• Journal of Microbiology and Biotechnology
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• v.27 no.6
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• pp.1039-1052
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• 2017

Endophytic fungi have currently been acknowledged as the most promising source of bioactive compounds for drug discovery, and considerable progress has been made in exploring their diversity, species richness, and bioprospecting. Fungal endophytes from unique environmental settings offer a pool of potentially useful medicinal entities. Owing to the constant stresses imposed on macroalgae by marine environments, it is believed that algae and their associated endophytic symbionts represent a good source of structurally diverse bioactive secondary metabolites. Despite the proven significance of active metabolites of algal endophytes, little have been exploited. This review highlights the latest discoveries in algicolous endophytic research, with particular focus on the bioactive metabolites from algal endophytes. Compounds are classified according to their reported biological activities, like anticancer, antibacterial, antifungal, and antioxidant properties. Present experimental evidence suggests that a majority of the bioactive metabolites were reported from Phaeophyceae followed by Rhodophyceae and Chlorophyceae. An intensive search for newer and more effective bioactive metabolites has generated a treasure trove of publications, and this review partially covers the literature published up to 2016.

• Journal of KIISE
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• v.41 no.9
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• pp.686-698
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• 2014

Recently, large-scale streaming sensor data have emerged due to explosive supply of smart phones, diffusion of IoT and Cloud computing technology, and generalization of IoT devices. Also, researches on combination of semantic web technology are being actively pushed forward by increasing of requirements for creating new value of data through data sharing and mash-up in large-scale environments. However, we are faced with big issues due to large-scale and streaming data in the inference field for creating a new knowledge. For this reason, we propose the RDFS rule based parallel reasoning scheme to service by processing large-scale streaming sensor data with the semantic web technology. In the proposed scheme, we run in parallel each job of Rete network algorithm, the existing rule inference algorithm and sharing data using the HBase, a hadoop database, as a public storage. To achieve this, we implement our system and evaluate performance through the AWS data of the weather center as large-scale streaming sensor data.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2568-2574
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• 2005

Control architecture of the action based robot engineering can be divided into two types of deliberate type - and reactive type- controller. Typical deliberate type, slow in reaction speed, is well suited for the realization of the higher intelligence with its capability to forecast on the basis of environmental model according to time flow, while reactive type is suitable for the lower intelligence as it fits to the realization of speedy reactive action by inputting the sensor without a complete environmental model. Looking at the environments in the application areas in which robots are actually used, we can see that they have been mostly covered by the uncertain and unknown dynamic changes depending on time and place, the previously known knowledge being existed though. It may cause, therefore, any deterioration of the robot performance as well as further happen such cases as the robots can not carry out their desired performances, when any one of these two types is solely engaged. Accordingly this paper aims at suggesting Goal-oriented Geometric Model(GGM) Based Intelligent System Architecture which leads the actions of the robots to perform their jobs under variously changing environment and applying the suggested system structure to the navigation issues of the robots. When the robots do perform navigation in human life changing in a various manner with time, they can appropriately respond to the changing environment by doing the action with the recognition of the state. Extending this concept to cover the highest hierarchy without sticking only to the actions of the robots can lead us to apply to the algorithm to perform various small jobs required for the carrying-out of a large main job.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.113-120
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• 2004

Considering the present and expected demand for human resources by the maritime community, its quantity and quality depend on the number of the ships and the technology applied to them. Scientific and economic developments in this community bring the intensive use of modem technology for many of ships operation. Generally it effects to reduce the quantity of manpower, while it increases the requirement of qualifications of human resources to utilize such advanced technology. Considering above, the maritime education, training and research activities should be revised and updated according to the demand of the community. Because of a difference between the transition of the demand for the human resources and development of the maritime education, training and research activities, there are two most common questions as “What to teach” and “How to teach”. The first question has been asked for many years. The contents of maritime education and training are always related to the existing maritime knowledge and technology and should be updated with consideration of changes of the demand namely “Globalisation of maritime community”. It brings globalisation of the maritime education, training and research activities. The second question is still keeping us busy to look for the best way. Presently traditional methods are used together with new system, while the use of sophisticated simulation, communication and information systems etc. and it is changing our understanding on teaching. This paper introduces the new role of Maritime Institutions from the viewpoints of the maritime education. training and research activities. The role of guide for seafarers and maritime companies is always essential and the concepts such as “Refreshment Training”, “On the Job Training”, “Lifelong” or “Continuous Training” bring new understanding to the training period, trainee's age and position. As a result, the maritime institutions should be ready for their new role, which is, in brief, guiding the maritime society, recommending and providing new learning environments, organising research and developments, performing the education, training and assessment, improving existing methods and developing new methods of the education, training and assessment.

• The Journal of Korean Association of Computer Education
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• v.11 no.3
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• pp.91-99
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• 2008

In recent years, wireless networks have been widely deployed and the use of mobile devices has been popularized. As a result, mobile devices are increasingly considered as a resource of the Grid However, there are some problems such as unstable wireless communication and disconnection of mobile devices caused by movement in Mobile Grid Therefore, a scheduling method allocating jobs to the mobile devices should progressively deal with this problem The existing scheduling methods in Mobile Grid have mainly focused on the connection time of mobile devices. The connection time of mobile devices shows typically a regular pattern according to a user's living environments such as vacation/class in school, weekday/weekend in work, and so on. In this paper, we analyze statistics information for the utilization patterns of mobile devices and propose global and local scheduling methods for Mobile Grid, based on the analyzed utilization patterns.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.204-226
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• 2018

Big data processing applications have been migrated into cloud gradually, due to the advantages of cloud computing. Hadoop Distributed File System (HDFS) is one of the fundamental support systems for big data processing on MapReduce-like frameworks, such as Hadoop and Spark. Since HDFS is not aware of the co-location of virtual machines in the cloud, the default scheme of block allocation in HDFS does not fit well in the cloud environments behaving in two aspects: data reliability loss and performance degradation. In this paper, we present a novel location-aware data block allocation strategy (LDBAS). LDBAS jointly optimizes data reliability and performance for upper-layer applications by allocating data blocks according to the locations and different processing capacities of virtual nodes in the cloud. We apply LDBAS to two stages of data allocation of HDFS in the cloud (the initial data allocation and data recovery), and design the corresponding algorithms. Finally, we implement LDBAS into an actual Hadoop cluster and evaluate the performance with the benchmark suite BigDataBench. The experimental results show that LDBAS can guarantee the designed data reliability while reducing the job execution time of the I/O-intensive applications in Hadoop by 8.9% on average and up to 11.2% compared with the original Hadoop in the cloud.

• Journal of Labour Economics
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• v.40 no.3
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• pp.29-55
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• 2017

We examine the effects of the self-reported subjective and the objective health indexes on work compensations. The compensations consist of monetary factors, such as wages, and non-monetary factors reflecting job risks such as the workplace accidence. The wages and workplace injuries are clearly affected by gender and age differences as the subjective and objective health factors of elderly workers are combined with physical and systematic work environments. Mental health problems such as work depression are more serious especially for high income elderly groups. The elderly workers experienced with physical problems and chronic illnesses are led to the decrease in wages and the increase in safety accident risks at work sharply. Therefore, we need to provide supporting services, retirement planning designed by companies, supported by the government enhanced risk working conditions and the weakness on protecting jobs.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.405-412
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• 2006

Real-time operating systems have been used in various computing environments, where a job must be completed in its deadline, with various conditions, such as effective scheduling policies, the minimum of an interrupt delay, and the solutions of priority inversion problems, that should be perfectly satisfied to design and develop optimal real-time operating systems. Up to now, in order to solve priority inversion problems among several those conditions. There have been two representative protocols: basic priority inheritance protocol and priority ceiling emulation protocol. However, these protocols cannot solve complicated priority inversion problems. In this paper, we design a protocol, called recursive priority inheritance (RPI), protocol that effectively solves the complicated priority inversion problems. Our proposed protocol is also implemented in the Linux kernel and is compared with other existing protocols in the aspect of qualitative analysis.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.173-186
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• 2000

Real-time embedded systems should accommodate many kinds of hardware platforms and resource management policies that vary depending on their operating environments and purposes. It is not an easy job to adapt a multitasking kernel to new system services and hardware platforms, as the kernel must strictly satisfy constraints on its size and performance. This paper describes the design and implementation of an object-oriented multitasking framework that can be reused for implementing microprocessor-based real-time embedded multitasking kernels, In this kernel framework, those parts that can vary depending on hardware platforms and system resource management policies are separated into the hot spots and encapsulated by abstract classes. Our framework thus can be effectively used to implement microprocessor-based real-time embedded kernels that demand high portability and adaptability.

• Fire Science and Engineering
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• v.28 no.1
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• pp.58-63
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• 2014

This study was performed to propose measures to improve and secure safety in the scene activities of firefighters. First, the majority of firefighters thought that working environment and equipment in fire station were inadequate for perforeming work tasks safely. Second, influential factors threatening safe scene activities mainly arose externally such as insecure working conditions of firefighting or emergency scene. Third, improvement in working environments was pointed out as the most urgent issue to secure safety. Firefighters recognized the expansion of field workforce in system, personnel management and the foundation of hospitals for firefighters hospital in working environment, and the development and distribution of safe equipment and change and inspection of air respirator facepiece on regular basis in equipment as urgent issues to be improved.