MULTIMEDIA NETWORKING A Leading-Edge Communication Technology

The realization of digital multimedia's full business potential requires networking. This article discusses the value-added benefits to the corporation of networked multimedia as well as the choice of architectures and technologies needed to deliver multimedia networking solutions.     

Grid Search for Predicting Coronary Heart Disease by Tuning Hyper-Parameters

Diagnosing the cardiovascular disease is one of the biggest medical difficulties in recent years. Coronary cardiovascular (CHD) is a kind of heart and blood vascular disease. Predicting this sort of cardiac illness leads to more precise decisions for cardiac disorders. Implementing Grid Search Optimization (GSO) machine training models is therefore a useful way to forecast the sickness as soon as possible. The state-of-the-art work is the tuning of the hyperparameter together with the selection of the feature by utilizing the model search to minimize the false-negative rate. Three models with a cross-validation approach do the required task. Feature Selection based on the use of statistical and correlation matrices for multivariate analysis. For Random Search and Grid Search models, extensive comparison findings are produced utilizing retrieval, F1 score, and precision measurements. The models are evaluated using the metrics and kappa statistics that illustrate the three models’ comparability. The study effort focuses on optimizing function selection, tweaking hyperparameters to improve model accuracy and the prediction of heart disease by examining Framingham datasets using random forestry classification. Tuning the hyperparameter in the model of grid search thus decreases the erroneous rate achieves global optimization.     

Application of ameliorated Harris Hawks optimizer for designing of low-power signed floating-point MAC architecture

Neural Computing and Applications - Recently established Harris Hawks optimization (HHO) has natural behaviour for finding an optimum solution in global search space without getting trapped in...     

3D word spotting using leap motion sensor

Multimedia Tools and Applications - Leap motion sensor provides a new way of interaction with computers or mobile devices. With this sensor, users can write in air by moving palm or finger, thus,...     

Effect of omega fatty acid-rich oil blend supplementation on the growth,carcass, meat quality,and gene expression of Barbari goats

This study investigated the effect of supplementing omega fatty acids-rich oil blend, composed of sunflower oil (1.5% and 3.0%), linseed oil (1.5% and 3.0%), and FineXNV1810 (20 g) on the carcass, meat quality, fatty acid profile, and genes (peroxisome proliferator-activated receptor-α, stearoyl-CoA desaturase, acetyl-CoA carboxylase, hydroxy-3-methylglutaryl coenzyme A, and leptin) of Barbari goats. The goat kids (n = 18) were divided into three groups, namely, group A: basal diet; group B: basal diet + oil blend level 1; and group C: basal diet + oil blend level 2, and subjected to the feeding trial for 120 days followed by slaughter and meat quality studies. No treatment effect was recorded in carcass characteristics, pH, water holding capacity, and proximate composition of meat. However, a significant (p < 0.05) treatment effect was observed in cooking loss, lightness, yellowness, and shear force values of meat. There were significant differences (p < 0.05) in linoleic acid, α-linolenic acids, conjugated linoleic acid (CLA), polyunsaturated fatty acids (PUFA), n − 3 and n − 6 PUFA, PUFA/saturated fatty acids and n − 6/n − 3 ratios, and thrombogenic index among groups. An upregulation of the studied genes in the supplemented groups was observed. There were upregulations in the studied genes in the supplemented groups. Practical applications: Goat meat is in great demand the world over, especially in tropical countries, including India, and does not carry any social or religious prohibition. Although goat meat has relatively less fat, consumers express their concern over the presence of undesirable fatty acids. The present study shows that the fatty acid configuration of goat meat can be improved by a dietary supplementation of an oil blend rich in omega fatty acids. The amount of n − 3 PUFA, n − 6 PUFA, and CLA in goat meat was significantly increased due to the dietary oil blend making it healthy for the consumers. Moreover, the dietary oil blend at the studied levels did not significantly affect the growth and meat quality parameters of the goats. Thus, the studied approach can be successfully followed to produce healthier goat meat.     

Z number improved reference ideal method-based decision-making process for enforcing cooperation during data dissemination in mobile ad hoc networks

In mobile ad hoc networks (MANETs), cooperative communication and resource constraint are the two important core characteristics essential to guarantee trusted data dissemination. The cooperative communication between mobile nodes depends on the trust rendered by them towards the process of reliable data routing. However, stringent resource constraints of mobile nodes such as energy, memory, communications, and computations result in the introduction of selfish and malicious node that completely degrades the network performance in different dimensions. In this paper, Z number improved reference ideal method (RIM)-based decision-making process (NIRIMDMP) is proposed with the merits of maximizing deviation method (MDM) and best–worst method (BWM) to ensure reliable data routing by modeling the cooperation degree in terms of Z number. This NIRIMDMP adopted Z number to represent the information reliability and handle the problem of inherent uncertainty during the process of evaluating each mobile node in the routing process. In specific, MDM and BWM are included into the proposed NIRIMDMP to determine comprehensive attribute weights based on the calculated objective and subjective weights that could be possible derived in routing. It extended the merits of classical RIM using Z numbers to confirm reliable ranking of mobile nodes, even when the optimal solution exists amid extreme values taken into consideration for assessing the mobile nodes during decision making. Simulation investigations of the proposed NIRIMDMP confirmed improved throughput and network lifetime with reduced control overhead, energy consumptions, and delay independent of the amount of malicious and non-cooperative nodes.     

Design and Investigation of Split Gate Dielectric Modulated JLFET for Detection of Biological Molecule Using TCAD Simulation

Silicon - Here, a split gate insulator-controlled Junction less FET also known as SG-DM-JLFET is investigated and proposed to recognize biomolecules such as uricase, biotin, or aminopropyl-...     

SCT Based Adaptive Data Aggregation for Wireless Sensor Networks

Communication overhead is a major concern in wireless sensor networks because of inherent behavior of resource constrained sensors. To degrade the communication overhead, a technique called data aggregation is employed. The data aggregation results are used to make crucial decisions. Certain applications apply approximate data aggregation in order to reduce communication overhead and energy levels. Specifically, we propose a technique called semantic correlation tree, which divides a sensor network into ring-like structure. Each ring in sensor network is divided into sectors, and each sector consists of collection of sensor nodes. For each sector, there will be a sector head that is aggregator node, the aggregation will be performed at sector head and determines data association on each sector head to approximate data on sink node. We propose a doorway algorithm to approximate the sensor node readings in sector head instead of sending all sensed data. The main idea of doorway algorithm is to reduce the congestion and also the communication cost among sensor nodes and sector head. This novel approach will avoid congestion by controlling the size of the queue and marking packets. Specifically, we propose a local estimation model to generate a new sensor reading from historic data. The sensor node sends each one of its parameter to sector head, instead of raw data. The doorway algorithm is utilized to approximate data with minimum and maximum bound value. This novel approach, aggregate the data approximately and efficiently with limited energy. The results demonstrate accuracy and efficiency improvement in data aggregation.