2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA)最新文献_第4页

Mobile Application for Halal Food Ingredients Identification using Optical Character Recognition 使用光学字符识别的清真食品成分识别移动应用程序

2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) Pub Date : 2018-11-01 DOI: 10.1109/ICSIMA.2018.8688756

M. Kartiwi, T. Gunawan, Aqmarina Anwar, Siti Sarah Fathurohmah

引用次数: 3

Precision Crop Management for Indoor Farming 室内农业作物精准管理

2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) Pub Date : 2018-11-01 DOI: 10.1109/ICSIMA.2018.8688791

F. N. Sabri, N. Hanif, Z. Janin

引用次数: 3

Development of Prismatic robotic arms for rehabilitation by using Electromygram(EMG) 基于肌电图的棱镜式康复机械臂的研制

2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) Pub Date : 2018-11-01 DOI: 10.1109/ICSIMA.2018.8688770

A. M. Ali, K. Kadir, M. Billah, Zulkhairi Yosuf, Z. Janin

引用次数: 1

Investigation on the Effect of Beating on the Physical and Mechanical Properties of Untreated Kenaf Based Insulation Paper 打温对原生红麻基绝缘纸物理力学性能影响的研究

2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) Pub Date : 2018-11-01 DOI: 10.1109/ICSIMA.2018.8688758

Muhammad Umair, N. Azis, R. Halis, J. Jasni

引用次数: 3

Mobile Applications for Teaching and Learning Arabic Braille 移动应用程序的教学和学习阿拉伯语盲文

2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) Pub Date : 2018-11-01 DOI: 10.1109/ICSIMA.2018.8688763

Nik Mohd Rahimi, Noor Hazrin Hany Mohamad Hanif, Z. Janin

{"title":"Mobile Applications for Teaching and Learning Arabic Braille","authors":"Nik Mohd Rahimi, Noor Hazrin Hany Mohamad Hanif, Z. Janin","doi":"10.1109/ICSIMA.2018.8688763","DOIUrl":"https://doi.org/10.1109/ICSIMA.2018.8688763","url":null,"abstract":"Nowadays, the literacy rate of the visually impaired people is decreasing and has become a big concern because reading is the main source of information. However, lack of skilled teachers is the main issue that restricts the learning of braille code for blind people. Most of the braille modules available in the market today are only catered for languages that utilize roman alphabets. This made it impossible for users to learn braille in languages with different alphabets or characters. The aim of this Arabic Braille Module is to help the visually impaired people to learn on reading and writing Arabic characters in braille code. It is also to facilitate the teachers in demonstrating the braille code in teaching process. A portable Arabic braille module is to be designed using miniature solenoids with Arduino Uno as microcontroller. In this work, simulation and experiments have been conducted to study the capability of the module to generate output according to specific input provided from teaching panel designed in mobile applications. At this current stage, the output of the system is a 3-by-2 array of LEDs to represent the raising dots of the braille codes. Hopefully with the invention of this Arabic Braille Module will encourage the visually impaired people to learn Arabic and eventually reading Quran in braille.","PeriodicalId":222751,"journal":{"name":"2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123606786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Analysis of Resistive Type Pressure Sensors for Static Calibration 电阻式压力传感器静态校准分析

2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) Pub Date : 2018-11-01 DOI: 10.1109/ICSIMA.2018.8688761

Dayang Nurul Nahar, S. Shafie, A. Mardhiyah, M. Hamidon, F. Ahmad

引用次数: 0

The effect of different light treatments on nutrient concentration and leaf exchange in Brassica Chinensis 不同光照处理对芸苔养分浓度和叶片交换的影响

2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) Pub Date : 2018-11-01 DOI: 10.1109/ICSIMA.2018.8688795

A. N. Harun, R. Ahmad, N. Mohamed, Abdul Rahman Abdul Rahim, Sheroz Khan

{"title":"The effect of different light treatments on nutrient concentration and leaf exchange in Brassica Chinensis","authors":"A. N. Harun, R. Ahmad, N. Mohamed, Abdul Rahman Abdul Rahim, Sheroz Khan","doi":"10.1109/ICSIMA.2018.8688795","DOIUrl":"https://doi.org/10.1109/ICSIMA.2018.8688795","url":null,"abstract":"The effect of different LED light treatments on nutrient concentration and leaf gas exchange in Brassica chinensis was performed in this study utilizing Internet of Things (IoT) technology as remote monitoring system. Brassica chinensis were grown under four different light treatments and have been used as light source. The experiments were conducted namely T1 (continues light; 24 h lights), T2 (pulse lights: 1 h lights 15 minutes darks), T3(various light intensities) and T4 (continues lights + Far red). The observation of nutrient concentration and activity leaf gas exchange plants were analyzed. An intelligent system using embedded system has been developed to automate the LED control and manipulation. The system is able to analze on data and monitor the environmental parameters of the plant factory on line via internet. The result shows that the system is stable and has a significant referential in the area of plant factory or indoor farming system. Based on the overall result, Continues Light (CL) gave a high impact towards Brassica chinensis growth. Therefore, combination CL and Far red also enhanced the plant nutrient concentration and the activity of leaf gas exchange.","PeriodicalId":222751,"journal":{"name":"2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA)","volume":"1 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128781392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Food Intake Calorie Prediction using Generalized Regression Neural Network 基于广义回归神经网络的食物摄入热量预测

2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) Pub Date : 2018-11-01 DOI: 10.1109/ICSIMA.2018.8688787

First Teddy Surya Gunawan, M. Kartiwi, N. A. Malik, N. Ismail

{"title":"Food Intake Calorie Prediction using Generalized Regression Neural Network","authors":"First Teddy Surya Gunawan, M. Kartiwi, N. A. Malik, N. Ismail","doi":"10.1109/ICSIMA.2018.8688787","DOIUrl":"https://doi.org/10.1109/ICSIMA.2018.8688787","url":null,"abstract":"Many devices have been proposed to monitor the calorie intake and eating behaviors. These wearable devices uses various sensing modalities, such as acoustic, visual, inertial, EEG (electroglottography), EMG (electromyography), capacitive and piezoelectric sensors. In this paper, Generalized Regression Neural Network (GRNN) will be utilized to predict the food intake calorie from the input of digital image. GRNN was utilized due its fast training compared to standard feedforward networks. The food image database comprises of 568 food including sweet, savory, processed, whole foods, and beverages. The calorie has the ranged from 0 kcal (plain water) to 11830 (roasted goose) with median 235.5 kcal. The optimum spread parameter for GRNN was found to be 0.46 when the 568 images was distributed randomly, i.e. 80% training and 20% testing. Due to very large variation of the calorie needs to be predicted, GRNN has rather large prediction error. This could be alleviated using more training data, use other features like texture and segmentation, or deep neural network.","PeriodicalId":222751,"journal":{"name":"2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127942200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

2019 IEEE International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) 2019 IEEE智能仪器、测量与应用国际会议(ICSIMA)

2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) Pub Date : 2018-11-01 DOI: 10.1109/icsima.2018.8688743

引用次数: 2

Fault Type Identification Method based on Wavelet Detail Coefficients of Modal Current Components 基于模态电流分量小波细节系数的故障类型识别方法

2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA) Pub Date : 2018-11-01 DOI: 10.1109/ICSIMA.2018.8688796

S. Myint, W. Wichakool

引用次数: 3