2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC)最新文献_第4页

Sustainable solution to address waste management and energy challenges in rural India 解决印度农村废物管理和能源挑战的可持续解决方案

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) Pub Date : 2021-09-30 DOI: 10.1109/R10-HTC53172.2021.9641529

Aditya Lokare, M.S. Sri Harish, G. Bhargav, S. Raghul, S. Thangavelu, Souresh Cornet

{"title":"Sustainable solution to address waste management and energy challenges in rural India","authors":"Aditya Lokare, M.S. Sri Harish, G. Bhargav, S. Raghul, S. Thangavelu, Souresh Cornet","doi":"10.1109/R10-HTC53172.2021.9641529","DOIUrl":"https://doi.org/10.1109/R10-HTC53172.2021.9641529","url":null,"abstract":"Waste management and access to energy for cooking are some of the pressing challenges faced by Indian rural areas. Most of the Municipal Solid Waste is burned or landfilled without treatment. In the same time, 85 % of rural Indian households rely on carbon-emitting sources of energy for cooking. The context of rural India is extremely challenging for technology development due to its complexity and resource constraints. This study explores how technological solutions can be developed to address the contextual needs of Indian rural communities, based on the case study of a village located in the Northwest India. The participatory research approach relied on Human Centered Design to understand the community perspective. Through active field engagement, a collaborative solution was developed, in the form of a community biogas plant. It was designed to address the interconnected sustainable development challenges of waste management, access to energy for cooking and even agriculture, based on the community specifics. This customized bottom-up process has proved to be successful to address the multiple challenges of technology development and adoption in rural India.","PeriodicalId":117626,"journal":{"name":"2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133789904","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

CoviDefender: Digital Personal Guard For Defending Against COVID19 CoviDefender:防范covid - 19的数字个人卫士

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) Pub Date : 2021-09-30 DOI: 10.1109/R10-HTC53172.2021.9641686

Piyumi Dayarathna, I. Kumara, Duranka Ranaweera, D. Nawinna, Gayani Karunaratne, J. Wijekoon

引用次数: 0

Design and Simulation of an Autonomous Surface Vehicle for Trash Collection using ROS 基于ROS的自动地面垃圾收集车辆设计与仿真

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) Pub Date : 2021-09-30 DOI: 10.1109/R10-HTC53172.2021.9641589

Garre SaiTeja, Pramod S

{"title":"Design and Simulation of an Autonomous Surface Vehicle for Trash Collection using ROS","authors":"Garre SaiTeja, Pramod S","doi":"10.1109/R10-HTC53172.2021.9641589","DOIUrl":"https://doi.org/10.1109/R10-HTC53172.2021.9641589","url":null,"abstract":"While it is true that the earth is covered with 70 percentage of water out of which only 3 percentage of it is drinkable in the form of rivers and lakes. However, by releasing sewage and industrial wastes water has become polluted and is undrinkable. The world water Assessment Program estimates that in developing countries, 70 percentage of industrial wastes are dumped untreated into waters where they pollute the usable water supply and in a country like india where rivers are considered as sacred waters like Ganga, Yamuna and Godavari are contaminated by bathing and throwing flowers, diyas and plastic waste in the name of worship. Every year an estimated 8 million tonnes of garbage is dumped from somewhere in the region of 600,00 places of worship into rivers. Rejuvenation of these holy bodies has been initiated by indian government in the name of Namami Gange. To aid the process of rejuvenation this paper presents a novel Autonomous Surface Vehicle (ASV) model that cleans the water bodies from floating trash, based on Robot Operating System (ROS) for design, simulation and its control system. The use of Unmanned Surface Vehicles as a tool for inspection, monitoring and exploring of water bodies in lakes and ponds has become a research area of growing interest. However, using real models to test and development of software and their deployment is not feasible due to expensive and complicated parts used in surface vehicles to overcome that, software simulations are used which can replicate real world environments in the simulation world and helps in developing control systems using sensor data. The model has been simulated in a water environment using ros for testing of the control system and movement of the model. Simulation results have shown that the proposed work can be an alternative to collect trash floating on the surface of water with low cost and minimum human intervention.","PeriodicalId":117626,"journal":{"name":"2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134437619","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

Detection of Plasmodium Falciparum Parasite Intraerythrocytic Stages using One Dimensional Distributed Bragg Reflector Biosensor 应用一维布喇格反射式生物传感器检测恶性疟原虫红细胞内分期

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) Pub Date : 2021-09-30 DOI: 10.1109/R10-HTC53172.2021.9641586

Ranjith B. Gowda, M. S. Manna, S. K, P. Sharan

{"title":"Detection of Plasmodium Falciparum Parasite Intraerythrocytic Stages using One Dimensional Distributed Bragg Reflector Biosensor","authors":"Ranjith B. Gowda, M. S. Manna, S. K, P. Sharan","doi":"10.1109/R10-HTC53172.2021.9641586","DOIUrl":"https://doi.org/10.1109/R10-HTC53172.2021.9641586","url":null,"abstract":"This work proposes, the design and analysis of 1D Distributed Bragg Reflector (DBR) with a central micro cavity to sense the presence of Plasmodium falciparum parasite which causes malaria disease. Early detection of malaria is a vital requirement in biomedical applications. Plasmodium falciparum parasite enter human body with the byte of infected female Anopheles mosquitoes. This parasite resides in the human Red Blood Cells and starts invading RBCs by growing and multiplying in the cell. P. falciparum undergoes various erythrocytic stages in the host RBC cells. Detection of these infected stages of RBC is utmost important by using appropriate diagnostic techniques. 1D Photonic Crystal biosensors find its application for the early detection of malignant cells. Here, a multi-layered DBR structure is designed and analyzed for the detection of P. falciparum parasite in its various stages in the analyte. The proposed structure uses N=3 layers for the initial analysis and is finally chosen as 8 layers to enhance the Q factor. The central defect cavity length is varied to choose proper defect length which gives better sensor sensitivity. The obtained sensitivity and Q factor for the proposed structure is 4500nm/RIU and 8333 respectively. Form the attained simulation results it is justifiable that the proposed sensor can be used for the detection malaria disease in its early stage.","PeriodicalId":117626,"journal":{"name":"2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134325494","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: 3

Deep Learning Based Atrial Fibrillation Detection Using Effective Denoising Methods and Dimensionality Reduction Techniques 基于深度学习的有效降噪方法和降维技术的房颤检测

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) Pub Date : 2021-09-30 DOI: 10.1109/R10-HTC53172.2021.9641550

Shrikanth Rao S. K, Krithika K, Anushree, M. Akhila, Archana, R. J. Martis

{"title":"Deep Learning Based Atrial Fibrillation Detection Using Effective Denoising Methods and Dimensionality Reduction Techniques","authors":"Shrikanth Rao S. K, Krithika K, Anushree, M. Akhila, Archana, R. J. Martis","doi":"10.1109/R10-HTC53172.2021.9641550","DOIUrl":"https://doi.org/10.1109/R10-HTC53172.2021.9641550","url":null,"abstract":"Atrial Fibrillation (AF) is one of the most common heart rhythm disorder observed by the physician on a daily basis. Automatic detection of AF is one of the major challenges in the field of heart arrhythmia. In this paper we propose an algorithm to classify Electrocardiogram (ECG) signal into three classes namely Normal, AF and other rhythms. Three different methods namely Discrete Wavelet Transform (DWT), Butterworth filter and Savitzky-Golay filter are used separately to remove high frequency noise and baseline wander. Two dimensionality reduction techniques namely Principal Component Analysis (PCA) and Independent Component Analysis (ICA) are used for feature extraction. Finally class specific accuracy of three classes viz: normal, AF and other rhythms are calculated using Decision Tree (DT) and Deep Convolutional Neural Network (DCNN) classifier separately. DWT method combined with ICA and DCNN classifier provided improved performance of 91.71% as overall accuracy which is higher compared to other methods. The proposed method can be used for mass screening in hospitals for detecting cardiac abnormalities","PeriodicalId":117626,"journal":{"name":"2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133415725","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

Implementing a Tollgate Queue Selector Based on Genetic Algorithm 基于遗传算法的收费站队列选择器实现

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) Pub Date : 2021-09-30 DOI: 10.1109/R10-HTC53172.2021.9641584

K. Obias, E. Magsino

引用次数: 0

Assessing visitors satisfaction about museum service quality using Kano model 利用Kano模型评价参观者对博物馆服务质量的满意度

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) Pub Date : 2021-09-30 DOI: 10.1109/R10-HTC53172.2021.9641707

P. Singh, Ruchi Kushwaha, Jyoti Kushwaha

{"title":"Assessing visitors satisfaction about museum service quality using Kano model","authors":"P. Singh, Ruchi Kushwaha, Jyoti Kushwaha","doi":"10.1109/R10-HTC53172.2021.9641707","DOIUrl":"https://doi.org/10.1109/R10-HTC53172.2021.9641707","url":null,"abstract":"Visitor satisfaction is considered as the main concern in museum services especially in the perspective of cut throat competition in the current situation of the tourism sector. Traditional approach assumes a linear relationship between visitor satisfaction and museum service quality attributes. That is, existence of specific quality attributes leads to visitor satisfaction and its nonexistence leads to visitor dissatisfaction. Although, only satisfying a few quality attributes is not sufficient to attain visitor satisfaction. Additionally, as contemporary approach the non-linearity correlation between service quality and visitor satisfaction is a much better concept for measurement of fulfillment of visitor satisfaction. In this context, Kano model has a different method that considers a two dimensional approach between service quality attributes and visitor satisfaction. This study aims to assess the visitors' satisfaction about museum service quality by using the application of Kano model. A survey study was performed among visitors visiting government freedom struggle museum in Meerut city of Uttar Pradesh province, India by using five dimensional HISTOQUAL scale that includes twenty four attributes. Findings of study indicated that out of twenty four attributes, majority of attributes belonged to must-be and attractive needs as classified by Kano model.","PeriodicalId":117626,"journal":{"name":"2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125757968","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: 3

Development of a Low-cost PC-based Single-channel EEG Acquisition System for Educational and Research Purpose 基于pc机的低成本单通道脑电图采集系统的研制

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) Pub Date : 2021-09-30 DOI: 10.1109/R10-HTC53172.2021.9641637

Pranti Tawheed, Jyoti Mollick, Nazmus Sakib, Md Kafiul Islam

{"title":"Development of a Low-cost PC-based Single-channel EEG Acquisition System for Educational and Research Purpose","authors":"Pranti Tawheed, Jyoti Mollick, Nazmus Sakib, Md Kafiul Islam","doi":"10.1109/R10-HTC53172.2021.9641637","DOIUrl":"https://doi.org/10.1109/R10-HTC53172.2021.9641637","url":null,"abstract":"EEG is a widely used brain recording technique for clinical and research purposes due to its non-invasiveness, user-friendliness and low-cost compared with other brain imaging techniques such as MRI or ECoG. The goal of this work is to build a single channel EEG acquisition and monitoring system for research and education purpose. By using discrete and locally available components, a low-cost analog frontend has been developed for EEG recording at channel Fp1 (prefrontal part of brain) location which can be interfaced with PC through Arduino UNO and can be analyzed in MATLAB platform. EEG is usually very low in amplitude (i.e. uV range) and gets contaminated by noise very easily which makes it challenging to acquire a good quality signal (i.e. good SNR). The single channel EEG recording and monitoring system that is designed and implemented in hardware can be used in various application like moving mouse cursor or build a security system like Face-unlocking. This recorded data can also be helpful for students to understand EEG better for further analysis and processing. The implemented system in hardware costs less than 25 USD whereas the available EEG device price starts from 100+ USD excluding the license cost to access the raw EEG. The developed system is tested and found that it can successfully record the EEG rhythms, especially the Alpha rhythms (dominates around 8–12 Hz frequency) during eye close.","PeriodicalId":117626,"journal":{"name":"2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125192860","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

Severity Assessment of Potato Leaf Disease Induced by Alternaria solani Fungus Using Hybrid Decision Tree and Support Vector Machine Regression 基于混合决策树和支持向量机回归的马铃薯马铃薯叶病严重程度评价

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) Pub Date : 2021-09-30 DOI: 10.1109/R10-HTC53172.2021.9641616

Heinrick L. Aquino, Ronnie S. Concepcion, E. Dadios, Christan Hail R. Mendigoria, Oliver John Y. Alajas, E. Sybingco

{"title":"Severity Assessment of Potato Leaf Disease Induced by Alternaria solani Fungus Using Hybrid Decision Tree and Support Vector Machine Regression","authors":"Heinrick L. Aquino, Ronnie S. Concepcion, E. Dadios, Christan Hail R. Mendigoria, Oliver John Y. Alajas, E. Sybingco","doi":"10.1109/R10-HTC53172.2021.9641616","DOIUrl":"https://doi.org/10.1109/R10-HTC53172.2021.9641616","url":null,"abstract":"Alternaria solani is a destructive fungus affecting potato crops that promotes early and late blight diseases. Early detection of its manifestation is an imperative step to prevent its spread. However, manual inspection of leaves is vulnerable to inefficient and inconsistent monitoring. As a solution, the application of computational intelligence and computer vision in identifying healthy and damaged leaves and detecting the percentage of damaged area (PDA) by Alternaria solani is presented in this paper. A total of 552 image sets (200 late blight, 200 early blight, and 152 healthy leaves) were utilized. Vegetation segmentation was employed via lazy snapping and CIELab color space for the healthy regions and PDA. Spectral (RGB, HSV, L*a*b*, YCbCr), Haralick textural (entropy, correlation, contrast, homogeneity, energy), and phenotypic (leaf canopy area) were extracted from the lettuce leaf canopies. With the use of the decision tree (DT), this 18-feature vector was narrowed down to the 10 most significant features (R, G, S, a*, Cb, Cr, contrast, energy, entropy, leaf canopy area). Support vector machine (SVM) has the best performance (which has 100% accuracy) in classifying the potato leaf health status, however, exhibited the longest time of processing. Optimized K-nearest neighbors (KNN) have a considerable accuracy (93.21%) and inference time (32.63 s). For PDA prediction, hybrid decision tree and support vector machine regression (HDT-RSVM) defeated other feature-based machine learning models. Ultimately, the formulated DT:SVM:RSVM model offers accurate disease identification and quantification on the potato leaf surface by using a consumer-grade camera that is translatable to low-income agricultural units.","PeriodicalId":117626,"journal":{"name":"2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121216770","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

BERT Model for Classification of Fake News using the Cloud Processing Capacity 基于云处理能力的假新闻分类BERT模型

2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC) Pub Date : 2021-09-30 DOI: 10.1109/R10-HTC53172.2021.9641632

Athiya Marium, G. Mamatha

{"title":"BERT Model for Classification of Fake News using the Cloud Processing Capacity","authors":"Athiya Marium, G. Mamatha","doi":"10.1109/R10-HTC53172.2021.9641632","DOIUrl":"https://doi.org/10.1109/R10-HTC53172.2021.9641632","url":null,"abstract":"This paper aims at conducting a predictive analysis on news articles in order to find if they are fake or real. After conducting an extensive research on the topic, various Machine Learning and Deep Learning models for the purpose of evaluating news articles were discovered. A new transfer learning model, Bi-directional Encoder Representation for Transformers (BERT), is tested using the Google Cloud GPU capacity for the purpose of detection. The first step in this direction will be to pre-process the data to clean out the garbage and missing values. After this, all the news articles collected will be tokenized, according to the BERT tokenizer. The tokenized corpus will be converted into tensors for the model to be trained. The data will be trained in batches with each batch having 32 articles. The final layer for training will consist of a five layered neural network. The model with the least validation loss will be tested for accuracy. The predictions for news articles will be made on this model. The paper will also explore the best cloud platform to host such a model and performance of the hosted model as well.","PeriodicalId":117626,"journal":{"name":"2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122529269","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: 0