This Paper deals with the economical equipment control which is used by internet network system at the industrial workplace. If the control devices can be accessed by internet, we can have the developed possibility of work conditions. in this paper, we presented the advanced digital timer which has a communication function to control and observe panel to realize control solution based on internet to be easily applicable at workplace with low cost, and we used RS-485 serial communication module to have parallel expansibility and safety. And, this system was experimented and designed for easy system management and status check from remote station through internet. As the result for experiment, the circuit configuration would be more simplified than the existing, and it is expected that multi connection control and monitoring can be simply implemented with low cost equipment at industrial workplace.

This paper presents a new method for finding the Block Pulse series coefficients and deriving the Block Pulse integration operational matrices which are necessary for the control fields using the Block Pulse functions. In order to apply the Block Pulse function technique to the problems of continuous-time dynamic systems more efficiently, it is necessary to find the more exact value of the Block Pulse series coefficients and drives the related integration operational matrices by using the Lagrange second order interpolation polynomial.

A new dynamic scheduling algorithm is proposed for CAN-based real-time system in this paper. The proposed algorithm is extended from an existing EDS(Earliest Deadline Scheduling) approach having a solution to the priority inversion. Using the proposed algorithm, the available bandwidth of network media can be checked dynamically, and consequently arbitration delay causing the miss of deadline can be avoided. Also, non-real time messages can be processed with their bandwidth allocation. Full network utilization and real-time transmission feasibility can be achieved through the algorithm. To evaluate the performance of algorithm, two simulation tests are performed. The first one is transmission data measurement per minute for periodic messages and the second one is feasibility in the system with both periodic messages and non-real time message.

Digital watermarking is the technique, which embeds an invisible signal including signal including owner identification and copy control information into multimedia data such as audio, video, and images for copyright protection. A new MPEG watermark embedding algorithm using complex block effect based on the Human Visual System(HVS) is introduced in this paper. In this algorithm, $8{\times}8$ dark blocks are selected, and the watermark is embedded in the DC component of the discrete cosine transform(DCT) by using quantization and modulus calculation. This algorithm uses a blind watermark retrieval technique, which detects the embedded watermark without using the original image. The experimental results show that the proposed watermark technique is robust against MPEG coding, bitrate changes, and various GOP(Group of Picture) changes.

In this paper, we propose a robust digital copyright-protection technique based on the concept of human auditory system. First, we propose a watermarking technique that accepts the various attacks such as, time scaling, pitch shift, add noise and a lot of lossy compression such as MP3, AAC WMA. Second, we implement audio PD(portable device) for copyright protection using proposed method. The proposed watermarking technique is developed using digital filtering technique. Being designed according to critical band of HAS(human auditory system), the digital filers embed watermark without nearly affecting audio quality. Before processing of digital filtering, wavelet transform decomposes the input audio signal into several signals that are composed of specific frequencies. Then, we embed watermark in the decomposed signal (0kHz~11kHz) by designed band-stop digital filer. Watermarking detection algorithm is implemented on audio PD(portable device). Proposed watermarking technology embeds 2bits information per 15 seconds. If PD detects watermark '11', which means illegal song. PD displays "Illegal Song" message on LCD, skips the song and plays the next song, The implemented detection algorithm in PD requires 19 MHz computational power, 7.9kBytes ROM and 10kBytes RAM. The suggested technique satisfies SDMI(secure digital music initiative) requirements of platform3 based on ARM9E core.

This paper presents a linear temperature/voltage relation over a temperature range(0~100$^{\circ}C$) with high-resolution, reasonably god response linearity, reliability, and overall improved performance. A notable feature of the proposed method is that the whole temperature span is divided by 16 subbands thus the variation span of measured voltage is narrowed. Therefore noise characteristic has been improved. The output voltage is amplified after the uniformed DC voltage component is eliminated by offset. We proposed circuit using median value and mean value of digital signal in order to reduce the noise effect. The proposed circuit offers linear temperature/voltage conversion over a wide dynamic range using DSP(TMS320C31) and steinhart equation.

As multimedia database and digital image libraries are enlarged, CBIR(Content Based Image Retrieval) has been getting importance for the efficient search. Generally, CBIR uses primitive features such as color, shape, texture and so on. Among various methods of CBIR, Gabor wavelet has good image retrieval performance with texture features but it has a disadvantage which does not perform well for a rotated image because of its direction oriented filter. In this paper, we propose a new method to solve this problem by modifying Gabor filter for all directions. And then we will compare the searching performance of the proposed method with those of conventional image retrieval methods through experiments with trademarks.

In this study, we developed a snoring detection algorithm that detects snores automatically. It consists of preprocessing and snoring detection part. The preprocessing part is composed of a noise removal part using spectrum subtraction, and segmentation part, and computation part of temporal and spectral features. And the snoring detection part decides whether detected blocks are snores with BPNN(Back-Propagation Neural Network). BPNN with one hidden layer and one output layer, is trained with data of 7 subjects and tested with data of 11 subjects of total 18 subjects. The proposed algorithm showed a Sensitivity of 90.41% and a Predictive Positive Value of 84.95%.