2022 24th International Multitopic Conference (INMIC)最新文献

Human Activity Recognition via Smartphone Embedded Sensor using Multi-Class SVM 基于多类支持向量机的智能手机嵌入式传感器人体活动识别

2022 24th International Multitopic Conference (INMIC) Pub Date : 2022-10-21 DOI: 10.1109/INMIC56986.2022.9972927

Danyal, Usman Azmat

{"title":"Human Activity Recognition via Smartphone Embedded Sensor using Multi-Class SVM","authors":"Danyal, Usman Azmat","doi":"10.1109/INMIC56986.2022.9972927","DOIUrl":"https://doi.org/10.1109/INMIC56986.2022.9972927","url":null,"abstract":"Human Activity tracking is the process of detection and understanding of the human activity. It can be done by analyzing human motion behavior data extracted from different smartphone-embedded sensors. Recognizing human activity has become widely popular and particularly attracted many researchers in different industries. Activity recognition has become increasingly important in many areas, especially for the recognition of fitness, sports, and health monitoring. This paper propose a robust model that is trained and tested on remotely extracted data from the smartphone-embedded inertial sensor. Initially, the system clean the input data and then performs windowing and segmentation. After pre-processing, a number of features are extracted. Further, the Lukasiewicz similarity measure (LS) based features selection is used to reduce the features set by removing the least important features. In the next step, the Yeo-Johnson power transformation method is utilized to optimize the selected features. The optimized features set is then forwarded to the multi-class support vector machines (SVM) classifier. The system was designed and experimented with over a well-known dataset named WISDM. The presented model performed well by achieving a mean accuracy rate of 94%.","PeriodicalId":404424,"journal":{"name":"2022 24th International Multitopic Conference (INMIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128981881","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

Enhancing Short-Term Load Forecasting using ES-dRNN with Context Vector 基于上下文向量的ES-dRNN短期负荷预测

2022 24th International Multitopic Conference (INMIC) Pub Date : 2022-10-21 DOI: 10.1109/INMIC56986.2022.9972954

Q. Ain, Sohail Iqbal

{"title":"Enhancing Short-Term Load Forecasting using ES-dRNN with Context Vector","authors":"Q. Ain, Sohail Iqbal","doi":"10.1109/INMIC56986.2022.9972954","DOIUrl":"https://doi.org/10.1109/INMIC56986.2022.9972954","url":null,"abstract":"Electrical load forecasting is an integral part of power system planning, operation, and control. Accurate load forecasting is beneficial for making various operational decisions such as energy generation, reliability analysis, and dispatch scheduling of generated energy. However, short-term load fore-casting is difficult due to the complexity posed by the nature of load time series as it expresses multiple seasonality and nonlinear trend. In this paper, we propose an extension of a novel hybrid hierarchical deep learning-based forecast model which incorporates multiple seasonality. The original groundbreaking hybrid forecasting model is developed by Smyl. The model presented in this paper is based on a dilated recurrent neural network with a context vector by integrating exponential smoothing (EScdRNN). Exponential smoothing performs the adaptive time series processing whereas dilated recurrent neural network using context vector helps in cross-learning. This helps in the selection of useful input information which leads to improved accuracy. The results of the proposed methodology are compared with different statistical machine learning methods which show the potential of our proposed approach in terms of increased accuracy.","PeriodicalId":404424,"journal":{"name":"2022 24th International Multitopic Conference (INMIC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127666544","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

Acupressure based Therapeutic Smart Shoe for Developing Countries 针对发展中国家的指压治疗型智能鞋

2022 24th International Multitopic Conference (INMIC) Pub Date : 2022-10-21 DOI: 10.1109/INMIC56986.2022.9972978

Syed Muhammad Razi Kazim Naqvi, Asma Iqbal, Sumbala Ameen, Namra Afzal

引用次数: 0

BaggedUNet: Deep Machine Vision approach for Polyps Segmentation in Gastrointestinal Tract 基于深度机器视觉的胃肠道息肉分割方法

2022 24th International Multitopic Conference (INMIC) Pub Date : 2022-10-21 DOI: 10.1109/INMIC56986.2022.9972945

Syed Muhammad Faraz Ali, M. Tahir, A. B. Khalid

{"title":"BaggedUNet: Deep Machine Vision approach for Polyps Segmentation in Gastrointestinal Tract","authors":"Syed Muhammad Faraz Ali, M. Tahir, A. B. Khalid","doi":"10.1109/INMIC56986.2022.9972945","DOIUrl":"https://doi.org/10.1109/INMIC56986.2022.9972945","url":null,"abstract":"Polyps segmentation is one of the key medical challenges in the gastrointestinal (GI) tract. Polyps segmentation provides the early-stage diagnosis of polyps which may lead to colon cancer in the GI tract. Deep learning models such as U-Net can segment polyps with good performance. But individual deep learning models may suffer from generalization problems. Deep ensemble learning combines the power of both deep and ensemble learning so that the final combined model has better generalization ability. In this paper, a bagging based U-Net architecture (BaggedUNet) is proposed to improve the polyps segmentation in GI-Tract. Our proposed BaggedUNet model trains several lighter U-Net architectures. Decisions from various models are then combined using majority voting. The proposed method is compared with recent deep learning architectures: U-Net and ResUNet++. The evaluation of models is performed using quantitative metrics including Dice coefficient and mean Intersection over Union (mIoU). The proposed BaggedUNet architecture was able to achieve 3 %-9 % improvement on different evaluation metrics on two publicly available datasets for polyps segmentation.","PeriodicalId":404424,"journal":{"name":"2022 24th International Multitopic Conference (INMIC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132074933","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

Class Incremental Learning for Visual Task using Knowledge Distillation 基于知识蒸馏的视觉任务类增量学习

2022 24th International Multitopic Conference (INMIC) Pub Date : 2022-10-21 DOI: 10.1109/INMIC56986.2022.9972924

Usman Tahir, Amanullah Yasin, Ahmad Jalal

引用次数: 0

A Machine Learning based Approach to Identify User Interests from Social Data 基于机器学习的社交数据用户兴趣识别方法

2022 24th International Multitopic Conference (INMIC) Pub Date : 2022-10-21 DOI: 10.1109/INMIC56986.2022.9972956

R. Tahir, M. Naeem

{"title":"A Machine Learning based Approach to Identify User Interests from Social Data","authors":"R. Tahir, M. Naeem","doi":"10.1109/INMIC56986.2022.9972956","DOIUrl":"https://doi.org/10.1109/INMIC56986.2022.9972956","url":null,"abstract":"Social media platforms like Twitter, Facebook, Instagram, etc., are considered a common source of extracting information about individuals, such as their needs, interests, and opinions. Our major contribution in this paper is to identify user interests and desires related to the fashion industry in Pakistan. Since people in Pakistan mostly write tweets and reviews in Roman Urdu, the dataset we focused on in this research was comprised of Roman Urdu Tweets and Google Map reviews. From the literature, we observed that not much effort has been done on Roman Urdu tweets and reviews because of its being a low resource language. In terms of methodology, we applied LDA, LSA, and BERT for topic modeling; Vadar combined with TextBlob and DistilBert for sentiment analysis; and K-Means for identifying user clusters with similar interests. In our experiments, we used 15000 tweets and 6000 Google reviews. We were able to create five distinct clusters for each brand. These clusters were further used to track the users based on their interests. We evaluated the performance of our approach and validated it empirically based on Cohen's Kappa score, and achieved a score of 0.45 that shows moderate agreement between human and machine.","PeriodicalId":404424,"journal":{"name":"2022 24th International Multitopic Conference (INMIC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126404144","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

Design of Power Divider for Groove Gap Waveguide at Millimeter Wave Spectrum 毫米波频谱沟槽波导功率分配器的设计

2022 24th International Multitopic Conference (INMIC) Pub Date : 2022-10-21 DOI: 10.1109/INMIC56986.2022.9972969

Ghiayas Tahir, Arshad Hassan

引用次数: 0

Moderating Effect of Entrepreneurial Orientation on Attitude Towards Intent to Start a New Venture 创业取向对创业意向态度的调节作用

2022 24th International Multitopic Conference (INMIC) Pub Date : 2022-10-21 DOI: 10.1109/INMIC56986.2022.9972971

Chaudry Bilal Ahmad Khan

引用次数: 0

Performance Evaluation of Priority Mechanisms for Industrial Wireless Sensor Networks 工业无线传感器网络优先级机制的性能评估

2022 24th International Multitopic Conference (INMIC) Pub Date : 2022-10-21 DOI: 10.1109/INMIC56986.2022.9972886

A. Khan, S. Siddiqui

引用次数: 0

A Comparative Study of Various Optimization Techniques to Size a Hybrid Renewable Energy System 混合可再生能源系统规模优化方法的比较研究

2022 24th International Multitopic Conference (INMIC) Pub Date : 2022-10-21 DOI: 10.1109/INMIC56986.2022.9972951

Rabia Fazal Dad, S. Saleem

引用次数: 0