Pub Date : 2023-05-20DOI: 10.20965/jaciii.2023.p0501
Lin Jia, Junming Zhang, Changfan Zhang, Jing He
In collaborative control of multi motors for heavy-duty locomotives, the output value of the motor frequently exceeds its maximum allowable value during power redistribution. This results in a saturated motor owing to the power redundancy of each wheel set of the train. In this study, an algorithm for the tracking control of a consistent total amount of the extended observer through anti-saturation is proposed. First, mathematical models of multi-motor traction systems are developed. The system includes uncertain parameter perturbations and external perturbations. Second, a new type of extended sliding mode observer (ESMO) is designed to reduce the influence of the tracking effect on the input saturation of the system. Subsequently, for collaborative control of multi motors in heavy-duty locomotives, a new scheme for dynamic and auxiliary anti-saturation compensation (anti-windup) is established. The perturbation observation results and the systems’ auxiliary status are respectively input into the sliding mode controller (SMC). A traction total-amount coordinated tracking control (TACTC) of multi motors is achieved to ensure consistency of the system’s total output torque and the given traction characteristic curve. Finally, simulations and tests are performed on the motor actuators to demonstrate a good control effect.
{"title":"Tracking Control Method of Multi Motor Actuator Saturation Based on Total Amount Consistency","authors":"Lin Jia, Junming Zhang, Changfan Zhang, Jing He","doi":"10.20965/jaciii.2023.p0501","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0501","url":null,"abstract":"In collaborative control of multi motors for heavy-duty locomotives, the output value of the motor frequently exceeds its maximum allowable value during power redistribution. This results in a saturated motor owing to the power redundancy of each wheel set of the train. In this study, an algorithm for the tracking control of a consistent total amount of the extended observer through anti-saturation is proposed. First, mathematical models of multi-motor traction systems are developed. The system includes uncertain parameter perturbations and external perturbations. Second, a new type of extended sliding mode observer (ESMO) is designed to reduce the influence of the tracking effect on the input saturation of the system. Subsequently, for collaborative control of multi motors in heavy-duty locomotives, a new scheme for dynamic and auxiliary anti-saturation compensation (anti-windup) is established. The perturbation observation results and the systems’ auxiliary status are respectively input into the sliding mode controller (SMC). A traction total-amount coordinated tracking control (TACTC) of multi motors is achieved to ensure consistency of the system’s total output torque and the given traction characteristic curve. Finally, simulations and tests are performed on the motor actuators to demonstrate a good control effect.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"13 1","pages":"501-510"},"PeriodicalIF":0.7,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87081014","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 : 2023-05-20DOI: 10.20965/jaciii.2023.p0445
Andi Prademon Yunus, Kento Morita, Nobu C. Shirai, Tetsushi Wakabayashi
Human motion forecasting is a necessary variable to analyze human motion concerning the safety system of the autonomous system that could be used in many applications, such as in auto-driving vehicles, auto-pilot logistics delivery, and gait analysis in the medical field. At the same time, many types of research have been conducted on 3D human motion prediction for short-term and long-term goals. This paper proposes human motion forecasting in the 2D plane as a reliable alternative in motion capture of the RGB camera attached to the devices. We proposed a method, the time series self-attention approach to generate the next future human motion in the short-term of 400 milliseconds and long-term of 1,000 milliseconds, resulting that the model could predict human motion with a slight error of 23.51 pixels for short-term prediction and 10.3 pixels for long-term prediction on average compared to the ground truth in the quantitative and qualitative evaluation. Our method outperformed the LSTM and GRU models on the Human3.6M dataset based on the MPJPE and MPJVE metrics. The average loss of correct key points varied based on the tolerance value. Our method performed better within the 50 pixels tolerance. In addition, our method is tested by images without key point annotations using OpenPose as the pose estimation method. Resulting, our method could predict well the position of the human but could not predict well for the human body pose. This research is a new baseline for the 2D human motion prediction using the Human3.6M dataset.
{"title":"Time Series Self-Attention Approach for Human Motion Forecasting: A Baseline 2D Pose Forecasting","authors":"Andi Prademon Yunus, Kento Morita, Nobu C. Shirai, Tetsushi Wakabayashi","doi":"10.20965/jaciii.2023.p0445","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0445","url":null,"abstract":"Human motion forecasting is a necessary variable to analyze human motion concerning the safety system of the autonomous system that could be used in many applications, such as in auto-driving vehicles, auto-pilot logistics delivery, and gait analysis in the medical field. At the same time, many types of research have been conducted on 3D human motion prediction for short-term and long-term goals. This paper proposes human motion forecasting in the 2D plane as a reliable alternative in motion capture of the RGB camera attached to the devices. We proposed a method, the time series self-attention approach to generate the next future human motion in the short-term of 400 milliseconds and long-term of 1,000 milliseconds, resulting that the model could predict human motion with a slight error of 23.51 pixels for short-term prediction and 10.3 pixels for long-term prediction on average compared to the ground truth in the quantitative and qualitative evaluation. Our method outperformed the LSTM and GRU models on the Human3.6M dataset based on the MPJPE and MPJVE metrics. The average loss of correct key points varied based on the tolerance value. Our method performed better within the 50 pixels tolerance. In addition, our method is tested by images without key point annotations using OpenPose as the pose estimation method. Resulting, our method could predict well the position of the human but could not predict well for the human body pose. This research is a new baseline for the 2D human motion prediction using the Human3.6M dataset.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"1 1","pages":"445-457"},"PeriodicalIF":0.7,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90728544","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 : 2023-05-20DOI: 10.20965/jaciii.2023.p0490
Wei Xu, Jian Ge, Hong Yu, Min Xiao
In a coil magnetometer, the size and uniformity of the bias magnetic field generated by the Helmholtz coil directly determine the accuracy of the solution of the geomagnetic direction. The design of traditional spherical coils relies heavily on the manual experience or mathematical derivation, making it difficult to obtain optimal parameters or requiring larger spherical coils. To address the problem, first, a coaxial symmetrical spherical coil model that improves space utilization was established. Second, an optimal design method for the spherical magnetic field generation coil based on a differential evolution algorithm was proposed. Third, the optimal bias magnetic field was obtained without increasing the volume of the coil. The verification results showed that the magnetic non-uniformity and magnetic gradient of the bias field generated by the optimized coil were reduced by 63.2% and 82.8%, respectively.
{"title":"Optimization Design Method of Spherical Magnetic Field Generation Coil Based on Differential Evolution Algorithm","authors":"Wei Xu, Jian Ge, Hong Yu, Min Xiao","doi":"10.20965/jaciii.2023.p0490","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0490","url":null,"abstract":"In a coil magnetometer, the size and uniformity of the bias magnetic field generated by the Helmholtz coil directly determine the accuracy of the solution of the geomagnetic direction. The design of traditional spherical coils relies heavily on the manual experience or mathematical derivation, making it difficult to obtain optimal parameters or requiring larger spherical coils. To address the problem, first, a coaxial symmetrical spherical coil model that improves space utilization was established. Second, an optimal design method for the spherical magnetic field generation coil based on a differential evolution algorithm was proposed. Third, the optimal bias magnetic field was obtained without increasing the volume of the coil. The verification results showed that the magnetic non-uniformity and magnetic gradient of the bias field generated by the optimized coil were reduced by 63.2% and 82.8%, respectively.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"24 1","pages":"490-495"},"PeriodicalIF":0.7,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74630989","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 : 2023-05-20DOI: 10.20965/jaciii.2023.p0372
Mingyuan Xie, Jinhua She, Zhen-Tao Liu, Zhaohui Yang
Tremors are a symptom of several disorders of the central and peripheral nervous systems, such as Parkinson’s disease (PD). Exoskeletons have been investigated as noninvasive tremor suppression alternatives to medication and surgery. The challenge in musculoskeletal tremor suppression is attenuation of tremor motion without impeding the patient’s voluntary motion. Linear low-pass filters (LPFs) are commonly used for tremor removal. This study presents an alternative method based on an adaptive filter. We compare the effectiveness of the LPFs and adaptive filter on the recorded acceleration signals from an online database.
{"title":"A Real-Time Voluntary Motion Extraction Method Based on an Adaptive Filter","authors":"Mingyuan Xie, Jinhua She, Zhen-Tao Liu, Zhaohui Yang","doi":"10.20965/jaciii.2023.p0372","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0372","url":null,"abstract":"Tremors are a symptom of several disorders of the central and peripheral nervous systems, such as Parkinson’s disease (PD). Exoskeletons have been investigated as noninvasive tremor suppression alternatives to medication and surgery. The challenge in musculoskeletal tremor suppression is attenuation of tremor motion without impeding the patient’s voluntary motion. Linear low-pass filters (LPFs) are commonly used for tremor removal. This study presents an alternative method based on an adaptive filter. We compare the effectiveness of the LPFs and adaptive filter on the recorded acceleration signals from an online database.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"55 1","pages":"372-377"},"PeriodicalIF":0.7,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75376806","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 : 2023-05-20DOI: 10.20965/jaciii.2023.p0411
Dianjun Wang, Jiahao Chen, Ya Chen, Xingkang Zheng, Liang Wang, Lele Wang
To improve the space utilization rates of intelligent stereo garages, their key execution equipment—parking robots—must be highly flexible; therefore, the chassis of parking robots use steering wheel systems. However, this design increases the complexity of robot motion control and path-tracking systems. Because of the large sizes of parking robots, large position and angle deviations can lead to derailment events, posing significant risk to users. Thus, in this study, based on the characteristics required for parking robots, a diagonally arranged parking robot with double steering wheels was developed and its kinematic model was established using the velocity–geometry method. For the positioning of the robot in a garage, a fusion positioning algorithm based on quick response (QR) codes and track calculation was used, considering the requirements of real-time response and accuracy. A discrete proportional-integral-derivative (PID) path-tracking algorithm for the synchronous compensation of the position and angle deviations was also devised. Using the Visual C++ platform, a path-tracking system that uses an industrial computer and motion control card was developed. Experiments on the path-tracking capability of the parking robot showed that, using the discrete PID path-tracking algorithm, it can track a planned path well. On Z- and U-type paths, its maximum tracking deviations were reduced by 84.8% and 64.0%, compared with the unused path-tracking system, reaching 10.4 mm and 10.9 mm, respectively. Thus, the tracking accuracy was significantly improved, proving that the developed robot well satisfies the path-tracking requirements of parking robots.
{"title":"Parking Robot Path-Tracking System Based on Discrete PID Algorithm","authors":"Dianjun Wang, Jiahao Chen, Ya Chen, Xingkang Zheng, Liang Wang, Lele Wang","doi":"10.20965/jaciii.2023.p0411","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0411","url":null,"abstract":"To improve the space utilization rates of intelligent stereo garages, their key execution equipment—parking robots—must be highly flexible; therefore, the chassis of parking robots use steering wheel systems. However, this design increases the complexity of robot motion control and path-tracking systems. Because of the large sizes of parking robots, large position and angle deviations can lead to derailment events, posing significant risk to users. Thus, in this study, based on the characteristics required for parking robots, a diagonally arranged parking robot with double steering wheels was developed and its kinematic model was established using the velocity–geometry method. For the positioning of the robot in a garage, a fusion positioning algorithm based on quick response (QR) codes and track calculation was used, considering the requirements of real-time response and accuracy. A discrete proportional-integral-derivative (PID) path-tracking algorithm for the synchronous compensation of the position and angle deviations was also devised. Using the Visual C++ platform, a path-tracking system that uses an industrial computer and motion control card was developed. Experiments on the path-tracking capability of the parking robot showed that, using the discrete PID path-tracking algorithm, it can track a planned path well. On Z- and U-type paths, its maximum tracking deviations were reduced by 84.8% and 64.0%, compared with the unused path-tracking system, reaching 10.4 mm and 10.9 mm, respectively. Thus, the tracking accuracy was significantly improved, proving that the developed robot well satisfies the path-tracking requirements of parking robots.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"26 1","pages":"411-420"},"PeriodicalIF":0.7,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84431861","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}
Logistics tracking technology at normal temperature is quite mature, but there are few tracking methods for the high-temperature production process. The main difficulties are that the label materials generally used cannot withstand the high temperature for a long time, and the detection devices are vulnerable to environmental impact. A high-temperature logistics tracking solution was developed for a carbon anode used in an aluminum electrolysis factory. It is based on concave coding and a multiscale low-level feature fusion and attention-DeepLabV3+ (MLFFA-DeepLabV3+) network extraction technique for the coded region of the concave coding. The concave coding is printed on the product as a tag that can endure a high temperature of more than 1,200°C, ensuring its integrity and identifiability. Because there is no obvious color distinction between the coding area and the background, direct recognition is ineffective. The MLFFA-DeepLabV3+ network extracts the coding region to improve the recognition rate. The DeepLabV3+ network is improved by replacing the backbone network and adding of a multiscale low-level feature fusion module and convolutional block attention module. Experimental results showed that the mean pixel accuracy and mean intersection over union of the MLFFA-DeepLabV3+ network increased by 2.37% and 2.45%, respectively, compared with the original DeepLabV3+ network. The network structure has only 11.24% of the number of parameters in the original structure. The solution is feasible and provides a basis for high-temperature logistics tracking technology in intelligent manufacturing.
{"title":"Label Design and Extraction in High-Temperature Logistics Based on Concave Coding and MLFFA-DeepLabV3+ Network","authors":"Xiaoyan Zhao, Pengfei Zhao, Yuguo Yin, Luqi Tao, Jianfeng Yan, Zhaohui Zhang","doi":"10.20965/jaciii.2023.p0467","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0467","url":null,"abstract":"Logistics tracking technology at normal temperature is quite mature, but there are few tracking methods for the high-temperature production process. The main difficulties are that the label materials generally used cannot withstand the high temperature for a long time, and the detection devices are vulnerable to environmental impact. A high-temperature logistics tracking solution was developed for a carbon anode used in an aluminum electrolysis factory. It is based on concave coding and a multiscale low-level feature fusion and attention-DeepLabV3+ (MLFFA-DeepLabV3+) network extraction technique for the coded region of the concave coding. The concave coding is printed on the product as a tag that can endure a high temperature of more than 1,200°C, ensuring its integrity and identifiability. Because there is no obvious color distinction between the coding area and the background, direct recognition is ineffective. The MLFFA-DeepLabV3+ network extracts the coding region to improve the recognition rate. The DeepLabV3+ network is improved by replacing the backbone network and adding of a multiscale low-level feature fusion module and convolutional block attention module. Experimental results showed that the mean pixel accuracy and mean intersection over union of the MLFFA-DeepLabV3+ network increased by 2.37% and 2.45%, respectively, compared with the original DeepLabV3+ network. The network structure has only 11.24% of the number of parameters in the original structure. The solution is feasible and provides a basis for high-temperature logistics tracking technology in intelligent manufacturing.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"10 1","pages":"467-473"},"PeriodicalIF":0.7,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87575457","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 : 2023-05-20DOI: 10.20965/jaciii.2023.p0394
Fumihiro Sakahira, Yuji Yamaguchi, Takao Terano
In this study, we applied natural language processing (NLP) techniques to texts of excavation reports on buried cultural properties to calculate the degree of similarity between the reports for determining archaeological sites that have a high degree of similarity. Specifically, we validated whether the similarity of sentence embeddings in the excavation reports of these sites is consistent with the existing classification. Four archaeological sites classified in existing archaeological research papers were used. For validation, 128 excavation reports from the four sites were used; sentence embeddings were obtained using Doc2Vec. We obtained the following results: 1) In applying NLP to excavation reports for determining the similarities of archaeological sites, merging the texts for each site into a single document and then processing it was more preferable than processing it in separate volumes of the excavation report. 2) The similarity based on sentence embedding of excavation reports using Doc2Vec was more consistent with the classification of the characteristics of archaeological sites than term frequency–inverse document frequency (TF-IDF). 3) When targeting a specific period, the sentence embedding exclusively for the text of the relevant period is consistent with the classification of the characteristics of the archaeological site from the artifacts and structural remains of that specific period. 4) When a specific period is targeted, the exclusive sentence embeddings of that period, obtained through the additive compositionality of sentence embeddings, can be used to classify the characteristics of archaeological sites based on the artifacts and structural remains on that period. Consequently, the similarities of texts based on NLP can reflect the similarities of archaeological sites. This holds true even for excavation reports that include spelling inconsistencies, optical character reader misrecognition, and garbled words.
{"title":"Understanding Cultural Similarities of Archaeological Sites from Excavation Reports Using Natural Language Processing Technique","authors":"Fumihiro Sakahira, Yuji Yamaguchi, Takao Terano","doi":"10.20965/jaciii.2023.p0394","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0394","url":null,"abstract":"In this study, we applied natural language processing (NLP) techniques to texts of excavation reports on buried cultural properties to calculate the degree of similarity between the reports for determining archaeological sites that have a high degree of similarity. Specifically, we validated whether the similarity of sentence embeddings in the excavation reports of these sites is consistent with the existing classification. Four archaeological sites classified in existing archaeological research papers were used. For validation, 128 excavation reports from the four sites were used; sentence embeddings were obtained using Doc2Vec. We obtained the following results: 1) In applying NLP to excavation reports for determining the similarities of archaeological sites, merging the texts for each site into a single document and then processing it was more preferable than processing it in separate volumes of the excavation report. 2) The similarity based on sentence embedding of excavation reports using Doc2Vec was more consistent with the classification of the characteristics of archaeological sites than term frequency–inverse document frequency (TF-IDF). 3) When targeting a specific period, the sentence embedding exclusively for the text of the relevant period is consistent with the classification of the characteristics of the archaeological site from the artifacts and structural remains of that specific period. 4) When a specific period is targeted, the exclusive sentence embeddings of that period, obtained through the additive compositionality of sentence embeddings, can be used to classify the characteristics of archaeological sites based on the artifacts and structural remains on that period. Consequently, the similarities of texts based on NLP can reflect the similarities of archaeological sites. This holds true even for excavation reports that include spelling inconsistencies, optical character reader misrecognition, and garbled words.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"136 1","pages":"394-403"},"PeriodicalIF":0.7,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74672975","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 : 2023-05-20DOI: 10.20965/jaciii.2023.p0481
Yuri Murayama, Ichiro Kobayashi
The differentiable neural computer (DNC) is a neural network model with an addressable external memory that can solve algorithmic and question-answering tasks. Improved versions of the DNC have been proposed, including the robust and scalable DNC (rsDNC) and DNC-deallocation-masking-sharpness (DNC-DMS). However, integrating structured knowledge and calculations into these DNC models remains a challenging research question. In this study, we incorporate an architecture for knowledge and calculations into the DNC, rsDNC, and DNC-DMS to improve their abilities to generate correct answers for questions with multi-hop reasoning and provide calculations over structured knowledge. Our improved rsDNC model achieves the best performance for the mean top-1 accuracy, and our improved DNC-DMS model scores the highest for the top-10 accuracy in the GEO dataset. In addition, our improved rsDNC model outperforms other models in regards to the mean top-1 accuracy and mean top-10 accuracy in the augmented GEO dataset.
{"title":"Toward Question-Answering with Multi-Hop Reasoning and Calculation over Knowledge Using a Neural Network Model with External Memories","authors":"Yuri Murayama, Ichiro Kobayashi","doi":"10.20965/jaciii.2023.p0481","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0481","url":null,"abstract":"The differentiable neural computer (DNC) is a neural network model with an addressable external memory that can solve algorithmic and question-answering tasks. Improved versions of the DNC have been proposed, including the robust and scalable DNC (rsDNC) and DNC-deallocation-masking-sharpness (DNC-DMS). However, integrating structured knowledge and calculations into these DNC models remains a challenging research question. In this study, we incorporate an architecture for knowledge and calculations into the DNC, rsDNC, and DNC-DMS to improve their abilities to generate correct answers for questions with multi-hop reasoning and provide calculations over structured knowledge. Our improved rsDNC model achieves the best performance for the mean top-1 accuracy, and our improved DNC-DMS model scores the highest for the top-10 accuracy in the GEO dataset. In addition, our improved rsDNC model outperforms other models in regards to the mean top-1 accuracy and mean top-10 accuracy in the augmented GEO dataset.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"15 1","pages":"481-489"},"PeriodicalIF":0.7,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73182786","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 : 2023-05-20DOI: 10.20965/jaciii.2023.p0421
Fengxiao Yan, Bo Shen, Chenyang Dai
Causal relation extraction is a crucial task in natural language processing. Current extraction methods have problems, including low accuracy of causal-event division and incorrect extraction of important semantic features. This study uses the bidirectional long short-term memory (BiLSTM) and attentive convolutional neural network (ACNN) models to construct a cascaded causal relationship extraction model to improve the precision of the extraction. The model uses two kinds of labels and then divides the causal event boundary after determining the relationship between the front and rear causal events. It automatically learns semantic features from sentences, reducing the dependence on external knowledge and improving the precision of extraction. The experimental results demonstrate that the precision of causality extraction can reach 81.67% and the F1 value can reach 83.2%.
{"title":"Causality Extraction Cascade Model Based on Dual Labeling","authors":"Fengxiao Yan, Bo Shen, Chenyang Dai","doi":"10.20965/jaciii.2023.p0421","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0421","url":null,"abstract":"Causal relation extraction is a crucial task in natural language processing. Current extraction methods have problems, including low accuracy of causal-event division and incorrect extraction of important semantic features. This study uses the bidirectional long short-term memory (BiLSTM) and attentive convolutional neural network (ACNN) models to construct a cascaded causal relationship extraction model to improve the precision of the extraction. The model uses two kinds of labels and then divides the causal event boundary after determining the relationship between the front and rear causal events. It automatically learns semantic features from sentences, reducing the dependence on external knowledge and improving the precision of extraction. The experimental results demonstrate that the precision of causality extraction can reach 81.67% and the F1 value can reach 83.2%.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"50 1","pages":"421-430"},"PeriodicalIF":0.7,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88235203","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 : 2023-05-20DOI: 10.20965/jaciii.2023.p0333
Amir A. Bracino, D. G. Evangelista, Ronnie S. Concepcion, Elmer P. Dadios, R. R. Vicerra
Rice is a plant with rounded hollow articulated culms, flat, well-attached leaf blades, and terminal spikes. Its cultivation and consumption shape the culture, diet, and economy of different groups, especially in Asia. However, farmers suffer great financial losses each year due to rice disease. Therefore, the identification and classification of rice diseases are very important. Prompt, timely, and accurate disease diagnosis prevents product loss and improves crop quality. This study focuses on the classification of whether rice paddy leaf is normal or has a disease (one of the following: bacterial leaf blight (BLB), bacterial leaf streaks (BLS), bacterial panicle blight (BPB): heart, downy mildew, hispa, and rice tungro disease (RTD)) using deep learning-based algorithms such as EfficientNet-b0, MobileNet-v2, and Places365-GoogLeNet. The best model for this simulation was found to be EfficientNet-b0 with an average accuracy of 97.74%.
{"title":"Non-Destructive Classification of Paddy Rice Leaf Disease Infected by Bacterial and Fungal Species Using Vision-Based Deep Learning","authors":"Amir A. Bracino, D. G. Evangelista, Ronnie S. Concepcion, Elmer P. Dadios, R. R. Vicerra","doi":"10.20965/jaciii.2023.p0333","DOIUrl":"https://doi.org/10.20965/jaciii.2023.p0333","url":null,"abstract":"Rice is a plant with rounded hollow articulated culms, flat, well-attached leaf blades, and terminal spikes. Its cultivation and consumption shape the culture, diet, and economy of different groups, especially in Asia. However, farmers suffer great financial losses each year due to rice disease. Therefore, the identification and classification of rice diseases are very important. Prompt, timely, and accurate disease diagnosis prevents product loss and improves crop quality. This study focuses on the classification of whether rice paddy leaf is normal or has a disease (one of the following: bacterial leaf blight (BLB), bacterial leaf streaks (BLS), bacterial panicle blight (BPB): heart, downy mildew, hispa, and rice tungro disease (RTD)) using deep learning-based algorithms such as EfficientNet-b0, MobileNet-v2, and Places365-GoogLeNet. The best model for this simulation was found to be EfficientNet-b0 with an average accuracy of 97.74%.","PeriodicalId":45921,"journal":{"name":"Journal of Advanced Computational Intelligence and Intelligent Informatics","volume":"233 1","pages":"333-339"},"PeriodicalIF":0.7,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77523980","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}
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