• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5654-5668
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• 2018

Driven by security and real-time demands of Internet of Things (IoT), the timing of fog computing and edge computing have gradually come into place. Gateways bear more nearby computing, storage, analysis and as an intelligent broker of the whole computing lifecycle in between local devices and the remote cloud. In fog computing, the edge broker requires X-aware capabilities that combines software programmability, stream processing, hardware optimization and various connectivity to deal with such as security, data abstraction, network latency, service classification and workload allocation strategy. The prosperous of Field Programmable Gate Array (FPGA) pushes the possibility of gateway capabilities further landed. In this paper, we propose a software-defined gateway (SDG) scheme for fog computing paradigm termed as Fog Computing Zero-Knowledge Gateway that strengthens data protection and resilience merits designed for industrial internet of things or highly privacy concerned hybrid cloud scenarios. It is a proxy for fog nodes and able to integrate with existing commodity gateways. The contribution is that it converts Privacy-Enhancing Technologies rules into provable statements without knowing original sensitive data and guarantees privacy rules applied to the sensitive data before being propagated while preventing potential leakage threats. Some logical functions can be offloaded to any programmable micro-controller embedded to achieve higher computing efficiency.

• Architectural research
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• v.22 no.4
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• pp.155-162
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• 2020

Numerous scholars have explored the modeling, control, and optimization of energy systems in buildings, offering new insights about technology and environments that can advance industry innovation. Eye trackers deliver objective eye-gaze data about visual and attentional processes. Due to its flexibility, accuracy, and efficiency in research, eye tracking has a control scheme that makes measuring rapid eye movement in three-dimensional space possible (e.g., virtual reality, augmented reality). Because eye movement is an effective modality for digital interaction with a virtual environment, tracking how users scan a visual field and fix on various digital objects can help designers optimize building environments and materials. Although several scholars have conducted Virtual Reality studies in three-dimensional space, scholars have not agreed on a consistent way to analyze eye tracking data. We conducted eye tracking experiments using objects in three-dimensional space to find an objective way to process quantitative visual data. By applying a 12 × 12 grid framework for eye tracking analysis, we investigated how people gazed at objects in a virtual space wearing a headmounted display. The findings provide an empirical base for a standardized protocol for analyzing eye tracking data in the context of virtual environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2225-2239
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• 2021

To assist in data collection, the use of a mobile sink has been widely suggested in the literature. Due to the limited sensor node's storage capacity, this manner to collect data induces huge latencies and drop packets. Their buffers will be overloaded and lead to network congestion. Recently, a new bio-inspired optimization algorithm appeared. Researchers were inspired by the swarming mechanism of salps and thus creating what is called the Salp Swarm Algorithm (SSA). This paper improves the sink mobility to enhance energy dissipation, throughput, and convergence speed by imitating the salp's movement. The new approach, named the Mobile Sink based on Modified Salp Swarm Algorithm (MSSA), is approved in a heterogeneous Wireless Sensor Network (WSN) data collection. The performance of the MSSA protocol is assessed using several iterations. Results demonstrate that our proposal surpass other literature algorithms in terms of lifespan and throughput.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.17-26
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• 2022

Sensor Nodes play a major role to monitor and sense the variations in physical space in various real-time application scenarios. These nodes are powered by limited battery resources and replacing those resource is highly tedious task along with this it increases implementation cost. Thus, maintaining a good network lifespan is amongst the utmost important challenge in this field of WSN. Currently, energy efficient routing techniques are considered as promising solution to prolong the network lifespan where multi-hop communications are performed by identifying the most energy efficient path. However, the existing scheme suffer from performance related issues. To solve the issues of existing techniques, a novel hybrid technique by merging particle swarm optimization and game theory model is presented. The PSO helps to obtain the efficient number of cluster and Cluster Head selection whereas game theory aids in finding the best optimized path from source to destination by utilizing a path selection probability approach. This probability is obtained by using conditional probability to compute payoff for agents. When compared to current strategies, the experimental study demonstrates that the proposed GTPSO strategy outperforms them.

• Smart Structures and Systems
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• v.30 no.6
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• pp.571-582
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• 2022

Optimal life-cycle management is a challenging issue for deteriorating regional bridges. Due to the complexity of regional bridge structural conditions and a large number of inspection and maintenance actions, decision-makers generally choose traditional passive management strategies. They are less efficiency and cost-effectiveness. This paper suggests a deep reinforcement learning framework employing double-deep Q-networks (DDQNs) to improve the life-cycle management of deteriorating regional bridges to tackle these problems. It could produce optimal maintenance plans considering restrictions to maximize maintenance cost-effectiveness to the greatest extent possible. DDQNs method could handle the problem of the overestimation of Q-values in the Nature DQNs. This study also identifies regional bridge deterioration characteristics and the consequence of scheduled maintenance from years of inspection data. To validate the proposed method, a case study containing hundreds of bridges is used to develop optimal life-cycle management strategies. The optimization solutions recommend fewer replacement actions and prefer preventative repair actions when bridges are damaged or are expected to be damaged. By employing the optimal life-cycle regional maintenance strategies, the conditions of bridges can be controlled to a good level. Compared to the nature DQNs, DDQNs offer an optimized scheme containing fewer low-condition bridges and a more costeffective life-cycle management plan.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4385-4399
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• 2021

The Internet of Things (IoT) eHealth systems composed by Wireless Body Area Network (WBAN) has emerged recently. Sensor nodes are placed around or in the human body to collect physiological data. WBAN has many different applications, for instance health monitoring. Since the limitation of the size of the battery, besides speed, reliability, and accuracy; design of WBAN protocols should consider the energy efficiency and time delay. To solve these problems, this paper adopt the end-edge-cloud orchestrated network architecture and propose a transmission based on reinforcement algorithm. The priority of sensing data is classified according to certain application. System utility function is modeled according to the channel factors, the energy utility, and successful transmission conditions. The optimization problem is mapped to Q-learning model. Following this online power control protocol, the energy level of both the senor to coordinator, and coordinator to edge server can be modified according to the current channel condition. The network performance is evaluated by simulation. The results show that the proposed power control protocol has higher system energy efficiency, delivery ratio, and throughput.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.35-40
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• 1995

Considering the higher discharge burnup, lower channel refuelling rate, lower linear element rating(LER), lower coolant void reactivity and axial power shape, CANFLEX-RU fuel bundle is optimized for CANDU-6 by grading the fissile composition in the ring-wise of the bundle and by applying fuel management scheme appropriately. The fissile composition of the fuel bundle is graded as the recovered uranium (0.9 w/o U-235) in the outer and intermediate elements, depleted Uranium (0.2 w/o U-235) in the center element, natural uranium (0.71 w/o U-235) in the inner elements. Enrichment is not required for these fuel. The fissile composition is optimized by lattice calculation and by time-averaged reactor simulation. CANFLEX-RU optimized for CANDU-6 resulted to be the 15% lower channel refuelling rate, acceptable axial power profile and power envelope, 70% higher discharge burnup, 15% lower LER and not increase coolant void reactivity compared with the 37-element natural uranium bundle for CANDU-6.

• Nonlinear Functional Analysis and Applications
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• v.28 no.2
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• pp.497-520
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• 2023

Numerous problems in science and engineering defined by nonlinear functional equations can be solved by reducing them to an equivalent fixed point problem. Fixed point theory provides essential tools for solving problems arising in various branches of mathematical analysis, such as split feasibility problems, variational inequality problems, nonlinear optimization problems, equilibrium problems, complementarity problems, selection and matching problems, and problems of proving the existence of solution of integral and differential equations.The theory of fixed is known to find its applications in many fields of science and technology. For instance, the whole world has been profoundly impacted by the novel Coronavirus since 2019 and it is imperative to depict the spread of the coronavirus. Panda et al. [24] applied fractional derivatives to improve the 2019-nCoV/SARS-CoV-2 models, and by means of fixed point theory, existence and uniqueness of solutions of the models were proved. For more information on applications of fixed point theory to real life problems, authors should (see [6, 13, 24] and the references contained in).

• Advances in Computational Design
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• v.7 no.4
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• pp.281-295
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• 2022

Tensile property is one of the excellent properties of ultra-high performance concrete (UHPC), and uniaxial tensile test is an important and challenging mechanical performance test of UHPC. Traditional uniaxial tensile tests of concrete materials have inherent defects such as initial eccentricity, which often lead to cracks and failure in non-test zone, and affect the testing accuracy of tensile properties of materials. In this paper, an original integrated design scheme of mould and end fixture is proposed, which achieves seamless matching between the tension end of specimen and the test fixture, and minimizes the cumulative eccentricity caused by the difference in the matching between the tension end of specimen and the local stress concentration at the end. The stress analysis and optimization design are carried out by finite element method. The curve transition in the end of specimen is preferred compared to straight line transition. The rationality of the new integrated design is verified by uniaxial tensile test of strain hardening UHPC, in which the whole stress-strain curve was measured, including the elastic behavior before cracking,strain hardening behavior after cracking and strain softening behavior.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.192-200
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• 2017

With the acceleration of construction industrialization, the buildings that China has adopted the construction of industrialization technology are increasing day by day, and Precast Concrete (PC) Structure technology is one of the main technologies of construction industrialization. Compared with the traditional cast-in-place concrete structure, PC structure is more conducive to shorten the construction period, reduce the number of construction workers and the site construction waste. Nevertheless, PC structure improves the requirements of hoisting machinery in the construction site, and the lay-out and selection of hoisting machinery become an important factor influencing the construction cost. The paper regards the typical tower crane in China as the research object, and establishes the time optimization model for the lifting scheme. The influence of the different precast rate on the selection of the tower crane is analyzed. This paper obtains the time variation of the tower crane under different precast rate, provides a theoretical basis for the design of precast concrete structures under the influence of assembly construction, and lays the foundation for the selection of tower crane under the precast rate.