that this work focuses only on TIaaS and WaaS. TIaaS provides vehicular nodes, more precisely subscribers, with the fine-grained traffic information constructed by CDM (Cloud Decision Module) as a result of the cooperation of the vehicles on the roads in the form of mobility vectors. On the other hand, WaaS provides subscribers with potential warning messages in case of hazard situations on the road. Communication between the cloud infrastructure and the vehicles is done through GTs (Gateway Terminals), whereas GTs are physically realized through RSUs (Road-Side Units) and vehicles with 4G Internet access. These GTs forward the coarse-grained cooperation from vehicles to cloud and fine-grained traffic information and warnings from cloud to vehicles (subscribers) in a secure, privacy-aware fashion. In our proposed scheme, privacy is conditionally preserved wherein the location and the identity of the cooperators are preserved by leveraging the modified location-based encryption and, in case of any dispute, the node is subject to revocation. To the best of our knowledge, our proposed scheme is the first effort to offshore the extended traffic view construction function and warning messages dissemination function to the cloud.

• The Southeast Asian review
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• v.24 no.1
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• pp.191-221
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• 2014

South Sumatra's capital, Palembang, has long maintained a river-oriented transportation system. With road transportation's increased importance for exploiting natural resources, however, hundreds of roads have been constructed since the Dutch colonial period. This article examines how the construction of roads and bridges affected people's lives and social networks in Palembang, and what social and political significance it has in the context of a region in the postcolonial Indonesia, with a focus on the huge river called the Musi River, which horizontally crosses the city. After independence, there has been strong aspiration to link these two parts by road, and in 1965 the Musi Bridge (then the Sukarno Bridge) over the river was eventually opened. The construction of the bridge apparently initiated socioeconomic transformations and development in the region, including Ulu (the southern river bank)'s rapid urbanization. However, the features of regional development actually were prerequisites for "national" development. The regional development was impossible without financial support from the central government, and the local or regional aspiration for development was often supported only when it fitted with national envision. The Musi Bridge was a model case that fitted with such national envision. While it was the symbol of regional development, it was also celebrated as an exemplary sign of "national" development, by both Sukarno's government and Suharto's New Order regime. By analyzing the discussions and discourses regarding the Musi project since early 1950s, in addition to its social and economic impact after the construction, this article explores the continuities and changes in the roles and significance of the (construction of the) Musi Bridge with the changing political backstops in both regimes. Together with it, this article also aims to reexamine the interplay between "the national" and "the regional" in the prevalent aspiration for the national and regional "development" throughout the 1950s and 1960s.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.198-205
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• 2021

For twenty years, in the EU there has been a trend of a lack of maritime infrastructure and a redundance of the road one, which has a negative impact on the economy. The intermodal transport market structure in the EU has not changed over the past ten years. The stability of transport systems due to the lack of changes in the transport market remains under threat, affecting supply chains and networks through the optimization of warehousing and transportation costs. The research methodology is based on a quantitative assessment of cause-and-effect relations between economic growth and transport and logistics in the EU. A statistical analysis of security indicators, intermodal and modal transport, international trade in goods within the EU and in the world trade in goods, the dynamics of GDP of the EU countries, the level of openness of the EU economy, investment and maintenance costs of different modes of transport and infrastructure has been carried out. The results show that in 2000- 2010 there were positive changes in the transport and logistics infrastructure of the EU, which had a positive effect on trade, openness of the economy of the EU, GDP growth. However, at that time, negative effects of environmental impact and the load on road and rail transport were accumulating. Investment in different modes of transport is limited, and technical maintenance and infrastructure maintenance costs form a significant part of GDP of the EU. A slowdown in economic growth leads to budget constraints and infrastructure financing gap. As a result, the freight and passenger intermodal and modal transport market structure remains virtually unchanged. The load on rail and road transport remains stable, despite the reduced level of transport hazards. Transport productivity has declined over the past ten years. Herewith, the intensification of trade and the openness of the EU economies require constant modernization and innovative renewal. The EU policy in this direction remains normative, uncontrolled, which is reflected in investment differences within the EU and maintenance costs.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.527-532
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• 2014

Recently, due to the proliferation of mobile smart devices, the inovation of bigdata, which analyzes and processes massive data collected from various sensors implaned in smart devices, expands to LBSs. Many location prediction techniques for moving objects have been studied in literature. However, as the majority of studies perform location prediction which depends on specific applications, they hardly reflect the technical requirements of next-generation spatio-temporal information services. Therefore, this paper proposes the design of general-purpose distributed moving object prediction query processing framework that is capable of performing primitive and various types of queries effectively based on massive spatio-temporal data of moving objects in real-world space networks.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.73-82
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• 2021

Rural roads are the significant infrastructure for developing and managing the rural areas, hence the utilization of the remote sensing datasets for managing the rural roads is necessary for expanding the rural transportation infrastructure and improving the life quality of the rural residents. In this research, the two different methods such as image classification and image segmentation were compared for mapping the rural road based on the given high-resolution satellite image acquired in the rural areas. In the image classification method, the deep learning with the multiple neural networks was employed to the given high-resolution satellite image for generating the object classification map, then the rural roads were mapped by extracting the road objects from the generated object classification map. In the image segmentation method, the multiresolution segmentation was employed to the same satellite image for generating the segment image, then the rural roads were mapped by merging the road objects located on the rural roads on the satellite image. We used the 100 checkpoints for assessing the accuracy of the two rural roads mapped by the different methods and drew the following conclusions. The image segmentation method had the better performance than the image classification method for mapping the rural roads using the give satellite image, because some of the rural roads mapped by the image classification method were not identified due to the miclassification errors occurred in the object classification map, while all of the rural roads mapped by the image segmentation method were identified. However some of the rural roads mapped by the image segmentation method also had the miclassfication errors due to some rural road segments including the non-rural road objects. In future research the object-oriented classification or the convolutional neural networks widely used for detecting the precise objects from the image sources would be used for improving the accuracy of the rural roads using the high-resolution satellite image.