2022 International Conference on Future Trends in Smart Communities (ICFTSC)最新文献

{"title":"Multi-sensor IF Estimation Based on Time-Frequency and Spatial Filtering","authors":"Nabeel Ali Khan, Sadiq Ali, Ateeq Ur Rehman","doi":"10.1109/ICFTSC57269.2022.10040066","DOIUrl":"https://doi.org/10.1109/ICFTSC57269.2022.10040066","url":null,"abstract":"Instantaneous frequency (IF) is an important parameter whose accurate estimation is useful in many applications including source localization, blind source separation and signal detection. We propose a computationally efficient and accurate multi-component IF estimator for multi-sensor recordings. The proposed method iteratively estimates the IF of signal components by first tracking the components based on their angle of arrival information and then removing components through time-frequency (TF) and spatial filtering. Experimental results indicate that the proposed method based on joint TF and spatial filtering leads to accurate IF estimates as compared to a recent method that only performs filtering in the TF domain.","PeriodicalId":386462,"journal":{"name":"2022 International Conference on Future Trends in Smart Communities (ICFTSC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133618937","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}

{"title":"Enhancements to PERCLOS Algorithm for Determining Eye Closures","authors":"Muhammad Ammar Zulkarnanie, K. S. Shanmugam, N. Badruddin, M. N. Saad","doi":"10.1109/ICFTSC57269.2022.10039811","DOIUrl":"https://doi.org/10.1109/ICFTSC57269.2022.10039811","url":null,"abstract":"This study presents an algorithm that can detect people’s facial features being studied and then applied mainly on daily basis activities, as an example in driving which is detection of driver drowsiness. In this study, the algorithm named ‘PERCLOS’ which stands for ‘percentage of eye closure’ was tested to detect face by using two face landmark detectors, that are pre-trained model and library Dlib’s 68-points facial landmark and 468 3D face landmarks detector from MediaPipe by Google as an alternative and detects the condition of a person’s eye based on Eye Aspect Ratio (EAR). Initial assessment of the Dlib’s solution on 151,537 frames (about 84 minutes) of one of tested subjects revealed that 98.66% of eye states were properly identified, resulting in 378 blinks to be recorded. Despite having rather good accuracy, the algorithm produced 166 more blinks than the 212 blinks that were expected. As for MediaPipe, with 264 blinks and only 52 additional blinks, the MediaPipe Face Mesh solution was able to categorize the identical subject with a classification accuracy of 99.87%. Additionally, adaptive thresholds for different subjects were applied in order to investigate a way to improve the studied algorithm. Surprisingly, the adaptive threshold method being studied resulted in decreasing accuracy and precision for some of the subjects. For one of tested subject, the resulted precision of studied algorithm somehow drops from 100% to 98.60%.","PeriodicalId":386462,"journal":{"name":"2022 International Conference on Future Trends in Smart Communities (ICFTSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130304787","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}

{"title":"Impact of New Enhanced Dispatch Arrangement (NEDA) Mechanism on the Cost Efficiency of Generation of Malaysian Representative System","authors":"Previnsha Naidu Poornachendran, R. Verayiah","doi":"10.1109/ICFTSC57269.2022.10039928","DOIUrl":"https://doi.org/10.1109/ICFTSC57269.2022.10039928","url":null,"abstract":"Transforming from a vertically integrated environment to a liberalized electricity market is not an easy task, and the rationale behind is the pressure to reduce electricity prices by relying on the enhanced efficiency of power plants and stiff competition in the generation sector. The New Enhanced Dispatch Arrangement (NEDA) is an initiative by EC (Energy Commission) to enhance efficiency in the short run electricity generation competition and drive down electricity prices. NEDA serves as a pre-cursor to the creation of an electricity market in Peninsular Malaysia. This paper analyses the impact of NEDA mechanism on the cost efficiency of a Malaysian Representative System. The PLEXOS simulation is done for two network constraints, which are the Southern and Northern constraint, using four types of load profiles to study the cost impact. To obtain the generation cost for each scenario, the methodology implemented will be Security Constrained Economic Dispatch (SCED). The objective function of SCED is to minimize the total system costs within various technical constraints and limitations. For Southern constraint, the results obtained showed an average of 1.3% cost savings per day, when 1000 MW of NEDA generation is injected into the grid. The annual cost savings is RM 226 million, translating to a 471% savings in generation prices. Expensive generators in the system are now being replaced by the generation from NEDA players which are paid at the System Marginal Price (SMP). On the other hand, for Northern constraint, the annual cost savings is approximately RM 191 million, which is equivalent to 366% cost savings. This will benefit the electricity industry by reducing generation cost, and consumers will be able to enjoy lower and cheaper electricity tariff.","PeriodicalId":386462,"journal":{"name":"2022 International Conference on Future Trends in Smart Communities (ICFTSC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126033297","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}

{"title":"Design and Development of PV Powered Intergraded DC - DC Converter Fed Multilevel Inverter for Standalone Application","authors":"K. Prathibanandhi, B. Meenakshi, T. Porselvi, R. Azhagumurugan, V. Chithra, V. Malini","doi":"10.1109/ICFTSC57269.2022.10040014","DOIUrl":"https://doi.org/10.1109/ICFTSC57269.2022.10040014","url":null,"abstract":"The use highlighter amount of nonconventional energy is causing greenhouse gas emissions worldwide, which is affecting the climate adversely. To avoid this, all counties keen to swapping conservative energy foundations to non-conservative foundations. There are variety of DC to DC converters reported in literature with various power-boosting performances which comprises of energy storing passive elements (in capacitors and inductors), with either 1: n transformers in aggregation along with power electronics switches (MOSFETs and Diodes), which are named as isolated and non-isolated converters respectively. These converters are selected for the specific application depends on the circuit complexity, reliability and cost. Sometimes, the reduction of power circuit components and/or power switches is need to this converter industry to meet out the growing demand, cost, and size. With respect to PV application straightforward increase larger voltage gain DC to DC converters are an option and this should a coordination to operate with DC to AC converter (inverter). Compare to the conventional 2-level inverter, multilevel inverter (MLI) is a better selection since it has a quality to suppress the harmonic distortion on the current and voltage. Although reduced switch MLI have been well recognized as a striking resolution for intermediate power PV and wind power generations’ claims, still challenges and opportunities are looking forward for the reduction voltage harmonic, voltage profile enhancement, increasing the voltage transfer gain, reduction in the switching losses etc. Hence, the proposed is dealt with a suitable high efficient DC to DC converter and MLI inverter can be improve the stand-alone PV power system. In this work, the generalized simulation and practical implementation of PV connected single switch performed seven-level MLI for 100W PV system The suggested work accurately models the relationship between voltage gain and boost duty ratio using theoretical data. investigation is verified experimentally.","PeriodicalId":386462,"journal":{"name":"2022 International Conference on Future Trends in Smart Communities (ICFTSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128885144","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}

{"title":"Variance Analysis on Functional Connectivity of Resting-state fMRI Signals in Alzheimer’s Disease Patients","authors":"A. Sadiq, N. Yahya, T. Tang, Hilwati Hashim, M. Saad","doi":"10.1109/ICFTSC57269.2022.10040043","DOIUrl":"https://doi.org/10.1109/ICFTSC57269.2022.10040043","url":null,"abstract":"The assessment of the brain network is a powerful tool for determining brain topological organisation, and it is been employed extensively in the study of mental disorders. Observing the brain’s connectivity patterns is one of the most effective approaches for analysing brain functionality. According to recent research, Alzheimer’s disease is significantly linked to the changes in network connection among distinct brain regions. In this work, five brain regions are chosen to be analyzed in showing the variation in functional connectivity. These regions are hippocampus, parahippocampus, olfactory, superior parietal gyrus and anterior cingulate gyrus. Pearson’s Correlation is used for determining the functional connection between the five brain regions. When comparing Alzheimer’s disease (AD) patients to Normal Controls, the findings indicate that there are higher variations of functional connectivity in AD patients.","PeriodicalId":386462,"journal":{"name":"2022 International Conference on Future Trends in Smart Communities (ICFTSC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132776150","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}

{"title":"The Influence of Audio Sensory Input on the Anxiety Level of the VR Users","authors":"Mahdiyeh Sadat Moosavi, Marcus Chong, Ainul Khairiyah Mohd Nazri, F. Mérienne, Christophe Guillet, D. R. A. Rambli, S. Sulaiman","doi":"10.1109/ICFTSC57269.2022.10040060","DOIUrl":"https://doi.org/10.1109/ICFTSC57269.2022.10040060","url":null,"abstract":"This study investigates subjects’ behavior in visual audio conflict conditions in stressful and stressless environments. To increase subjects’ stress and anxiety in subjects we placed subjects in a chaotic city and to decrease subjects’ stress we benefit from a green virtual environment. On the other hand to study the effect of sound on physiological data we designed confilict condition in which in the City environment participants heared the sound of Forest and in the Forest nvironment they heared the sound of City. To evaluate our findings we benefit from the heart rate of the participants which is directly related to subjects’ emotions and participants can not involve their opinion to change this feature autonomously.","PeriodicalId":386462,"journal":{"name":"2022 International Conference on Future Trends in Smart Communities (ICFTSC)","volume":"335 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116458130","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}

{"title":"Effect of Thickness of the Poly(vinyl alcohol) Passivation Layer on Ambipolar Characteristics of Graphene Field-effect Transistor","authors":"Nadia Norhakim, H. F. Hawari, Z. A. Burhanudin","doi":"10.1109/ICFTSC57269.2022.10039724","DOIUrl":"https://doi.org/10.1109/ICFTSC57269.2022.10039724","url":null,"abstract":"Pristine graphene field-effect transistor (GFET) typically has an ambipolar transport characteristic. However, unintentional doping during fabrication and post-fabrication typically leads to p-doping of the graphene layer. This unintentional doping is further exacerbated when the GFET is operated in an ambient environment rich with oxygen and water molecules. In this work, the recovery of the ambipolar transport characteristics of the GFET by passivating the graphene with poly(vinyl alcohol) (PVA) is demonstrated. Two approaches were considered, i.e. drop casting and spin coating. It is found that the spin coating approach produces a rather uniform PVA film with thickness ~0.83 μm. It can recover and further retain the ambipolar transport characteristics of GFET in ambient environments. By manipulating the number of ions in the PVA, it is believed that the characteristics could be prolonged making GFET more suitable for sensing in ambient environment.","PeriodicalId":386462,"journal":{"name":"2022 International Conference on Future Trends in Smart Communities (ICFTSC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129191709","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}

{"title":"Potato Crop Health Assessment Using Multispectral Image Analysis","authors":"Amelia Sarah Binti Abdul Rahman, P. Sebastian, L. I. Izhar","doi":"10.1109/ICFTSC57269.2022.10039849","DOIUrl":"https://doi.org/10.1109/ICFTSC57269.2022.10039849","url":null,"abstract":"In order to categorize healthy and stressed potato crops obtained from UAV-based multispectral photos, this study will use machine learning. It also aims to determine which spectral band offers the best separation for classification. These machine learning techniques are compared to classify healthy and stressed crops: Random Forest Classifier (RF), K-Nearest Neighbors Classifier (KNN), and Gradient Boosting Classifier (GBC), as well as Support Vector Classifier (SVC) and Linear Support Vector Classifier (LSVC). The Normalized Difference Vegetation Index (NDVI) and the Red Edge Normalized Difference Vegetation Index (NDRE), RED, GREEN, Near-Infrared (NIR), REDEDGE bands, are used by machine learning techniques to categorize data. The suggested approach consists of three main parts: (1) extraction of vegetation indicators; (2) Utilising thresholding technique to remove the background containing weeds and soil; and (3) classification and model training using machine learning classifier. As a consequence of its strong performance and good accuracy (0.777% accuracy and AUC score of 0.92), the paper’s findings demonstrate that RF is the best appropriate classifier for healthy and unhealthy plants. The NIR band is the most accurate in spotting unhealthy plants, with a 0.169 feature significance score. This band is connected to the two vegetative indices, NDVI and NDR, which had the best spectral characteristics in the classification model, with feature significance scores of 0.189 and 0.181, respectively.","PeriodicalId":386462,"journal":{"name":"2022 International Conference on Future Trends in Smart Communities (ICFTSC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120985528","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}

{"title":"Optimal Node Placement and Congestion Reduction in an Industrial Wireless Mesh Network using HHO Algorithm","authors":"H. Abdulrab, F. Hussin, A. Awang, I. Ismail, P. Devan, Hussein Shutari","doi":"10.1109/ICFTSC57269.2022.10039952","DOIUrl":"https://doi.org/10.1109/ICFTSC57269.2022.10039952","url":null,"abstract":"When it comes to improving the performance of a wireless mesh network, the positioning of routers is critical. In order to provide the greatest network accessibility, it is essential that mesh routers be installed in appropriate locations. One way to improve the network’s performance is to increase the coverage while utilizing an optimum number of routers. The network coverage may be optimised using a number of different techniques that have been developed over time in the scientific literature. An algorithm called Harris Hawk’s Optimization (HHO) is being used in this study to optimally locate mesh routers in a mesh network in order to optimise coverage and reduce network congestion. The HHO identifies the best positions to place the routers in order to have the best possible network topology by removing the overlapping routers to minimize the number of routers while keeping the coverage maximized. In this research, 60, and 100 mesh routers are deployed in two different network topologies. The simulation results are analysed and compared with Sine Cosine Algorithm (SCA), Gray Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithm. With regard to network coverage and congestion reduction, simulation results show that HHO surpasses the benchmark algorithms by having 98% coverage and 34% reduction in the network size.","PeriodicalId":386462,"journal":{"name":"2022 International Conference on Future Trends in Smart Communities (ICFTSC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121938070","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}

{"title":"Detection of Alzheimer’s Disease Using Dynamic Functional Connectivity Patterns in Resting-State fMRI","authors":"M. I. Al-Hiyali, N. Yahya, I. Faye, A. Sadiq, Mohamad Naufal bin Mohamad Saad","doi":"10.1109/ICFTSC57269.2022.10039735","DOIUrl":"https://doi.org/10.1109/ICFTSC57269.2022.10039735","url":null,"abstract":"Alzheimer’s disease (AD) is a slowly progressive neurological disorder associated with impaired functional connectivity of the brain. A common approach is to examine functional connectivity patterns (FC) for AD diagnosis either statically based on Pearson correlation coefficients (PCC) or dynamically based on time-frequency coefficients of resting-state fMRI BOLD signals. However, there is still a need to develop a AD diagnostic model with dynamic FC patterns that can improve the performance of the classifier. In this paper, a classification of AD from normal cases is proposed by combining a machine learning algorithm with dynamic FC patterns (DFC). The proposed method introduces a new feature vector for the maximum value of variation in the time-frequency domain, called (MWCF). Moreover, analysis of variance (ANOVA) is used to select the most informative features. Compared to previous studies, the proposed method outperforms state-of-the-art methods with an accuracy of 98.4%. The proposed method is an efficient predictor for the classification of AD vs. NC and can be used as a potential biomarker in AD diagnosis.","PeriodicalId":386462,"journal":{"name":"2022 International Conference on Future Trends in Smart Communities (ICFTSC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133961843","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}