• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1508-1517
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• 2021

In CCTV environments, a lot of learning image data is required to monitor illegal dumping of garbage with a typical image-based object detection using deep learning method. In this paper, we propose a system to monitor unauthorized dumping of garbage by learning the articular points of the person using only a small number of images without immediate use of the image for deep learning. In experiment, the proposed system showed 74.97% of garbage dumping detection performance with only a relatively small amount of image data in CCTV environments.

• Journal of information and communication convergence engineering
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• v.22 no.2
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• pp.109-120
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• 2024

Trash or garbage is one of the most dangerous health and environmental problems that affect pollution. Pollution affects nature, human life, and wildlife. In this paper, we propose modern solutions for cleaning the environment of trash pollution by enforcing strict action against people who dump trash inappropriately on streets, outside the home, and in unnecessary places. Artificial Intelligence (AI), especially Deep Learning (DL), has been used to automate and solve issues in the world. We availed this as an excellent opportunity to develop a system that identifies trash using a deep convolutional neural network (CNN). This paper proposes a real-time garbage identification system based on a deep CNN architecture with eight distinct classes for the training dataset. After identifying the garbage, the CCTV camera captures a video of the individual placing the trash in the incorrect location and sends an alert notice to the relevant authority.

• Journal of KIISE
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• v.43 no.2
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• pp.152-162
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• 2016

Most traditional garbage collectors commonly use the language level metadata, which is designed for pointer type searching. However, because it is difficult to use this metadata in non-volatile memory allocation platforms, a new garbage collection technique is essential for non-volatile memory utilization. In this paper, we design new metadata for managing information regarding non-volatile memory allocation called "Allocation Tree". This metadata is comprised of tree data structure for fast information lookup and a node that holds an allocation address and an object ID pair in key-value form. The Garbage Collector starts collecting when there are insufficient non-volatile memory spaces, and it compares user data and the allocation tree for garbage detection. We develop this algorithm in a persistent heap based non-volatile memory allocation platform called "HEAPO" for demonstration.

• ETRI Journal
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• v.41 no.4
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• pp.494-505
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• 2019

In this paper, we propose a new framework for detecting the unauthorized dumping of garbage in real-world surveillance camera. Although several action/behavior recognition methods have been investigated, these studies are hardly applicable to real-world scenarios because they are mainly focused on well-refined datasets. Because the dumping actions in the real-world take a variety of forms, building a new method to disclose the actions instead of exploiting previous approaches is a better strategy. We detected the dumping action by the change in relation between a person and the object being held by them. To find the person-held object of indefinite form, we used a background subtraction algorithm and human joint estimation. The person-held object was then tracked and the relation model between the joints and objects was built. Finally, the dumping action was detected through the voting-based decision module. In the experiments, we show the effectiveness of the proposed method by testing on real-world videos containing various dumping actions. In addition, the proposed framework is implemented in a real-time monitoring system through a fast online algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.68.4-68
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• 2002

$\textbullet$ This report presents an implementation a set of reusable software components which use of fault-tolerance embedded controller for railway signalling systems. These components can be used in real-time applications without application reprogramming. $\textbullet$ This library runs under VxWorks operating system and is oriented on real-time embedded systems. The library includes fault detection, fault containment, checkpointing and recovery components. $\textbullet$ The library enables to support high-speed response to fault occurrence in application software. Garbage collector together with VxWorks Watchdog provides both dead tasks detection and useless resources removing to avoid an overflow. Control flow...

• KIISE Transactions on Computing Practices
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• v.23 no.8
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• pp.459-465
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• 2017

Although the performance of computer hardware is increasing due to the development of manycore technologies, software lacking a proportional increase in throughput. Functional languages can be a viable alternative to improve the performance of parallel programs since such languages have an inherent parallelism in evaluating pure expressions without side-effects. Specifically, Haskell is notably popular for parallel programming because it provides easy-to-use parallel constructs based on monads. However, the scalability of parallel programs in Haskell tends to fluctuate as the number of cores increases, and the garbage collector is suspected to be the source of this fluctuations because it affects both the space and the time needed to execute the programs. This paper uses the tuning tool, GC-Tune, to improve the scalability of the performance. Our experiment was conducted with a parallel plagiarism detection program, and the scalability improved. Specifically, the fluctuation range of the speedup was narrowed down by 39% compared to the original execution of the program without any tuning.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.453-466
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• 2024

To improve the monitoring of Coastal Debris in the South Korea, which is difficult to estimate due to limited resources and vertex-based surveys, an approach based on UAV(Unmanned Aerial Vehicle) images and the RT-DETR(Realtime DEtection TRansformer) model was proposed for detecting Coastal Debris. By comparing to field investigation, the study suggested the possibility of quantitatively detecting coastal garbage and estimating the total capacity of garbage deposited on the natural coastline of the South Korea. The RT-DETR model achieved an accuracy of 0.894 for mAP@0.5 and 0.693 for mAP@0.5:0.95 in training. When applied to unmanaged coasts, the accuracy for the total number of coastal debris items was 72.9%. It is anticipated that if guidelines for defining monitoring of unmanaged coasts are established alongside this research, it should be possible to estimate the total capacity of the deposited coastal debris in the South Korea.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.73-78
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• 2016

In wireless sensor networks, sensors have capabilities of sensing and wireless communication, computing power and collect data such as sound, movement, vibration. Sensors need to communicate wirelessly to send their sensing data to other sensors or the base station and so they are vulnerable to many attacks like garbage packet injection that cannot be prevented by using traditional cryptographic mechanisms. To defend against such attacks, a behavior-based attack detection is used in which some specialized monitoring nodes overhear the communications of their neighbors(normal nodes) to detect illegitimate behaviors. It is desirable that the total sensing area of normal nodes covered by monitoring nodes is as large as possible. The previous researches have focused on selecting the monitoring nodes so as to maximize the number of normal nodes(node coverage), which does not guarantee that the area sensed by the selected normal nodes is maximized. In this study, we have developed an algorithm for selecting the monitoring nodes needed to cover the maximum sensing area. We also have compared experimentally the covered sensing areas computed by our algorithm and the node coverage algorithm.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.571-580
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• 2022

Marine deposited waste is a major cause of problems such as a lot of damage and an increase in the estimated amount of garbage due to abandoned fishing grounds caused by ghost fishing. In this paper, we implement a real-time marine deposited waste detection artificial intelligence system to understand the actual conditions of waste fishing gear usage, distribution, loss, and recovery, and study methods for performance improvement. The system was implemented using the yolov5 model, which is an excellent performance model for real-time object detection, and the 'data screening process' and 'class segmentation' method of learning data were applied as performance improvement methods. In conclusion, the object detection results of datasets that do screen unnecessary data or do not subdivide similar items according to characteristics and uses are better than the object recognition results of unscreened datasets and datasets in which classes are subdivided.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1478-1485
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• 2009

A sensor network which is composed of a large number of sensors that perform various sensing is applied in a variety of fields. The sensor networks can be widely used for various application area like as home automation, fire detection and security area. Development of new sensor to have appropriate functions and deployment of networks for suitable application are served actively. In this paper, we design and implement a system that monitors various factory facilities by deploying sensor network at a working place which threatens the worker's safety. A sensor node reports its sensing data like as temperature and humidity to monitor facilities to a sink node. And the server which is connect to the sink node gathers and provides information by user interface. In addition, digital data which are generated at a work place can be transferred via the sensor network to increase the efficiency of works. The proposed sensor network provides the convenience of working, since it is deployed at a garbage collection company to monitor a temperature and humidity of garbage and to transmit data about the weight of trucks which enters the company.