Titlebook: Data Science and Communication; Proceedings of ICTDs Jo?o Manuel R. S. Tavares,Joel J. P. C. Rodrigues, Conference proceedings 2024 The Edi

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書(shū)目名稱(chēng)Data Science and Communication影響因子(影響力)




書(shū)目名稱(chēng)Data Science and Communication影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Data Science and Communication網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Data Science and Communication網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Data Science and Communication被引頻次




書(shū)目名稱(chēng)Data Science and Communication被引頻次學(xué)科排名




書(shū)目名稱(chēng)Data Science and Communication年度引用




書(shū)目名稱(chēng)Data Science and Communication年度引用學(xué)科排名




書(shū)目名稱(chēng)Data Science and Communication讀者反饋




書(shū)目名稱(chēng)Data Science and Communication讀者反饋學(xué)科排名

我悲傷

Portable Device-Based Stress Level Estimation Using Biological Rhythms, and human mental problems, are the consequences of it. In general, humans experience stress, especially those who are involved in work in developed capitalist countries and under huge mental workloads continuously and endless technological development. Stressors come across in our daily life (for

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Maritime Surveillance Using Instance Segmentation Techniquesrative objects, such as spyboats/refugees, take advantage of a dense marine environment to carry out illegal activities such as drug and human trafficking and being unnoticed. It broadly uses a combination of different sensor-based technologies, such as radar, visual sensors, or cameras, along with

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Arduino Uno Driven Toxic Gas Monitoring and Alert System Within Sewagencreasing day by day. The manual scavengers risk their lives every day and die due to infections and diseases like fibrosis, lung cancer, typhoid, hepatitis, asthma, etc. caused by more prolonged exposure to hazardous gases. Gases like hydrogen Sulphide (H.S), Carbon Monoxide (CO), Methane (CH.), Am

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A Comparative Study on Speech Emotion Recognition Using Machine Learnings study SAVEE and IEMOCAP datasets were used with regards to the task of speech emotion recognition. There are seven emotions in the SAVEE datasets and four out of eleven emotions in the IEMOCAP dataset which are considered. Features are extracted from the raw audio files, namely ZCR, F0, MFCC, and

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Vehicle Detection in Aerial Images: A Surveygery. High accuracy and speed were required to do this critical assignment. Aerial image properties and the technology being utilized, such as diverse automobile sizes and their orientations, densities, small datasets, and inference speed, make this a highly difficult assignment. Numerous approaches