The proceedings contain 71 papers. The topics discussed include: soft computing algorithms applied to the segmentation of nerve cell images;pattern recognition based on time-frequency distributions of radar micro-Dopp...
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ISBN:
(纸本)0769522947
The proceedings contain 71 papers. The topics discussed include: soft computing algorithms applied to the segmentation of nerve cell images;pattern recognition based on time-frequency distributions of radar micro-Doppler dynamics;a quantitative software quality evaluation model for the artifacts of component based development;a new approach to software requirements elicitation;using data mining technology to design an intelligent CIM system for IC manufacturing;data mining for imprecise temporal associations;analysis of breast cancer using data mining and statistical techniques;analyzing the conditions of coupling existence based on program slicing and some abstract information-flow;a study of model layers and reflection;a general scalable implementation of fast matrix multiplication algorithms on distributed memory computers;error prediction for multi-classification;an integer support vector machine;and layered neural networks computations.
In this study, machine-learning technique is used to collect environmental data in real time and measures other aspects like soil moisture, temperature, water level, humidity. Water use efficiency has recently increas...
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ISBN:
(数字)9798331543358
ISBN:
(纸本)9798331543365
In this study, machine-learning technique is used to collect environmental data in real time and measures other aspects like soil moisture, temperature, water level, humidity. Water use efficiency has recently increased because to new agricultural techniques, sophisticated sensors as Micro Controller, and Wireless Sensor Network (WSN). Irrigation Fault Detection method based on XGBoost (IFD-XGBoost) Algorithm used as proposed method as robust to missing values imputing them naturally during tree splitting. The Suggested method is optimized for speed, using parallel and distributedcomputing to make predictions faster compare to other Regression Algorithm and avoid over fitting. Using Min-Max Normalization, features with different sizes and units can affect the efficacy of several machine learning algorithms. By warping the statistical relationship between features, removal of noisy data and error detection can reduce the machine learning models' efficiency. Lasso Regression is a linear model that combines regularization and feature selection. Additionally, less data will be kept in the centralized cloud as a result. Using the IFD-XGBoost Algorithm's ability to handle missing data, learn from past errors, and adjust parameters, our proposed approach would be the best model to implement. It outperform from other algorithm in Predictive accuracy, making it reliable for calculating water needs and forecasting weather. Investigating the implementation of several machine learning models that can offer the best real-world irrigation decision management is the main goal of this article. The comparative analysis to evaluate the IFD-XGBoost method yielded a minimum RMSE of 0.3524, MAE of 0.1832, MAPE of 4.24 with the highest accuracy of 99.2%, precision of 96.2% and AUC-ROC of 95%, indicates when combined, these metrics provide insightful data about each model's ability to anticipate future developments in irrigation systems.
The proceedings contain 19 papers. The topics discussed include: a robust zero-watermark algorithm based on singular value decomposition and discreet cosine transform;u-traditional market model based on 5W1H context a...
ISBN:
(纸本)9783642227059
The proceedings contain 19 papers. The topics discussed include: a robust zero-watermark algorithm based on singular value decomposition and discreet cosine transform;u-traditional market model based on 5W1H context aware technology;an HD virtual studio system using chroma key;a secure patient information access scheme through identity-based signcryption;towards improving SCADA control systems security with vulnerability analysis;numerical simulation on anchorage effect of joint rock;the judgment for inverse M-matrices in signal processing;estimates for the upper and lower bounds on the inverse elements of strictly diagonally dominant periodic adding element tridiagonal matrices in signal processing;a fast algorithm for the inverse matrices of periodic adding element tridiagonal matrices;singular value decomposition for k-order row(column) extended matrix in signal processing;prolog-based formal reasoning for security protocols;and the brief explanation of physical violence in sociology.
We present here a heuristic for broadcasting and a heuristic for gossiping. These heuristics outperform the previous heuristics in several network generators. The heuristic for gossiping also has a lower time complexi...
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ISBN:
(纸本)9780889866379
We present here a heuristic for broadcasting and a heuristic for gossiping. These heuristics outperform the previous heuristics in several network generators. The heuristic for gossiping also has a lower time complexity than the best heuristic in practice.
Understanding cell–cell interactions is crucial for unraveling the complexities of multicellular organisms and holds promising implications for advancements in medical science. These interactions, mediated through sp...
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Wireless Mesh networks (WMNs) provide a wireless network infrastructure that most application scenarios assume to be fixed. Different from highly mobile networks, assumptions can be made on this infrastructure to incr...
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ISBN:
(纸本)9780889866386
Wireless Mesh networks (WMNs) provide a wireless network infrastructure that most application scenarios assume to be fixed. Different from highly mobile networks, assumptions can be made on this infrastructure to increase performance. Now, features in the WiFi protocol stack become unnecessary for doing mesh networking, but still have an impact on the bandwidth performance. The contribution of this work is to show that WiFi produces a considerable bandwidth overhead within the WMN backbone infrastructure that could be avoided.
The paper aims at finding fundamental principles for traffic analysis of mobile sensor networks. An analytical modeling technique is developed to find the main parameters of data transmission in mobile sensor networks...
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ISBN:
(纸本)9780889866379
The paper aims at finding fundamental principles for traffic analysis of mobile sensor networks. An analytical modeling technique is developed to find the main parameters of data transmission in mobile sensor networks. In particular, the applied model allows itself to be treated as an immobile sensor network and a mobile part of the sensor network. With use of the derived relations we obtain the main dependencies for data transmission to the sink of a sensor network and to the clusterhead sensor nodes of this network. The viewpoint enables us to take performance measures for modeling mobile sensor networks. Moreover, the study shows that the proposed model can also be used for ordinary sensor networks which are static.
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