Optimized Identification with Severity Factors of Gastric Cancer for Internet of Medical Things

The Internet of Medical Things (IoMT) emerges with the vision of the Wireless Body Sensor Network (WBSN) to improve the health monitoring systems and has an enormous impact on the healthcare system for recognizing the levels of risk/severity factors (premature diagnosis, treatment, and supervision of chronic disease i.e., cancer) via wearable/electronic health sensor i.e., wireless endoscopic capsule. However, AI-assisted endoscopy plays a very significant role in the detection of gastric cancer. Convolutional Neural Network (CNN) has been widely used to diagnose gastric cancer based on various feature extraction models, consequently, limiting the identification and categorization performance in terms of cancerous stages and grades associated with each type of gastric cancer. This paper proposed an optimized AI-based approach to diagnose and assess the risk factor of gastric cancer based on its type, stage, and grade in the endoscopic images for smart healthcare applications. The proposed method is categorized into five phases such as image pre-processing, Four-Dimensional (4D) image conversion, image segmentation, K-Nearest Neighbour (K-NN) classification, and multi-grading and staging of image intensities. Moreover, the performance of the proposed method has experimented on two different datasets consisting of color and black and white endoscopic images. The simulation results verified that the proposed approach is capable of perceiving gastric cancer with 88.09% sensitivity, 95.77% specificity, and 96.55% overall accuracy respectively.     

Optimized Reliable Hybrid Routing Protocol Based Link Stability for Mobile Wireless Networks

Wireless Personal Communications - During the last two decades, there has been a tremendous growth in the use of MANETs, not only due to the development of the technology but also due to their high...     

BROWNING OF SAGO (METROXYLON SAGU) PITH SLURRY AS INFLUENCED BY HOLDING TIME, pH AND TEMPERATURE

The effect of holding time, pH and temperature of sago pith slurry on its browning was evaluated. Holding time of sago pith slurry, which browning took place, proved to be an important factor in determining the amount of soluble phenolic compounds that were oxidized. This subsequently led to the development of color. The amount of (+)-catechin and (-)-epicatechin that was oxidized increased with pH particularly above pH 4.5. This resulted in simultaneous development of color in the sago pith slurry. The oxidation of phenolic compounds in acidic conditions was suggested to be caused by latent polyphenol oxidase (LPPO) as it is activated by acidic pH. The amount (+)-catechin and (-)-epicatechin oxidized also increased with increase in temperature particularly above 30C.     

A survey on trust based detection and isolation of malicious nodes in ad-hoc and sensor networks

Mobile ad-hoc networks (MANETs) and wireless sensor networks (WSNs) have gained remarkable appreciation and technological development over the last few years. Despite ease of deployment, tremendous applications and significant advantages, security has always been a challenging issue due to the nature of environments in which nodes operate. Nodes’ physical capture, malicious or selfish behavior cannot be detected by traditional security schemes. Trust and reputation based approaches have gained global recognition in providing additional means of security for decision making in sensor and ad-hoc networks. This paper provides an extensive literature review of trust and reputation based models both in sensor and ad-hoc networks. Based on the mechanism of trust establishment, we categorize the stateof-the-art into two groups namely node-centric trust models and system-centric trust models. Based on trust evidence, initialization, computation, propagation and weight assignments, we evaluate the efficacy of the existing schemes. Finally, we conclude our discussion with identification of some unresolved issues in pursuit of trust and reputation management.     

Microstructure and corrosion behavior of Mg-Sn-Ca alloys after extrusion

Mg-Sn-Ca alloys promise a reasonable corrosion resistance in combination with good creep resistance, likely due to the presence of Ca2-xMgxSn and other phases. The selected alloys with 3% Sn and Ca in the range of 1%-2% have been extruded in order to achieve more homogeneous microstructure compared with the as-cast alloys. Optical microscopy(OM) and X-ray diffraction(XRD) techniques were used to study the microstructure and phases of these alloys. The corrosion behavior of these alloys was investigated by means of salt spray test and potentio-dynamic measurements. The results obtained on the alloys Mg-3Sn (T3), Mg-3Sn-1Ca (TX31), and Mg-3Sn-2Ca (TX32) indicate the presence of the same phases in as-cast and after extrusion, namely Mg2Sn, Ca2-xMgxSn, and Ca2-xMgxSn/Mg2Ca, respectively. However, due to the occurrence of extensive recrystallization in the extrusion process, the grain size has significantly reduced after extrusion. The reduction leads to the improvement of the corrosion resistance after extrusion which is then comparable with the commercial alloy AZ91D.     

Security & Privacy in Software Defined Networks,Issues, Challenges and Cost of Developed Solutions: A Systematic Literature Review

International Journal of Wireless Information Networks - Due to fast development in digital systems, the traditional network architecture is becoming inadequate for the requirements of new...