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Background: Large ruminants are considered as high risk anaesthesia patient for abdominal surgery because of their heavy weight, the late-term gravidity and the expected long duration of anaesthesia. In order to augment cardiopulmonary function, we aimed at decreasing the requirement of inhalant agents for surgery. Several studies have revealed that lignocaine infusion significantly reduces the minimum alveolar concentration (MAC) of inhalation agents in a variety of species. Thus the present study is focused on assessing the adjunct property of intravenous lignocaine CRI in multimodal general anaesthetic protocol employed for intestinal surgery in cattle. Methods: The study was carried out in 12 clinical cases of cattle which were randomly categorized into two equally groups. All the animals were premedicated with dexmedetomidine and butorphanol tartrate at the dose rate of 0.5 µg per kg and 0.02 mg per kg body weight i.v. respectively. After five minutes of premedication, induction of anaesthesia was achieved with double drip solution containing ketamine hydrochloride 2 mg and guaifenesin 50 mg per mL respectively, administered i.v. “to effect”. Anaesthesia was maintained with isoflurane in all the animals. In group II animals ten minutes prior to skin incision, slow intravenous lignocaine bolus at the dose rate of 2 mg per kg and continuous rate infusion at the dose rate of 50 µg per kg per min was delivered through volumetric infusion pump. Result: The Isoflurane liquid utilised for maintenance decreased significantly in group II than group I, which signifies that the inclusion of lignocaine in the anaesthetic protocol has 14.95 per cent isoflurane sparing effect.

In today’s world, brain tumor is detected in many people. The count of people affected with brain tumor, increases every day, irrespective of age and gender. The survival rates of brain tumor is very less when compared to other tumor cells. Brain tumor is the abundant growth of thick and unusual cells in brain. Brain tumor perhaps can be malignant tumor or benign. Malignant tumors aggressively spread to distant part of the body. Tumor that does not spread nearby tissue called as benign. Detection of brain tumor using various technologies is still under research. Brain tumor identification and segmentation in recent years is done by Magnetic Resonance Imaging (MRI). Software for accurate identification of brain tumor is still under existence. So, we propose an idea for identification and segmentation of brain tumor using deep learning. The first step will be processing the Magnetic Resonance Imaging (MRI) by giving it as the input, it is analyzed and segmented using various deep learning techniques such as initializing the CNN, pooling, flattening, compiling the CNN using Tensor Flow as backend. Thus, Identification and segmentation of brain tumor can be identified easily and efficiently.

A 60 days nursery-based co-culture of Indian white shrimp, Penaeus indicus along with seaweed, Gracilaria tenuistipitata trial was carried out in Recirculatory Aquaculture System (RAS) of 6000 Liters capacity tank (FRP, reinforced fibre plastics) by using biofloc technology (BFT) to evaluate the growth, survival performance and immune potential. Accordingly a completely randomized experiment was designed with six treatments. These treatments were: T1- Static system (Control), T2 - RAS with BFT, T3 - RAS with Gracilaria, T4 - RAS and BFT customized with bacterial consortium, T5 - RAS with BFT + Gracilaria + bacterial consortium, T6 - Static + Gracilaria + BFT (without consortium and without RAS). Shrimp post larvae (0.08 ± 0.03 g) were stocked at a density of 3000 nos./ton. RAS with BFT along with the seaweed and bacterial consortium showed significantly higher growth and survival compared to control (T1) and treatments without BFT (T3). The control (T1) exhibited significantly lower growth, weight gain, specific growth rate, yield and higher FCR value than that of the RAS + BFT (T2), RAS+ seaweed (T3) and RAS + BFT or their combinations with bacterial consortium (T4 and T5). The treatment having seaweed without BFT (T3) showed higher survival than the static control (T1), but no significant difference in growth. The highest ABW of 4.23 ± 0.39 was obtained in T4 (BFT customized with consortium) followed by T5 (BFT + seaweed + bacterial consortium) and lowest was observed in T1 (2.14 ± 0.4). Similarly, the highest survival (92.33 ± 1.52) and production (10.39 ± 0.24 kg/ton) was observed in T5. Significantly higher NH4-N and NO2-N was accumulated in the control (T1) in comparison with other treatment like T4 and T5. Immune parameters viz., PPO activity, Total Serum Protein and Total Hemocyte Count (THC) showed significantly higher values in all the treatments compared to control. This study establishes the novel concept of incorporation of macroalgae in biofloc based RAS improving the production performance and immune response of shrimp during nursery as well as grow-out phase.

The study was carried out in 12 clinical cases of cattle to assess the cardiovascular effects of intravenous continuous rate infusion of lignocaine as an adjunct to general anaesthesia for intestinal surgeries. The animals were indiscriminately selected and categorized equally into two groups. All the animals were premedicated with dexmedetomidine and butorphanol tartrate at the dose rate of 0.5 µg per kg and 20 µg per kg body weight i.v. respectively. After five minutes of premedication, induction of anaesthesia was achieved with double drip solution containing ketamine hydrochloride 2 mg and guaifenesin 50 mg per mL respectively, administered i.v. “to effect”. Anaesthesia was maintained with isoflurane in all the animals. In group II animals ten minutes prior to skin incision, slow intravenous lignocaine bolus at the dose rate of 2 mg per kg and continuous rate infusion at the dose rate of 50 µg per kg per min was delivered through volumetric infusion pump. There was no significant difference in cardiovascular parameters noticed between the group which signifies that intravenous lignocaine at this dose in anaesthetised cattle is cardiovascular dynamic.

Waste management has become a serious issue, especially in developing countries with very high population. Lack of bins or proper disposal facilities remains a problem to date. Various governments are also trying hard to push for a cleaner nation by helping curb pollution and improving public sanitation. The smart bin is an important and significant application to deliver cleanliness. A smart bin with automated metal and non-metal segregator is modeled. Using NodeMCU, the level of the bin is monitored in real time and sent to the cloud for further analysis. A novel mathematical model to calculate the most optimal way of distributing the bins in one dimension has also been discussed. Tourist areas, parks, educational institutions, etc., can use the bins in a network to improve sanitation.

The major role of electronics device is to provide low power dissipation and compact area with high speed performance. Among the major modules in digital building blocks system, multiplier is the most complex one and main source of power dissipation. Approximate Computing to multiplier design plays major role in electronic applications, like multimedia by providing fastest result even though it possesses low reliability. In this paper, a design approach of 16bit Wallace Tree approximate multiplier with 15-4 compressor is considered to provide more reliability. The 16×16 Wallace tree multiplier is synthesized and simulated using Xilinx ISE 14.5 software. The multiplier occupies about 15% of total coverage area. The dissipated power and delay of the multiplier are 0.042µw, 3.125ns respectively.

Path planning algorithms provide autonomy in mobile robots to reach targets even in unknown environments. Path planning using grid based techniques such as A ∗ and D ∗ , are cost function based, which is primarily a function of the distance to be travelled to reach the target. Robots targeted for outdoor environments should consider the terrain features also during path planning. In this paper, a modified approach of D ∗ path planning algorithm is proposed. In addition to distance to be travelled, terrain slope estimate is also used in cost function computation to plan the path. The algorithm was simulated and tested with different terrain slopes. Results with different test scenarios are also brought out.

The furthermost eco-amicable challenge nowadays is ecumenical warming. Energy disaster conveys green computing. Dynamic voltage scaling (DVS) has been a crucial procedure in exploiting the hardware characteristics of cloud datacenters to preserve energy by lowering the supply voltage and operating frequency. The study presents modified power consumption can be reduced by live migration of the virtual machines (VM) as required and by switching off idle machines. So, proposed a dynamic threshold predicated approach DMM CPU utilization for host at data center. This consolidation will work on dynamic and capricious workload evading nonessential power consumption. It will meet energy efficiency requisite but would withal ascertain quality of accommodation to the utilizer by minimizing the Service Level Agreement(SLA) contravention. The proposed is a graphic implement Cloud Sim as its simulation engine and offers a facile-to-use utilizer interface, report generation features and engenderment of extensions in a plugin fashion. Dynamic consolidation of virtual machines (VMs) utilizing live migration and switching idle nodes to the slumber manner sanction Cloud providers to optimize resource custom and diminish Energy consumption.

The concept of “biofloc technology” is changing the facet of intensive aquaculture with scope to attain high productivity in a sustainable manner. In biofloc, dense heterotrophic bacterial community is developed through C:N ratio manipulation, where the system becomes bacterial dominated rather than algae dominated and takes care of the wastes generated through in situ bioremediation. Protein is utilised in two ways; as feed for the shrimp and as microbial floc when the heterotrophic microbes convert the nitrogenous wastes into protein. It also promises a healthy rearing system, which is increasingly identified as one possible solution for disease problems especially those striking at early stages. The purpose of this study was to evaluate the effect of biofloc and periphyton technology (BPT) on the growth and immunomodulatory performance of Pacific white shrimp Penaeus vannamei during nursery and grow-out culture. The experimental BPT treatments with three tier substrate system with molasses as carbohydrate (CHO) source were compared with the conventional autotrophic system. Theimmunomodulation and cumulative percentage mortality upon challenge with pathogenic strain of Vibrio parahaemolyticus were assessed in the reared animals. We have successfully demonstrated the BPT based nursery and grow-out systems for P. vannamei with the advantage of providing significantly (p

Spacecraft Testing forms an integral part of spacecraft realization. The various subsystems of the spacecraft and its interfaces are evaluated through Integrated Spacecraft Tests. During these tests appropriate Telecommands are sent to the spacecraft. The decoding and execution of these commands are verified and confirmed against the expected behavior of various subsystems. Users send instructions using Checkout Command Language (CCL). Telecommands are generated from the CCL based on the project requirements. Total Automation for Spacecraft Checkout aims at providing an automatic test facility to carry out Spacecraft Testing. Based on satellite or project requirements Telecommand code pattern may vary from mission to mission. A Generic Telecommand Executor is developed for catering to Telecommand generation and execution for different projects. This paper brings out the design and implementation aspects of generic Telecommand Executor.

Text mining refers to the process of deriving high-quality information from text. Text processing involves in search and replace in electronic format of text. A number of approaches have been developed to represent and classify text documents. Most of the approach tries to attain good classification performance while taking a document only by words. We propose a concept based methodology instead of terms. It represents the meaning of text to reduce the features. Support Vector Machine (SVM) algorithm is applied for document classification. Then the performance measure is compared with document classification using original features and concept based features. This methodology enhances the document classification accuracy.

The vein structure is stable over time and can be manipulated for identifying human. The sclera portion of the human eye has blood vessel pattern which is unique for each human being. So, the sclera vein pattern can be used for a useful biometric feature. A few research works has been done over finger vein pattern recognition. Finger vein is an important biometric technique for personal identification and authentication. The finger vein is a blood vessel network under the finger skin. The network pattern is distinct for each individual, unaffected by aging and it is internal i.e. inside human skin which can always guarantee more security authentication. Sclera vein pattern recognition can face a few challenges like: the vein structure moves as the eye moves, low image quality, multilayered structure of the sclera vein and thickness of the sclera vein changes with the excitement level of the human body. To overcome this limitation, the multimodel biometrics is proposed through which the user can be authenticated either sclera vein or finger vein recognition. Sclera vein recognition used Y-shape descriptor and finger vein recognition used repeated line tracking based feature extraction method to effectively eliminate the most unlikely matches respectively. According to the available work in literatures and commercial utilization experiences, sclera vein and finger vein multimodality ensures higher performance and spoofing resistance. Thus building the multimodel biometric system increases the population coverage and improves the accuracy of the human recognition.

2 Abstract: Multiplication is one of the most critical arithmetic operation, which is extensively used in many VLSI systems such as application specific based digital signal processor architectures and microprocessor. Multipliers are the major source of power dissipation in the VLSI systems. By reducing the power consumption of the multipliers the power consumption of the VLSI system can be reduced. This paper presents the CLRCL full adder based 4*4 Wallace and Dadda multipliers. The CLRCL full adder has only ten transistors which is less in number when compared with conventional full adders which is used to design these multipliers. Designing Wallace and Dadda multiplier by using CLRCL full adder will reduce the transistor count and power consumption. The proposed design is simulated using 0.12µm.

In recent years, power dissipation is one of the biggest challenge in VLSI design. Multipliers are the main source of power dissipation in DSP block. Power of any multiplier can be reduced by designing a full adder which will consume very less power. So a lot of researches have been made to decrease the power consumption of the full adder. Here a structured approach for analysing the Wallace and Dadda multiplier is introduced. These multiplier are designed using existing full adders like 28T,16T,14T, and TGFA. These designs are studied and the analysis is made based on the simulation parameter like no of transistors count and power consumption using micro wind tool.

This dissertation exploits an Android base application gives clarification to assist parents to pathway their adolescent activity. It was implemented to locate the location based on real time map only when the user is found to be missing or kidnap cases. A parent's tool has to propel a application spot SMS to the child's tool to acquire the spot of the child. On the other side, the child's tool accept the acknowledgement and retort the GPS spot to the parent's tool upon request, but it was costly and was intricate as information's can be customized. This is based on Douglas peucker algorithm. This application provides the adolescent to be secure from the susceptible milieu by monitoring their commotion by exploring the android hook up in a smart handset of the adolescent tenuously.

Spacecraft Checkout operations form a crucial part in clearing the satellite along with its subsystems for launch. The environment presents numerous challenges where multiple tests are to be carried out meticulously and study the impact on different subsystems to ensure the proper and efficient behavior of those. Automatic Checkout System aims at providing an integrated system where tests can be carried out and results can be analyzed with minimal manual intervention. The system comprises of multiple tasks which schedule the test procedures, execute the same and monitor the results. Inter process communication is essential amongst these tasks to successfully perform the designed functions. In this paper a Message Server is presented which acts as the communication backbone of the Automatic Checkout System. The proposed method uses a combination of socket based communication technique and shared memory to effectively pass the message amongst the Client applications. Implementation aspects along with the results are also briefed in this paper.

The main aim of this paper is to improve the wireless system recital. Though there are many safeties measure hinder its wide use in common. Also the well-known pollution attacks, here is one more stern hazard, that of wormhole attacks, which weaken the recital increase of network coding. Because the fundamental uniqueness of network coding systems is diversely different from usual wireless networks, the blow of wormhole attacks and counter measure is unidentified. In this paper, we enumerate wormholes overwhelming destructive blow on network coding system recital throughout this trial. We propose a midest algorithm to sense wormholes and illustrate its rightness thoroughly. For the disseminated wireless network, we use DAWN, Distributed detection Algorithm against Wormhole in wireless Network coding systems, by discovering the transform of the surge direction of the novel packets caused by wormholes. We thoroughly prove that DAWN pledges a better inferior bound of unbeaten discovery speed. We achieve on the resistance of DAWN beside conspiracy attacks. We discover that the heftiness depends on the density of the network node, and establish an essential situation to attain collusion resistance. DAWN doesn't rely on any spot sequence, global organization. It relies only on local sequence which can attain usual network coding protocols and the overhead of the algorithm is moderate.

Web services are utilized to illuminate some particular assignment. When a single web service cannot solve a given task, several web services are composed. Composition can be done either statically at design time or dynamically at runtime. Dynamic composition is more suitable for business applications where in business policies and user requirements frequently changes. Interleaved dynamic composition and execution of services is beneficial for adapting to changing user preferences. One of the main issues in such a scenario is that whether the component services that are composed operate according to the business rules specified. Safety, liveness and deadlock freedom properties of a composition depend on the behavior of individual services. Existing modeling techniques capture these properties and perform model checking only statically. Hence in this work, a two level model verification approach has been proposed to verify the correctness of dynamically composed services.

Remote Body Area Networks are relied on to expect a basic part in the field of patient-thriving checking inside the not so distant future, which increases beast thought among specialists beginning late. One of the inconveniences is to build up a protected correspondence design among sensors and clients, while watching out for the typical security and protection concerns. In this paper, we propose a correspondence planning for BANs, and outline a course of action to secure the information exchanges between introduced/wearable sensors. Our course of action accomplishes an area based access control by utilizing an entry control tree portrayed by the attributes of the information. We likewise outline two customs to safely recover the touchy information from a BAN and instruct the sensors in a BAN.

Automatic image classification is most important process in medical imaging for analyzing difference between normal patients and those who have the possibility of having abnormalities or tumor. MRI image consists of different gray levels and intensities. Brain tumor is varied in size and shape. Radiologist can diagnose and find location of lesions based on visual diagnosis with help of available software. While performing visual diagnosis, error may be introduced in finding location of tumor. To solve this problem there is need to develop a computer based automatic technique for detecting and classifying tumor from brain MRI images. The proposed system classifies the abnormalities in brain tumor by extracting the feature from brain tumor image and normal image using the GLCM and DWT. From the features classified by the classifier into two classes normal and abnormal along with different type of tumor by using the multiclass SVM which will give a promising result.

A new decoder architecture for nonbinary low-density parity check (LDPC) codes is presented in this paper to reduce the hardware operational complexity and power consumption. Adaptive message control (AMC) is to achieve the low decoding complexity, that dynamically trims the message length of belief information to reduce the amount of memory accesses and arithmetic operations. A new horizontal nonbinary LDPC decoder architecture is developed to implement AMC. Key components in the architecture have been designed with the consideration of variable message lengths to leverage the benefit of the proposed AMC. Simulation results demonstrate that the proposed nonbinary LDPC decoder architecture can significantly reduce hardware operations and power consumption as compared with existing work with negligible performance degradation.

Opinions are the fundamental aspect to almost all decision making activities. The increased usage of internet and the exchange of user opinions through social media and public forums on the web has become the motivation for sentiment analysis. Due to the infinite amount of user opinions available throughout the web it is necessary to automatically analyze and classify sentiment expressed in opinions. The basic task of sentiment analysis or opinion mining is sentiment classification which classifies the content as positive, negative and irrelevant. This paper discusses an approach where an exposed stream of tweets from the Twitter micro blogging site are preprocessed and classified based on their sentiments. In sentiment classification system the concept of opinion subjectivity has been accounted. In this paper, we present opinion detection and organization subsystem, which have already been integrated into our larger question-answering system. The subjectivity classification system uses Genetic-Based Machine Learning (GBML) technique that considers subjectivity as a semantic problem. The classification of a review is predicted through the average semantic orientation of the phrases in the review that contain adjectives or adverbs. Experimental results of the proposed techniques are efficient and generate eminent evaluations.

The fast growth of information and communication technology and particularly the Internet has changed traditional methods of research, storage, retrieval, and communication of information. Internet has emerged as the most powerful medium for storage and retrieval of information. The Internet facility has enabled teachers and students to enhance their academic excellence by providing them the latest information and access to worldwide information. The present study highlights the existing situation of Internet services provided by the various departments of Alagappa University. The study shows that female respondents constitute more in number than male respondents, corroborating the greater number of women in higher education in Tamil Nadu state. It also reveals that most respondents (56.76%) use the Internet for educational purposes, while 36.49% use online services for research purposes.

GSM based Door Access Security System has principle application in security frameworks and it can be utilized as a part of Industries, Shops, Offices and in our homes. It replaces the customary security frameworks which utilizes key to open entryway. This venture has keyless passage to the entryway. Client needs to send secret key through SMS utilizing his/her portable. In the event that the secret key is right then Microcontroller turns on a DC engine and a Relay. Bell is turned on for wrong secret key. In its most straightforward shape Home security is the capacity to control entryway open or close Family security remotely. The transmitter depends on remote GSM strategy the idea Door bolting and opening System utilizes GPRS to open and close the entryway. Not with standing this security will be given utilizing GSM in the event of any unapproved get to. DC engine will then perform activity on entryway either bolting or opening.

Statistics and Mathematical models can be in many forms, including differential equations, or theoretic models. Lack of correlation between theoretical mathematical models and experimental measurements sometime leads to development of better theories in the area of biology. The mathematical design finds wide application in nutrient media optimization for microbial enzyme production. On the other hand these mathematical tools in the field of statistics play an important role with data analysis of proteomics and genomics studies. For the MS/MS spectroscopic data, micro array, RT-PCR data analysis, linkage study, gene-gene interaction studies are very difficult to interpret, but the statistical tools made it very easier from the conventional method of data analysis in both Biotechnology and Bioinformatics.