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Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation

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Proceedings of the ACM on Human-computer Interaction 2023年第CSCW1期7卷 1-32页

作者： Zhang, Angie Walker, Olympia Nguyen, Kaci Dai, Jiajun Chen, Anqing Lee, Min Kyung School of Information The University of Texas Austin United States Dept. of Computer Science The University of Texas Austin United States School of Business The University of Texas Austin United States Dept. of Electrical and Computer Engineering The University of Texas Austin United States

Research exploring how to support decision-making has often used machine learning to automate or assist human decisions. We take an alternative approach for improving decision-making, using machine learning to help stakeholders surface ways to improve and make fairer decision-making processes. We created "Deliberating with AI", a web tool that enables people to create and evaluate ML models in order to examine strengths and shortcomings of past decision-making and deliberate on how to improve future decisions. We apply this tool to a context of people selection, having stakeholders - -decision makers (faculty) and decision subjects (students) - -use the tool to improve graduate school admission decisions. Through our case study, we demonstrate how the stakeholders used the web tool to create ML models that they used as boundary objects to deliberate over organization decision-making practices. We share insights from our study to inform future research on stakeholder-centered participatory AI design and technology for organizational decision-making. © 2023 ACM.

关键词： Decision making

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Inflation Prediction: A Comparative Study of ARIMA and LSTM Models Across Different Temporal Resolutions 3

Inflation Prediction: A Comparative Study of ARIMA and LSTM ...

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3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Lakshmi Narayanaa, T. Skandarsini, R.R. Ida, S. Jhansi Sabapathy, S. Rathana Nanthitha, P. RMK Engineering College Dept. of Computer Science and Business Systems Thiruvallur India Panimalar Engineering College Dept. of Information Technology Chennai India

ISBN: (纸本)9798350343632

This research study focuses on the prediction of inflation rates using two distinct models, Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM), tailored to accommodate the temporal resolutions of monthly and quarterly inflation data. While a comprehensive evaluation across varying time horizons was not conducted, the results suggest that the ARIMA model excels in short-term forecasting, as evidenced by its impressive performance on a 2021 holdout dataset. Conversely, the LSTM model displays potential for medium-term predictions. This study underscores the significance of aligning forecasting models with data characteristics, emphasizes the importance of temporal resolution, and discusses potential avenues for improvement, such as multivariate modeling or alternative techniques like Prophet. The findings have broad implications for economists, policymakers, and analysts seeking precise inflation forecasts, shedding light on the nuanced interplay between models and data in the domain of inflation prediction. © 2023 IEEE.

关键词： ARIMA Model Inflation Prediction LSTM Model Short-Term Forecasting Temporal Resolution Time Series Forecasting

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Electric Vehicle Charging System Using RFID and IoT for Enhanced User Experience 5

Electric Vehicle Charging System Using RFID and IoT for Enha...

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5th IEEE Middle East and North Africa COMMunications Conference, MENACOMM 2025

作者： Hassain, Md Mehedi Haque Jamil, Injamul Hoque, Md Mahmudul Hasan, Md. Jahid International Islamic University Chittagong Dept. of Electrical and Electronics Engineering Chittagong Bangladesh University of Greenwich Dept. of Computing and Mathematical Sciences London United Kingdom CCN University of Science and Technology Dept. of Computer Science and Engineering Cumilla Bangladesh Comilla University Dept. of Information and Communication Technology Cumilla Bangladesh

ISBN: (纸本)9798331519957

Electric vehicles (EVs) are surging in popularity globally, offering a greener and more energy-efficient alternative to traditional cars. Our research aims to develop an RFID based system designed to automate EV charging with minimal user input. This system integrates RFID readers, tags, a microcontroller, and a relay module to manage and monitor charging sessions efficiently. An IoT platform supports real time monitoring and remote control, while a secure payment mechanism handles transactions seamlessly. RFID tags identify vehicles for automatic charging initiation, and the relay module prevents overcharging by disconnecting power after a set time. The system uses MQTT for data transmission and offers real-Time insights into energy use and account balances. All information is updated and displayed in real-Time on the server. MySQL ensures scalability, enabling effective handling of large volumes of data. The mobile application dashboard provides a view of the charging and discharging processes for user monitoring, and an email notification is sent after the recharge. EV battery charging status is monitored through visual graphs. Key benefits include a streamlined user experience, improved charging management, and support for EV adoption. This innovation advances sustainable mobility with a user friendly, efficient charging solution. © 2025 IEEE.

关键词： Radio frequency identification (RFID)

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Hash Tag-Based Sentiment Analysis Using A Deep Learning Approach 10

Hash Tag-Based Sentiment Analysis Using A Deep Learning Appr...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Venkatesan, R. Sangeetha, M. Nivedha, S. Selvakumar, M. Chandru, K.S. Parthasarathi, P. Bannari Amman Institute of Technology Department of Information Technology Erode India K S Rangasamy College of Technology Department of Information Technology Namakkal India Hindusthan College of Engg and Technology Dept. of Computer Science & Engineering Coimbatore India Bannari Amman Institute of Technology Dept. Computer Science & Business Systems Erode India Bannari Amman Institute of Technology Dept. Computer Science and Engineering Erode India

ISBN: (纸本)9798350384369

Social commerce uses a variety of social networking sites like Facebook, Instagram, Twitter, Pinterest, and business Whatsapp as a platform to promote products and services. Since advertising, a product, or service in s-comm will reach as high as a possible number of users on networking sites. Ads will spread virally by sharing among friends and friends of friends. So that wider reachability is possible and shortly will get the customer for our business. The success of an s-comm campaign is measured by the degree to which consumers interact with the sellers through review comments, likes, and shares between friends. Customer behavior analysis is needed for s-comm marketing because social commerce can significantly boost economic growth. The sentiment analysis of customer recommendations was investigated using a dataset of women's s-comm apparel hashtags and reviews. So for such reviews are experimented with different machine learning algorithms (Decision tree, SVM, Random Forest, KNN, Naïve Bayes and LSTM). These models handled the common English reviews and compared the metrics (Accuracy, Sensitivity and Specificity) with one another. Instead of working with individual model, this paper introduces a novel hybrid approach that integrates CNN and Ada Boost LSTM algorithms to provide better results in sentiment analysis when compared to other machine learning algorithms mentioned above. While considering the hash tag with common review comments the hybrid system is out performed. The comparison analysis is done for performance matrices namely accuracy of 98%, specificity of 98.1%, and sensitivity of 98.1%. In the s-commerce transaction industry, this hybrid approach will help to create a deeper understanding of consumer sentiment analysis and psychologically attract clients. © 2024 IEEE.

关键词： Tweets

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Estimation of Clinical Parameters for Glaucoma Detection Using Image Processing and Deep Learning Techniques from the Biomedical Human Eye Images

Estimation of Clinical Parameters for Glaucoma Detection Usi...

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2024 International Conference on Emerging Innovations and Advanced Computing, INNOCOMP 2024

作者： Guru Prasad, M.S. Chandrappa, S. Dhasmana, Gulshan Naveen Kumar, H.N. Mathpati, Shilpa Gangodkar, Ninad Dept. of Computer Science and Engg. Dehradun India Dept. of Computer Science and Engneering Bengaluru India Vidyavardhaka College of Engineering Department of ECE Mysuru India School of Computing and Information Technology REVA University Bengaluru India

ISBN: (纸本)9798350376470

The technique for distinguishing the essential glaucoma is being exhibited in this segment utilizing a changed neural system with the back spread calculation ideas. The morphological administrators ideas are being utilized for the handling of the cup and disc, in the sense, the cup and the disc zones are discovered from which the proportion is registered, from where the illness can be recognition seeing the proportion. Utilizing an updated highlight extraction process, the highlights of the disc portion and the cup can be discovered, which could be utilized in the idea of cup to plate apportion (cup to disc ratio) recognition, regardless of whether the given test image is glaucomatic or not. Classification is also done using artificial neural networks (ANN) along with the training process. Simulations have been done in the Matlab environment by developing. m codes. Once the developed program is run, the simulation results are observed. From the simulation results, it can be observed that using the computed values of the cup to disc ratio, the severity of the disease can be computed (whether it is normal or moderate or severe glaucoma). Databases have been taken from the hospitals and on-line standard websites. The quantitative results are tabulated in a table. Finally, it was found that after taking a survey of 50 images, 16 were affected with normal, 16 were affected with moderate and the rest were affected with severe case of glaucoma. The Matlab results of the simulation done using coding demonstrated the profoundness with respect to the strategy proposed or developed in this exploration write-up using the concept of neural networks. © 2024 IEEE.

关键词： MATLAB

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High Gain, E-Shaped Microstrip Antenna with Two Identical Slits for 5G Applications in the 60 GHz Band 3

High Gain, E-Shaped Microstrip Antenna with Two Identical Sl...

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3rd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2023

作者： Ali, Ala'a N. S. Gaid, AbdulGuddoos S. A. Saeed, Mamoon M. Saeed, Rashid A. Hawash, Burkan Taiz University Faculty of Engineering & Information Technology Dept. of Communications & Computer Taiz Yemen Faculty of Engineering Dept. Communications & Electronics Engineering Sana'a Yemen College of Computers & Information Technology Taif University Dept. of Computer Engineering Taif21944 Saudi Arabia Faculty of Information Science & Technology Selangor Malaysia

ISBN: (纸本)9798350305333

This article presents a simple, high-gain, E-shaped antenna suitable for 5G applications in the unlicensed 60 GHz band, characterized by high absorption and path losses. In order to optimize the reflection coefficient performance, enhance the gain, and adjust the resonance frequency of the proposed antenna, two identical slits are incorporated into the front edge of the radiating patch. The proposed structure is built on a Rogers RT/Duroid 5880 dielectric substrate, characterized by a thickness of 0.118 mm, a dielectric constant of 2.2, and a tangent loss of 0.0009. The optimized design with a compact size of 3.8 x 6 x 0.118 mm3 achieves an impedance bandwidth ( © 2023 IEEE.

关键词： Radiation efficiency

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Machine Learning-Based Wine Quality Prediction 2

Machine Learning-Based Wine Quality Prediction

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2nd IEEE International Conference on Advances in information Technology, ICAIT 2024

作者： Dhondiyal, Shiv Ashish Kumar, Rohit Verma, Himanshu Dhyani, Ashish Singh, Sumeshwar Dept. of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India GNIOT Institute of Professional Studies Greater Noida India Dept. of Hospitality Management Graphic Era Deemed to be University India Dept. of Computer Science and Engineering Jaypee Institute of information technology sector 62 India

ISBN: (纸本)9798350383867

The main goal of this attempt is to assess the quality of wine and determine if it is excellent or terrible. Humans have been engaging in the act of tasting for generations and have consistently made predictions using their sensory organs. A number of industries have recently embraced new technology and used it to a variety of uses. However, human knowledge is required in a number of businesses, such as product quality assurance. With the increasing popularity of the product, modern innovations have increased the cost of the treatment. To ensure the quality of the output, this study looks at a number of machines learning algorithms, including Random Forest Classification, Decision Tree classifiers, and Support Vector Machines (SVM). These methods make use of the product's current attributes to simplify the quality control procedure. © 2024 IEEE.

关键词： Adversarial machine learning

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A Study on Gait Pattern Identification and MNA Detection Methodologies used for Human Medical Diagnosis using Wearable Sensors 7

A Study on Gait Pattern Identification and MNA Detection Met...

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7th International Conference on Trends in Electronics and Informatics, ICOEI 2023

作者： Pushpalatha, S. Math, Shrishail Puiari, Chandrakanth G Dr. Ambedkar Institute of Technology Dept. of Information Science and Engineering Bengaluru India Sri Krishna Institute of Technology Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350397284

In ambulatory monitoring, different sensors such as pulse oximetry, accelerometer, gyroscope, etc. are used for monitoring probes. Generally, these sensors are used for monitoring daily physical activity, stress, and sleep pattern of the respective probe. However, the measurement obtained from these sensors is highly affected due to motion and noise artifacts (MNAs). This study conducts a survey of various existing methodologies presented for mitigating motion and noise artifact of measurement obtained through wearable sensors. The survey is composed of both supervised and non-supervised techniques used for mitigating MNAs, detecting HAR, and classifying Obstructive Sleep Apnea (OSA) using wearables. This survey further highlights research issues in monitoring probes using wearable sensors and presents a future solution to overcome research issues. © 2023 IEEE.

关键词： Wearable sensors

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A Self-Supervised Semantic Segmentation Method for Identifying Barrett' s Esophagus in Endoscopic Images 24

A Self-Supervised Semantic Segmentation Method for Identifyi...

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6th Asia Pacific information Technology Conference, APIT 2024

作者： Lin, Guo-Shiang Chang, Ku-Yaw Hsu, Wen-Teng Yang, Sheng-Chih Yan, Shen-Lei Dept. of Artificial Intelligence and Computer Engineering National Chin-Yi University of Technology Taiwan Dept. of Computer Science and Information Engineering National Chin-Yi University of Technology Taiwan Dept. of Internal Medicine Chang Bing Show Chwan Memorial Hospital Taiwan

ISBN: (纸本)9798400716218

Barrett's esophagus is considered a precancerous condition that may lead to esophageal cancer. The condition is usually diagnosed through an endoscopy with biopsy. This careful imaging examination is quite labor-intensive and usually lacks of diagnostic consistency. In this paper, a computer-aided diagnosis (CAD) method was proposed to assist pathologist in Barrett's esophagus diagnosis from endoscopic images. The proposed semantic segmentation was built based on the U-Net architecture, which features capturing detailed spatial information and context to produce accurate pixel-wise predictions. An autoencoder, which is quite capable of learning a compact and meaningful representation of the input data, is incorporated to achieve self-supervised learning. A two-stage pretraining for the encoder and the decoder is adopted for better performance and reduced data requirements. The proposed method can extract features and patterns from unlabeled data without requiring human annotation or labels, which is very suitable in many biomedical image analyses. The experimental results show that the segmentation accuracy with mean pixel accuracy, mean dice coefficient, and mIoU reaches 98.20%, 87.96%, and 83.18% respectively, indicating that the proposed method has a good performance on the identification of Barrett's esophagus in endoscopic images. © 2024 Owner/Author.

关键词： Semantic Segmentation

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Project Management and Evaluation system Using Node JS 3

Project Management and Evaluation system Using Node JS

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Kumar, Sanjay Umrao, Sandhya Gupta, Harsha Saxena, Kumud Greater Noida Institute of Technology Dept. of Computer Science Engineering Greater Noida India Noida Institute of Engineering and Technology Dept. of Computer Science Engineering Greater Noida India Noida Institute of Engineering and Technology Dept. of Information Technology Greater Noida India

ISBN: (纸本)9798350399264

Project Management is a social hub for students to interact and showcase their projects in a dynamic environment where other students and faculty can also put their thoughts. Major Project is the essential part of student's graduation, where they need to apply all the learning and build something innovative and inspiring. Students don't understand that what other students are developing because of no interaction. Thus with the help of this application, it is tried to solve this problem. An application is proposed to address about how student can go through an application to identify their capabilities and get an idea to develop a project accordingly. Students will be able to address a problem and find a solution to it, although through its inception organizing major projects can be a hassle therefore It is aptly called "Project Management"as students can join in a league with like-minded students for their major projects. Depending on factors like area of interest, the number of milestones covered and the grade received, the live popularity project tracking system provides a highly-standardized, automated technique for ranking. Top 10 projects are displayed on the homepage based on these *** are two key features in PMi)User Interactionii)Project Progress Tracking. © 2023 IEEE.

关键词： Students

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