• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.11-16
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• 2021

At the present time, the number of accidents has enlarged speedily and in country like India per day there are about 204 accidents occurred. Accidents of two-wheeler compose a foremost segment of every accident and it can be true for the reason that two-wheelers like bikes not able to produce as many as security measurements normally incorporated in cars, truks and bus etc. General main rootcost of the two-wheeler accidents happen only when people community not remember to wearing a device helmet and during the driving time feels like sleep condition, alcohol disbursement, many of the drivers doesn't know heavy vehicles like Loory and buses approaching into very closer to their two wheelers, contravention of two wheelers in traffic rules and regulations. Let's overcome the above situations; our important objective is to develop an intelligent system device that can successfully facilitate in avoidance of every kind of problems. Suppose any of the above stated situations occurs, at that moment how system device identify and represents the commanders and community, and finally the stated situation be able to taken care of straight away without any further delay. A smart intelligent helmet system is a defending head covering used by rider for making bike riding safer than earlier. This is finished by incorporating sophisticated features like detecting the usage of helmet by the rider, connected Bluetooth module in helmet. In order to maintain the temperature inside the helmet device we need to include CPU fan module inside the device. RF based helmet prevents road accidents and identify whether people community is not using a component helmet or used. Main responsibility of the system is to detect accidents by vibration sensors, accelerometers and also with the help of modules global positioning system and global system for mobile commnicaiton module. A wireless communication device used to discover the accident area site location and likewise notifying the two-wheeler drived people's relatives and short message text information passed to the positioned hospitals.

• 대한토목학회논문집
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• 제38권6호
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• pp.917-923
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• 2018

최근 도입되고 있는 첨단 차량 장치는 교통 안전분야에서 중요한 이슈가 되어왔던 중대형 사고 위주의 자료수집, 사고 자료의 정확성과 같은 다양한 문제를 해결할 수 있는 대안으로 부각되고 있다. 본 연구는 이러한 첨단 차량 장치의 하나인 차량 블랙박스 자료를 활용하여, 이륜차(two wheeler: TW) 즉, 자전거 혹은 오토바이와 택시간 사고 발생 시 이륜차 운전자의 사고 심각도를 분석하고자 하였다. 연구를 위해 인천시에서 2010년부터 2011년까지 영업용 택시 블랙박스에 기록된 택시-이륜차 사고 자료를 활용하였으며, 심각도 분석을 위해 순서형 프로빗 모형을 적용하였다. 결과적으로 기존 연구결과에서는 확인할 수 없는 새로운 심각도 요인이 발견되었다. 즉, 충돌 직전의 택시 속도가 높을수록, 택시 또는 이륜차의 파손이 발생한 경우, 사고 후 이륜차 운전자의 보행이 불가능할 경우, 그리고 1차 사고 후 이륜차 운전자가 2, 3차 충격으로 이어진 경우 사고 심각도는 더욱 높아지는 것으로 나타났다.

• 지식경영연구
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• 제25권1호
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• pp.217-233
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• 2024

최근 배달문화의 확산으로 이륜차 수요가 증가하면서 이륜차 운행도 함께 증가하고 있다. 이륜차 운행은 혼잡한 교통상황이나 경제적으로 효율적이지만 이륜차 난폭 운전과 명확하게 정립되지 않은 이륜차에 대한 교통 법규로 이륜차 사고는 새로운 사회문제로 나타나고 있다. 이륜차는 차체 특성 상 치사율이 높기 때문에 이륜차 사고가 발생하면 그 심각성 및 위험이 크다. 그러므로, 이륜차 사고에 대한 특성을 분석함으로써 이륜차 사고의 특성을 제대로 파악하는 것이 필요하다. 그리하여, 본 연구에서는 이륜차 사고 데이터를 기반으로 K-prototypes 알고리즘을 이용하여 이륜차 사고의 특성을 분류하였다. 그 결과, 이륜차 사고 특성에 따라 4개의 군집으로 분류되었다. 각 군집마다 사고발생 도로, 주요 위반법규, 사고 유형, 사고 발생 시간 등에서 다른 특성을 나타내었다. 이를 기반으로 이륜차 사고 예방을 위한 구체적인 방안을 제안한다. 각 사고 특성에 따른 단속 방법 및 규율을 개정함으로써 수도권 지역의 이륜차 사고 발생을 최소화하고 궁극적으로는 도로 안전성 향상에 기여한다. 더불어, 머신러닝 기법을 도시교통 및 안전 분야에 적용함으로써 관련 문헌확장에도 기여한다.

• 한국멀티미디어학회논문지
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• 제18권11호
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• pp.1302-1312
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• 2015

Recent research has been devoted and focused on detecting pedestrian and vehicle in intelligent vehicles except for the vulnerable road user(VRUS). In this paper suggest a new projection method which has robustness for rotation invariant and reducing dimensionality for each cell from original image to detect two-wheeler. We applied new weighting values which are calculated by maximum curvature containing very important object shape features and uniform local binary pattern to remove the noise. This paper considered the Adaboost algorithm to make a strong classification from weak classification. Experiment results show that the new approach gives higher detection accuracy than of the conventional method.

• Journal of Multimedia Information System
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• 제2권4호
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• pp.303-310
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• 2015

Vulnerable road users such as bike, motorcycle, small automobiles, and etc. are easily attacked or threatened with bigger vehicles than them. So this paper suggests a new approach two-wheelers detection system riding on people based on modified histogram of oriented gradients (HOGs) which is weighted by curvature and local correlation coefficient. This correlation coefficient between two variables, in which one is the person riding a bike and other is its background, can represent correlation relation. First, we extract edge vectors using the curvature of Gaussian and Histogram of Oriented Gradients (HOG) which includes gradient information and differential magnitude as cell based. And then, the value, which is calculated by the correlation coefficient between the area of each cell and one of bike, can be used as the weighting factor in process for normalizing the HOG cell. This paper applied the Adaboost algorithm to make a strong classification from weak classification. The experimental results validate the effectiveness of our proposed algorithm show higher than that of the traditional method and under challenging, such as various two-wheeler postures, complex background, and even conclusion.

• 대한의용생체공학회:의공학회지
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• 제32권4호
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• pp.336-344
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• 2011

This article describes a new recognition algorithm using correlation coefficient for intelligent wheelchair to avoid collision for elderly or disabled people. The correlation coefficient can be used to represent the relationship of two different areas. The algorithm has three steps: Firstly, we extract an edge vector using the Histogram of Oriented Gradients(HOG) which includes gradient information and unique magnitude for each cell. From this result, the correlation coefficients are calculated between one cell and others. Secondly, correlation coefficients are used as the weighting factors for normalizing the HOG cell. And finally, these features are used to classify or detect variable and complicated shapes of two wheelers using Adaboost algorithm. In this paper, we propose a new feature vectors which is calculated by weighted cell unit to classify with multiple view-based shapes: frontal, rear and side views($60^{\circ}$, $90^{\circ}$ and mixed angle). Our experimental results show that two wheeler detection system based on a proposed approach leads to a higher detection accuracy than the method using traditional features in a similar detection time.

• Journal of Multimedia Information System
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• 제4권1호
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• pp.33-38
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• 2017

This article suggests a new algorithm for detecting two-wheelers on the road that have various shapes according to viewpoints. Because of complicated shapes, it is more difficult than detecting a human. In general, the Histograms of Oriented Gradients(HOG) feature is well known as a useful method of detecting a standing human. We propose a method of detecting a human on a two-wheelers using the spatial relocation of HOG (Histogram of Oriented Gradients) features. And this paper adapted the contrast method which is generally using in the image process to improve the detection rate. Our experimental results show that a two-wheelers detection system based on proposed approach leads to higher detection accuracy, less computation, and similar detection time than traditional features.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2018년도 제58차 하계학술대회논문집 26권2호
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• pp.509-512
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• 2018

최근 미세먼지에 대한 관심이 높아지고 있으며, 미세먼지를 줄이기 위한 다양한 기술이 연구되고 있다. 본 연구에서는 기존 가솔린 이륜차의 단점을 극복하고 미세먼지 발생을 줄일 수 있는 배터리 교환식 이륜차 및 IoT 기반 지원시스템을 소개한다. 전기 이륜차에 탑재되는 IoT Edge device에서는 배터리 잔량, 배터리 ID, 위치 정보 등의 정보를 LTE-M 통신을 통해 IoT 클라우드에 전송하고, 배터리 교환이 필요한 경우 주변의 배터리 교환기 위치 및 교환 가능한 배터리 정보 전달 받을 수 있다. 현재 전기이륜차에 탑재될 IoT Edge device 및 사용자용 스마트폰앱을 개발하고 있으며, 배터리 교환기 및 클라우드 서비스 개발도 수행될 예정이다.

• 대한토목학회논문집
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• 제7권4호
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• pp.103-113
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• 1987

본(本) 연구(硏究)는 단순변동하중하(單純變動荷重下)에서의 피로균열성장거동(疲勞龜裂成長擧動)을 고찰하고 해석방법(解析方法)을 구하고자, 용접구조용강(鎔接構造用鋼) SWS 58을 사용하여 CT 시험편을 제작하고 간단한 하중모델을 설정(設定)하여 피로실험(疲勞實驗)을 행했다. 그 결과 단일과하중작용직후(單一過荷重作用直後)에는 가속효과(加速效果)가 경미(輕微)하게 발생하였으며 그후 상당한 지연효과(遲延效果)가 발생했다. 2단중복하중하(段重復荷重下)에서는 low-high인 경우 약간의 가속효과(加速效果)가 발생하나 high-low인 경우는 상당한 지연효과(遲延效果)가 발생했다. 이러한 하중변화(荷重變化)에 따른 균열성장율(龜裂成長率)(da/dN)은 균열선단(龜裂先端)의 잔류응력(殘留應力)과 소성영역(塑性領域)으로 인한 상호영향(相互影響)때문이며, 이러한 미시적(微視的) 균열성장거동(龜裂成長擧動)은 Elber의 crack closure model로 잘 설명(說明)될 수 있으나 피로균열성장해석방법(疲勞龜裂成長解析方法)으로는 불충분(不充分)하다. 반면 변동하중하(變動荷重下)에서의 피로균열성장해석방법(疲勞龜裂成長解析方法) 중(中) Wheeler의 retardation model은 간편하면서도 적합한 이론임을 알 수 있었다.

• Journal of Microbiology and Biotechnology
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• 제32권2호
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• pp.149-159
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• 2022

Cancers of the lung and liver are the top 10 leading causes of cancer death worldwide. Thus, it is essential to identify the genes specifically expressed in these two cancer types to develop new therapeutics. Although many messenger RNA (mRNA) sequencing data related to these cancer cells are available due to the advancement of next-generation sequencing (NGS) technologies, optimized data processing methods need to be developed to identify the novel cancer-specific genes. Here, we conducted an analytical comparison between Bowtie2, a Burrows-Wheeler transform-based alignment tool, and Kallisto, which adopts pseudo alignment based on a transcriptome de Bruijn graph using mRNA sequencing data on normal cells and lung/liver cancer tissues. Before using cancer data, simulated mRNA sequencing reads were generated, and the high Transcripts Per Million (TPM) values were compared. mRNA sequencing reads data on lung/liver cancer cells were also extracted and quantified. While Kallisto could directly give the output in TPM values, Bowtie2 provided the counts. Thus, TPM values were calculated by processing the Sequence Alignment Map (SAM) file in R using package Rsubread and subsequently in python. The analysis of the simulated sequencing data revealed that Kallisto could detect more transcripts and had a higher overlap over Bowtie2. The evaluation of these two data processing methods using the known lung cancer biomarkers concludes that in standard settings without any dedicated quality control, Kallisto is more effective at producing faster and more accurate results than Bowtie2. Such conclusions were also drawn and confirmed with the known biomarkers specific to liver cancer.