Deep learning is now being used in the medical field to detect ailments such as cancer, diabetes, kidney disease, etc. Kidney disease has become a major public health concern around the globe. If CKD is not diagnosed at an early stage, it can lead to loss of kidney function and which require costly treatments like dialysis and a kidney transplant. Using CNN, an automatic model has been developed to predict chronic renal disease. The major goal of this study is to predict CKD and non-CKD patients. Convolutional neural networks are used to classify chronic renal disease in this proposed system, and the batch prediction method is evaluated for CKD prediction. The precision with which renal disease can be predicted is 95%, and the accuracy for the classification of CKD ultrasound images using CNN is 80%.
The overall development of the internet allows internet attacks to occur, which can cause damage to a system. Threats and attacks on internet networks are more vulnerable to the surface because the internet is fully open to users. We need data protection from threats and attacks to maintain confidentiality, availability, and system information. Threats or disturbances can be referred to as anomalies. Anomaly detection is needed to prevent changes in traffic flow. Anomaly detection is one of three techniques of the Intrusion Detection System (IDS). Network characteristics tracked by network anomaly detection programs at scale include packets, bandwidth, bytes, traffic volume, and the used protocols. Suspicious events are recorded in Interface, IP Group, Transmission Control Protocol (TCP), User Data Protocol (UDP), and Internet Control Message Protocol (ICMP) reports. Therefore, this research was carried out to detect anomalies using the Machine Learning algorithm: Decision Tree. This study analyzed 4998 records with 34 attributes, with one attribute as a class. Using the decision tree method, the highest accuracy results are 99.95%.
A triple band flexible microstrip (FM) antenna is presented for Wireless Local Area Network (WLAN), Worldwide Interoperability for Microwave Access (WiMAX), and Ultra Wideband (UWB) applications. The basic C-slot antenna has been modified with an extra I-slot added in the middle. Felt substrate, with permittivity 1.22 and height 4 mm, is taken as substrate which adds flexibility to the design and makes it more robust. The proposed FM antenna resonate at three frequencies, viz. 2.5/5.4/7.1 GHz with 10-dB impedance bandwidths of 95/367/568 MHz and voltage standing wave ratios (VSWR) of 1.44/1.9/1.5 respectively. It also provides a significant overall directive gain of 8.75 dB. With fair certainty, it can be declared that the suggested antenna is suitable for usage in all three of the aforementioned applications due to its straightforward construction, small size, flexible nature, and acquired results. High Frequency Structure Simulator (HFSS) has been used for the design and analysis.
“All-media“ is the result of the deep integration of various media under the support of information and network technology. With the advent of the era of all-media, all-effective media, all-member media, holographic media and full-scale media are gradually formed, and life is more intelligent and convenient. With technology empowerment, reading content is getting richer and richer, and ‘‘ Audio Reading’’ has developed as both a carrier and platform for content, and a medium to connect content dissemination and recipients. This paper develops an interactive platform for Audio Reading based on the progressive framework Vue, which simplifies the event-driven user interface; based on the modular idea, it designs the specific module composition of the system interface and interaction, and builds a reader based on FBReader to meet the needs of audio reading in the era of allmedia.
