Pub Date : 2021-12-21DOI: 10.1109/NICS54270.2021.9701560
T. Le-Tien, Duy Ho-Van, Nhu Pham-Ng-Quynh, Hanh Phan-Xuan, Tuan Nguyen-Thanh
The crucial problem of forensic techniquesis is how to detect/recognize tampered images through public media platforms under the attactks of subjective modifications. Because of many accessible photoshop programs, an image/video such as in Facebook, Instagram, Reddit Twitter, etc. can be easily tampered to falsify the information within the image. Accoding to the requirement of an efficient method for detecting fake images, we have developed modifed CNN models which are combined with the super-resolution approach to solve this issue. In the paper, we present an appropriate method using CNN models to detect tampered images with the increase in resolutions of the tampered areas, the proposed model can detect and point out the areas that have been tampered. The ResNet50 and mUNet modified models are used for classification and segmentation respectively. With the developed models, the results were given with an accuracy of at least 90% on the evaluation sets.
{"title":"Modified CNN model-based Forgery Detection applied to Multiple-Resolution Tampered Images","authors":"T. Le-Tien, Duy Ho-Van, Nhu Pham-Ng-Quynh, Hanh Phan-Xuan, Tuan Nguyen-Thanh","doi":"10.1109/NICS54270.2021.9701560","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701560","url":null,"abstract":"The crucial problem of forensic techniquesis is how to detect/recognize tampered images through public media platforms under the attactks of subjective modifications. Because of many accessible photoshop programs, an image/video such as in Facebook, Instagram, Reddit Twitter, etc. can be easily tampered to falsify the information within the image. Accoding to the requirement of an efficient method for detecting fake images, we have developed modifed CNN models which are combined with the super-resolution approach to solve this issue. In the paper, we present an appropriate method using CNN models to detect tampered images with the increase in resolutions of the tampered areas, the proposed model can detect and point out the areas that have been tampered. The ResNet50 and mUNet modified models are used for classification and segmentation respectively. With the developed models, the results were given with an accuracy of at least 90% on the evaluation sets.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124576537","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}
Pub Date : 2021-12-21DOI: 10.1109/NICS54270.2021.9701470
Nam Nguyen-Tat, Luong Nguyen-Xuan, Thanh Nguyen
The TDK’s MIL-STD-461F/G CE102-comp1iant test is a semi-automatic solution using the leading edge standards-compliant MXE EMI test receiver Keysight N9038A and the authorized TDK®Emission Labs 9.68 software package. This however still results in longer measuring time and inferior measuring performance. Hence, a novel fully automatic test scheme in accordance with control software integrating suitable compensation algorithms is proposed to surmount these disadvantages. The proposal though uses less advanced models such as the low-cost X-Series N9000A CXA, or the high-performance X-Series N9030A PXA Keysight signal analyzers yet creates higher measuring performance in a shorter time. The test configuration with related problems are investigated and resolved then the experimental results are presented to compare with that of the TDK’s solution showing the proposal’s advantages.
{"title":"A Cost-Effective High-Performance Conducted Emission Test Solution to Comply with MIL-STD-461F/G Standard","authors":"Nam Nguyen-Tat, Luong Nguyen-Xuan, Thanh Nguyen","doi":"10.1109/NICS54270.2021.9701470","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701470","url":null,"abstract":"The TDK’s MIL-STD-461F/G CE102-comp1iant test is a semi-automatic solution using the leading edge standards-compliant MXE EMI test receiver Keysight N9038A and the authorized TDK®Emission Labs 9.68 software package. This however still results in longer measuring time and inferior measuring performance. Hence, a novel fully automatic test scheme in accordance with control software integrating suitable compensation algorithms is proposed to surmount these disadvantages. The proposal though uses less advanced models such as the low-cost X-Series N9000A CXA, or the high-performance X-Series N9030A PXA Keysight signal analyzers yet creates higher measuring performance in a shorter time. The test configuration with related problems are investigated and resolved then the experimental results are presented to compare with that of the TDK’s solution showing the proposal’s advantages.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115337768","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}
Pub Date : 2021-12-21DOI: 10.1109/NICS54270.2021.9701485
Minh Le Nguyen, X. Tran, Vu-Duc Ngo, Quang-Kien Trinh
In modern wireless communication, Multiple-Input Multiple-Output (MIMO) takes advantage of spatial diversity to increase the capacity and spectrum efficiency effectively. This technology, however, poses many technical challenges for device implementation. optimizing the computational workload with an acceptable bit error rate (BER) becomes the critical design problem for the MIMO relay station. This paper proposes a novel detection algorithm for the wireless MIMO in the two-way relay station (TWRS). We adopt the relay architecture that doubles the receive antennas for communication data between two MIMO terminals. The core processing block employs a variable K-Best detection (V-KBD). The simulation for $4times 4$ MIMO two-way relay results shows that our relay model could achieve BER close to the conventional SD algorithm systems with fixed and lower complexity.
{"title":"A Low Complexity Detector For Two-Way Relay Stations in Wireless MIMO-SDM-PNC Systems","authors":"Minh Le Nguyen, X. Tran, Vu-Duc Ngo, Quang-Kien Trinh","doi":"10.1109/NICS54270.2021.9701485","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701485","url":null,"abstract":"In modern wireless communication, Multiple-Input Multiple-Output (MIMO) takes advantage of spatial diversity to increase the capacity and spectrum efficiency effectively. This technology, however, poses many technical challenges for device implementation. optimizing the computational workload with an acceptable bit error rate (BER) becomes the critical design problem for the MIMO relay station. This paper proposes a novel detection algorithm for the wireless MIMO in the two-way relay station (TWRS). We adopt the relay architecture that doubles the receive antennas for communication data between two MIMO terminals. The core processing block employs a variable K-Best detection (V-KBD). The simulation for $4times 4$ MIMO two-way relay results shows that our relay model could achieve BER close to the conventional SD algorithm systems with fixed and lower complexity.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132570180","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}
Pub Date : 2021-12-21DOI: 10.1109/NICS54270.2021.9701540
Tu N. Vu, T. T. Dinh, Nguyen D. Vo, T. Tran, Khang Nguyen
Surveillance systems have long been considered as an effective tool to capture various realistic abnormal actions or events in various domains such as traffic management or security. With the smart city development, thousand of installed surveillance cameras have played a vital role in detection and prevention of dangerous events. However, there is a lack of anomaly datasets for developing automatic anomaly detection systems in Vietnam. In this study, we introduce a new dataset named VNAnomaly for anomaly detection in Vietnam. Moreover, we also conduct a thorough evaluation of current state-of-the-art for unsupervised anomaly detection methods based on deep architectures including MLEP, Future frame prediction, MNAD, and MNAD with modified inference on benchmark datasets and our dataset. Experimental results indicate that the proposed method almost always outperforms the competitors and achieves the best performance in terms of Area Under the Curve (AUC) score at 61.14%.
监控系统长期以来一直被认为是在交通管理或安全等各个领域捕捉各种现实异常行为或事件的有效工具。随着智慧城市的发展，成千上万的监控摄像头在发现和预防危险事件方面发挥了至关重要的作用。然而，越南缺乏用于开发自动异常检测系统的异常数据集。在本研究中，我们引入了一个名为VNAnomaly的新数据集，用于越南的异常检测。此外，我们还对基于深度架构的无监督异常检测方法进行了全面的评估，包括MLEP、未来帧预测、MNAD和MNAD，并对基准数据集和我们的数据集进行了修改推理。实验结果表明，该方法几乎总是优于竞争对手，在曲线下面积(Area Under the Curve, AUC)得分方面达到了61.14%的最佳性能。
{"title":"VNAnomaly: A novel Vietnam surveillance video dataset for anomaly detection","authors":"Tu N. Vu, T. T. Dinh, Nguyen D. Vo, T. Tran, Khang Nguyen","doi":"10.1109/NICS54270.2021.9701540","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701540","url":null,"abstract":"Surveillance systems have long been considered as an effective tool to capture various realistic abnormal actions or events in various domains such as traffic management or security. With the smart city development, thousand of installed surveillance cameras have played a vital role in detection and prevention of dangerous events. However, there is a lack of anomaly datasets for developing automatic anomaly detection systems in Vietnam. In this study, we introduce a new dataset named VNAnomaly for anomaly detection in Vietnam. Moreover, we also conduct a thorough evaluation of current state-of-the-art for unsupervised anomaly detection methods based on deep architectures including MLEP, Future frame prediction, MNAD, and MNAD with modified inference on benchmark datasets and our dataset. Experimental results indicate that the proposed method almost always outperforms the competitors and achieves the best performance in terms of Area Under the Curve (AUC) score at 61.14%.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131440976","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}
Pub Date : 2021-12-21DOI: 10.1109/NICS54270.2021.9701532
Vinh Tran-Quang, Anh Ha-Ngoc
In aquaculture, there is always a potential risk of changing the water environment, hindering the growth of aquatic products, or even causing mass death, causing great damage to farmers. Therefore, it is vital to predict the quality of water resources early. A lot of methods have been introduced, including SVM, GM, RNN. These methods focus only on forecasting water quality in general, as well as fewer diversity of forecasting parameters, but do not focus on water characteristics in aquaculture. In this paper, we propose an aquaculture environment prediction based on an improved LSTM (long-short-term memory network) deep learning model. We conduct a characteristic analysis of the environmental parameters of lobster culture. Then use these features to improve the traditional LSTM model to improve the accuracy of the prediction model. The data used to train and test the proposed model are exploited from the actual set of environmental parameters measurement data for lobster farming of the environmental monitoring center in the Xuan Dai bay area, Phu Yen province, Vietnam. The prediction results of the improved LSTM model are compared with those of the RNN models. The results show that the improved LSTM model performs more accurate predictions of changes in aquatic environmental parameters than other compared solutions.
{"title":"Aquaculture Environment Prediction Based on Improved LSTM Deep Learning Model","authors":"Vinh Tran-Quang, Anh Ha-Ngoc","doi":"10.1109/NICS54270.2021.9701532","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701532","url":null,"abstract":"In aquaculture, there is always a potential risk of changing the water environment, hindering the growth of aquatic products, or even causing mass death, causing great damage to farmers. Therefore, it is vital to predict the quality of water resources early. A lot of methods have been introduced, including SVM, GM, RNN. These methods focus only on forecasting water quality in general, as well as fewer diversity of forecasting parameters, but do not focus on water characteristics in aquaculture. In this paper, we propose an aquaculture environment prediction based on an improved LSTM (long-short-term memory network) deep learning model. We conduct a characteristic analysis of the environmental parameters of lobster culture. Then use these features to improve the traditional LSTM model to improve the accuracy of the prediction model. The data used to train and test the proposed model are exploited from the actual set of environmental parameters measurement data for lobster farming of the environmental monitoring center in the Xuan Dai bay area, Phu Yen province, Vietnam. The prediction results of the improved LSTM model are compared with those of the RNN models. The results show that the improved LSTM model performs more accurate predictions of changes in aquatic environmental parameters than other compared solutions.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"79 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131894415","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}
Pub Date : 2021-12-21DOI: 10.1109/NICS54270.2021.9700990
Nguyen Thi Phuoc Van, Dao Minh Son, K. Zettsu
The lacking data from wearable sensors to solve different problems in the healthcare area is obvious since it is not easy to find enough volunteers to collect data. Moreover, human reacts very differently to medical treatment/ exercise levels/ stress and so on. Therefore, we need an advanced prediction model which can reuse the public data and can be adapt to personal data to predict health parameters. This paper introduces a solution for this issue. We present a novel personalized adaptive algorithm based on ensemble learning to predict sleeping efficiency, the proposed framework can be extended to solve many problems in healthcare applications. In this work, the global model is built based on ensemble learning with common features from all clients. The global model is then combined with the model from the client with more personalized features. The client model will learn and be updated model every day. Our proposed framework was tested in two data sets PMData and another private data set and showed better results than the conventional method. The proposed algorithm/ framework is a great step to solve the prediction problem in healthcare since each person has their own characteristics, responds differently to treatments/environment/stressful levels. The proposed algorithm is a big enhancement in building a health navigator system to enhance human health.
{"title":"A Personalized Adaptive Algorithm for Sleep Quality Prediction using Physiological and Environmental Sensing Data","authors":"Nguyen Thi Phuoc Van, Dao Minh Son, K. Zettsu","doi":"10.1109/NICS54270.2021.9700990","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9700990","url":null,"abstract":"The lacking data from wearable sensors to solve different problems in the healthcare area is obvious since it is not easy to find enough volunteers to collect data. Moreover, human reacts very differently to medical treatment/ exercise levels/ stress and so on. Therefore, we need an advanced prediction model which can reuse the public data and can be adapt to personal data to predict health parameters. This paper introduces a solution for this issue. We present a novel personalized adaptive algorithm based on ensemble learning to predict sleeping efficiency, the proposed framework can be extended to solve many problems in healthcare applications. In this work, the global model is built based on ensemble learning with common features from all clients. The global model is then combined with the model from the client with more personalized features. The client model will learn and be updated model every day. Our proposed framework was tested in two data sets PMData and another private data set and showed better results than the conventional method. The proposed algorithm/ framework is a great step to solve the prediction problem in healthcare since each person has their own characteristics, responds differently to treatments/environment/stressful levels. The proposed algorithm is a big enhancement in building a health navigator system to enhance human health.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132345796","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}
Pub Date : 2021-12-21DOI: 10.1109/NICS54270.2021.9701578
S. Guilley
Cryptographic libraries have become an integral part of every digital device. Studies have shown that these systems are not only vulnerable due to bugs in cryptographic libraries, but also due to misuse of these libraries. In this paper, we focus on vulnerabilities introduced by the application developer. We performed a survey on the potential misuse of well-known libraries such as PKCS #11. We introduce a generic tool CRYScanner, which is designed to identify such misuses during and post development. It works on the similar philosophy of an intrusion detection system for an internal network. The tool provides verification functions needed to check the safety of code, such as detecting incorrect call flow and input parameters. We performed a feature-wise comparison with the existing state of the art solutions. Our tool aimed to add more features, keeping all the capabilities of both static and dynamic analysis. We also show the detection of potential vulnerabilities in the several sample codes found online.
{"title":"Keynote Talk #1 : Cryscanner: Finding Cryptographic Libraries Misuse","authors":"S. Guilley","doi":"10.1109/NICS54270.2021.9701578","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701578","url":null,"abstract":"Cryptographic libraries have become an integral part of every digital device. Studies have shown that these systems are not only vulnerable due to bugs in cryptographic libraries, but also due to misuse of these libraries. In this paper, we focus on vulnerabilities introduced by the application developer. We performed a survey on the potential misuse of well-known libraries such as PKCS #11. We introduce a generic tool CRYScanner, which is designed to identify such misuses during and post development. It works on the similar philosophy of an intrusion detection system for an internal network. The tool provides verification functions needed to check the safety of code, such as detecting incorrect call flow and input parameters. We performed a feature-wise comparison with the existing state of the art solutions. Our tool aimed to add more features, keeping all the capabilities of both static and dynamic analysis. We also show the detection of potential vulnerabilities in the several sample codes found online.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114530798","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}
Pub Date : 2021-12-21DOI: 10.1109/NICS54270.2021.9701529
Nhat-Tuan Pham, Nhu-Y Tran-Van, Kim-Hung Le
Solar radiation is an unlimited source of clean energy with huge exploitation potential. To effectively exploit this valuable resource, the arrival of the solar forecast has shown an improvement in incorporating renewable energy into the grid system. Having accurate solar prediction would yield useful information to ensure the power grid’s stability, gain the advantage of renewable energy, and minimize mineral resource consumption. In this paper, we introduce a novel deep learning model, namely LSTM-Based Solar Power Prediction (LS-SPP), combining long short-term memory and a recurring neural network (LSTM-RNN). The proposed model is stacked with two LSTM layers to produce a high prediction accuracy based on historical meteorological time series. Our practical experiment on real datasets shows that the LS-SSP model achieves up to 96.78% accuracy in performance, higher than the best of competitors reported about 94.19%.
太阳辐射是一种无限量的清洁能源，具有巨大的开发潜力。为了有效地利用这一宝贵的资源，太阳能预测的到来显示了将可再生能源纳入电网系统的改进。准确的太阳能预测将提供有用的信息，以确保电网的稳定，获得可再生能源的优势，并最大限度地减少矿产资源的消耗。在本文中，我们介绍了一种新的深度学习模型，即LSTM-Based Solar Power Prediction (LS-SPP)，它结合了长短期记忆和循环神经网络(LSTM-RNN)。该模型与两个LSTM层叠加，在历史气象时间序列的基础上产生较高的预测精度。我们在真实数据集上的实际实验表明，LS-SSP模型的性能准确率高达96.78%，高于竞争对手报道的最佳准确率94.19%。
{"title":"LS-SPP: A LSTM-Based Solar Power Prediction Method from Weather Forecast Information","authors":"Nhat-Tuan Pham, Nhu-Y Tran-Van, Kim-Hung Le","doi":"10.1109/NICS54270.2021.9701529","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701529","url":null,"abstract":"Solar radiation is an unlimited source of clean energy with huge exploitation potential. To effectively exploit this valuable resource, the arrival of the solar forecast has shown an improvement in incorporating renewable energy into the grid system. Having accurate solar prediction would yield useful information to ensure the power grid’s stability, gain the advantage of renewable energy, and minimize mineral resource consumption. In this paper, we introduce a novel deep learning model, namely LSTM-Based Solar Power Prediction (LS-SPP), combining long short-term memory and a recurring neural network (LSTM-RNN). The proposed model is stacked with two LSTM layers to produce a high prediction accuracy based on historical meteorological time series. Our practical experiment on real datasets shows that the LS-SSP model achieves up to 96.78% accuracy in performance, higher than the best of competitors reported about 94.19%.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123523759","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}
Pub Date : 2021-12-21DOI: 10.1109/NICS54270.2021.9701536
Chinmoy Deka, S. Sah, Abhishek Shrivastava, Mridumoni Phukon, Lipsa Routray
Conversational AI has tremendous potential in different application domains due to its rapid development and improved accuracy in recognizing natural languages. Researchers have developed numerous applications and have shown state-of-the-art results. However, acceptability by users for such Conversational AI applications is imperative for successful deployment. This paper aims to assess a Conversational AI for a banking application in terms of usability, attractiveness, and intuitiveness. For this purpose, two different prototype versions were developed with varying dialog design and visual backgrounds. The experiment was conducted by letting 40 participants interact with the prototype versions, exploiting the Wizard-of-Oz (WoZ) paradigm, and administering three questionnaires to measure their perception of the Conversational AI prototype. Qualitative and Quantitative assessment of the questionnaires suggests that the Conversational AI prototype is highly usable, attractive, and intuitive, providing evidence that users will appreciate such Conversational AI in banking applications.
{"title":"Assessing a Voice-Based Conversational AI prototype for Banking Application","authors":"Chinmoy Deka, S. Sah, Abhishek Shrivastava, Mridumoni Phukon, Lipsa Routray","doi":"10.1109/NICS54270.2021.9701536","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701536","url":null,"abstract":"Conversational AI has tremendous potential in different application domains due to its rapid development and improved accuracy in recognizing natural languages. Researchers have developed numerous applications and have shown state-of-the-art results. However, acceptability by users for such Conversational AI applications is imperative for successful deployment. This paper aims to assess a Conversational AI for a banking application in terms of usability, attractiveness, and intuitiveness. For this purpose, two different prototype versions were developed with varying dialog design and visual backgrounds. The experiment was conducted by letting 40 participants interact with the prototype versions, exploiting the Wizard-of-Oz (WoZ) paradigm, and administering three questionnaires to measure their perception of the Conversational AI prototype. Qualitative and Quantitative assessment of the questionnaires suggests that the Conversational AI prototype is highly usable, attractive, and intuitive, providing evidence that users will appreciate such Conversational AI in banking applications.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115680205","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}
Pub Date : 2021-12-21DOI: 10.1109/NICS54270.2021.9701576
Doanh C. Bui, Truc Trinh, Nguyen D. Vo, Khang Nguyen
Scene text-based Image Captioning is the problem that generates caption for an input image using both contexts of image and scene text information. To improve the performance of this problem, in this paper, we propose two modules, Objects-augmented and Grid features augmentation, to enhance spatial location information and global information understanding in images based on M4C-Captioner architecture for text-based Image Captioning problems. Experimental results on the TextCaps dataset show that our method achieves superior performance compared with the M4C-Captioner baseline approach. Our highest result on the Standard Test set is 20.02% and 85.64% in the two metrics BLEU4 and CIDEr, respectively.
{"title":"An Augmented Embedding Spaces approach for Text-based Image Captioning","authors":"Doanh C. Bui, Truc Trinh, Nguyen D. Vo, Khang Nguyen","doi":"10.1109/NICS54270.2021.9701576","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701576","url":null,"abstract":"Scene text-based Image Captioning is the problem that generates caption for an input image using both contexts of image and scene text information. To improve the performance of this problem, in this paper, we propose two modules, Objects-augmented and Grid features augmentation, to enhance spatial location information and global information understanding in images based on M4C-Captioner architecture for text-based Image Captioning problems. Experimental results on the TextCaps dataset show that our method achieves superior performance compared with the M4C-Captioner baseline approach. Our highest result on the Standard Test set is 20.02% and 85.64% in the two metrics BLEU4 and CIDEr, respectively.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127827225","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：