EMITTER - International Journal of Engineering Technology
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Sustainable and Resilient Smart Water Grids: A Solution for Developing Countries
Full text linkAccording to a United Nations report, the world population will increase from 7 billion to 9 billion by 2050. Further, the water stress level is more than 70% in 22 countries while in another 31 countries it is between 25% and 70%. More than 2 billion people live in these 53 countries which are all underdeveloped. Water use has increased by 1% per year since the 1980s, so global demand is expected to rise by 30% by 2050. Thus, efficient water grid management is imperative to ensure there is sufficient water for the future. Information and Communication Technology (ICT) can be used to create smart water grids to optimize water distribution, reduce waste and leakage, and resolve quality and overuse issues. In this work, a low cost, real-time, reliable and sustainable IoT based solution called SmartTubewell is proposed for smart water grid management. It is composed of two components, a sensor node installed at tube wells and an application layer on Amazon Web Services (AWS) for data analysis, storage and processing. The sensor node is based on a Raspberry Pi with integrated current and voltage sensors and a local database. The sensor data is transmitted to AWS using a cellular (GPRS) network. A comparison between the proposed system and SCADA is presented which shows that SmartTubewell has a much lower cost. A field test with multiple tube wells in Peshawar, Pakistan indicates that this is a suitable solution for developing countries
Hospital Length of Stay Prediction based on Patient Examination Using General features
Full text linkAs of the year 2020, Indonesia has the fourth most populous country in the world. With Indonesia’s population expected to continuously grow, the increase in provision of healthcare needs to match its steady population growth. Hospitals are central in providing healthcare to the general masses, especially for patients requiring medical attention for an extended period of time. Length of Stay (LOS), or inpatient treatment, covers various treatments that are offered by hospitals, such as medical examination, diagnosis, treatment, and rehabilitation. Generally, hospitals determine the LOS by calculating the difference between the number of admissions and the number of discharges. However, this procedure is shown to be unproductive for some hospitals. A cost-effective way to improve the productivity of hospital is to utilize Information Technology (IT). In this paper, we create a system for predicting LOS using Neural Network (NN) using a sample of 3055 subjects, consisting of 30 input attributes and 1 output attribute. The NN default parameter experiment and parameter optimization with grid search as well as random search were carried out. Our results show that parameter optimization using the grid search technique give the highest performance results with an accuracy of 94.7403% on parameters with a value of Epoch 50, hidden unit 52, batch size 4000, Adam optimizer, and linear activation. Our designated system can be utilised by hospitals in improving their effectiveness and efficiency, owing to better prediction of LOS and better visualization of LOS done by web visualization
Indian Sign Language Recognition through Hybrid ConvNet-LSTM Networks
Full text linkDynamic hand gesture recognition is a challenging task of Human-Computer Interaction (HCI) and Computer Vision. The potential application areas of gesture recognition include sign language translation, video gaming, video surveillance, robotics, and gesture-controlled home appliances. In the proposed research, gesture recognition is applied to recognize sign language words from real-time videos. Classifying the actions from video sequences requires both spatial and temporal features. The proposed system handles the former by the Convolutional Neural Network (CNN), which is the core of several computer vision solutions and the latter by the Recurrent Neural Network (RNN), which is more efficient in handling the sequences of movements. Thus, the real-time Indian sign language (ISL) recognition system is developed using the hybrid CNN-RNN architecture. The system is trained with the proposed CasTalk-ISL dataset. The ultimate purpose of the presented research is to deploy a real-time sign language translator to break the hurdles present in the communication between hearing-impaired people and normal people. The developed system achieves 95.99% top-1 accuracy and 99.46% top-3 accuracy on the test dataset. The obtained results outperform the existing approaches using various deep models on different datasets
Develop a User Behavior Analysis Tool in ETHOL Learning Management System
Full text linkStudents have different learning styles when studying online. Meanwhile, lecturers use the same method for all students who take their online lectures. These different learning styles can affect the level of understanding and the results obtained by students. By knowing student learning styles, lecturers are expected to be able to use the right way in delivering material. In this research, we developed a student behavior analysis feature on self-developed Virtual Learning Environment (VLE) called Enterprise Hybrid Online Learning (ETHOL). Students’ data collected includes data on online activities, personal data, and survey data on student learning styles. User behavior analysis was carried out by dividing into three clusters: average scores, time to collect assignments, and student learning styles. The clustering method used is the Hierarchical K-Means. The results obtained are students who have the habit of collecting assignments on time have higher scores than others. In addition, the lecturer is able to see the results of the analysis of the behavior and learning styles of each student. These results can be used as information in delivering lecture material
Scouting Interactive Games for Scouts Based on Embodied Interaction Using Embedded System
Full text linkScouts is the scouting level after the cub scout aged 11-15 years old. In their age range, they can use logical thinking in the form of physical objects to solve a problem. The development of the Scout Movement has had ups and downs, and recently the number of children interest in scouting activities decreases. The impact is the scouting insight they get isn't optimal. One strategy to solve this problem is by developed forms, tools, and learning media of scouting. Game is one of the learning media that can be used to create effective learning. The educational game is a popular learning media and widely developed by experts, as well as in Indonesia. Unfortunately, in the field of scouting, educational games are less developed. In this research, the author will build an educational scouting game for scouts. In the scouts level, they began to be introduced about communication code, skills, natural recognition, and others. Games created using Embodied Interaction technology. This technology allows users to control the game using body movement. The purpose of this game is to increase the interest and insight of children on Scout activities. From the results of research that has been done, it can be seen that after playing the game, 95,7% of children thought it is exciting, and 87% of them became enthusiastic join scouting activity. Based on the results of the pre-test and post-test, scouting insight increased after playing the game with an average percentage of increased insight being 18.7%
The Development of A Reliability Evaluation Application for Power Plant Steam Turbine Vibrations to Predict Its Failure
Full text linkA steam turbine is the most critical component in a thermal power plant. Due to its crucial function, it should be maintained to be able to operate without failure. This paper aims to develop an application that can be used to analyze the reliability and synchronization of vibrations in a single evaluation through the application. The application is helpful to decide the proper time the maintenance should be performed in order to provide a better maintenance strategy. In this paper, the application was used to make an ease in evaluating the reliability and vibration of a 670 MW power plant steam turbine. The reliability was analyzed by qualitative and quantitative methods. The vibration evaluation using Fast Fourier Transform (FFT) was done by diagnosing the failure symptoms from vibration spectrum. The analysis of synchronization of vibrations conducted by comparing the vibration frequency and the natural frequency of the system which can be calculated easily using the application. The algorithm program of both evaluations was built using GNU Octave software to make a friendly user interface. From the evaluation result, the most critical components of the steam turbine are coupling, labyrinth seals, bearing, diaphragm, turbine control valve, and turbine stop valve. The maintenance interval based on the expected reliability of 90% produces the highest reliability improvement. Based on the vibration analysis, there is no failure symptoms detected in the turbine bearings. Furthermore, the dominant frequencies of vibration are distant from the natural frequency. Therefore, the steam turbine condition is acceptable to operate
Review on Multi Level Inverter Topologies and Control Strategies for Solar Power Conversion
Full text linkNowadays solar power has become an alternate method of power generation for standalone systems for both urban and rural electrification. The Power Electronics converters used for the power conversion should provide quality AC output to have near sinusoidal voltage. The inverter topology and the PWM technique of the inverter play a vital role in providing quality output. This paper reviews recent contribution to establish the current status and development of the technology to provide reader with an insightful review of multilevel inverters and its control strategy. A brief overview of Multi Level Inverters (MLI) topology and advantages of Cascaded H-Bridge Multi Level Inverter (CHBMLI) for solar power conversion is presented and the various control strategies for CHBMLI are discussed with view point of quality output. Among the different PWM techniques discussed, the Elliptical Multi Carrier PWM (EMC PWM) control strategy is the new modulation technique which successfully improves the DC bus utilization without over-modulation and without adding third harmonic to fundamental frequency. Also, the technique is successful in reducing the %THD at the output voltage. The control strategy is simple even with increased level of output voltage, which is not possible in SVPWM technique. Hence, the EMC PWM technique is having better performance when compared to Multi Carrier PWM (MCPWM) technique, Space Vector PWM (SVPWM) technique and Third Harmonic Injection PWM (THIPWM) technique. 
An Improved Crow Search Algorithm for Data Clustering
Full text linkMetaheuristic algorithms are often trapped in local optimum solutions when searching for solutions. This problem often occurs in optimization cases involving high dimensions such as data clustering. Imbalance of the exploration and exploitation process is the cause of this condition because search agents are not able to reach the best solution in the search space. In this study, the problem is overcome by modifying the solution update mechanism so that a search agent not only follows another randomly chosen search agent, but also has the opportunity to follow the best search agent. In addition, the balance of exploration and exploitation is also enhanced by the mechanism of updating the awareness probability of each search agent in accordance with their respective abilities in searching for solutions. The improve mechanism makes the proposed algorithm obtain pretty good solutions with smaller computational time compared to Genetic Algorithm and Particle Swarm Optimization. In large datasets, it is proven that the proposed algorithm is able to provide the best solution among the other algorithms
Energy Efficiency Optimization for Intermediate Node Selection Using MhSA-LEACH: Multi-hop Simulated Annealing in Wireless Sensor Network
Full text linkEnergy usage on nodes is still a hot topic among researchers on wireless sensor networks. This is due to the increasing technological development increasing information requirements and caused the occurrence of information exchange continuously without stopping and impact the decline of lifetime nodes. It takes more effort to manually change the energy source on nodes in the wireless sensor network. The solution to such problems is to use routing protocols such as Low Energy Adaptive Clustering Hierarchy (LEACH). The LEACH protocol works by grouping nodes and selecting the Cluster Head (CH) in charge of delivering data to the Base Station (BS). One of the disadvantage LEACH protocols, when nodes are far from the CH, will require a lot of energy for sending data to CH. One way to reduce the energy consumption of each node-far is to use multi-hop communication. In this research, we propose a multi-hop simulated annealing (MhSA-LEACH) with an algorithm developed from the LEACH protocol based on intra-cluster multi-hop communication. The selection of intermediate nodes in multi-hop protocol is done using Simulated Annealing (SA) algorithm on Traveling Salesman Problem (TSP). Therefore, the multi-hop nodes are selected based on the shortest distance and can only be skipped once by utilizing the probability theory, resulting in a more optimal node path. The proposed algorithm has been compared to the conventional LEACH protocol and the Multi-Hop Advance Heterogeneity-aware Energy Efficient (MAHEE) clustering algorithm using OMNeT++. The test results show the optimization of MhSA-LEACH on the number of packets received by BS or CH and the number of dead or alive nodes from LEACH and MAHEE protocols
Fire Image Set for Evoking Panic
Full text linkFire is the closest disaster to us, a person who put cigarettes around flammable objects could burn one to dozens of houses. The last thing that happens was a mass panic. In this kind of situation, panic is one of the keys to determine how much probability someone will survive. However, detecting someone's panic during a fire is impossible. This leads some scientists to assume that mass panic was never happening and some studies use simple functions to determine someone when panic. Currently, thanks to technological advances we can easily build virtual worlds that resemble real events. To build a virtual world that could evoke panic we still need the right stimulus. In this paper, we will discuss with terms of fire disaster stimulus that possible to impel someone to feel panic. While some stimulus datasets that already exist have more broad categories, we wanted to focus on a specific problem. The determined parameters are considered through several elements that could cause a person to panic, either before or during a fire. By using the Self-Assessment Manikin system to obtain valance and arousal matrix, we conduct a test to see how much influence the fire categories stimulus provided