• Journal of Auto-vehicle Safety Association
• /
• v.11 no.2
• /
• pp.35-43
• /
• 2019

This paper describes the improved environment recognition algorithms using some type of sensors like LiDAR and cameras. Additionally, integrated control algorithm for an autonomous vehicle is included. The integrated algorithm was based on C++ environment and supported the stability of the whole driving control algorithms. As to the improved vision algorithms, lane tracing and traffic sign recognition were mainly operated with three cameras. There are two algorithms developed for lane tracing, Improved Lane Tracing (ILT) and Histogram Extension (HIX). Two independent algorithms were combined into one algorithm - Enhanced Lane Tracing with Histogram Extension (ELIX). As for the enhanced traffic sign recognition algorithm, integrated Mutual Validation Procedure (MVP) by using three algorithms - Cascade, Reinforced DSIFT SVM and YOLO was developed. Comparing to the results for those, it is convincing that the precision of traffic sign recognition is substantially increased. With the LiDAR sensor, static and dynamic obstacle detection and obstacle avoidance algorithms were focused. Therefore, improved environment recognition algorithms, which are higher accuracy and faster processing speed than ones of the previous algorithms, were proposed. Moreover, by optimizing with integrated control algorithm, the memory issue of irregular system shutdown was prevented. Therefore, the maneuvering stability of the autonomous vehicle in severe environment were enhanced.

• Cross-Cultural Studies
• /
• v.37
• /
• pp.31-49
• /
• 2014

Peking has peculiar features as capital city, and has gone through various transformations, with its name changed from Peking to Peiping to Peking. Even when it did not serve as a capital city, it still played an unrivaled role in cultural aspects. Laoshe, a great writer of 'Peking flavour' literature, is famous for works full of cultural charms of Peking. In his works, which show the manners, norms, art, culture and optimistic life style of Peking, Peking culture is described as an extension of cultural traditions of Qiren. In addition, his critical view of reality is also expressed in the works. Linhaiyin's literary works show ordinary hutongs she experienced in the 1920s in Chengnan, the southern part of Peking, and the quiet and simple life of warm-hearted people living there. Her vague memories of Peking, along with her nostalgia for the city, let her describe the city with recreated happy memories of it instead of the harsh critical view. Her works express the city in her recreated memory full of hope, with her dark memories of the city being glossed over. As seen above, Laoshe realistically described the tragic and difficult life of low class people in hutongs of Peking as well as lower middle class people of the city. Meanwhile, in ChengnanJiushi, Linhaiyin expresses the daily routine and ordinary life of people in Peking from the perspective of middle class people. In addition, she showed the sympathetic view of middle class citizens towards their low-class neighbors. In Peking Menghualu, Wangdewei mentioned that the 'castle of memory' which old Peking people in Taiwan tried to establish fills an important gap for the continuity of Peking cultural history and cultural imagination. This indicates that the 'Peking castle of memories,' which Linhaiyin, a Taiwanese writer well known for 'Peking flavour,' has established plays a big role in filling part of such gap. ChengnanJiushi, Wuyigong's film based on Linhaiyin's novel of the same title, also describes the daily sceneries and culture of the southern Peking in the 1920s, which both Taiwanese and Chinese people miss, through sophisticated images with 'profound yearning tinted with calm sadness', accomplishing an artistic achievement different from that of the novel.

• Korean Journal of Construction Engineering and Management
• /
• v.20 no.6
• /
• pp.34-43
• /
• 2019

The maintenance cost for road pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance preventive maintenance requires the establishment of a strategic plan through accurate prediction of road pavement. Hence, In this study, the deep neural network(DNN) and the recurrent neural network(RNN) were used in order to develop the expressway pavement damage prediction model. A superior model among these two network models was then suggested by comparing and analyzing their performance. In order to solve the RNN's vanishing gradient problem, the LSTM (Long short-term memory) circuits which are a more complicated form of the RNN structure were used. The learning result showed that the RMSE value of the RNN-LSTM model was 0.102 which was lower than the RMSE value of the DNN model, indicating that the performance of the RNN-LSTM model was superior. In addition, high accuracy of the RNN-LSTM model was verified through the comparison between the estimated average road pavement condition and the actually measured road pavement condition of the target section over time.

• The KIPS Transactions:PartC
• /
• v.10C no.3
• /
• pp.273-280
• /
• 2003

When an existing user authorization systems in Grid access many user to local system and subject DN (Distinguished Name) in a user-proxy authenticate and ID in local system is one-to-one mapping, they have difficulties in ID management, memory resource management and resource management. At this, a variety of subject DN is shared of one local ID in an existing Grid. But this faces many difficulties in applying all requirements for many Grid users. Thus, we suppose user authorization system based on a certificate not them based on ID in this paper. That is, we add user's access level to extension field in a certificate, and make a supposed authorization system decide access limitation level on resources instead of an existing ID mapping methods.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.233-238
• /
• 1993

In this paper, two diagnosis algorithms using the simple fuzzy, cognitive map (FCM) that is an useful qualitative model are proposed. The first basic algorithm is considered as a simple transition of Shiozaki's signed directed graph approach to FCM framework. And the second one is an extended version of the basic algorithm. In the extension, three important concepts, modified temporal associative memory (TAM) recall, temporal pattern matching algorithm and hierarchical decomposition are adopted. As the resultant diagnosis scheme takes short computation time, it can be used for on-line fault diagnosis of large scale and complex processes that conventional diagnosis methods cannot be applied. The diagnosis system can be trained by the basic algorithm and generates FCM model for every experienced process fault. In on-line application, the self-generated fault model FCM generates predicted pattern sequences, which are compared with observed pattern sequences to declare the origin of fault. In practical case, observed pattern sequences depend on transport time. So if predicted pattern sequences are different from observed ones, the time weighted FCM with transport delay can be used to generate predicted ones. The fault diagnosis procedure can be completed during the actual propagation since pattern sequences of tvo different faults do not coincide in general.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.9 no.6
• /
• pp.63-68
• /
• 2009

In the whole information technology area, the protection of information from hacking or tapping becomes a very serious issue. Therefore, the more effective, convenient and secure methods are required to make the safe operation. Encryption algorithms are known to be computationally intensive. They consume a significant amount of computing resources such as CPU time and memory. In this paper we propose the scalable encryption scheme with four criteria, the compression of plaintext, variable size of block, selectable round and software optimization. We have tested our scheme by c++. Experimental results show that our scheme achieves the faster execution speed of encryption/decryption.

• Journal of the Korean Institute of Telematics and Electronics T
• /
• v.35T no.1
• /
• pp.40-47
• /
• 1998

The optical heads as the key parts of digital audio/video players are applied extensively from general household electric appliances to computer memory or game apparatuses, and the demand of them tends to be increased according to the extension of optical medium market. In this paper, the 2-axis actuator, the key component for focus servo and tracking servo of the optical head is designed as a type of the cantilever suspended by 4 wires. The design propriety is verified through its simulation and the characteristic analysis of its mock-ups. The other factors which influence the performance of 2-axis actuators besides the design factors of them, are also verified through the mock-up analysis.

• Journal of Communications and Networks
• /
• v.13 no.2
• /
• pp.187-200
• /
• 2011

We present the design and implementation of a novel anti-malware system called SplitScreen. SplitScreen performs an additional screening step prior to the signature matching phase found in existing approaches. The screening step filters out most non-infected files (90%) and also identifiesmalware signatures that are not of interest (99%). The screening step significantly improves end-to-end performance because safe files are quickly identified and are not processed further, and malware files can subsequently be scanned using only the signatures that are necessary. Our approach naturally leads to a network-based anti-malware solution in which clients only receive signatures they needed, not every malware signature ever created as with current approaches. We have implemented SplitScreen as an extension to ClamAV, the most popular open source anti-malware software. For the current number of signatures, our implementation is $2{\times}$ faster and requires $2{\times}$ less memory than the original ClamAV. These gaps widen as the number of signatures grows.

• ETRI Journal
• /
• v.30 no.4
• /
• pp.576-586
• /
• 2008

In most parallel loops of embedded applications, every iteration executes the exact same sequence of instructions while manipulating different data. This fact motivates a new compiler-hardware orchestrated execution framework in which all parallel threads share one fetch unit and one decode unit but have their own execution, memory, and write-back units. This resource sharing enables parallel threads to execute in lockstep with minimal hardware extension and compiler support. Our proposed architecture, called multithreaded lockstep execution processor (MLEP), is a compromise between the single-instruction multiple-data (SIMD) and symmetric multithreading/chip multiprocessor (SMT/CMP) solutions. The proposed approach is more favorable than a typical SIMD execution in terms of degree of parallelism, range of applicability, and code generation, and can save more power and chip area than the SMT/CMP approach without significant performance degradation. For the architecture verification, we extend a commercial 32-bit embedded core AE32000C and synthesize it on Xilinx FPGA. Compared to the original architecture, our approach is 13.5% faster with a 2-way MLEP and 33.7% faster with a 4-way MLEP in EEMBC benchmarks which are automatically parallelized by the Intel compiler.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.356-361
• /
• 1998

Neural Networks, modeled succinctly from the real nervous system of a living body, can be categorized into two folds; artificial neural network(ANN) and biological neural network(BNN). While the former has been developed to solve practical problems using function approximation capability, pattern classification) clustering algorithm, etc, the latter has been focused on verifying the information processing capability to which brain research gives an impetus, by mimicking real biological systems. However, BNN suffers Iron severe nonlinearities dealt with. A bridge between two neural networks is chaotic neural network(CNN), which simply delineate the real nor-vous system and comprises almost all the ANN structures by selecting parameters. Main research theme of this area is to develop an explanation tool to clarify the information processing mechanism in biological systems and its extension to engineering applications. The CNN has a Gaussian-shaped refractory function with hysteresis effect and the chaotic responses of it have been observed fur a wide range of parameter space. Through the examination of the coupling effects of excitatory and inhibitory connections, the secrets of information processing and memory structure will appear.