A Comprehensive Revise on Discovering Public Media Psychological Disorders through Online Public Media Search

The explosive increase in social networking popularity results in problem usage. A number of social mental illnesses in the network have been reported, including cyber relationship dependence, overload of information and Net Compulsion. The symptoms of these psychiatric illnesses are mostly passively observed today and lead to delayed treatment procedure. We do not rely on self-review of these mental factors through questionnaires in psychology, as our methodology is new and groundbreaking with regard to SNMD detection. We instead provide a deep learning system that exploits features taken from the social network's data to correctly classify possible SNMD incidents. We also suggest the social network's mental disorder detection framework. In order to increase precision, we also use multi-source training in SNMDD and suggest a new SNMD-based tensor model. We further enhance reliability with accuracy guarantees in order to maximize STM's scalability. Our system is assessed by a sample analysis of 3126 apps. A function analysis and SNMDD on massive databases are performed and the properties of the three categories of SNMD analyzed. The findings demonstrate that SNMDD is good at finding consumers of future SNMDs online social network

Endogenous plant metabolites influence on shelf-life extension of tuberose flowers

Tuberose is highly valuable for making floral ornaments, bouquets, artistic garlands, button holes and essential oil. The present study aimed to increase the shelf life of loose flowers by the exogenous application of endogenous plant metabolites i.e. polyamines-putrescine and spermidine at 15 and 20 mg each and with two controls (with/ without packaging). The polyamine-dipped tuberose florets were packed in polyethylene zip covers (56 microns thickness & 1% ventilation), and stored at room temperature (32±1oC and 65 ± 3% RH). Results revealed that putrescine (20 mg) and spermidine (20 mg) treated florets had reduced physiological loss in weight and spoilage percentage with delayed flower opening, and higher sensory acceptance when compared to other treatments and also extended vase life (4 days). The shelf life of untreated flowers without a package was just on the harvested day. Thus, the exogenous application of polyamines had a synergic effect on the shelf life of tuberose loose flowers and can be effectively utilized in the supply chain of tuberose

Implementation of DEEC Protocol Using Optimization Technique in Wireless Sensor Technology

Wireless sensor networks are employed in several applications like military, medical, household and environmental. In these applications energy factor is the determining factor in the performance of wireless sensor networks. In wireless sensor network, clustering is used as an effective technique to achieve scalability, self-organization, power saving, channel access, routing etc. Lifetime of sensor nodes determines the lifetime of the network and is crucial for the sensing capability. Clustering is the key technique used to extend the lifetime of a sensor network and also reduce energy consumption etc,. Energy-efficient clustering protocols should be designed for the characteristic of heterogeneous wireless sensor networks[1]. DEEC which is named as distributed energy efficient clustering protocol is selected as clustering protocol[1]. In DEEC, the cluster heads are elected by a probability based on the ratio between residual energy of each node and the average energy of the network. Since in DEEC, the lifetime of sensors as well as network degrades very quickly. Hence in order to increase the network lifetime a new algorithm is proposed. This technique balances the cluster by using some backup nodes. The backup high energy and high processing power nodes replace the cluster head after the cluster reaches to its threshold limit. This approach will increase the network lifetime and will provide high throughput

A Reliable Traffic and Energy Aware Routing Protocol for Diverse Wireless Sensor Networks

Wireless Sensor Network (WSN) knowledge is a significant building block of IoT scope. Thought of heterogeneity e.g., energy, link and computational heterogeneities can recover the presentation of WSN routing algorithms in rapports of system generation, steadiness, dependability, network delay, etc.  A fresh routing algorithm named Traffic and Energy Aware Routing (TEAR) is presented, which contemplates node’s traffic requirements laterally with its liveliness levels while production CH selection. TEAR displays advances in terms of solidity period, consistent lifetime of the WSN before the expiry of its first node ended existing algorithms EACH, SEP and DEEC under the situation

Highly Sensitive Electrospun Multiwalled Carbon Nanotubes Embedded Zinc Oxide Nanowire Based Interface for Label Free Biosensing

We demonstrate synthesis of Multiwalled carbon nanotubes (MW CNTs) embedded highly oriented Zinc Oxide (ZnO) nanowires targeted towards development of ultrasen sitive electrochemical nanobiosensors using electrospinning method. The synthesized composite nanowires combines advantages of ZnO such as biocompa tibility, electrostatic affinity towards biomolecules with the excellent conductivity and surface functi onalization capabilities of MWCNTs. Calcinatio n temperature is optimized so as to ensure MWCNTs are present in their original form and at the same time highly crystalline ZnO is obtained. The key advantage o f this process is that there is no separate functionalization pr ocess is required to create functional groups on MWCNTs. Furthermore, the electrochemical activity of MWCNTs embedded ZnO nanowires is much higher as compared to pure ZnO nanowires. We have demonstrated the performance of electrochem ical nanobiosensor using Biotin -streptavidin interaction as model system. The sensor exhibits excellent sensitivity in the range 10 μ gmL -1 - 0.5 fgmL -1 of streptavidin with 0.5fgmL -1 limit of detection

Efficient tree structured algorithm for providing confidentiality of location data to minimize communication overhead in LBS Services

We present an effective and protection safeguarding polygons spatial inquiry structure for area based administrations, called Polaris. With Polaris, the LBS supplier redistributes the encoded LBS information to cloud server, and the enrolled client can question any polygon range to get precise LBS results without revealing his/her inquiry data to the LBS supplier and cloud server. Proficient uncommon polygons spatial inquiry calculation over ciphertext is developed dependent on an enhanced homomorphic encryption innovation over Composite request gathering. With SPSQ, Polaris can look re-appropriated scrambled LBS information in cloud server by the encoded demand, and react the scrambled polygons spatial question results precisely

Congestion Detection and Mitigation Technique for Multi-Hop Communication in WSN

The primary function of a network system is to gather information from the observation region and transmit it to the base station. The network life span and congestion are the two major concerns in wireless networks. To enhance the lifespan of the sensor system; multi-hopping has been proved as best in class. Congestion is an important factor to be taken, where multiple nodes forward data to one another in the process of communication. Hence to overcome the issue of congestion in WSN, we proposed a congestion detection and mitigation method along with the multi-hop concept. In this technique, we have considered different routes among communication units that were classified on distance, relative attainment rate (RAR) and node storage occupancy. A utility function (U) has been proposed and calculated using the above illustrated factors for every node that acts as a neighbour to the transmitting node. Neighbour node with highest U-valued will be considered as the packet forwarding node's next hop. In this manner congestion free nodes are selected for data transmission

Token Bucket Algorithm with Modernization Techniques to Avoid Congestion in DEC Protocol of Wsn

A wireless sensor system is an essential aspect in many fields. It consists of a great deal of sensor nodes. These sensor networks carry out a number of tasks, including interaction, distribution, recognition, and power supply. Data is transmitted from source to destination and plays an important role. Congestion may occur during data transmission from one node to another and also at cluster head locations. Congestion will arise as a result of either traffic division or resource allocation. Energy will be wasted due to traffic division congestion, which causes packet loss and retransmission of removed packets. As a result, it must be simplified; hence there are a few Wireless sensor networks with various protocols that will handle Congestion Control. The Deterministic Energy Efficient Clustering (DEC) protocol, which is fully based on residual energy and the token bucket method, is being investigated as a way to increase the energy efficiency. In the event of congestion, our proposal provides a way to cope with it and solves it using this method to improve lifespan of the sensor networks. Experiments in simulation show that the proposed strategy can significantly enhance lifetime, energy, throughput, and packet loss