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Neighboring radio networks are those that do not instantly supply communications infrastructure after deployment, have radio transceivers with restricted transmission range, and are unaware of possible neighbors. Vehicle-to-vehicle communication is an effective means to convey information through an asymmetric vehicle ad hoc network, and it can provide high security while also reducing energy usage. A new protocol is known as energy efficiency, the D-LAR (Directed Location Assist) protocol, is used to determine a node's energy efficiency. To determine the sleep and active states of nodes, propose a sleep scheduling technique. It can also provide a more accurate location of a moving vehicle than existing location support protocols. In comparison to other current systems, the simulation results suggest that the proposed D-LAR technique has the advantages of decreasing the collision attack detection delay time and enhancing security.

Internet of things (IoT) is an inventive technology which permit the association of physical things by means of the digital world throughout the use of heterogeneous networks and communication technologies. Ad-hoc routing protocols may be dispersed and involve every node in route discovery process by making routing data more reliable. Mobile-Adhoc-Networks (MANETs) consist of many portable nodes that can commune directly with each other or through intermediate nodes. Repeatedly, nodes in a MANETs operate with batteries and can roam freely, and thus, a node may exhaust its energy or move away without providing any notice to its cooperative nodes. IoT system using a combination of MANET, a route consists of numerous links in sequence, and so, its lifetime is based on the lifetime of every node and also the wireless links among adjacent nodes. In this research work Fuzzified Particle Swarm Optimization oriented Routing (FPSOR) algorithm is planned to minimize data loss and computational overhead, which in turn maximizes the lifetime of MANETs. Particle Swarm Optimization oriented Routing protocol (PSOR) have taken energy competence as significant criterion for processing routing and driving optimized path for the data accelerating and processing to the source node. The PSOR produces a fresh route for routing by considering fitness value of energy to evaluate diverse path and to choose best-optimized path whose energy consumption is less as compared to ant colony optimization routing paths. This algorithm utilizes a good approach focusing energy levels/status of the nodes through fuzzification and the lengths of the routed ways. NS2 simulator is casted for performance evaluation.

The motivation of the research work is Respiratory Rate (RR) monitoring which is susceptible to environmental and physiological stimuli, knowing it may help in assessing the health of patients. In this work, at rest, six trials on a treadmill were to be completed by 10 healthy males, while low-speed jogging in order to evaluate a new approach based on Principal Component Analysis (PCA). Random Forest (RF) with PCA for sensory selection using a special wearable system with six piezoresistive sensors. For instance, a single sensor is needed for a breathing evaluation while at rest, three sensors are needed for a low-speed walk, and four sensors are needed for a high-speed walk and run assessment. The findings may be helpful in the deployment of specialized algorithms to continuously and accurately monitor RR, as well as the creation of the best instrumented wearable devices for RR monitoring both while the subject is at rest and when they are engaging in physical activity. A smart garment was utilized to obtain the breathing information delivering six respiration signals in the three compartmental parts, and a data gathering board (DAQ NI USB6002 from National Instruments) was used to gather the reference respiratory data. The performance measurements are often calculated using it (e.g., accuracy, sensitivity, specificity, precision and F1 score).

Ships and other large equipment must meet strict standards for equipment integrity and operational dependability in order to perform missions. To meet this demand, one of the essential linkages is to guarantee the long-term safe and healthy functioning of their power transmission equipment. The Optimized Back Propagation Neural Network (OBPNN) technique used in this study introduces a unique method for monitoring sensor data and evaluating the health state, with the SVM being optimized using the fish swarm algorithm (FSA). A major problem that maintenance is facing nowadays is reliable fault prediction. One of the trickiest difficulties is arguably automatically modelling typical behaviour from condition monitoring data, particularly when there is little information about actual failures. A data-driven learning framework with the best bandwidth selection is suggested to address this challenge. It is based on nonparametric density estimation for outlier identification and OBPNN for normality modelling. The distance to the separating hyper plane's log-normalization is used to provide a health score that is also available. The algorithm's viability is shown by experimental findings while evaluating the progression of a major defect over time in a marine diesel engine. Improved prediction capabilities and low false positive rates on healthy data are realized.

Cloud Computing, employed in various applications and services, refers to using computational resources as a service depending on customer needs via the Internet. The computing paradigm is built on data outsourcing to third-party-controlled data centers. Despite the significant developments in Cloud Services and Applications, various security vulnerabilities remain. This research proposes the EBBKG Model for Efficient Data Sharing in Cloud. For secure data sharing in the cloud, the approach combines BBKG with ABS. The method offers good data management that efficiently specifies the subsequent processing processes. The paradigm imposes encrypted access control, along with specific enhanced access capabilities. Secondly, the user's privacy may be adequately protected with a secure authentication paradigm that employs ABS to safeguard the user's private data. The key is optimized using BOA to enhance security and cloud providers and limit dangerous user threats using these implementations. Criteria like security, time complexity, and accountability govern the suggested method's effectiveness.

Abstract The farmer interest in biological control-based management practices using entomopathogenic fungi (EPF) for the control of many economically important insects has increased. In this process, selection of effective strains of EPF is an important criterion to control the target insect pests in efficient manner. In this context, this research work was formulated to find out environmentally effective strains of EPF in the soils of costal districts of Andhra Pradesh, India. Out of 135 soil samples collected, 9 yielded 9 strains of Lecanicillium lecanii. Among all 9 L. lecanii isolates, the least median lethal concentration (LC50) for 3rd instar larvae of the tobacco caterpillar, Spodoptera litura (Fabricius) (Lepidoptera: Noctuidae), was 1.17 × 106 spores ml−1 in L-8, followed by 1.27 × 106 spores ml−1 in L-5 in an increasing order. Likewise, the median lethal time (LT50) values of different isolates of EPF against the 3rd instar of S. litura were calculated for the uniform highest concentration of 1 × 108 spores ml−1. Among all 9 L. lecanii isolates, the lowest median lethal time (LT50) was observed as 7.70 days by L-8, followed by 7.77 days by L-5 and 8.50 days by L-7.

Abstract In the recent years, the keen interest has been increased towards biological control-based management practices using entomopathogenic fungi (EPF) for the control of many economically important insects. In this management practices, selection of right strains of EPF is an important criteria to control the target pests in effective manner. In this context, this research work was formulated to find out environmentally effective strains of EPF in the soils of costal districts of Andhra Pradesh. Out of 135 soil samples collected, 8 soil samples yielded 8 strains of Metarhizium anisopliae. Among all 8 M. anisopliae isolates, the least median lethal concentration (LC50) for 2nd instar of the tobacco caterpillar, Spodoptera litura (Lepidoptera: Noctuidae) was 1.24 × 105 spores ml-1 in M-7, followed by 1.72 × 105 spores ml-1 in M-5 and 1.86 × 105 spores ml-1 in M-4 in an increasing order. Likewise, the median lethal time (LT50) values of different isolates of EPF against 2nd instar of S.litura were calculated for a uniform highest dose of 1 × 108 spores ml−1. Among all 8 M. anisopliae isolates, the lowest LT50 was observed as 186.44 hours post infection (hpi) with M-5 and 189.34 hpi with M-7.

Epilepsy can well be stated as a disorder of the central nervous systems (CNS) that brought about recurring seizures owing to chronic abnormal blasts of electrical discharge on the brain. Knowing if an individual is having a seizure and diagnosing the seizure type or epilepsy syndrome could be hard. Many methods were developed to recognize this disease. But the existing techniques for detection of epilepsy are not satisfied with accuracy, and cannot identify the diseases effectively. To trounce these drawbacks, this paper proposes an approach for the recognition of Epilepsy as of the electroencephalography (EEG) signals. This is implemented as follows. Primarily, the Kalman filter (KF) is utilized for pre-processing to eradicate the impulse noise present in the EEG signals. This filtered signal is then decomposed utilizing variable modes decomposition (VMD). Feature extraction (FE) is performed by computing 7 features. The dimensionality of this signal is then lessened using Modified-Principal Components Analysis (M-PCA). Finally, classification is conducted utilizing the artificial neural networks (ANN) that is optimized using the hybrid dragonfly algorithm (HDA). Disparate performance metrics such as sensitivity, accuracy, and false discovery rates (FDR) are ascertained and as well weighted against with the existent works.

Along with the great increase of internet and e-commerce, the use of credit card is an unavoidable one. Due to the increase of credit card usage, the frauds associated with this have also increased. There are a lot of approaches used to detect the frauds. In this paper, behavior based classification approach using Support Vector Machines are employed and efficient feature extraction method also adopted. If any discrepancies occur in the behaviors transaction pattern then it is predicted as suspicious and taken for further consideration to find the frauds. Generally credit card fraud detection problem suffers from a large amount of data, which is rectified by the proposed method. Achieving finest accuracy, high fraud catching rate and low false alarms are the main tasks of this approach.

Bluetooth is a short range radio technology to form a small wireless system. It is used in low –cost, low power ad-hoc networks and it suffers from long service discovery delay and high power consumption. Bluetooth employs the 2.4 GHz ISM band, sharing the same bandwidth with the wireless LAN implementing the IEEE 802.11 standards. Thus it causes significantly lower interference. For improving the efficiency of SDP, we present an implementation of Bluetooth 2.1 in the NS-2 simulator, discuss the IEEE 802.11b as a Bluetooth controller and propose a new alternative Bluetooth Controller based on Adaptive Frequency Hopping techniques using Amplifier Power. The resulting approach significantly reduces the service discovery time, thereby lowering power consumption and increasing the throughput. We present the benefits of our new approach and compare it with existing approach using NS-2 Simulations and we have presented the comparison graphs in support of our approach.

A field experiment on drip irrigation for Chowghat Orange Dwarf X West Coast Tall (COD X WCT) coconut hybrid was conducted in laterite soil at Central Plantation Crops Research Institute, Kasaragod (Kerala, India) to study the drip irrigation requirement and its influence on growth and yield. The treatments included were three levels of drip irrigation (at 33, 66 and 100% E0 daily), basin irrigation (100% E0) and rainfed control. The experimental results revealed that annual leaf production and leaf nutrient status of coconut palm was significantly higher in the irrigated treatments compared to the rainfed control. The female flower production and nut yield with 66 per cent of Eo was on par with 100 per cent of Eo through drip and 100 per cent of Eo through basin irrigation and significantly superior compared to drip irrigation at 33 per cent of E0 and rainfed control. Drip irrigation equal to 66 per cent of open pan evaporation (Eo) proved to be the economically efficient method of irrigation with water saving of 34 per cent compared to 100 per cent of Eo through basin and drip method.

A field experiment on drip irrigation for Chowghat Orange Dwarf X West Coast Tall (COD X WCT) coconut hybrid was conducted in laterite soil at Central Plantation Crops Research Institute, Kasaragod (Kerala, India) to study the drip irrigation requirement and its influence on growth and yield. The treatments included were three levels of drip irrigation (at 33, 66 and 100% E0 daily), basin irrigation (100% E0) and rainfed control. The experimental results revealed that annual leaf production and leaf nutrient status of coconut palm was significantly higher in the irrigated treatments compared to the rainfed control. The female flower production and nut yield with 66 per cent of Eo was on par with 100 per cent of Eo through drip and 100 per cent of Eo through basin irrigation and significantly superior compared to drip irrigation at 33 per cent of E0 and rainfed control. Drip irrigation equal to 66 per cent of open pan evaporation (Eo) proved to be the economically efficient method of irrigation with water saving of 34 per cent compared to 100 per cent of Eo through basin and drip method.

A field experiment was conducted at Central Plantation Crops Research Institute, Kasaragod, India for six years (1993-1999) to study the impact of drip irrigation levels and mulching on coconut in littoral sandy soil. The treatments consisted of three levels of drip irrigation (66, 100, and 133 % of open pan evaporation (E0)) along with basin irrigation (100 % of E0) and rainfed control as main plot treatments and mulching with coconut leaves and no mulching as sub plot treatments. The experimental results revealed that annual leaf production and leaf nutrient status of coconut was better in the irrigated treatments compared to the rainfed control. The drip irrigation at 66 per cent of E0 (27 litres of water per palm per day during December-January months and 32 litres of water per palm per day during February-May months) resulted in water saving and the nut yield was on par with 100 per cent and 133 per cent of E0 through drip and 100 per cent of E0 through basin irrigation and differed significantly compared to rainfed control. The nut characters like nut weight, husk weight, copra thickness, copra content and copra yield was superior under irrigated treatments compared to rainfed control. The copra yield was 499 kg per ha under rainfed condition, where as it was 2087 to 2202 kg per ha under irrigated treatments. Irrigation along with mulching with coconut leaves resulted in significantly higher nut yields.

Coconut-Based Mixed Farming System which evolved from the Central Plantation Crops Research Institute is one of the technologies recommended for sustainable coconut production. The economic analysis of this system for the period 1989-90 to 1997-98, realized a net return between Rs. 49,700 to Rs. 126,900. The Cash Flow Analysis preformed using a discount rate of 14% realized the Benefit-Cost Ratio (BCR) of 1.36, the Net Present Worth of the system was Rs.286,500,, the Internal Rate of Return was 27.44%, and, the Pay Back Period was five years.

Analysis of past weather data indicated increase in maximum temperature at varied magnitudes over various coconut growing areas across the country except in southern Kerala. In case of minimum temperature, sixty percent of the locations studied showed a declining trend, widening the difference between maximum and minimum temperatures. The days above 33 oC, optimal for coconut growth and development, were in increasing trend in most of the coconut growing area while days below 15 oC are increasing in northern Kerala, plains of Karnataka and western Tamil Nadu. Annual Rainfall showed declining trend in most of the coconut growing areas with change in amount. Dry spells are in increasing trend in parts of Karnataka and Kerala. Change in coconut productivity during past three decades across the country ranged from -114 to 270 nuts/ha/year. The productivity of coconut during the study period was in increasing trend except for parts of Maharastra, Karnataka and Tamil Nadu, where consecutive droughts affected the yields.