• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.478-487
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• 1996

A " plucking rolls device" was developed in this study to improve the quality of harvested tea leaves. In this report, the outline of the system and the results of performance experiments in our laboratory are discussed. Tow kinds of performance experiments were carried out. The first experiment checked harvesting accuracy by using a plucking unit that was developed for harvesting machine installation. The second experiment was a harvesting experiment which utilized a fron bar in order to prevent cutting of the tea buds which had been a problem in precious experiments . As a results of the first experiments , it was confirmed that selective harvesting obtained high quality tea leaves. but a cutting problem that, when the harvesting seed was faster than the working speed, which was non-selective harvesting , was also seen. In the second experiment, the cutting rate decreased to a maximum of 50% level, when tea buds most bent ahead by the front bar. The effect was seen that cutt ng problem was alleviated from this.

• Journal of applied mathematics & informatics
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• v.22 no.1_2
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• pp.387-401
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• 2006

This paper deals with the problem of a ratio-dependent prey- predator model with combined harvesting. The existence of steady states and their stability are studied using eigenvalue analysis. Boundedness of the exploited system is examined. We derive conditions for persistence and global stability of the system. The possibility of existence of bionomic equilibria has been considered. The problem of optimal harvest policy is then solved by using Pontryagin's maximal principle.

• Kyungpook Mathematical Journal
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• v.51 no.4
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• pp.353-364
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• 2011

Duality in the optimal harvesting for a nonlinear age-spatial structured population dynamic model is studied in the framework of optimal control problem. In this paper the duality theory that displays the conjugacy of the primal problem is established and an application is given. Duality theory plays an important role in both optimization theory and methodology and the results may be applied to a realistic biological system on the point of optimal harvesting.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.151-161
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• 2012

This paper considers a two-user Gaussian interference channel with energy harvesting transmitters. Different than conventional battery powered wireless nodes, energy harvesting transmitters have to adapt transmission to availability of energy at a particular instant. In this setting, the optimal power allocation problem to maximize the sum throughput with a given deadline is formulated. The convergence of the proposed iterative coordinate descent method for the problem is proved and the short-term throughput maximizing offline power allocation policy is found. Examples for interference regions with known sum capacities are given with directional water-filling interpretations. Next, stochastic data arrivals are addressed. Finally, online and/or distributed near-optimal policies are proposed. Performance of the proposed algorithms are demonstrated through simulations.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.140-150
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• 2012

In this paper, we investigate the optimal packet scheduling problem in a two-user multiple access communication system, where the transmitters are able to harvest energy from the nature. Under a deterministic system setting, we assume that the energy harvesting times and harvested energy amounts are known before the transmission starts. For the packet arrivals, we assume that packets have already arrived and are ready to be transmitted at the transmitter before the transmission starts. Our goal is to minimize the time by which all packets from both users are delivered to the destination through controlling the transmission powers and transmission rates of both users. We first develop a generalized iterative backward waterfilling algorithm to characterize the maximum departure region of the transmitters for any given deadline T. Then, based on the sequence of maximum departure regions at energy arrival instants, we decompose the transmission completion time minimization problem into convex optimization problems and solve the overall problem efficiently.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.504-521
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• 2016

Recently, energy harvesting technology has been integrated into wireless sensor networks to ameliorate the nodes' energy limitation problem. In theory, the wireless sensor node equipped with an energy harvesting module can work permanently until hardware failures happen. However, due to the change of power supply, the traditional hierarchical network routing protocol can not be effectively adopted in energy harvesting wireless sensor networks. In this paper, we improve the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol to make it suitable for the energy harvesting wireless sensor networks. Specifically, the cluster heads are selected according to the estimation of nodes' harvested energy and consumed energy. Preference is given to the nodes with high harvested energy while taking the energy consumption rate into account. The utilization of harvested energy is mathematically formulated as a max-min optimization problem which maximizes the minimum energy conservation of each node. We have proved that maximizing the minimum energy conservation is an NP-hard problem theoretically. Thus, a polynomial time algorithm has been proposed to derive the near-optimal performance. Extensive simulation results show that our proposed routing scheme outperforms previous works in terms of energy conservation and balanced distribution.

• Journal of Satellite, Information and Communications
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• v.11 no.2
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• pp.55-59
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• 2016

Conventional RF energy harvesting systems can harvest energy and decode information from same source as an Hybirid-AP (H-AP). However, harvesting efficiency is seriously dependent on distance between users and H-AP. Therefore, in this paper, we proposed a transmission model for RF harvesting consisting of information and power source separately called Decoupled RF Energy harvesting networks. Main purpose of this paper is to maximize energy efficiency under various constraints of transmit power from H-AP and power beacon (PB), minimum quality of service and quality of harvested power of each users. To measure proposed model's performance, we proposed optimal time scheduling algorithms for energy efficiency (EE) maximization using Lagrangian dual decomposition theory that locally maximizes the EE by obtaining suboptimal values of three arguments : transmit power of H-AP, transmit power of PB, frame splitting factor. Experiment results show that the proposed energy-efficient algorithms converge within a few iterations with its optimality and greatly improve the EE compared to that of baseline schemes.

• Smart Media Journal
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• v.8 no.2
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• pp.21-28
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• 2019

Recent research on energy harvesting wireless sensor networks focuses on the development of techniques to solve the limited energy resource problem and to extend the whole network life efficiently. Energy harvesting technology can increase the lifetime of a network, but data transmission becomes unavailable when it harvests energy from radio frequency, resulting longer network delay with respect to the increased time in energy harvesting. Therefore, building energy harvesting wireless sensor network should consider the possible network delay as well as the network lifetime problem. In this paper, we propose a new MAC protocol that minimizes end-to-end network delay by adjusting the data transmission time for a packet based on estimating the energy for data transmission along with the amount of traffic flowing into the network and harvested energy. For this goal, it engineers an energy management mechanism that adjusts the sleep time of the network by measuring energy harvesting time. In addition, with simulation results it shows that the proposed MAC protocol improves the performance in terms of energy consumption and end-to-end delay, compared to the existing MAC protocols.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1184-1191
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• 2009

Energy harvesting from environment can make the energy constrained systems such as sensor networks to sustain their lifetimes. However, environmental energy is highly variable with time, location, and other factors. Unlike the existing solutions, we solved this problem by allowing the sensor nodes with mobilizer to move in search of energy and recharge from remote energy station. In this paper we present and analyze a new harvesting aware framework for mobile sensor networks with remote energy station. The framework consists of energy model, motion control system and data transfer protocol. Among them, the objective of our data transfer protocol is to route a data packet geographically towards the target region and at the same time balance the residual energy and the link connectivity on nodes with energy harvesting. Our results along with simulation can be used for further studies and provide certain guideline for realistic development of such systems.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.141-145
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• 2017

Spectrum sensing is a critical functionality of Cognitive Radio(CR) systems and the CR systems can be applied to RF energy harvesting systems to improve an energy harvesting rate. There are number of spectrum sensing techniques. One of techniques is energy detection. Energy detection is the simplest detection method and is the most commonly used. But, energy detection has a hidden terminal problem in real wireless communication, because of secondary user (SU) can be affected by frequency fading and shadowing. Cooperative spectrum sensing can solve this problem using spatial diversity of SUs. But it has a problem of increasing data by processing multiple secondary. So, we propose the system model using adaptive spectrum sensing algorithm and system model is simulated. This algorithm chooses sensing method between single energy sensing and cooperative energy according to the received signal's Signal to Noise Ratio (SNR) from Primary User (PU). The simulation result shows that adaptive spectrum sensing has an efficiency and improvement in CR systems.