Water quantity and quality monitoring at Taipei Watershed Management Bureau (WRATB) is not only a daily business but also a long term job. WRATB is responsible for providing high quality drinking water to about four millions population in Taipei. The quality of drinking water provided by WRATB is among one of the best in Taiwan. The total area is 717 square kilometers. The water resource pollution is usually divided into two categories, point source pollution and nonpoint source pollution. Garbage disposal is the most important component of the point source pollution, especially those by tourist during holidays and weekends. Pesticide pollution, fertilizer pollution, and natural pollution are the major contributions for nonpoint source pollution. The objective of this paper is to implement remote sensing, geographic information systems, and global positioning systems to monitor water quantity and water quality at WRATB. There are 12 water quality monitoring stations and four water gauge stations at WRATB. The coordinates of the 16 stations were determined by GPS devices and created into the base maps. MapObjects and visual BASIC were implemented to create application modules for water quality and quantity monitoring. Water quality of the two major watersheds at WRATB was put on Internet for public review monthly. The GIS software, ArcIMS, can put location maps and attributes of all 16 stations on Internet for general public review and technical implementations at WRATB. Inquiry and statistic charts automatic manipulations for the past 18 years are also available. Garbage disposal by community and tourist were also managed by GIS and GPS. The storage, collection, and transportation of garbage were reviewed by ArcMap file format. All garbage cart and garbage can at WRATB can be displayed on the base maps. Garbage disposal by tourist during holidays and weekends can be managed by a PDA with a GPS device and a digital camera. Man power allocation for tourist garbage disposal management can be done in an integration of GIS and GPS. Monitoring of water quality and quantity at WRATB can be done on Internet and by a PDA.
Methanol fuel cells having advantages of relatively favorable reaction kinetics and higher energy density have attracted increasing interests as best alternative to hydrogen fuel cell because of H2 production, storage and distribution issues. While there have been extensive research works on developing key components such as electrocatalysts as well as their physicochemical properties in practical formic acid fuel cells, there have also been urgent requests for investigating which fuel sources will be more suitable for direct liquid fuel cells in future. In this mini-review, we highlight the overall interest and outlook of formic acid fuel cells in terms of electrocatalysts, fuel supply and crossover, water management, fuel cell efficiency and system integration in comparison with methanol fuel cells.
The Terra-Scope system is an affordable 4-D down-hole seismic monitoring system based on independent, microprocessor-controlled sensor Pods. The Pods are nominally 50 mm in diameter, and about 120 mm long. They are expected to cost approximately $6000 each. An internal 16-bit, extremely low power MCU controls all aspects of instrumentation, eight programmable gain amplifiers, and local signal storage. Each Pod measures 3-D acceleration, tilt, azimuth, temperature, and other parametric variables such as pore water pressure and pH. Each Pod communicates over a standard digital bus (RS-485) through a completely web-based GUI interface, and has a power consumption of less than 400 mW. Three-dimensional acceleration is measured by pure digital force-balance MEMS-based accelerometers. These accelerometers have a dynamic range of more than 115 dB and a frequency response from DC to 1000 Hz with a noise floor of less than $30ng_{rms}/{\surd}Hz$. Accelerations above 0.2 g are measured by a second set of MEMS-based accelerometers, giving a full 160 dB dynamic range. This paper describes the system design and the cooperative shared-time scheduler implemented for this project. Restraints accounted for include multiple data streams, integration of multiple free agents, interaction with the asynchronous world, and hardened time stamping of accelerometer data. The prototype of the device is currently undergoing evaluation. The first array will be installed in the spring of 2006.
Kim, H.J.;Jin, H.B.;Youm, W.S.;Kim, Y.G.;Park, K.H.
Electronics and Telecommunications Trends
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v.34
no.5
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pp.14-25
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2019
As the Internet of Things, artificial intelligence and big data have received a lot of attention as key growth engines in the era of the fourth industrial revolution, data acquisition and utilization in mobile, automotive, robotics, manufacturing, agriculture, health care and national defense are becoming more important. Due to numerous data-based industrial changes, demand for sensor technologies is exploding, especially for intelligent sensor technologies that combine control, judgement, storage and communication functions with the sensors's own functions. Intelligent sensor technology can be defined as a convergence component technology that combines intelligent sensor units, intelligent algorithms, modules with signal processing circuits, and integrated plaform technologies. Intelligent sensor technology, which can be applied to variety of smart IT convergence services such as smart devices, smart homes, smart cars, smart factory, smart cities, and others, is evolving towards intelligent and convergence technologies that produce new high-value information through recognition, reasoning, and judgement based on artificial intelligence. As a result, development of intelligent sensor units is accelerating with strategies for miniaturization, low-power consumption and convergence, new form factor such as flexible and stretchable form, and integration of high-resolution sensor arrays. In the future, these intelligent sensor technologies will lead explosive sensor industries in the era of data-based artificial intelligence and will greatly contribute to enhancing nation's competitiveness in the global sensor market. In this report, we analyze and summarize the recent trends in intelligent sensor technologies, especially those for four core technologies.
Journal of the Architectural Institute of Korea Planning & Design
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v.34
no.12
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pp.13-20
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2018
This research is to analyze the public cases of information facilities in terms of central circulations in multi level volumes such as atrium or court which provide visual intervention between different spaces and physical connections such as bridges. Hunt Library design balances the understood pre-existing needs with the University's emerging needs to create a forward-thinking learning environment. While clearly a contemporary structure within a traditional context of the NCSU campus, the Hunt Library provides a positive platform for influencing its surroundings. Both technical and programmatic innovations are celebrated as part of the learning experience and provide a versatile and stimulating environment for students. Public library as open spaces connecting to an interactive social domain over communities can provide variety of learning environments, or technology based labs. There are many cases of the public information spaces with dynamic networks where participants can play their roles in physical space as well as in the intellectual stimulation. In the research, new public projects provide typologies of information spaces with user oriented media. The research is to address a creative transition between the reading space and the experimental links of the integration of state-of-the-art technology is highly visible in the building's design. The user-friendly browsing system that replaces the traditional browsing with the virtual shelves classified and archived by their form, is to reduce the storage space of the public library and it is to allow more space for collaborative learning. In addition to the intelligent robot of information storages, innovative features is the large-scale visualization space that supports team experiments to carry out collaborative online works and therefore the public library's various programs is to provide visitors with more efficient participatory environment.
International Journal of Computer Science & Network Security
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v.22
no.2
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pp.107-114
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2022
The main purpose of this study is to substantiate the theoretical and methodological foundations of the organizational and economic mechanism of development of the agro-industrial complex in modern conditions. Organizational and economic mechanism is presented as a complex organizational structure of the system type, which is aimed at performing specific functions, the characteristic feature of which is the constant support of process changes without which the organizational and economic mechanism can not exist. There are four components of the agro-industrial complex, represented by agriculture and the national economy, which ensure its operation, including industry, processing of agricultural products, its storage and transportation, sale and repair and maintenance of agricultural machinery and more. It is proved that the organizational and economic mechanism of development of agro-industrial complex in modern conditions it is expedient to consider: from the point of view of system and process approaches; as a set of economic levers and organizational measures to influence the agro-industrial complex; constituent components of organizational influence on the development of the complex; a set of components, elements that are integrated into the system of economic relations of the subjects of the agro-industrial complex; a set of purposeful stimulators of agro-industrial complex development. The functions of the organizational component of the mechanism of agro-industrial complex include: redistributive, planning, interaction, control, integration and regulatory functions, the functions of the economic component include consumer, investment and innovation, social, incentive, monitoring functions of the mechanism. The symbiosis of the functions of organizational and economic components ensure the effectiveness of the organizational and economic mechanism of the organizational and economic mechanism through its functionalities as a whole.
Recently, interest in smart factories is increasing. Investments to improve intelligence/automation are also being made continuously in manufacturing plants. Facility automation based on sensor data collection is now essential. In addition, we are operating our factories based on data generated in all areas of production, including production management, facility operation, and quality management, and an integrated standard information system. When producing LCD polarizer products, it is most important to link trace information between data generated by individual production processes. All systems involved in production must ensure that there is no data loss and data integrity is ensured. The large-capacity data collected from individual systems is composed of key values linked to each other. A real-time quality analysis processing system based on connected integrated system data is required. In this study, large-capacity data collection, storage, integration and loss prevention methods were presented for optimization of LCD polarizer production. The identification Risk model of inspection products can be added, and the applicable product model is designed to be continuously expanded. A quality inspection and analysis system that maximizes the yield rate was designed by using the final inspection image of the product using big data technology. In the case of products that are predefined as analysable products, it is designed to be verified with the big data knn analysis model, and individual analysis results are continuously applied to the actual production site to operate in a virtuous cycle structure. Production Optimization was performed by applying it to the currently produced LCD polarizer production line.
International Journal of Computer Science & Network Security
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v.22
no.12
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pp.37-50
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2022
Modern supply chains include multiple activities from collecting raw materials to transferring final products. These activities involve many parties who share a huge amount of valuable data, which makes managing supply chain systems a challenging task. Current supply chain management (SCM) systems adopt digital technologies such as the Internet of Things (IoT) and blockchain for optimization purposes. Although these technologies can significantly enhance SCM systems, they have their own limitations that directly affect SCM systems. Security, performance, and scalability are essential components of SCM systems. Yet, confidentiality and scalability are one of blockchain's main limitations. Moreover, IoT devices are lightweight and have limited power and storage. These limitations should be considered when developing blockchain-based IoT-SCM systems. In this paper, the requirements of efficient supply chain systems are analyzed and the role of both IoT and blockchain technologies in providing each requirement are discussed. The limitations of blockchain and the challenges of IoT integration are investigated. The limitations of current literature in the same field are identified, and a secure and scalable blockchain-based IoT-SCM system is proposed. The proposed solution employs a Hyperledger fabric blockchain platform and tackles confidentiality by implementing private data collection to achieve confidentiality without decreasing performance. Moreover, the proposed framework integrates IoT data to stream live data without consuming its limited resources and implements a dualstorge model to support supply chain scalability. The proposed framework is evaluated in terms of security, throughput, and latency. The results demonstrate that the proposed framework maintains confidentiality, integrity, and availability of on-chain and off-chain supply chain data. It achieved better performance through 31.2% and 18% increases in read operation throughput and write operation throughput, respectively. Furthermore, it decreased the write operation latency by 83.3%.
Asma Albassam;Fatima Almutairi;Nouf Majoun;Reem Althukair;Zahra Alturaiki;Atta Rahman;Dania AlKhulaifi;Maqsood Mahmud
International Journal of Computer Science & Network Security
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v.23
no.6
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pp.17-26
/
2023
Blockchain technology has emerged as one of the most crucial solutions in numerous industries, including healthcare. The combination of blockchain technology and cloud computing results in improving access to high-quality telemedicine and healthcare services. In addition to developments in healthcare, the operational strategy outlined in Vision 2030 is extremely essential to the improvement of the standard of healthcare in Saudi Arabia. The purpose of this survey is to give a thorough analysis of the current state of healthcare technologies that are based on blockchain and cloud computing. We highlight some of the unanswered research questions in this rapidly expanding area and provide some context for them. Furthermore, we demonstrate how blockchain technology can completely alter the medical field and keep health records private; how medical jobs can detect the most critical, dangerous errors with blockchain industries. As it contributes to develop concerns about data manipulation and allows for a new kind of secure data storage pattern to be implemented in healthcare especially in telemedicine fields is discussed diagrammatically.
The classical multiscale finite element (FE2 ) method involves iterative calculations of micro-boundary value problems for representative volume elements at every integration point in macro scale, making it a computationally time and data storage space. To overcome this, we developed the data-driven multiscale analysis method based on the mean-field homogenization (MFH). Data-driven computational mechanics (DDCM) analysis is a model-free approach that directly utilizes strain-stress datasets. For performing multiscale analysis, we efficiently construct a strain-stress database for the microstructure of composite materials using mean-field homogenization and conduct data-driven computational mechanics simulations based on this database. In this paper, we apply the developed multiscale analysis framework to an example, confirming the results of data-driven computational mechanics simulations considering the microstructure of a hyperelastic composite material. Therefore, the application of data-driven computational mechanics approach in multiscale analysis can be applied to various materials and structures, opening up new possibilities for multiscale analysis research and applications.
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