• Journal of Radiation Protection and Research
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• v.48 no.4
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• pp.167-174
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• 2023

Background: A nondestructive test is commonly used to inspect the surface defects and internal structure of an object without any physical damage. X-rays generated from an electron accelerator or a tube are one of the methods used for nondestructive testing. The high penetration of X-rays through materials with low atomic numbers makes it difficult to discriminate between these materials using X-ray imaging. The interaction characteristics of neutrons with materials can supplement the limitations of X-ray imaging in material discrimination. Materials and Methods: The radiation image acquisition process for air-cargo security inspection equipment using X-rays and neutrons was simulated using a GEometry ANd Tracking (Geant4) simulation toolkit. Radiation images of phantoms composed of 13 materials were obtained, and the R-value, representing the attenuation ratio of neutrons and gamma rays in a material, was calculated from these images. Results and Discussion: The R-values were calculated from the simulated X-ray and neutron images for each phantom and compared with those obtained in the experiments. The R-values obtained from the experiments were higher than those obtained from the simulations. The difference can be due to the following two causes. The first reason is that there are various facilities or equipment in the experimental environment that scatter neutrons, unlike the simulation. The other is the difference in the neutron signal processing. In the simulation, the neutron signal is the sum of the number of neutrons entering the detector. However, in the experiment, the neutron signal was obtained by superimposing the intensities of the neutron signals. Neutron detectors also detect gamma rays, and the neutron signal cannot be clearly distinguished in the process of separating the two types of radiation. Despite these differences, the two results showed similar trends and the viability of using simulation-based radiation images, particularly in the field of security screening. With further research, the simulation-based radiation images can replace ones from experiments and be used in the related fields. Conclusion: The Korea Atomic Energy Research Institute has developed air-cargo security inspection equipment using neutrons and X-rays. Using this equipment, radiation images and R-values for various materials were obtained. The equipment was reconstructed, and the R-values were obtained for 13 materials using the Geant4 simulation toolkit. The R-values calculated by experiment and simulation show similar trends. Therefore, we confirmed the feasibility of using the simulation-based radiation image.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.423-429
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• 2007

Since the wireless smart card has played a main role in the identification security application for the building access; this research has its purpose to improve the performance of the smart card system and aims to offer more convenient to user. The contactless cards do not require insertion into a card reader and can work up to centimeters away from the reading device. To be able to cope with this performance the controlling of power consumption through the adaptive modulation and error control is needed. This paper addresses a forward error control (FEC) scheme with the adaptive Reed-Solomon code rate and an M-ary frequency shift keying (M-FSK) modulation scheme with the varying symbol size M over the link. The result of comparing energy efficiencies of adaptive error correction and adaptive modulation to other various static schemes shows to save over 50% of the energy consumption.

• Journal of Forest and Environmental Science
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• v.25 no.2
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• pp.131-138
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• 2009

Recently, various efforts for the extended utilization of woody biomass has been attempted due to the fact that global warming, energy and environmental problems are urgent ones to be solved. Development of new energy sources at our national security level is desperately needed as we depend on almost all of energies supplied from other countries, let alone the economic crisis caused by oil price hike. Woody biomass can be converted to energy by means of thermochemical, biological, or direct combustion processes. Many processes are available for producing bioenergy, such as bioethanol, wood pellet, wood chip, combined heat, and power system. Political support and R&D investment should be provided that can boost the utilization of the wood biomass, the eco-environment, and recyclable and alternative energy resources for national power security. In addition, a long-term strategy that can utilize unused and low efficient woody biomass resources, and systematically collect and manage them in a national level should be set up. Even though the possibility in total exchange of fossil oil with woody biomass is quite low, technology developments of woody biomass for the solution to global warming and environmental problem through its commercialization are expected to grow steadily.

• Convergence Security Journal
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• v.15 no.3_1
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• pp.75-82
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• 2015

Recently, lot of researches on multi-level protocol have been done to balance the sensor node energy consumption of WSN and to improve the node efficiency to extend the life of the entire network. Especially in multi-hop protocol, a variety of models have been studied to improve energy efficiency and apply it in real system. In multi-hop protocol, we assume that energy consumption can be adjusted based on the distance between the sensor nodes. However, according to the physical property of the actual WSN, it's hard to establish this. In this paper, we propose low-power sub-cluster protocol to improve the energy efficiency based on the spread of distance. Compared with the previous protocols, the proposed protocol is energy efficient and can be effectively used in the wireless sensing network.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.163-172
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• 2022

The interconnection of an enormous number of devices into the Internet at a massive scale is a consequence of the Internet of Things (IoT). As a result, tasks offloading from these IoT devices to remote cloud data centers become expensive and inefficient as their number and amount of its emitted data increase exponentially. It is also a challenge to optimize IoT device energy consumption while meeting its application time deadline and data delivery constraints. Consequently, Fog Computing was proposed to support efficient IoT tasks processing as it has a feature of lower service delay, being adjacent to IoT nodes. However, cloud task offloading is still performed frequently as Fog computing has less resources compared to remote cloud. Thus, optimized schemes are required to correctly characterize and distribute IoT devices tasks offloading in a hybrid IoT, Fog, and cloud paradigm. In this paper, we present a detailed survey and classification of of recently published research articles that address the energy efficiency of task offloading schemes in IoT-Fog-Cloud paradigm. Moreover, we also developed a taxonomy for the classification of these schemes and provided a comparative study of different schemes: by identifying achieved advantage and disadvantage of each scheme, as well its related drawbacks and limitations. Moreover, we also state open research issues in the development of energy efficient, scalable, optimized task offloading schemes for Fog computing.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.177-182
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• 2022

Technology is progressing with every passing day and the enormous usage of electricity is becoming a necessity. One of the techniques to enjoy the assistances in a smart home is the efficiency to manage the electric energy. When electric energy is managed in an appropriate way, it drastically saves sufficient power even to be spent during hard time as when hit by natural calamities. To accomplish this, prediction of energy consumption plays a very important role. This proposed prediction model Coherent Weighted K-Means Clustering ARIMA (CWKMCA) enhances the weighted k-means clustering technique by adding weights to the cluster points. Forecasting is done using the ARIMA model based on the centroid of the clusters produced. The dataset for this proposed work is taken from the Pecan Project in Texas, USA. The level of accuracy of this model is compared with the traditional ARIMA model and the Weighted K-Means Clustering ARIMA Model. When predicting,errors such as RMSE, MAPE, AIC and AICC are analysed, the results of this suggested work reveal lower values than the ARIMA and Weighted K-Means Clustering ARIMA models. This model also has a greater loglikelihood, demonstrating that this model outperforms the ARIMA model for time series forecasting.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.140-146
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• 2023

Resource allocation is one of the top challenges in Internet of Things (IoT) networks. This is due to the scarcity of computing, energy and communication resources in IoT devices. As a result, IoT devices that are not using efficient algorithms for resource allocation may cause applications to fail and devices to get shut down. Owing to this challenge, this paper proposes a novel algorithm for managing computing resources in IoT network. The fog computing devices are placed near the network edge and IoT devices send their large tasks to them for computing. The goal of the algorithm is to conserve energy of both IoT nodes and the fog nodes such that all tasks are computed within a deadline. A bi-partite graph-based algorithm is proposed for stable matching of tasks and fog node computing units. The output of the algorithm is a stable mapping between the IoT tasks and fog computing units. Simulation results are conducted to evaluate the performance of the proposed algorithm which proves the improvement in terms of energy efficiency and task delay.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.10-16
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• 2023

The ever-increasing amount of data generated by various industries and systems has led to the development of data mining techniques as a means to extract valuable insights and knowledge from such data. The electrical energy industry is no exception, with the large amounts of data generated by SCADA systems. This study focuses on the analysis of historical data recorded in the SCADA database of the Libyan Electricity Company. The database, spanned from January 1st, 2013, to December 31st, 2022, contains records of daily date and hour, energy production, temperature, humidity, wind speed, and energy consumption levels. The data was pre-processed and analyzed using the WEKA tool and the Apriori algorithm, a supervised machine learning technique. The aim of the study was to extract association rules that would assist decision-makers in making informed decisions with greater efficiency and reduced costs. The results obtained from the study were evaluated in terms of accuracy and production time, and the conclusion of the study shows that the results are promising and encouraging for future use in the Libyan Electricity Company. The study highlights the importance of data mining and the benefits of utilizing machine learning technology in decision-making processes.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.169-178
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• 2023

Wireless sensor network is wieldy use for IoT application. The sensor node consider as physical device in IoT architecture. This all sensor node are operated with battery so the power consumption is very high during the data communication and low during the sensing the environment. Without proper planning of data communication the network might be dead very early so primary objective of the cluster based routing protocol is to enhance the battery life and run the application for longer time. In this paper we have comprehensive of twenty research paper related with clustering based routing protocol. We have taken basic information, network simulation parameters and performance parameters for the comparison. In particular, we have taken clustering manner, node deployment, scalability, data aggregation, power consumption and implementation cost many more points for the comparison of all 20 protocol. Along with basic information we also consider the network simulation parameters like number of nodes, simulation time, simulator name, initial energy and communication range as well energy consumption, throughput, network lifetime, packet delivery ration, jitter and fault tolerance parameters about the performance parameters. Finally we have summarize the technical aspect and few common parameter must be fulfill or consider for the design energy efficient cluster based routing protocol.

• Journal of Energy Engineering
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• v.13 no.1
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• pp.60-67
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• 2004

The recent movement to deregulated and competitive electricity market reacquires new concepts against existing central dispatch in the system operation and pinning. As power systems tend to be operated more closely to their ultimate ratings, the role of SCOPF (Security Constrained Optimal Power flow) is changed and the importance for real-time security inhancement will be more increased i]1 the new and com partitive electricity market. This paper deals with the application of the SCOPF which makes possible the On-Line application. The security margin of power system truly is changed according to the conditions or configuration of power systems, therefore, the sensitivity factor reiated to the security is recalculated and the application should be updated in accordance with the state of power system. The goal of this paper is to obtain proper security through the effluent usage of the sensitivity and to apply this a1gorithm to system operation. The proposed mechanism has been tested on a sample system and the results show more secure conditions against critical contingencies.