Prof. Dr. Christopher Abraham has three Post Graduate qualifications in HRM, Business Administration (Marketing), Labor & Administrative Law and is a PhD in Business Administration (Design Thinking & Innovation). He is a Certified Design Thinker from IDEO/Stanford and is a Fellow of the Chartered Institute of Marketing (FCIM), UK. He has thirty-four years’ experience in management consulting, marketing, and management education in India, Singapore and the UAE.
Currently he is the CEO & Head – Dubai campus and Sr. Vice President (Institutional Development) at the S P Jain School of Global Management, a Forbes Top 10, Economist & FT Top 100 ranked Business School, with campuses in Dubai, Singapore, Mumbai and Sydney. He has been a visiting Professor at many leading universities in Australia, USA, Canada, Singapore and UK. Earlier in Dubai, he headed the Executive MBA Program of XLRI, Jamshedpur, one of Asia’s top business schools.
His areas of competence are Innovation, Design Thinking, Behavioural Design, Neuroscience of Decision Making, Future of Education, Science of Happiness, Leadership, Marketing & Strategy.
A much sought after 3 x TEDx and international keynote speaker, he has successfully presented in numerous global forums and has also conducted many consulting and executive development assignments for global organizations, including The World Bank, The Executive Council (Govt. of Dubai), Emirates Airlines, SEWA (Government of Sharjah), Aramex, DHL, P & G, LG, AW Rostamani (Nissan Auto) etc.
Dr. Deni is a Senior Research Scientist Research Center for Advanced Materials, National Research and Innovation Agency (BRIN), Indonesia. He has also been a faculty member at the Department of Mechanical Engineering, Universitas Mercu Buana, since 2017 to present. He received his Dr. Eng. in Energy Conversion Engineering, specifically on solid oxide fuel cells, from Hirosaki University, Japan in 2016. He received various awards including the 2015 doctorate student research excellence award from the President of Hirosaki University. Dr. Deni has 14 patents, 1 licensed (commercialized) patent, 1 trademark, 1 industrial design, and has published over 70 scientific papers with an h-index of 11 with more than 300 citations.
Professor Dr. Anwar Ahmad is an Environmental Engineer and currently Professor in the College of Engineering and Architecture and Deptt. Of Civil Engineering, University of Nizwa, Sultanate of Oman. Before, he was appointed as a Professor, in King Saud University 2012-2018. Also worked in University Malaysian Pahang (Faculty of Engineering and Earth Resources) in 2009- November 2011; Jamia Millia Islamia University 2000-2007. More than 100 research paper published in high impact journal and conferences, NATURE Index J. published, 15 patents (Two US Patents), five gold medal, three silver and two bronze, 67 national and international conferences attended, edited proceedings and Documented Research reports More than 47 Ph.D and Master students completed degree under his supervision. He completed more than 35 projects national international levels and actively involved in many collaborations with industries, universities and academicians. He is organized a number of training program and symposia for the benefits of practicing engineer and professionals. Current research areas: Wastewater electrolysis for bioenergy, electricity, hydrogen and sustainable energy production, established industrial high demand research center (national innovation center, sustainable design and design renewable sources energy), Industrial ecology and sustainability approach for energy and materials decarbonation flow production and environment, Assessment carbon sustainable development
Abdy is the Founder and President of MonsoonSIM, a Business Simulation and Experiential Learning platform currently used by over 200 academia for over 90000 learners globally. Abdy believes in advancing education through technology. He is passionate about creating a level playing field for all education institutions through innovative transformations. He and his team have come up with a unique "horizontal experiential learning model" (click https://www.youtube.com/watch?v=c9DgEUgK99M to learn more) that is now implemented fully in MonsoonSIM. Abdy is a frequently invited speaker in various international conferences on Business Simulation and Experiential Learning. Countries include USA, Australia, UK, Canada, India, Estonia, Ukraine and China. Abdy is an entrepreneur with 30 years of enterprise software development experience. Throughout his career, Abdy had worked for global software vendors SAP, IFS and Unisys holding various executive positions in Los Angeles, Jakarta, Hong Kong, Shanghai and Singapore. Abdy graduated from the University of Southern California with a Masters in Computer Engineering
The article focused on the influence of part orientation on the surface roughness of cuboid parts during the process of fabricating by SLM technology. The components, in this case, is simple cuboid part with the dimensions 15 mm x 15mm x 30 mm. SLM or Selective Laser Melting is Additive manufacturing technology based on the Powder Bed Fusion process. SLM is designed to use high power-density laser to melt and fuse metallic powder. A part is built by selectively melting and fusing regions of metallic powders within and between layers. For the research purposes, five different orientations in the X-axis of the cuboid part were set: 0°, 30°, 45°, 60°, and 90°. The internal structure was set at a value of 100%. In this research, we manufactured five specimens for scanning speed 650 mm.min-1 and five specimens for scanning speed 1000 mm.min-1. In the research metallic powders were used, namely austenitic stainless steel SS 316L. In this experiment, we manufactured a total of 10 specimens. Surface parameters (Ra, Rz, Rq) were measured five-time in a row for each print. Prints were carried out on an SLM machine from Renishaw with the designation AM400. After the 3D printing, the surface “A” was investigated by portable surface roughness tester Mitutoyo SJ-210. Surface roughness in the article is shown in the form of graphs. Results show an increase in part roughness with an increasing degree of part orientation. When the direction of applied layers on the measured surface was horizontal, a significant improvement in surface roughness was observed. Findings in this paper can be taken into consideration when designing parts, as they can contribute to achieving lower surface roughness values.
This term project aims to simulate a wide bandpass filter that is composed of first-order and second-order high pass filters that are cascaded in series. The filters are composed of 3-terminal op-amps, 1V AC source with 1kHz frequency, 1uF capacitors, and 1k-ohm resistors. To determine the phase shift and frequency response, the filters are simulated in Multisim Live using AC sweep analysis. On the other hand, to acquire the step response and root locus plot of the circuits, they are treated as control systems and their transfer function formulas were simulated using MATLAB. At the end of the study, the researchers were able to confirm the different properties and parameters these filters have.
Inefficiency and environmental hostility are major concerns in cosmetics small and medium industries (SMIs). Sustainability has become a goal desired by cosmetic customers. This study aims to encourage the development of sustainable cosmetics SMIs by integrating lean and green principles into production practice. This research combines the lean and green methods and tools suitable for SMIs, namely, green value stream mapping and life cycle impact assessment to evaluate manufacturing waste and environmental impact. We conducted kaizen events to improve existing processes. A case study of a liquid face soap manufacturing company was analyzed. The proposed ideas improved their manufacturing cycle effectiveness (MCE) by 1.8%, shortened inventory lead time by 36%, and reduced environmental impact by 33%. The company also achieved monthly electricity cost reductions of 41%. Despite an insignificant rise in the MCE, this study highlights the scope for using lean and green principles for social-environmental improvement, particularly in reducing damage to human health. Various other industries can emulate these methods.
This research discusses about the system improvement using Business Process Reengineering (BPR) framework integrated with Enterprise Resource Planning. The object of this study is the business process of cosmetics and household goods sub-sector company. This study carries the problem of supplier lead time when shipping raw materials supply which results delays in production. Furthermore, the Business Process Reengineering method used for this study aimed to reduce the sub-process time with support of IDEF0. Process mapping was carried out by doing interviews and Focus Group Discussions (FGD) with three experts. This study results the process of As-Is and To-Be that reduced the business process time up to 36%. By the improvement of time efficiency, the cosmetics and household goods sub-sector company experiences rapid changes in working hours. In addition, with the ERP implementation of Snell X's, it helped the workers to carry out their job only by one integrated business management application
Coal drying process using FBD (fluidized bed dryer) which utilizes low temperature waste heat, especially from industrial air heaters, has been developed in the United States by the GRE (Great River Energy) team since 1997. Technology is still considered an expensive investment. This study uses a prototype FBD with a drying heat source is an air heater that simulates the amount of water content that can be removed in low-calorie coal for boiler use. Furthermore, it can be considered the use of waste heat recovery from machines in the industry as a substitute for the energy source of the dryer by the air heater. The water content or Total Moisture Content that can be removed by using FBD with an air heater dryer energy source is 20%. The savings due to TM which has decreased by 20% in the industrial scale of the power plant can be calculated as 650,289 EUR/Year. The savings will be even greater, if the energy of the air heater dryer is replaced with waste heat recovery from industrial machines such as air heaters or boilers
The study aimed to investigate the impacts of internal and external factors on developing global digital innovation by means of a case study of the Provincial Electricity Authority (PEA) in Thailand. The research framework was based on the concepts of disruptive leadership, Thailand 4.0, Industry 4.0, PEA Digital Utility or Electric Utility of the Future, ICT/Digital Innovation, and Sufficiency Economy Principles (SEP). The research sample group comprised 419 PEA employees randomly selected from throughout the country. The research tools consisted of structured questionnaires on content and technical quality validated by five qualified experts. Assumptions of multiple regression analysis- normality, linearity, no multicollinearity, independence, and homoscedasticity were examined. The data verifying the assumptions were analyzed by multiple regression and PEA Digital Utility, Industry 4.0, ICT/Digital Innovation, Disruptive Leadership, and Thailand 4.0 were estimated for the development of global digital innovation. It was also found that most PEA employees, or 51.55 percent, refer to the innovation they know of as PEA Smart Plus. This is because PEA will focus on the use of communication technology to improve efficiency in the distribution system which is the foundation for further development of other parts of the system. Furthermore, most PEA employees identified innovation as being environmentally friendly.
The success rate of implementation and development of IT Infrastructure technology on the pharmaceutical industry in Indonesia is greatly influenced by project management readiness. One aspect that receives little attention in project implementation is information security control. This aspect is a critical point that the instance must manage to maintain information security from the confidentiality (C), integrity (I), and availability (A) sides. The data from the pharmaceutical IT security team in 2021 also shows that there have been incidents caused by internal and external threats of 2928 every month and have a close correlation with the IT Infrastructure project. So that in this study a plan and governance of the application of information security controls to IT Infrastructure management projects using the ISO 27001: 2013 approach will be carried out. The application of these security controls is expected to reduce incidents and can be a recommendation to address vulnerabilities to security threats that could affect future business processes
As a successor to the present 4G technology, 5G is a modern technology with a new interface that is being developed. The main purpose of 5G is to deliver a diversified collection of services to clients worldwide, including fast data speeds, wider coverage, low latency, cheap cost, high system capacity, and a variety of connectivity alternatives. Every major carrier intends to build both millimetre wave and sub-6 5G networks, but they choose to start with the lowest frequency bands and work their way up the frequency spectrum. The sub-6 spectrums are a better option for 5G. The recent deployments of the 5G networks are focused on the sub-6GHz spectrums. However, there are limited works reported on the 5G in sub-6GHz and this has motivated us to evaluate the performance of the 5G network in sub-6GHz spectrums. This project evaluates the performance of a 5G sub-6GHz network and the performance of the 5G is compared with the 4G Long-Term Evolution (LTE) network. The Vienna 5G System Level Simulator is a numerical model of wireless communication networks that is used to develop and improve mobile communication standards. It allows the community to do repeatable simulations of crucial scenarios in preparation for 5G and beyond. The performance of the 5G sub-6GHz throughputs is evaluated using the Vienna 5G Simulator. Extensive simulation works that considered a variety of factors, i.e., bandwidths, the number of users, users speed, and carrier frequencies were carried out to evaluate the performance of the 5G sub-6GHz network. The numerical findings indicate that 5G sub-6GHz performance is always better than LTE performance under identical simulation circumstances, demonstrating that 5G always outperforms LTE. The average cell throughput of the 5G sub-6GHz is 8 times more than the 4G network. The average peak throughput dropped when the mobility speed of the users increased. The throughput of the 5G network is directly proportional to the frequency bandwidth allocated.
The increase in the population of senior citizens created a new challenge of the shortage of healthcare workers to take care of the elderly. The elderly with multiple chronic conditions face problems in managing their daily medication intake. This has inspired us to design a low-cost Smart Internet of Things (IoT) Mobile Medication Dispenser (SMMD) to take care of the daily medication intake of the elderly. SMMD consists of hardware (medication dispenser) and software (an app for the user to control the SMMD and program the time to dispense the medication). The NodeMCU is used to control the stepper motor, organic light-emitting diode (OLED), and motor driver. The OLED displays the current time and the time set by the caregiver/elderly to take the medicine. The SMMD with three wheels enables it to move and dispense medication to the elderly. The NodeMCU is connected to the Firebase database to access the time required to dispense the medicine. The total cost of SMMD is USD50 and is affordable for the elderly from the lower-income group and making the process of taking medicine not a hassle for the elderly. The price of SMMD can be much lower when it is mass-produced
Artificial intelligence (AI) has come a long way in the last several years, both in hardware implementation and software algorithms and applications. This paper examines recent advances in artificial intelligence applications in biomedicine, such as living aid, illness diagnosis, biomedical research, and biomedical information processing. It also reviews deep learning as a technique in Artificial intelligence in healthcare and compares it to traditional methods. This review will better comprehend technology availability, keep the pace of new scientific developments, appreciate the enormous potential of artificial intelligence in biomedicine, and inspire researchers working in related domains. It is fair to say that the use of AI in biomedicine is in its early stages, like artificial intelligence itself. Artificial intelligence will continue to push the boundaries and broaden the scope of its applications as new improvements and discoveries are made, and substantial advancements are projected shortly.
This paper presents an Internet of Things (IoT) smart environmental monitoring for oyster mushroom production which is based on Arduino microcontroller. These IoT sensors measures various changes like the humidity and temperature and sent to the Arduino microcontroller for configuring the control algorithm. Oyster mushrooms (Pleurotus ostreatus) can be produced from a wide array of agricultural waste material, which makes them the easiest mushrooms grown. It can grow at moderate temperature ranging from 20 to 300 C and humidity 55-70% for a period of 6 to 8 months in a year. The misting system can automatically control the water pumping system on the misting site based on the moisture content of the soil media acquired from the moisture content sensor. Misting is the best and widely used to get good propagation, a balance in humidity and transpiration is needed to allow water and nutrient uptake without excess dehydration especially in mushroom culture. If the growing medium is also saturated with water, there is a potential for the growth of bacteria.
One of the surface hardening processes is chill casting. Chill casting is used for surface hardening of nodular cast iron materials. The problem that often occurs in the chill casting method is porosity which is influenced by the fast cooling rate between the casting object and the mold wall. This study aims to analyze the microstructure, hardness, and porosity that will form on the surface of the Y-shaped specimen after chilled casting. The material used for casting the Y-Shape specimen is nodular cast iron and the chill material is stainless steel plate. The chill is varied with a thickness of 0.2mm and 0.4mm and will be coated on the surface of the sand mold wall then the chill is preheated at a temperature of 700oC and 900oC, then pouring is done at a temperature of 1400oC. The average hardness value on the surface of the specimen is 500HV-900HV, but in the middle area the hardness only reaches 200HV while the microstructure results in the surface layer are cementite and ledeburite phases, but in the middle area ferrite, and perlite are seen surrounding the nodule graphite structure. In the chill-coated area, although the hardness is high, there are micro-porosities and macro-porosities formed randomly.
There are so many ways to detect vehicles’ speed these days, which can be categorized into two different approaches: a non-computer-vision based and a computer-vision based. In this paper, we propose a computer-vision-based approach using YOLOv4 and XGBoost Regression. To predict vehicles’ speed efficiently, we use YOLOv4 for vehicle detection and XGBoost regression for speed prediction. In order to get the best speed prediction, we build our dataset by recording the local traffic and measuring their speed using a speed gun. From those traffic videos, we detect vehicles by using YOLOv4 to generate its bounding boxes. From the bounding boxes, we can extract its coordinates relative to the screen and its time to get from point A to point B. This information will be our input, and the speed from the speed gun will serve as the target to train our XGBoost regression model. In this paper, we conduct several experiments using various inputs and parameters to get the best model. Our experiments conclude that our speed prediction approach using YOLOv4 and XGBoost regression has a very high performance regarding to the ground truth with an MAE of just 2 km/h.
One of the major issues during the regression test of the new version of Real Time Operating System (RTOS) is the time involved in test case execution. The main reason being a single embedded system device under test (DUT) is used to execute the test list containing several test cases. This traditional method of regression test also leads to wasted productivity of the other devices at hand that could be otherwise used during this regression test. Hence, in this paper, we propose a technique that aims at reducing the overall regression test cycle time of a newer version of a Real Time Operating System (RTOS) by employing a method known as “test-list sharding” in a distributed test environment. In the proposed work, multiple DUTs are connected to the test server via a communication network. The test server executes the test list containing several test cases and performs the test-list sharding, that is, distributing test cases to different DUTs and executing them in parallel. After the test is executed on the DUT, the test results are sent back to the test server which will summarize all the results. In the proposed work, the sharding is done by distributing the test cases without overloading or under loading any of the DUTs. Test list is sharded in such a way that the same tests are not sent to multiple DUTs. The main advantage of the proposed method is that the test sharding can be easily scalable to accommodate any number of devices that can be connected to the test server. Also, the test list sharding is done in a dynamic way so that the tests are distributed to an idle DUT that has completed a test execution and ready for another test to execute. The comparison study of executing a sample test list sequentially on a single DUT and distributed test system with multiple DUTs is performed. Results obtained showed the performance gain in terms of test cycle time reduction, scalability, equal load distribution and effective resource utilization.
Water pollution is a significant problem in the Philippines, and rivers are one of the bodies of water that are affected by this pollution. Accumulation of solid waste from rivers that hinder the quality and life below water is one reason for this pollution. According to the Comprehensive Land Use Plan of the Municipality of Odiongan, rivers and creeks are used as solid and liquid dumping sites, resulting in pollution. This project aims to design floating trash traps installed in the municipality's three (3) rivers. These plastic-made traps are strategically placed near downstream rivers to stop solid waste from floating further downstream without hampering aquatic life movements and are installed in a parabolic path to maximize their collection capacity. The materials used in the proposed design consist of plastic bottles, poultry net, and nylon. Fieldwork was done at the rivers and characterized the collected wastes by their wet weight. The floating trash traps generated a total of 260.56 kilograms. A total of 74% (193.08 kilograms) of biodegradable waste were collected, consisting of leaves, twigs, logs, driftwoods, and branches of trees. For non-biodegradable, 5% (13.3 kilograms) of trash were gathered containing plastic packaging, styrofoam, miscellaneous plastics, and cigarette butts. 15% (39.05 kilograms) of the waste is recycled material (plastic bottles and cans), and 6% (15.13 kilograms) is residual waste, mainly heavily soiled plastics, were accumulated. In conclusion, the design of the floating trash traps has been proven as a potential solution for collecting marine wastes, particularly in rivers.
The rapid spreading of the Coronavirus throughout the world is terrifying. In order to slow down the transmission of the above-mentioned virus the government has no choice but to apply the health protocol to protect its citizens from getting infected. There are steps applied to protect its citizens, such as large-scale restrictions. The restrictions cover working hours, and workers' numbers. However applying this strategy affects the economic and business sectors, especially the construction sector. This study aims to analyze the performance of construction projects in Indonesia during pandemic COVID- 19 based on the risk. Furthermore Toll Road Tebing Tinggi-Prapat, North Sumatera, is chosen for the object of the research. Literature review and questionnaire will be used for gaining the data. The probability and the impact matrix are the methods used to analyze the risk. In additionThere are 23 respondents selected to complete the questionnaires. The research found out that there were eight high risks such as follow. Late payment from the employerCritical activity delay; Financial impact; additional cost limited working hours of the employees; Interruption of Planning and scheduling; Supply shortage. This study is considered essential for construction during the COVID-19 outbreak and the main purpose is for a vital project to keep running.
It is imperative for educators to provide frequent and immediate feedback concerning the academic performances of their respective students. However, this mandate is quite taxing to implement without an automated system in place. This applied research is all about an automated system that may be used in the distribution of the students’ academic performance ratings. The agile software development methodology has been employed; a number of stakeholders also used a product quality evaluation system - the ISO/IEC 25010. The system achieved the research participants’ expectations about the facets of a quality software product. Such is also a commendable start for the promotion of e-governance in the academe, once the said application program has been ultimately implemented and maintained.
Cloud Automation Testing is a concept that entails testing cloud-deployed applications that make use of cloud-based resources. Companies can save provisioning time by employing a cloud infrastructure system for testing because the cloud allows test servers to be provisioned as needed. Selenium is a free and open-source testing tool that may be used to test a variety of online applications. However, selenium has a number of drawbacks, including the inability to generate structured reports and cross-browser testing. To work around these issues, selenium is frequently combined with additional tools like as JMeter, Junit, and Test-NG. By combining and comparing several tools that are expected to be effective for cloud automation testing alongside selenium, this article presents a study of some of the technologies that are estimated to be effective for cloud automation testing by combining and comparing various technologies together with selenium
The Pelton turbine is a type of water turbine whose working principle utilizes the potential energy of water which is converted into kinetic energy through a nozzle. The fluid coming out of the nozzle push the bucket and rotates the Pelton turbine which ultimately produces electrical energy. Micro-hydro power plants that usually use Pelton turbines need to be developed to remote villages to meet electricity needs in Indonesia. Pelton turbine buckets, which are usually made of metal, are not only difficult to manufacture so they have to be specially ordered, but also easy to rust. Therefore, in this study, the bucket was made easier and simpler using an epoxy resin composite material reinforced with palm fiber. This makes it lighter and more corrosion resistant. The results of this study indicate that the epoxy composite fiber reinforced with 9% fiber volume has a higher tensile strength than the volume fraction 0%, 3%, 5%, 7%. The maximum tensile strength for 9% fiber content is 32.61 N/mm2. Then the tensile strength results are applied to the Pelton turbine bucket geometry with laboratory scale sizes that have been varied into 3 different size models in: bowl width (b), bowl height (h), and bowl height (h1). All variations of the laboratory scale bucket design that were simulated using solidworks software with 33.055 N loading had a safety factor above 6. The bucket design that has the highest safety factor is design 3 where the minimum deformation is 0.07922 mm, stress is 2.6670575 N/mm2, strain is 0.000557, and the safety factor is 6.945.
In this research, Taguchi Method is used for optimizing the quantity of the samples in investigating the properties of composite material. The objective of this study is investigating the validity of Taguchi method to optimize the sample quantity in the research on the impact strength of polymer matrix composite reinforced with oil palm fibres. The result was compared to the full factorial design. There were 3 factors used in this work, i.e.: fibre contents/ percentage, Fibre length and chemical treatment. Every factor consists of three levels. The fibre contents were varied into 3 different percentages: 5%, 7% and 10%. The fibre lengths were also varied in three sizes: 5mm, 7mm and 10mm. The level of chemical used factors consist of Untreated, Treated and Coupling agent. NaOH is used here to treat the fibre while PPgMA (Polypropylene grafted Maleic Anhydride) is used here as the coupling agent. The analysis graph, from the two methods were obtained almost same graph. The analyze of multiple regression analysis also results similar regression equation, with the p-value of all independent variables also below 0.05 which indicated all independent variables are significant. Even There are little different in coefficient number of the two equations. But still too small. Taguchi method has succeeded in making research more efficient. The use of a small number of sample combinations is able to produce good analytical validity, equivalent to a complete factorial method which is 3 times the number of combination samples.
IThe search for alternative energy is increasing along with the increasing global demand for electricity. Utilization of dam as an alternative energy source using a floating solar power plant (PLTS) by utilizing the pool area of the reservoir. Floating PLTS is a flagship program, the electricity price is quite good, licensing is simpler, does not require land acquisition, and can be developed with a large enough capacity. This research utilizes the open space of the Bening Widas Dam, Madiun, Indonesia to be developed as a floating solar power plant. The research method uses quantitative analysis of secondary data to calculate rainfall intensity, planned flood discharge and PLTS design on the surface of the water and the Global Solar Atlas application to calculate the duration of sunlight around the reservoir. The results showed that the area of inundation in the Bening Widas Dam was 570 ha, with a maximum utilization of 5%, namely 285,000 m2. This is in accordance with the Regulation of the Ministry of Public Works and Public Housing PUPR Ministerial Regulation No. 6 of 2020, namely the determination of the use of dams for generating purposes is 5% of the inundation area of the dam at normal water levels. The value of Global Horizon Irradiation (GHI) around Bening Widas dam is 1,962.3 Kwh/m2. The role of the Bening Widas dam as a flood controller can be maximized by placing an EWS tool called FEDS (Floods Early Detection System), a flood early detection tool equipped with sensors for rainfall, water discharge and water level.
The use of Smooth Variable Structure Filter (SVSF) has been successfully overcoming the Localization problem. Generally, its performance depends on the knowledge of noise statistics for the process and measurement. Because this knowledge is not available, both are determined and kept to be constant for all iterations. However, this approach will lead SVSF to the divergence condition. Accordingly, a novel improvement, namely FISGAIAE ASVSF, is proposed in this paper. This name represents the role of the Genetic Algorithm (GA) used to optimize the Fuzzy Inference System (FIS) that is initially applied for enhancing the adaptive SVSF. Unlike the traditional way, this strategy can recursively update the noise covariance of the process 𝑄 and measurement 𝑅. In detail, FIS supervises the adaptive SVSF to reduce the mismatch between the reference and estimated covariance of error innovation. To effectively arrange the membership function of FIS, the GA is adopted. Lastly, it is implemented to solve the localization problem of mobile robots in the synthetic simulation perception. By using the term RMSE, the comparatively presented results are analyzed. And the proposed method shows better performance in terms of accuracy and stability.
Removal of pollutants in the exhaust system was an interesting field and it was inspired by the invention of modern Catalytic Converter (CATCO). The problem is low emission conversion from CO, NOx and HC to H2O, CO2 and NO2 due to low CATCO material conductivity. Therefore, the objective of this research is to investigate the conductivity and resistivity of FeCrAl material for CATCO that coated by combined technique of electroplating and ultrasonic methods. Nickel (Ni) plate as anode and FeCrAl as cathode. The distance between anode and cathode was adjusted at 25 mm. Ultrasonic was carried out using frequency of 35kHz. Ultrasonic and electroplating were conducted for several variation times of 15, 30, 45, 60 and 75 minutes. Drying process was performed after electroplating process at temperature of 600C for 12 hours. The conductivity and resistivity analysis will be conducted using 4 point probe machine. Resistivity and conductivity analysis show that the smallest resistivity and highest conductivity has been observed at UB+EL 30 minute for 2.67E+03 ohm-cm and 3.75E-04 S/cm, respectively. UB samples has lower resistivity and higher conductivity than EL, and UBdEL samples. It may caused by surface roughness of the FrCrAl material that embedded during the coating process.