2022 25th International Conference on Computer and Information Technology (ICCIT)最新文献_第3页

Advanced Waterway Transport System Based on Internet of Things (IoT): A Novel Approach 基于物联网的先进水路运输系统:一种新途径

2022 25th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2022-12-17 DOI: 10.1109/ICCIT57492.2022.10055423

Md. Imtiaj Miah, Joy Chandra Gope, Ananta Deb Nath, A.K.M. Janaite Nain, Faria Nasir Mitu, Jannatun Noor

{"title":"Advanced Waterway Transport System Based on Internet of Things (IoT): A Novel Approach","authors":"Md. Imtiaj Miah, Joy Chandra Gope, Ananta Deb Nath, A.K.M. Janaite Nain, Faria Nasir Mitu, Jannatun Noor","doi":"10.1109/ICCIT57492.2022.10055423","DOIUrl":"https://doi.org/10.1109/ICCIT57492.2022.10055423","url":null,"abstract":"Nowadays the inland waterway transport sector has grown significantly in recent years, offering a large possible contribution to environmentally friendly and cost-effective transportation to reduce congestion on the roads. Accidents in developing nations’ waterways occur on a daily basis all throughout the year. For example, in Bangladesh, a total of 320 incidents resulted in the deaths of 496 people between 2014 and 2020, while 5425 accidents resulted in 6220 injuries. Hence, the need to develop a much more safe, secure, and efficient system is highly needed. In this paper, we propose a architecture to ensure safety in inland waterways using IoT to unlock new way for developing waterway transportation using a different type of sensors and protocols to collect data. Besides, our architecture comprises weight calculation using load line image processing system, automated speed and distance control system over vessels using ACC (Adaptive Cruise Control), priority data encoding system, and continuous monitoring having post accident safety measurement. Finally, we evaluate our model efficacy using Arduino Uno microprocessor, Ultrasonic Sonar Sensor HC- SR04, DHT11–Temperature Sensor, Humidity Sensor, LM393 Speed Sensor, and Smoke Sensor through a real implementation. In addition, we use ESP8266 Wi-Fi MCU and LoRa as the Data communication module and present the collected data through our implementation on ThingSpeak Cloud.","PeriodicalId":255498,"journal":{"name":"2022 25th International Conference on Computer and Information Technology (ICCIT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114750378","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

An Improved Machine Learning Based Customer Churn Prediction for Insight and Recommendation in E-commerce 基于改进机器学习的客户流失预测在电子商务中的洞察和推荐

2022 25th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2022-12-17 DOI: 10.1109/ICCIT57492.2022.10054771

Ishrat Jahan, Tahsina Farah Sanam

{"title":"An Improved Machine Learning Based Customer Churn Prediction for Insight and Recommendation in E-commerce","authors":"Ishrat Jahan, Tahsina Farah Sanam","doi":"10.1109/ICCIT57492.2022.10054771","DOIUrl":"https://doi.org/10.1109/ICCIT57492.2022.10054771","url":null,"abstract":"Since keeping existing customers costs far less in e-commerce, recruiting new customers is no longer a wise approach. Therefore, businesses are increasingly putting greater emphasis on lowering their customer churn rate due to the level of competition present in the business-to-consumer (B2C) e-commerce arena and the significant investments necessary to recruit new customers. Large volumes of data about their current customers’ transactions, searches, frequency of purchases, etc. are typically held by e-commerce businesses. Artificial intelligence (AI) can be used to evaluate customer behavior and predict potential customer attrition, allowing for the adoption of targeted marketing techniques to keep them as customers. In this paper a customer churn forecasting framework has been developed using the best classifier for insight and recommendation in order to improve the accuracy of forecasts of customers who would churn and make it simpler to identify non-churn consumers. There are five components in the framework, including exploratory data analysis (EDA), data preprocessing, model tuning, comparison among different models after model tuning, insight and recommendation. Experimental results shows that the proposed method can predict customer churn with high accuracy.Accuracy and F1- score are used for model evaluation.According to experimental analysis, CatBoost performed the best in Dataset, with 100% accuracy and 100% F1-score. After selecting the best classifier, the recursive feature elimination (RFE) was applied to find the rank of feature for insight and recommendation so that the paper fills a research gap and contributes to the existing literature in the area of developing a customer churn prediction method.","PeriodicalId":255498,"journal":{"name":"2022 25th International Conference on Computer and Information Technology (ICCIT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117023704","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

Semantic Topic Extraction from Bangla News Corpus Using LDA and BERT-LDA 基于LDA和BERT-LDA的孟加拉语新闻语料语义主题提取

2022 25th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2022-12-17 DOI: 10.1109/ICCIT57492.2022.10055173

P. Paul, Md Shihab Uddin, M. T. Ahmed, Mohammed Moshiul Hoque, Maqsudur Rahman

{"title":"Semantic Topic Extraction from Bangla News Corpus Using LDA and BERT-LDA","authors":"P. Paul, Md Shihab Uddin, M. T. Ahmed, Mohammed Moshiul Hoque, Maqsudur Rahman","doi":"10.1109/ICCIT57492.2022.10055173","DOIUrl":"https://doi.org/10.1109/ICCIT57492.2022.10055173","url":null,"abstract":"In order to infer topics from unstructured text data, topic modeling techniques is extensively employed in the field of Natural Language Processing. Latent Dirichlet Allocation (LDA), a popular technique in topic modeling, can be used for the automatic identification of topics from a vast sample of textual documents. The LDA-based topic models, however, may not always yield good outcomes on their own. One of the most efficient unsupervised machine learning methods, clustering, is often employed in applications like topic modeling and information extraction from unstructured textual data. In our study, a hybrid clustering based approach using Bidirectional Encoder Representations from Transformers (BERT) and LDA for large Bangla textual dataset has been thoroughly investigated. The BERT has done the contextual embedding with LDA. The experiments on this hybrid model are carried out to show the efficiency of clustering similar topics from a noble dataset of Bangla news articles. The outcomes of the experiments demonstrate that clustering with BERT-LDA model would aid in the inference of more coherent topics. The maximum coherence value of 0.63 has been found for our noble dataset using LDA and for BERT-LDA model, the value is 0.66.","PeriodicalId":255498,"journal":{"name":"2022 25th International Conference on Computer and Information Technology (ICCIT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116036147","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

ADPT: An Automated Disease Prognosis Tool Towards Classifying Medical Disease Using Hybrid Architecture of Deep Learning Paradigm ADPT:一种基于深度学习范式混合架构的自动疾病预测工具

2022 25th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2022-12-17 DOI: 10.1109/ICCIT57492.2022.10055867

Sabila Al Jannat, Al Amin, Md. Shazzad Hossain, Elias Hossain, Erfanul Haque, Nasim Ahmed Roni

{"title":"ADPT: An Automated Disease Prognosis Tool Towards Classifying Medical Disease Using Hybrid Architecture of Deep Learning Paradigm","authors":"Sabila Al Jannat, Al Amin, Md. Shazzad Hossain, Elias Hossain, Erfanul Haque, Nasim Ahmed Roni","doi":"10.1109/ICCIT57492.2022.10055867","DOIUrl":"https://doi.org/10.1109/ICCIT57492.2022.10055867","url":null,"abstract":"The Covid 19 beta coronavirus, commonly known as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently one of the most significant RNA-type viruses in human health. However, more such epidemics occurred beforehand because they were not limited. Much research has recently been carried out on classifying the disease. Still, no automated diagnostic tools have been developed to identify multiple diseases using X-ray, Computed Tomography (CT) scan, or Magnetic Resonance Imaging (MRI) images. In this research, several Tate-of-the-art techniques have been applied to the Chest-Xray, CT scan, and MRI segmented images’ datasets and trained them simultaneously. Deep learning models based on VGG16, VGG19, InceptionV3, ResNet50, Capsule Network, DenseNet architecture, Exception and Optimized Convolutional Neural Network (Optimized CNN) were applied to the detecting of Covid-19 contaminated situation, Alzheimer’s disease, and Lung infected tissues. Due to efforts taken to reduce model losses and overfitting, the models’ performances have improved in terms of accuracy. With the use of image augmentation techniques like flip-up, flip-down, flip-left, flip-right, etc., the size of the training dataset was further increased. In addition, we have proposed a mobile application by integrating a deep learning model to make the diagnosis faster. Eventually, we applied the Image fusion technique to analyze the medical images by extracting meaningful insights from the multimodal imaging modalities.","PeriodicalId":255498,"journal":{"name":"2022 25th International Conference on Computer and Information Technology (ICCIT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127058522","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

Abstractive Dialog Summarization using Two Stage Framework with Contrastive Learning 两阶段框架下的抽象对话总结与对比学习

2022 25th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2022-12-17 DOI: 10.1109/ICCIT57492.2022.10055286

Sudipto Dip Halder, Mahit Kumar Paul, Bayezid Islam

{"title":"Abstractive Dialog Summarization using Two Stage Framework with Contrastive Learning","authors":"Sudipto Dip Halder, Mahit Kumar Paul, Bayezid Islam","doi":"10.1109/ICCIT57492.2022.10055286","DOIUrl":"https://doi.org/10.1109/ICCIT57492.2022.10055286","url":null,"abstract":"In the modern era, a large amount of text conversation data between two or more interlocutors is generated by different online service consumers every hour. Converting such a long conversation into a concise form is more useful for further analysis and can boost service quality when conducted in an efficient manner. Abstractive summarization models usually suffer from performance degradation due to the different objective functions used in the training and inference steps. Contrastive learning is a powerful technique for developing training objectives that are similar to evaluation metrics and thus improve performance. Two-stage framework with contrastive learning are gaining popularity to mitigate this gap but this approach is very daunting in the field because of its huge computation time and demand for memory usage. To address this issue, we propose an optimization in the two-stage framework architecture for dialog summarization using the ALBERT pre-trained model in the evaluator section which is more efficient with respect to the usage of resources. Our method significantly outperforms strong baselines on SAMSum and DialogSum dataset for abstractive dialog summarization task.","PeriodicalId":255498,"journal":{"name":"2022 25th International Conference on Computer and Information Technology (ICCIT)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127354208","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

Blood Vessel Segmentation in Retinal Images Using Machine Learning Approach 基于机器学习方法的视网膜图像血管分割

2022 25th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2022-12-17 DOI: 10.1109/ICCIT57492.2022.10055476

Mohoshina Akter Toma, Nuzhat Tabassum Promi, Maria Afnan Pushpo, M. H. Kabir

{"title":"Blood Vessel Segmentation in Retinal Images Using Machine Learning Approach","authors":"Mohoshina Akter Toma, Nuzhat Tabassum Promi, Maria Afnan Pushpo, M. H. Kabir","doi":"10.1109/ICCIT57492.2022.10055476","DOIUrl":"https://doi.org/10.1109/ICCIT57492.2022.10055476","url":null,"abstract":"A segmented vessel network can be beneficial for the diagnosis, therapy planning, coordination, and evaluation of eye-related illnesses such as glaucoma, vein occlusions, and diabetic retinopathy (DR). Since manually segmenting vessels is a time-consuming and challenging task, many ways for autonomously segmenting retinal blood vessels have been presented over the years. However, most known retinal vascular segmentation algorithms still have limitations such as low generalization capacity and poor accuracy due to a lack of consideration given to dataset preparation and processing. This research offers a fully supervised method for segmenting and extracting blood vessels from retinal fundus images using machine learning techniques along with appropriate data processing and dataset enhancement strategies to obtain a robust framework and achieve better performance while reducing computation time. The proposed method has two main components: Extracting feature maps from modified U-net and Segmenting the images using Multilayer Perceptron (MLP). We tested the framework quantitatively and qualitatively on three publicly available data sets, STARE, DRIVE, and HRF. The results were compared to ground truth images and other methodologies from previous research. The framework received an average accuracy of 99.78%, 98.34%, and 98.85% on these datasets, respectively.","PeriodicalId":255498,"journal":{"name":"2022 25th International Conference on Computer and Information Technology (ICCIT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128909492","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

Recognizing Bangladeshi Traffic Signs in the Wild 在野外识别孟加拉国交通标志

2022 25th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2022-12-17 DOI: 10.1109/ICCIT57492.2022.10055612

Ahmed Nusayer Ashik, Md Saimul Haque Shanto, Rizwanul Haque Khan, M. H. Kabir, Sabbir Ahmed

{"title":"Recognizing Bangladeshi Traffic Signs in the Wild","authors":"Ahmed Nusayer Ashik, Md Saimul Haque Shanto, Rizwanul Haque Khan, M. H. Kabir, Sabbir Ahmed","doi":"10.1109/ICCIT57492.2022.10055612","DOIUrl":"https://doi.org/10.1109/ICCIT57492.2022.10055612","url":null,"abstract":"Traffic sign detection is an indispensable part of autonomous driving and transportation safety systems. However, accurate detection and recognition of traffic signs remain challenging, especially under extreme conditions, such as various weather and geo-social features. Though a lot of work has been done in the domain of Traffic Sign Detection and Recognition (TSDR), only a few of them focus on a dataset that comprises a wide variety of real-world challenges. Moreover, in the context of Bangladeshi traffic sign detection, the research is in a very preliminary stage, whereas, the geo-social features of Bangladesh add some unique challenges that are not seen in most parts of the world. In this regard, we have curated a dataset containing 2986 images belonging to 15 different classes of Bangladeshi traffic signs collected under conditions like varying distance, occlusion, blurry conditions, geological variations, varying lighting conditions, etc., reflecting several real-world scenarios. We have provided a thorough performance analysis with different state-of-the-art object detection algorithms where the YOLOv7 architecture has been found to be the best-performing model with a mAP value of 0.889, making it a suitable model for real-life applications.","PeriodicalId":255498,"journal":{"name":"2022 25th International Conference on Computer and Information Technology (ICCIT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131026103","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

A Comparative Study on the Effectiveness of IDM and Card Sorting Method for Autism Specialized School Website 自闭症专科学校网站IDM与卡片分类方法的效果比较研究

2022 25th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2022-12-17 DOI: 10.1109/ICCIT57492.2022.10055352

Maria Afnan Pushpo, Zareen Tasneem, Sheikh Tasfia, Anusha Aziz, M. Islam

{"title":"A Comparative Study on the Effectiveness of IDM and Card Sorting Method for Autism Specialized School Website","authors":"Maria Afnan Pushpo, Zareen Tasneem, Sheikh Tasfia, Anusha Aziz, M. Islam","doi":"10.1109/ICCIT57492.2022.10055352","DOIUrl":"https://doi.org/10.1109/ICCIT57492.2022.10055352","url":null,"abstract":"With the advent of new technologies, software and web applications have been an integral part of today’s modern life. These applications are exclusively designed and developed for different themes and purposes. Present day an autism-related web application, being one of the most demanding applications requires effective, efficient and satisfactory services with a package of portability across all platforms. The success of a product significantly depends upon the factor of usability. A clear, concise, and user-interactive design interface is the key to a successful product or application. In the current literature reviewed, no particular design technique has so far been proposed to implement a multi-channel autism application. The objective of our study is to create two websites using Card sorting and Interactive Dialogue Model (IDM) on the same topic, compare between these two websites and perform a comparative study considering some parameters to find out which approach is a better approach for website making. We have developed an autism application using card sorting and IDM. An evaluation was carried out with a number of participants. As an outcome, we have proposed one design technique to produce an effective and easy-to-use web application for autistic children.","PeriodicalId":255498,"journal":{"name":"2022 25th International Conference on Computer and Information Technology (ICCIT)","volume":"582 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132447093","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

Circuit Implementation of Vernam Cipher-based Data Encryption Using Cellular Automata 基于Vernam密码的元胞自动机数据加密电路实现

2022 25th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2022-12-17 DOI: 10.1109/ICCIT57492.2022.10055452

Shafayeth Jamil, Nishat Tasnim Hiramony, Tanshia Tahreen Tanisha, Rajat Chakraborty

引用次数: 0

LSTM-ANN Based Price Hike Sentiment Analysis from Bangla Social Media Comments 基于LSTM-ANN的孟加拉社交媒体评论涨价情绪分析

2022 25th International Conference on Computer and Information Technology (ICCIT) Pub Date : 2022-12-17 DOI: 10.1109/ICCIT57492.2022.10055290

Sovon Chakraborty, Muhammad Borahn Uddin Talukdar, Muhammed Yaseen Morshed Adib, Sowmen Mitra, Md. Golam Rabiul Alam

{"title":"LSTM-ANN Based Price Hike Sentiment Analysis from Bangla Social Media Comments","authors":"Sovon Chakraborty, Muhammad Borahn Uddin Talukdar, Muhammed Yaseen Morshed Adib, Sowmen Mitra, Md. Golam Rabiul Alam","doi":"10.1109/ICCIT57492.2022.10055290","DOIUrl":"https://doi.org/10.1109/ICCIT57492.2022.10055290","url":null,"abstract":"Price hike has always been a substantial concern for people all over the world. The crisis gets more conspicuous, and people find themselves more confounded when even the bare minimum of expenses still exceeds the amount they can get to earn. This tension tends to invite chaos in society as the number of people affected increases. Bangladesh is currently undergoing a formidable wave of price hikes. People have been expressing mixed reactions on social media regarding this issue. Hence, understanding the overall public sentiment can be crucial for policymaking and preventing chaos in society. This study utilizes social media comments for analyzing underlying sentiments. Data were collected from the Facebook pages of some popular Bangladeshi media for this purpose, and thereby a specialized dataset was constructed. The dataset contains 2000 public comments annotated with three polarity values- positive, negative, and neutral. A hybrid LSTM-ANN deep architecture has been exploited in this research. The model outperforms other state-of- the-art models in terms of less trainable parameters along with an F1-score of 88.47%.","PeriodicalId":255498,"journal":{"name":"2022 25th International Conference on Computer and Information Technology (ICCIT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130483491","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