http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
오늘 본 자료
Integrated Power Optimization with Battery Friendly Algorithm in Wireless Capsule Endoscopy
Mehmood, Tariq,Naeem, Nadeem,Parveen, Sajida International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.11
The recently continuous enhancement and development in the biomedical side for the betterment of human life. The Wireless Body Area Networks is a significant tool for the current researcher to design and transfer data with greater data rates among the sensors and sensor nodes for biomedical applications. The core area for research in WBANs is power efficiency, battery-driven devices for health and medical, the Charging limitation is a major and serious problem for the WBANs.this research work is proposed to find out the optimal solution for battery-friendly technology. In this research we have addressed the solution to increasing the battery lifetime with variable data transmission rates from medical equipment as Wireless Endoscopy Capsules, this device will analyze a patient's inner body gastrointestinal tract by capturing images and visualization at the workstation. The second major issue is that the Wireless Endoscopy Capsule based systems are currently not used for clinical applications due to their low data rate as well as low resolution and limited battery lifetime, in case of these devices are more enhanced in these cases it will be the best solution for the medical applications. The main objective of this research is to power optimization by reducing the power consumption of the battery in the Wireless Endoscopy Capsule to make it battery-friendly. To overcome the problem we have proposed the algorithm for "Battery Friendly Algorithm" and we have compared the different frame rates of buffer sizes for Transmissions. The proposed Battery Friendly Algorithm is to send the images on average frame rate instead of transmitting the images on maximum or minimum frame rates. The proposed algorithm extends the battery lifetime in comparison with the previous baseline proposed algorithm as well as increased the battery lifetime of the capsule.
Sentiment Analysis to Evaluate Different Deep Learning Approaches
Sheikh Muhammad Saqib,Tariq Naeem International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.11
The majority of product users rely on the reviews that are posted on the appropriate website. Both users and the product's manufacturer could benefit from these reviews. Daily, thousands of reviews are submitted; how is it possible to read them all? Sentiment analysis has become a critical field of research as posting reviews become more and more common. Machine learning techniques that are supervised, unsupervised, and semi-supervised have worked very hard to harvest this data. The complicated and technological area of feature engineering falls within machine learning. Using deep learning, this tedious process may be completed automatically. Numerous studies have been conducted on deep learning models like LSTM, CNN, RNN, and GRU. Each model has employed a certain type of data, such as CNN for pictures and LSTM for language translation, etc. According to experimental results utilizing a publicly accessible dataset with reviews for all of the models, both positive and negative, and CNN, the best model for the dataset was identified in comparison to the other models, with an accuracy rate of 81%.
Hafiz Badaruddin Ahmad,Muhammad Zuber,Yasir Abbas,Mazhar Hussain,Naeem Akhtar,Tariq Mahmood Ansari,Khalid Mahmood Zia,Shafiq Ahmad Arain 한국화학공학회 2014 Korean Journal of Chemical Engineering Vol.31 No.2
Arsenic and nitrate are ill-famed environmental pollutants that are responsible for various lethal diseases. Their removal from drinking water is very essential. In present study, newly synthesized alumina supported nano zerovalentzinc (Alumina-nZvZ) has been tested to remove arsenic and nitrate. Quantitative analyses of arsenic have beenperformed spectrophotometrically and while that of nitrates ions colorimetrically. After optimization of time and amountof adsorbent, Langmuir, Freundlich and D-R isotherms were applied to determine different parameters for the assessmentof adsorption. Synthesized samples were characterized by scanning electron microscopy (SEM) to evaluate porosityand void size. Alumina coated with reduced ZnCl2 showed better efficiency for removal of arsenic and nitrate ions. Kinetics of adsorption was evaluated by using pseudo first-order and pseudo second-order rate equations.