This paper proposes an optimal tuning of Power System Stabilizer (PSS) using Artificial Immune System (AIS) algorithm for damping oscillation of multi-machine power system. PSS is the efficient devices to damp the power system oscillations which are caused by interruptions. This study presents a robust algorithm to determine the PSS parameters using AIS algorithm. The PSS parameters tuning is usually formulated as the objective function with constraints, including the damping ratio and damping factor. Optimization with maximum value of the damping factor and the damping ratio of power system modes are taken as the goals functions, when designing the PSS parameters. This optimization procedure could enhance the cloning process and lead to a better outcome. In this work, the two-area multi-machine power system of IEEE model, under a wide range of system configurations and operation conditions is investigated. The system has been used to illustrate the performance of the proposed algorithm. The performance of the AIS-based PSS is compared to the Delta w PSS and Delta Pa PSS. The results verify that, AIS-based PSS, Delta w PSS and Delta Pa PSS gives relatively good in reducing oscillation system variables of which transfer electrical power, changes in angular velocity generator, and the generator terminal voltage. All PSS can work well in order to stabilize the system under interruption. However, AISbased PSS have relatively better than Delta w PSS and Delta Pa PSS in terms of ability to reduce oscillation and speed of reaching a state of instability.

An optimal tuning of pss using ais algorithm for damping oscillation

Cigarette smoke is very dangerous for both active and passive smokers who smoke inside a room because nicotine from cigarette smoke can stick on the wall or in the furniture and produce carcinogenic substances when reacting with air. The carcinogen chemicals in cigarettes are more dangerous when cigarette smoke is trapped in a limited space. An exhaust fan is usually used in a special room for smokers that serves to remove cigarette smoke without exchanging air in it. A smart smoking room tool specifically for smokers was made to answer the problem. The room used an ‘in and out’ exhaust fan ventilator. This fan ventilator rotated based on the quantity of carbon monoxide (CO) gas in the room detected by using a smoke sensor. Arduino Uno based on Fuzzy Decision Tree algorithm was used to control of the input voltage level in the fan ventilator. The result showed that by using the tool, the cigarette smoke in the room can be controlled effectively.

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Smart Smoking Area based on Fuzzy Decision Tree Algorithm

Motorcycle accidents caused by sudden deceleration or exceed maximum safe speed of vehicles are still common. There is no tool that can provide alerts when the speed has exceeded the safe speed limit for vehicles allowed. Hence, the study aims to design and manufacture implementation of ATmega16 as an indicator of the maximum speed. Output data is obtained in the form of increasing speed. Maximum speed indicator system consists of atmega 16 as the main processing unit, sensor optocoupler, 4x4 keypad, buzzer and LCD LM162. It includes the output of the transducer which is processed by a microcontroller keypad which is then forwarded to the buzzer and LCD LMB162. Testing is conducted by direct tests on the vehicle running, and the obtained results show the maximum speed indicator device made to work properly and in accordance with the specifications of the predetermined design, so that it can give a warning when the safe speed is being and has been exceeded

Atmega 16 implementation as indicators of maximum speed

Pedestrians are one of the street users who have the right to get priority on security. Highway users such as vehicle drivers sometimes violate the traffic lights that is endanger pedestrians and make pedestrians feel insecure when crossing the street. Based on this problem, a tool is designed to provide a warning for the drivers or riders violating the traffic lights and prevent traffic accident by spraying water. The system is able to detect traffic violation based on changes in the value of the vehicle position on the stop line obtained from the Ultrasonic HC-SR04 sensor. When a violation is detected, a decision tree algorithm turns on the pump to spray water to the traffic violators as a deterrent effect. The results show that the vehicle located closest to the sensor has 94% precision, 88% recall and 85% accuracy, the vehicle located in the middle has 73% precision, 100% recall, and 75% accuracy, and the vehicle located furthest to the sensor has 75% precision, 100% recall and 80% accuracy.

/pdf/pedestrian-crossing-safety-system-at-traffic-lights-based-on-21k9gn9cf3.pdf

Pedestrian Crossing Safety System at Traffic Lights based on Decision Tree Algorithm

This article discusses devising an IoT system to monitor weather parameters and gas pollutants in the air along with a n HTML web-based application. Weather parameters measured include; speed and direction of the wind, rainfall, air temperature and humidity, barometric pressure, and UV index. On the other side, the gas es measured a re; ammonia, hydrogen, methane, ozone, carbon monoxide, and carbon dioxide. This article is introducing a technique to send all parameter data. All parameters read by each sensor are converted into a string then joined into a string dataset, where this dataset is sent to the server periodically. On the UI side, the dataset that has been downloaded from the server-parsed for processing and then displayed. This system uses Google Firebase as a real-time database server for sensor data. Also, using the GitHub platform as a web hosting. The web application uses the HTML programming platform. The results of this study indicate that the device operates successfully to provide information about the weather and gases condition as real-time data.

https://beei.org/index.php/EEI/article/download/3030/2211

Real-time monitoring system for weather and air pollutant measurement with HTML-based UI application

The crime level including motorcycle theft has been increasing. It occurs regardless the time and place. The owner of the motorcycle needs to ensure the security of his motorcycle by adding either manual or electronic lock. However, both the manual and electronic locks are still incapable to protect the motorcycle from the theft. Based on the problem, this research created an automatic motorcycle safety system, namely, germs narcissistic. Germs narcissist is the key innovation of automatic vehicle security using, GPS (global positioning system), and GSM (global system for mobile communication), and RFID (Radio Frequency Identification). This system was created by using short message service (SMS) to provide vehicle information such as time, position, and alarm informed to the owner of the motorcycle. The arrangement of the technologies can be used as a practical and effective safety key of motorcycle.

/pdf/microcontroller-based-rfid-gsm-and-gps-for-motorcycle-4nofom6b3y.pdf

Microcontroller-based rfid, gsm and gps for motorcycle security system

Skin cancer refers to a condition where there exists abnormal growth of skin cells, mostly occurs on skin exposed to the sun. There are several types of skin cancer, where the most common types include basal cell carcinoma, squamous cell carcinoma, and melanoma. Without proper treatment, skin cancer, particularly in the melanoma form, can lead to deaths. Fortunately, early detection and classification of skin cancer are highly effective in preventing serious damages from skin cancer. In this paper, we train Multi-layer Perceptron, a custom convolutional neural network, and VGG-16 for skin cancer classification on a large skin cancer dataset, HAM10000. The performance of each trained model is subsequently compared and analyzed in terms of classification accuracy and computational time. Our experimental setups reveal that the VGG-16 model can set the best classification accuracy among the compared networks while in terms of testing time, the VGG-16 and custom CNN models are being much faster than the Multi-layer Perceptron. The results of our study are beneficial in providing systematic comparison and analysis of several neural networks in skin cancer classification.

Performance of Multi Layer Perceptron and Deep Neural Networks in Skin Cancer Classification

Ceramic wall ornaments that are commonly used as interior building and encountered in hotels, restaurants, residential elite, museums and places of worship. Ceramic is a decoration signifying strong characters or special characteristics of the building. This character is usually in the form of ornaments that adorn the walls and are designed according to the history of the development of the times. The basic characteristic of Islamic Ornament generally shaped floral such as leaves, stems, buds, flowers, and palms. Wall tiles with special needs with unique ornaments and precision are very unlikely produced by some industrial ceramics in Indonesia at this time which still depends on hand made. This study has introduced a range of novel applications that combine digital manufacturing technology and conventional fabrication in the ceramic industry. The input image with the nuances of Islamic motifs with the format. JPG successfully raised to 2.5 D CAD models using ArtCAM software. To get the master pattern prints that precision, accurate and appropriate use of technology additive manufacturing with 3D Objet 30Pro. Conventional ceramics Manufacturing process technology at PT. Nuanza Porcelain Indonesia used to get ceramic products with Islamic nuances of Pattern puzzle flora. The integration of two technologies of CAD and RP this managed to get the design ceramic wall ornamental Islamic precision and detail with the dimensional error of less than 2.00 mm. Ceramic design results in accordance with Islamic ornamentation and was already installed in the mosque of Al Huda in 2018.

Puzzle Islamic Floral Patterns Product Tiles for Wall and Ceiling to Decorate of Al Huda Mosque Indonesia—Design, Manufacturing, and Fabrication

Development of waste-to-energy plant is regarded as one of a solution to reduce fossil energy dependency and switch to another alternative energy sources, thus needs to be implemented immediately. Research on the potential of organic waste by taking case studies at UMY green campus program can be an illustration that in the future UMY can process this potential into an alternative renewable energy. This research was conducted by studying waste management and data collection methods, such as field observations, discussions with related parties about the waste cycle, and calculations with the concept of gasification. Calculation of biomass produced by organic waste is then supplied to the motor generator for electricity production. Annually, 31.8 tons of organic waste could produce 7.9 kiloliters of biomass and channel it to the power plant system for generating electricity energy as much as 5.3 MWh per year. This number equals to the electricity supply of five small-housing in Indonesian typical house.

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Kunnu Purwanto

Papers

Microcontroller-based rfid, gsm and gps for motorcycle security system

Smart Smoking Area based on Fuzzy Decision Tree Algorithm

Performance of Multi Layer Perceptron and Deep Neural Networks in Skin Cancer Classification

Puzzle Islamic Floral Patterns Product Tiles for Wall and Ceiling to Decorate of Al Huda Mosque Indonesia—Design, Manufacturing, and Fabrication

Potentials of Organic Waste Conversion in a Green Campus Concept