• Title/Summary/Keyword: JMIS

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Fast Extraction of Pedestrian Candidate Windows Based on BING Algorithm

  • Zeng, Jiexian;Fang, Qi;Wu, Zhe;Fu, Xiang;Leng, Lu
    • Journal of Multimedia Information System
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    • v.6 no.1
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    • pp.1-6
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    • 2019
  • In the field of industrial applications, the real-time performance of the target detection problem is very important. The most serious time consumption in the pedestrian detection process is the extraction phase of the candidate window. To accelerate the speed, in this paper, a fast extraction of pedestrian candidate window based on the BING (Binarized Normed Gradients) algorithm replaces the traditional sliding window scanning. The BING features are extracted with the positive and negative samples and input into the two-stage SVM (Support Vector Machine) classifier for training. The obtained BING template may include a pedestrian candidate window. The trained template is loaded during detection, and the extracted candidate windows are input into the classifier. The experimental results show that the proposed method can extract fewer candidate window and has a higher recall rate with more rapid speed than the traditional sliding window detection method, so the method improves the detection speed while maintaining the detection accuracy. In addition, the real-time requirement is satisfied.

Evaluation of Subtractive Clustering based Adaptive Neuro-Fuzzy Inference System with Fuzzy C-Means based ANFIS System in Diagnosis of Alzheimer

  • Kour, Haneet;Manhas, Jatinder;Sharma, Vinod
    • Journal of Multimedia Information System
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    • v.6 no.2
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    • pp.87-90
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    • 2019
  • Machine learning techniques have been applied in almost all the domains of human life to aid and enhance the problem solving capabilities of the system. The field of medical science has improved to a greater extent with the advent and application of these techniques. Efficient expert systems using various soft computing techniques like artificial neural network, Fuzzy Logic, Genetic algorithm, Hybrid system, etc. are being developed to equip medical practitioner with better and effective diagnosing capabilities. In this paper, a comparative study to evaluate the predictive performance of subtractive clustering based ANFIS hybrid system (SCANFIS) with Fuzzy C-Means (FCM) based ANFIS system (FCMANFIS) for Alzheimer disease (AD) has been taken. To evaluate the performance of these two systems, three parameters i.e. root mean square error (RMSE), prediction accuracy and precision are implemented. Experimental results demonstrated that the FCMANFIS model produce better results when compared to SCANFIS model in predictive analysis of Alzheimer disease (AD).

Comparative Study to Measure the Performance of Commonly Used Machine Learning Algorithms in Diagnosis of Alzheimer's Disease

  • kumar, Neeraj;manhas, Jatinder;sharma, Vinod
    • Journal of Multimedia Information System
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    • v.6 no.2
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    • pp.75-80
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    • 2019
  • In machine learning, the performance of the system depends upon the nature of input data. The efficiency of the system improves when the behavior of the input data changes from un-normalized to normalized form. This paper experimentally demonstrated the performance of KNN, SVM, LDA and NB on Alzheimer's dataset. The dataset undertaken for the study consisted of 3 classes, i.e. Demented, Converted and Non-Demented. Analysis shows that LDA and NB gave an accuracy of 89.83% and 88.19% respectively in both the cases whereas the accuracy of KNN and SVM improved from 46.87% to 82.80% and 53.40% to 88.75% respectively when input data changed from un-normalized to normalized state. From the above results it was observed that KNN and SVM show significant improvement in classification accuracy on normalized data as compared to un-normalized data, whereas LDA and NB reflect no such change in their performance.

Medical Diagnosis Algorithm Based on Tongue Image on Mobile Device

  • Zhou, Zibo;Peng, Dongliang;Gao, Fumeng;Leng, Lu
    • Journal of Multimedia Information System
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    • v.6 no.2
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    • pp.99-106
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    • 2019
  • In traditional Chinese medical (TCM) science, tongue images can be observed for medical diagnosis; however, the tongue diagnosis of TCM is influenced by the subjective factors of doctors, and the diagnosis results vary from person to person. Quantitative TCM tongue diagnosis can improve the accuracy of diagnosis and increase the application value. In this paper, digital image processing and pattern recognition technologies are employed on mobile device to classify tongue images collected in different health states. First, through grayscale integral projection processing, the trough is found to localize the tongue body. Then the tongue body image is transferred from RGB color space to HSV color space, and the average H and S values are considered as the color features. Finally, the diagnosis results are obtained according to the relationship between the color characteristics and physical symptoms.

A Study on the Possibility of Introducing Korean Technologies into Vietnam for Monitoring and Prevention of Solitary Deaths of Elderly

  • Nguyen, Thi-Hong
    • Journal of Multimedia Information System
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    • v.6 no.1
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    • pp.31-35
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    • 2019
  • The Socialist Republic of Vietnam has become one of the top ten nations with the highest aging rate. The proportion of their aging population increased from 7.2% to 10.95% from 1989 to 2017 and entered into the aging society six years earlier than what had been anticipated in 2011. The main issues in such a society are the problems associated with the elderly living by themselves and their solitary deaths. This study attempts to find a solution which would mitigate the burdens of aging or aged population who are living in a lonely and solitary living condition focusing on the system used for the purpose of managing or monitoring of their daily lives to prevent any undesirable outcomes including solitary deaths. The study also discusses the possibility of introducing the system into Vietnam.

Laparoscopic Rectovaginal Septal Repair without Mesh for Anterior Rectocele

  • Kwak, Han Deok;Ju, Jae Kyun
    • Journal of Minimally Invasive Surgery
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    • v.21 no.4
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    • pp.177-179
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    • 2018
  • A rectocele with a weakened rectovaginal septum can be repaired with various surgical techniques. We performed laparoscopic posterior vaginal wall repair and rectovaginal septal reinforcement without mesh using a modified transperineal approach. A 63-year-old woman with outlet dysfunction constipation complained of lower pelvic pressure and sense of heaviness for 30 years. Initial defecography showed an anterior rectocele with a 45-mm anterior bulge and perineal descent. Laparoscopic procedures included peritoneal and rectovaginal septal dissection directed toward the perineal body, rectovaginal septal suturing, and peritoneal closure. The patient started a soft diet the following day and was discharged on the 5th postoperative day without any complications. The patient had no dyschezia or dyspareunia, and no problem with bowel function; 3-month follow-up defecography showed a decrease in bulging to 18 mm. Laparoscopic posterior vaginal wall and rectovaginal septal repair is safe and feasible for treatment of a rectocele, and enables early recovery.

Function-Preserving Surgery in Gastric Cancer

  • Bueno, Jan Andrew D.;Park, Young-Suk;Ahn, Sang-Hoon;Park, Do Joong;Kim, Hyung-Ho
    • Journal of Minimally Invasive Surgery
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    • v.21 no.4
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    • pp.141-147
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    • 2018
  • The rising incidence of early gastric cancer has enabled the development of function-preserving gastrectomy with the focus on post gastrectomy quality of life and adherence to sound oncologic principles. It is concurrent with the growing popularity of minimally invasive surgery; and both are commonly used together. The different kinds of function-preserving gastrectomy included in this review are: pylorus-preserving and proximal gastrectomy, vagus nerve preservation, sentinel node navigation, and various endoscopic & minimally-invasive techniques. In this article the indications, techniques, oncologic safety, functional benefit, and outcomes of each kind of function-preserving gastrectomy are discussed.

Near-body Interaction Enhancement with Distance Perception Matching in Immersive Virtual Environment

  • Yang, Ungyeon;Kim, Nam-Gyu
    • Journal of Multimedia Information System
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    • v.8 no.2
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    • pp.111-120
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    • 2021
  • As recent virtual reality technologies provide a more natural three-dimensional interactive environment, users naturally learn to explore space and interact with synthetic objects. The virtual reality researcher develops a technique that realizes realistic sensory feedback to get appropriate feedback to sense input behavior. Although much recent virtual reality research works extensively consider the human factor, it is not easy to adapt to all new virtual environment contents. Among many human factors, distance perception has been treated as very important in virtual environment interaction accuracy. We study the experiential virtual environment with the feature of the virtual object connected with the real object. We divide the three-dimensional interaction, in which distance perception and behavior have a significant influence, into two types (whole-body movement and direct manipulation) and analyze the real and virtual visual distance perception heterogeneity phenomenon. Also, we propose a statistical correction method that can reduce a near-body movement and manipulation error when changing the interaction location and report the experiment results proving its effectiveness.

Frontal Face Generation Algorithm from Multi-view Images Based on Generative Adversarial Network

  • Heo, Young- Jin;Kim, Byung-Gyu;Roy, Partha Pratim
    • Journal of Multimedia Information System
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    • v.8 no.2
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    • pp.85-92
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    • 2021
  • In a face, there is much information of person's identity. Because of this property, various tasks such as expression recognition, identity recognition and deepfake have been actively conducted. Most of them use the exact frontal view of the given face. However, various directions of the face can be observed rather than the exact frontal image in real situation. The profile (side view) lacks information when comparing with the frontal view image. Therefore, if we can generate the frontal face from other directions, we can obtain more information on the given face. In this paper, we propose a combined style model based the conditional generative adversarial network (cGAN) for generating the frontal face from multi-view images that consist of characteristics that not only includes the style around the face (hair and beard) but also detailed areas (eye, nose, and mouth).

Linearized Transistor Model Based Automated Biasing Scheme for Analog Integrated Circuits

  • Lacek, Matthew;Nahra, Daniel;Roter, Ben;Lee, Kye-Shin
    • Journal of Multimedia Information System
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    • v.8 no.2
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    • pp.143-146
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    • 2021
  • This work presents an automated transistor biasing scheme for analog integrated circuits. In order to effectively bias the transistor at a desired operating point, the proposed method uses a linearized transistor circuit model along with the curve fitted expressions obtained from the pre-simulated I-V characteristics of the actual transistor. As a result, the transistor size that leads to the desired operating point can be easily determined without heavily relying on the circuit simulator, which will lead to significant design time reduction. Furthermore, the proposed method is applied to an actual amplifier circuit where the design time based on the proposed biasing method showed 10× faster than the conventional design approach using the circuit simulator.