• KIISE Transactions on Computing Practices
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• v.24 no.2
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• pp.99-104
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• 2018

Recently, there are increasing damages by ransomware in the world. Ransomware is a malicious software that infects computer systems and restricts user's access to them by locking the system or encrypting user's files saved in the hard drive. Victims are forced to pay the 'ransom' to recover from the damage and regain access to their personal files. Strong countermeasure is needed due to the extremely vicious way of attack with enormous damage. Malware analysis method can be divided into two approaches: static analysis and dynamic analysis. Recent malwares are usually equipped with elaborate packing techniques which are main obstacles for static analysis of malware. Therefore, this paper suggests a dynamic analysis method to monitor activities of ransomware. The proposed method can analyze ransomwares more accurately. The suggested method is comprised of extracting signatures of benign program, malware, and ransomware, and selecting the most appropriate signatures for ransomware detection.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.171-175
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• 2014

Gu$\acute{e}$ret et al. tries to obtain the solution using linear programming with $O(m^4)$ time complexity for cane sugar production problem a kind of bin packing problem that is classified as NP-complete problem. On the other hand, this paper suggests the maximum loss of lot first production greedy rule algorithm with O(mlogm) polynomial time complexity underlying assumption of the polynomial time rule to find the solution is exist. The proposed algorithm sorts the lots of sugar loss slope into descending order. Then, we select the lots for each slot production capacity only, and swap the exhausted life span of lots for lastly selected lots. As a result of experiments, this algorithm reduces the $O(m^4)$ of linear programming to O(mlogm) time complexity. Also, this algorithm better result than linear programming.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1567-1587
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• 2014

Virtual Machine (VM) resource management is crucial to satisfy the Quality of Service (QoS) demands of various multimedia services in a media cloud platform. To this end, this paper presents a VM resource allocation model that dynamically and optimally utilizes VM resources to satisfy QoS requirements of media-rich cloud services or applications. It additionally maintains high system utilization by avoiding the over-provisioning of VM resources to services or applications. The objective is to 1) minimize the number of physical machines for cost reduction and energy saving; 2) control the processing delay of media services to improve response time; and 3) achieve load balancing or overall utilization of physical resources. The proposed VM allocation is mapped into the multidimensional bin-packing problem, which is NP-complete. To solve this problem, we have designed a Mixed Integer Linear Programming (MILP) model, as well as heuristics for quantitatively optimizing the VM allocation. The simulation results show that our scheme outperforms the existing VM allocation schemes in a media cloud environment, in terms of cost reduction, response time reduction and QoS guarantee.

• Korean Journal of Agricultural Science
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• v.45 no.2
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• pp.298-307
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• 2018

The aim of this study was to enhance the value of the chestnut industry by analyzing the value chain structure. Based on the value chain theory, it is divided into primary activities and support activities. Thus, in total, 27 subjects from Gongju, Buyeo, and Cheongyang were interviewed and self-administered questionnaire. Regarding the value chain structure of the chestnut industry, the primary activities consisted of production followed by cultivation and storing, sorting and packaging, transportation and marketing sales. The support activities were divided into production infrastructure, policy, R&D, and systematization. The primary activities are able to maximize profits through cost reductions. The production was divided into general and environmentally friendly cultivation. Depending on the labor force, it is family-centered labor. However, the installation of harvest nets depends on a hired labor force (40 - 60%) such that it would be necessary to have a mechanized harvest to replace the manpower for the cost reduction. Transportation, marketing sales, and backdoor selling (38.1%) were higher than the existing channels (31.0%) using the National Agricultural Cooperative Federation. The enhancement of value could be created by maximizing profits through the reinforcement of the links between each subject. The production showed strong connections with cultivation/storing, sorting/packing, and backdoor selling and the National Forestry Cooperative Federation. The processing stage is a very simple structure, it would be necessary to have R&D and to support promotions, infrastructure, machines, and sales increases, which should be expanded by connections with other industries like the food industry.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.131-136
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• 2015

The chemical tank loading problem has been classified as nondeterministic polynomial time (NP)-complete problem because of the polynomial-time algorithm to find the solution has been unknown yet. Gu$\acute{e}$ret et al. tries to obtain the optimal solution using linear programming package with $O(m^4)$ time complexity for chemical tank loading problem a kind of bin packing problem. On the other hand, this paper suggests the rule of loading chemical into minimum margin tank algorithm with O(m) time complexity. The proposed algorithm stores the chemical in the tank that has partial residual of the same kind chemical firstly. Then, we load the remaining chemical to the minimum marginal tanks. As a result of experiments, this algorithm reduces the $O(m^4)$ of linear programming to O(m) time complexity for NP-complete chemical tank loading problem.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.95-102
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• 2022

This paper proposed a linear time algorithm for a three-partition problem(TPP) in which a polynomial time algorithm is not known as NP-complete. This paper proposes a backtracking method that improves the problems of not being able to obtain a solution of the MM method using the sum of max-min values and third numbers, which are known polynomial algorithms in the past. In addition, the problem of MM applying the backtracking method was improved. The proposed algorithm partition the descending ordered set S into three and assigned to the forward, backward, and best-fit allocation method with maximum margin, and found an optimal solution for 50.00%, which is 5 out of 10 data in initial allocation phase. The remaining five data also showed performance to find the optimal solution by exchanging numbers between surplus boxes and shortage boxes at least once and up to seven times. The proposed algorithm that performs simple allocation and exchange optimization with less O(k) linear time performance complexity than the three-partition m=n/3 data, and it was shown that there could be a polynomial time algorithm in which TPP is a P-problem, not NP-complete.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2019.10a
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• pp.83-83
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• 2019

Increasing the CO₂ concentration in the atmosphere induce high temperature and rising sea levels. So the technology that capture and reuse of the CO₂ have been recently become popular. Among other methods, CRR(CO2₂ reduction reaction) is typical method of CO₂ reusing. Electrocatalyst can show more higher efficiencies in CRR than photocatalyst because it doesn't use nature source. Nowadays, finding high efficient electrocatalyst by controlling electronic (affected by stoichiometry) and geometric (affected by atomic arrangement) factors are very important issues. Mono-atomic electro-catalyst has limitations on controlling binding energy because each intermediate has own binding energy range. So the Multi-metallic electro-catalyst is important to stabilize intermediate at the same time. Carbon monoxide(CO) which is our target product and important feedstock of useful products. Au is known for the most high CO production metal. With copper, Not only gold/copper has advantages which is they have FCC packing for easily forming solid solution regardless of stoichiometry but also presence of adsorbed CO on Cu promotes the desorption of CO on Au because of strong repulsion. And gold/copper bi-metal catalyst can show high catalytic activity(mass activity) although it has low selectivity relatively Gold. Actually, multi-metallic catalyst structure control method is limited in the solution method which is takes a lot of time. In here, we introduce CTS(carbo thermal shock) method which is using heat to make MMNP in a few seconds for making gold-copper system. This method is very simple and efficient in terms of time(very short reaction time and using carbon substrate as a direct working electrode) and increasing reaction sites(highly dispersed and mixing alloy structures). Last one is easy to control degree of mixing and it can induce 5 or more metals in one alloy system. Gold/copper by CTS can show higher catalytic activity depending on metal ratio which is altered easily by changing simple variables. The ultimate goals are making CO₂ test system by CTS which can check the selectivity depending on metal types in a very short time.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.21-31
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• 2018

Cyber penetration attacks can not only damage cyber space but can attack entire infrastructure such as electricity, gas, water, and nuclear power, which can cause enormous damage to the lives of the people. Also, cyber space has already been defined as the fifth battlefield, and strategic responses are very important. Most of recent cyber attacks are caused by malicious code, and since the number is more than 1.6 million per day, automated analysis technology to cope with a large amount of malicious code is very important. However, it is difficult to deal with malicious code encryption, obfuscation and packing, and the dynamic analysis technique is not limited to the performance requirements of dynamic analysis but also to the virtual There is a limit in coping with environment avoiding technology. In this paper, we propose a machine learning based malicious code analysis technique which improve the weakness of the detection performance of existing analysis technology while maintaining the light and high-speed analysis performance applicable to commercial endpoints. The results of this study show that 99.13% accuracy, 99.26% precision and 99.09% recall analysis performance of 71,000 normal file and malicious code in commercial environment and analysis time in PC environment can be analyzed more than 5 per second, and it can be operated independently in the endpoint environment and it is considered that it works in complementary form in operation in conjunction with existing antivirus technology and static and dynamic analysis technology. It is also expected to be used as a core element of EDR technology and malware variant analysis.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.47 no.3
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• pp.250-253
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• 2002

The post harvest treatment of barley had many hard work steps, such as drying, cleaning, and packing. This is a reason why farmer doesn't like to cultivate barley. This study was conducted to investigate the optimum post harvest management of bulk-harvested barley using rice processing complex (RPC). Bulk-harvested barley was stored to 61.1% after 6pm at RPC. Grain moisture contents of bulk-harvested barley differed from storing date, farmer household, and field. Required dry hours were different with grain moistures contents. The average dry hour was 9.5 hours per 10a and dry rate was 0.89%. The proportion of impurity removed by coarse cleaning differed from grain moisture contents, as higher grain moisture content made impurity rate increase up to 38.9%. Cost of drying of bulk-harvested barley was 50won per ㎏ at above 24% of grain moisture contents, and the average dry cost was 41.25 won/㎏ and 14,400won/10a. The 62% of barley treated was stored in indoor-grain bin, and the others packed in 500 ㎏-poly con bag were stored in warehouse insulated.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.151-158
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• 2023

The researchers entirely focused on meta-heuristic method for generalized assignment problem(GAP) that is known as NP-hard problem because of the optimal solution within polynomial time algorithm is unknown yet. On the other hand, this paper proposes a heuristic greedy algorithm with rules for finding solutions. Firstly, this paper reduces the weight matrix of original data to w_ij ≤ b_i/l in order to n jobs(items) pack m machines(bins) with l = n/m. The maximum profit of each job was assigned to the machine for the reduced data. Secondly, the allocation was adjusted so that the sum of the weights assigned to each machine did not exceed the machine capacity. Finally, the k-opt swap optimization was performed to maximize the profit. The proposed algorithm is applied to 50 benchmarking data, and the best known solution for about 1/3 data is to solve the problem. The remaining 2/3 data showed comparable results to metaheuristic techniques. Therefore, the proposed algorithm shows the possibility that rules for finding solutions in polynomial time exist for GAP. Experiments demonstrate that it can be a P-problem from an NP-hard.