Automatika最新文献_第9页

Energy efficient optimal hop transmission using minimum power least cost algorithm in cooperative routing for wireless sensor network 基于最小功率最小代价算法的无线传感器网络协作路由节能最优跳数传输

IF 1.9 4区计算机科学

Automatika Pub Date : 2023-08-15 DOI: 10.1080/00051144.2023.2246242

Immanuvel Arokia James K., M. P., G. G, K. A.

{"title":"Energy efficient optimal hop transmission using minimum power least cost algorithm in cooperative routing for wireless sensor network","authors":"Immanuvel Arokia James K., M. P., G. G, K. A.","doi":"10.1080/00051144.2023.2246242","DOIUrl":"https://doi.org/10.1080/00051144.2023.2246242","url":null,"abstract":"Cooperative communication has gained a lot of popularity recently. Through a variety of shortest path methods, this article's paradigm may efficiently reduce the amount of power consumed and hop transmission. In this research, we construct the Minimum Power Least Cost Routing (MPLCR) algorithm and evaluate its performance. The design of the proposed algorithm took into account link computation, sequential scanning algorithm approach, and balance (residual) energy. To prevent connection failures and lessen network traffic, the link calculation is used to choose the best route (relay node). In order to reduce network power consumption, a sequential scanning technique was used to find the shortest path with the fewest hops. And also discuss relay nodes and their characteristics in order to improve the transmission stream's quality of service. An ideal path is one that ensures end-to-end transmission while using the least amount of transmitted power. The minimum power least cost routing algorithm uses cooperative communications to help build the smallest power route. When compared to the current algorithms, the proposed approach uses less energy by more than 30%.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47748675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computer aided detection of leaf disease in agriculture using convolution neural network based squeeze and excitation network 基于压缩和激励网络的卷积神经网络对农业叶片病害的计算机辅助检测

IF 1.9 4区计算机科学

Automatika Pub Date : 2023-08-11 DOI: 10.1080/00051144.2023.2241792

R. Krishnan, E. G. Julie

{"title":"Computer aided detection of leaf disease in agriculture using convolution neural network based squeeze and excitation network","authors":"R. Krishnan, E. G. Julie","doi":"10.1080/00051144.2023.2241792","DOIUrl":"https://doi.org/10.1080/00051144.2023.2241792","url":null,"abstract":"ABSTRACT The support rendered by artificial intelligence in plant disease diagnosis and with drastic progression in the agricultural technology, it is necessary to do pertinent research for the cause of long-term agricultural development. Numerous diseases like early and late blight have a significant influence on the quality and quantity of potatoes. Manual interpretation turns out to be a time-consuming process in sorting out leaf diseases. In order to classify various diseases like fungal, viral and bacterial infections in the potato leaf, an enhanced Convolution Neural Network based on VGG16 is used for potato leaf disease classification. Improved Median filter is also used which eradicates the noise to a greater extent. The convolution layers of VGG16 along with the Inception and the SE block are used in this research for classification. The global average pooling layer is used to reduce model training parameters, layer and Squeeze and Excitation Network attention mechanism is used to improve the model’s ability to extract features. The approximate calculations can be done by using soft computing. Compared with other traditional convolutional neural networks, the proposed model achieved the highest classification accuracy of 99.3%","PeriodicalId":55412,"journal":{"name":"Automatika","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42064067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Newsgist: video generation from news stories 新闻记者:从新闻故事中生成视频

IF 1.9 4区计算机科学

Automatika Pub Date : 2023-08-02 DOI: 10.1080/00051144.2023.2241774

M. S. Karthika Devi, R. Baskaran

{"title":"Newsgist: video generation from news stories","authors":"M. S. Karthika Devi, R. Baskaran","doi":"10.1080/00051144.2023.2241774","DOIUrl":"https://doi.org/10.1080/00051144.2023.2241774","url":null,"abstract":"Digital transition has started to change the way people read news articles more through a digital device and less on paper. Youngsters today do not spend enough time reading news articles. In this work, a knowledge-driven news story generation using collaborative learning to represent the gist of news is proposed. The entire work focuses on two major concerns. Initially, the dialogues associated with the corresponding speaker are extracted from the news. Secondly, the audio of the mapped dialogues is incorporated into the final video. Logistic Regression is deployed to identify the theme the news. Deep learning techniques are employed to identify the main characters in a supervised manner using Named Entity Recognition (NER) tagging algorithm, suitable cartoon dispositions and their semantic relations. This approach improves not the reader's comprehension and creativity but also improves mutual goals, opportunities for peer discussion and engaging the underachievers to think reflexively. In addition, it also improves the learner’s motivation and participation. The proposed framework outperforms an accuracy of 83.98% when compared with conventional methods also suggests that the readers found the packages interesting and informative on digital devices. Moreover, this method can be used efficiently in real-time for various applications.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43755556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FAT-based adaptive and velocity feedback control of cooperative manipulators handling a flexible object 基于FAT的柔性物体协同机械手自适应速度反馈控制

IF 1.9 4区计算机科学

Automatika Pub Date : 2023-08-02 DOI: 10.1080/00051144.2023.2236857

Abdul Rahman Samewoi, Norsinnira Zainul Azlan, Md. Raisuddin Khan

{"title":"FAT-based adaptive and velocity feedback control of cooperative manipulators handling a flexible object","authors":"Abdul Rahman Samewoi, Norsinnira Zainul Azlan, Md. Raisuddin Khan","doi":"10.1080/00051144.2023.2236857","DOIUrl":"https://doi.org/10.1080/00051144.2023.2236857","url":null,"abstract":"The previous regressor-based control method to control two cooperative manipulators in handling a deformable object leads to complex calculations and complicated programming in experimental hardware tests. There is an existing lack of studies about the development of the controller based on a partial differential equation (PDE)-based model and considering the model’s uncertainties. Previous studies have shown fewer experimental validations regarding two cooperative manipulators that handle deformable objects under uncertain model parameters. This study proposes a composite controller comprising a function approximation technique (FAT)-based adaptive control (FATAC) for a slow subsystem and a velocity feedback control (VFC) for a fast subsystem. The proposed FATAC is used for trajectory tracking, and VFC is used to suppress the vibration of the deformable object. Lyapunov stability analysis has been carried out to design controllers that stabilize a non-linear system of two cooperative manipulators handling the flexible object. Simulation and hardware experimental tests have been carried out to validate the performance of proposed controllers. The results verified that the proposed composite controller comprising the FATAC has successfully driven the cooperative manipulators to handle the deformable object so that it follows the desired trajectories. The VFC has successfully suppressed the transverse vibration of the deformable object.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49226764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Watchdog malicious node detection and isolation using deep learning for secured communication in MANET 基于深度学习的MANET安全通信看门狗恶意节点检测与隔离

IF 1.9 4区计算机科学

Automatika Pub Date : 2023-08-01 DOI: 10.1080/00051144.2023.2241766

Narmadha A. S., M. S, D. S. N.

{"title":"Watchdog malicious node detection and isolation using deep learning for secured communication in MANET","authors":"Narmadha A. S., M. S, D. S. N.","doi":"10.1080/00051144.2023.2241766","DOIUrl":"https://doi.org/10.1080/00051144.2023.2241766","url":null,"abstract":"Mobile Ad-hoc Networks (MANETs) are wireless networks formed dynamically by connecting or leaving nodes to and from the network without any fixed infrastructure. These categories of wireless networks are susceptible to different attacks based on their dynamic topological structure. Due to this, security is a primary constraint in MANETs to preserve communication between mobile nodes. A Deep Neural Learned Projective Pursuit Regression-based Watchdog Malicious Node Detection and Isolation (DNLPPR-WMNDI) technique is proposed and modelled in this paper to improve the security feature of MANETs. The newly proposed DNLPPR-WMNDI technique initially selects the neighbouring nodes by applying the projection pursuit regression function. In multicasting, the route paths are established through the intermediate node with the help of control commands named RREQ and RREP. After then, Watchdog Malicious Node Detection and Isolation (WMNDI) technique is applied to detect malicious nodes based on the data packet forwarding time. Basically, a malicious node is affected by a node isolation attack. For better communication, a malicious node is isolated from the network and multicast routing is carried out by selecting the next neighbouring node and this improves the communication security. Simulation is done for the developed technique based on different performance metrics.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41296910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A novel neural network method using radial basis function for effective assessment of stiffness index on lumbar disc degenerative subjects 利用径向基函数的神经网络方法有效评估腰椎间盘退变受试者的僵硬指数

IF 1.9 4区计算机科学

Automatika Pub Date : 2023-07-28 DOI: 10.1080/00051144.2023.2223496

C. Sreeja, V. Meena Devi, M. Aneesh

{"title":"A novel neural network method using radial basis function for effective assessment of stiffness index on lumbar disc degenerative subjects","authors":"C. Sreeja, V. Meena Devi, M. Aneesh","doi":"10.1080/00051144.2023.2223496","DOIUrl":"https://doi.org/10.1080/00051144.2023.2223496","url":null,"abstract":"ABSTRACT Lumbar disc degenerative disc disease with back pain and its severity is a leading health issue in society and MRI is the best modality to detect the severity and degree of disc degeneration. The most critical component of degenerative disc disease deals with triggering rapid action for real-time-based system identification. The input is obtained from the non-invasive device called finger pulse plethysmography to assess the stiffness and its correlation with body composition in lumbar disc degeneration. The recent methodology contributions aim at predicting the stiffness which uses pulse wave velocity and reflection on signal features. As the signals are very sensitive to differences between high and low ranges, finger pulse plethysmography effectively detects irregularities at early stages. Based on the severity of degeneration, shown by the MRI report, subjects were grouped into the disc bulging group (DBG) and the nerve compression group (NCG). The supervised features help in training the signals to correct the limitations of prediction. Finally, the Radial Basis Function neural network approach helps in diminishing the local minimal values in the signal. It helps in the effective categorization of anomalous and ordinary stiffness index measurements for lumbar disc degeneration.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46926749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Homomorphism on bipolar-valued fuzzy sub-bigroup of a bigroup for secured data transmission over WSN WSN上安全数据传输双群的双极值模糊子双群的同态

IF 1.9 4区计算机科学

Automatika Pub Date : 2023-07-27 DOI: 10.1080/00051144.2023.2226945

Sheena K. P., K. Devi

引用次数: 0

Analysis of cost estimation using the web metrics and cost driver in the high performance of web developers 在web开发人员的高性能中使用web度量和成本驱动因素的成本估计分析

IF 1.9 4区计算机科学

Automatika Pub Date : 2023-07-27 DOI: 10.1080/00051144.2023.2216540

A. E. Suniram, J. Charles

引用次数: 0

Stock market prediction based on deep hybrid RNN model and sentiment analysis 基于深度混合RNN模型和情绪分析的股市预测

IF 1.9 4区计算机科学

Automatika Pub Date : 2023-07-27 DOI: 10.1080/00051144.2023.2217602

Ancy John, T. Latha

{"title":"Stock market prediction based on deep hybrid RNN model and sentiment analysis","authors":"Ancy John, T. Latha","doi":"10.1080/00051144.2023.2217602","DOIUrl":"https://doi.org/10.1080/00051144.2023.2217602","url":null,"abstract":"Stock market movements, stocks, and exchange rates are the primary subjects and active areas of research for analysts and researchers. The stock prices is being influenced by financial news, which has been demonstrated to be an important element in fluctuating stock prices. Furthermore, previous research mostly evaluated shallow characteristics and ignored functional relationships between words in a sentence. Many studies have attempted to analyse the sentiment of investors’ reactions to corresponding news occurrences. In this paper, we proposed a unique methodology for predicting the stock prices trend by using both stock features and financial news. The proposed methodology is the hybrid Recurrent Neural-Network (HyRNN) architecture. This design includes Bidirectional Long Short-Term Memory (Bi-LSTM) on top of the Gated Recurrent Unit (GRU) and stacked Long Short-Term Memory (sLSTM). The performance of HyRNN for forecasting stock price can be considerably improved by mixing the sentiments of financial news with the features of stock as an input to the model. In comparison to earlier statistical models, the suggested model increases the analysing capability of GRU, LSTM, RNN, and proposed models independently. The findings of this study shows the deep learning (DL) approach has high potential for predicting stock price changes.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44420926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An eye bolt shape slotted microstrip patch antenna design utilizing a substrate-integrated waveguide for 5G systems 一种采用基板集成波导的5G系统眼螺栓形开槽微带贴片天线设计

IF 1.9 4区计算机科学

Automatika Pub Date : 2023-07-25 DOI: 10.1080/00051144.2023.2228065

J. Merin Joshiba, D. Judson

{"title":"An eye bolt shape slotted microstrip patch antenna design utilizing a substrate-integrated waveguide for 5G systems","authors":"J. Merin Joshiba, D. Judson","doi":"10.1080/00051144.2023.2228065","DOIUrl":"https://doi.org/10.1080/00051144.2023.2228065","url":null,"abstract":"Antenna design is usually done on FR4 substrates, since they have a dielectric constant of 4.4, and a loss tangent of 0.02. The proposed microstrip patch antenna operates at 28 GHz and incorporates substrate-integrated waveguides (SIW) in a 0.8 mm thick FR4 substrate into the design to increase bandwidth performance so that the 5G network can function reliably. In comparison with conventional patch antennas, substrate-integrated waveguides bear the advantage of being able to shift to a frequency of 29 GHz, therefore resulting in a more effective antenna. A slot of eyebolt shape has been added to the patch to increase antenna gain. The design was simulated with HFSS software, and it was able to attain a maximum bandwidth of 8 GHz (28%), a gain of 5.5 dB, and a minimal return loss of −38 dB. The VSWR of this antenna is 1.02, which indicates good impedance matching, and a high efficiency of 87% has been achieved as a result. This is a low-profile antenna that combines enhanced bandwidth with the ability to be mounted at the edge of a device, making it an ideal choice for the use of 5G technology to enable machine-to-machine communication.","PeriodicalId":55412,"journal":{"name":"Automatika","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45091954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0