QoS multi meshed tree routing in tethered MANET

The QoS Multi Meshed Tree Routing is a routing protocol designed to provide Quality of Service (QoS) in Tethered Mobile Ad hoc Networks (tMANET) in terms of bandwidth. This project is a part of the research project titled Framework for Seamless Roaming, Handoff, and QOS Mapping in Next Generation Networks conducted at the Laboratory for Wireless Networking and Security, headed by faculty member Dr. Nirmala Shenoy. OPNET (Optimum Performance Network), a well-known network simulation tool, is used to implement the design and conduct performance studies of QoS MMT. QoS MANET protocol implements features such as route discovery, link failure identification, bandwidth calculation, resource reservation, and resource release. Various simulations were run to collect statistics of the following performance parameters: Node-Joining Time, End-End delays, Throughput, Route failure notification, and Route availability which were analyzed

A Study Resource Optimization Techniques Based Job Scheduling in Cloud Computing

Cloud computing has revolutionized the way businesses and individuals utilize computing resources. It offers on-demand access to a vast pool of virtualized resources, such as processing power, storage, and networking, through the Internet. One of the key challenges in cloud computing is efficiently scheduling jobs to maximize resource utilization and minimize costs. Job scheduling in cloud computing involves allocating tasks or jobs to available resources in an optimal manner. The objective is to minimize job completion time, maximize resource utilization, and meet various performance metrics such as response time, throughput, and energy consumption. Resource optimization techniques play a crucial role in achieving these objectives. Resource optimization techniques aim to efficiently allocate resources to jobs, taking into account factors like resource availability, job priorities, and constraints. These techniques utilize various algorithms and optimization approaches to make intelligent decisions about resource allocation. Research on resource optimization techniques for job scheduling in cloud computing is of significant importance due to the following reasons: Efficient Resource Utilization: Cloud computing environments consist of a large number of resources that need to be utilized effectively to maximize cost savings and overall system performance. By optimizing job scheduling, researchers can develop algorithms and techniques that ensure efficient utilization of resources, leading to improved productivity and reduced costs. Performance Improvement: Job scheduling plays a crucial role in meeting performance metrics such as response time, throughput, and reliability. By designing intelligent scheduling algorithms, researchers can improve the overall system performance, leading to better user experience and customer satisfaction. Scalability: Cloud computing environments are highly scalable, allowing users to dynamically scale resources based on their needs. Effective job scheduling techniques enable efficient resource allocation and scaling, ensuring that the system can handle varying workloads without compromising performance. Energy Efficiency: Cloud data centres consume significant amounts of energy, and optimizing resource allocation can contribute to energy conservation. By scheduling jobs intelligently, researchers can reduce energy consumption, leading to environmental benefits and cost savings for cloud service providers. Quality of Service (QoS): Cloud computing service providers often have service-level agreements (SLAs) that define the QoS requirements expected by users. Resource optimization techniques for job scheduling can help meet these SLAs by ensuring that jobs are allocated resources in a timely manner, meeting performance guarantees, and maintaining high service availability. Here in this research, we have used the method of the weighted product model (WPM). For the topic of Resource Optimization Techniques Based Job Scheduling in Cloud Computing For calculating the values of alternative and evaluation parameters. A variation of the WSM called the weighted product method (WPM) has been proposed to address some of the weaknesses of The WSM that came before it. The main distinction is that the multiplication is being used in place of additional. The terms "scoring methods" are frequently used to describe WSM and WPM Execution time on Virtual machine, Transmission time (delay)on Virtual machine, Processing cost of a task on virtual machine resource optimization techniques based on job scheduling play a crucial role in maximizing the efficiency and performance of cloud computing systems. By effectively managing and allocating resources, these techniques help minimize costs, reduce energy consumption, and improve overall system throughput. One of the key findings is that intelligent job scheduling algorithms, such as genetic algorithms, ant colony optimization

The growth of Tamil Nadu fisheries: An empirical analysis

Tamil Nadu is one of the states in India blessed with marine and inland fishery resources. It is also one of the states to have first started a department for fisheries in 1907 with the mandate to develop fisheries. In the late eighties it added to its mandate the promotion of fisher-folk welfare as an important objective

Tamil Nadu fisheries: An analysis of its growth

Tamil Nadu is one of the states in India blessed with marine and inland fishery resources. It is also one of the states to have first started a department for fisheries in 1907 with the mandate to develop fisheries. In the late eighties it added to its mandate the promotion of fisher-folk welfare as an important objective

The impact of modern headlamps on the design of sag vertical curves

Incorporating safety in the design of a highway is one of the foremost duties of a design engineer. Design guidelines provide standards that help engineers include safety in the design of various geometric features. However, design guidelines are not frequently revised and do not accommodate for the frequent changes in vehicle design. One such example is the change in vehicle headlamps. These changes significantly impact the illuminance provided on the road and in turn the design formula. Roadway visibility is critical for nighttime driving. In the absence of roadway lighting, vehicle headlamps illuminate the road ahead of a vehicle. Sag vertical curve design depends on the available headlight sight distance provided by the 1 degree upward diverging headlamp beam. The sag curve design formulas were developed in the early 1940s when sealed beam headlamps were predominant. However, headlamps have changed significantly and modern headlamps project less light above the horizontal axis. In this research, the difference in illuminance provided by sealed beam headlamps and modern headlamps was examined. For the theoretical analysis, three different sag curves were analyzed. On these curves, about 26 percent reduction in illuminance was observed at a distance equal to the stopping sight distance when comparing sealed beam to modern headlamps. A change in the headlamp divergence angle from 1.0 degree to 0.85 degree will provide the required illuminance on the road when using modern headlamps. A field study was performed to validate the theoretical calculations. It was observed that for modern headlamps, a divergence angle less than 1 degree and greater than 0.5 degrees will provide illuminance values comparable to sealed beam headlamps. As a part of this research, a preliminary study, examining the impact of degraded headlamp lenses on the illuminance provided on sag vertical curves was conducted. A significant reduction in illuminance reaching the roadway on sag curves was observed, due to headlamp lens degradation

Impacto de las Herramientas Lean en el consumo de energía

Lean principles are mainly used for increasing productivity, reducing lead time, and eliminating waste. Energy impacts can also be assessed by using the lean principles. The objective of this paper is to measure the impact of Lean Manufacturing tools on energy consumption, with the base assumption that they should help decrease it. The methodology assesses and documents the energy utilization as a part of VSM. A pilot application in an industrial setting is presented.  Los principios de Lean Manufacturing se usan principalmente para mejorar la productividad, reducir el tiempo de entrega y eliminar desperdicios. Los impactos en consumo de energía también se pueden estimar usando principios de Lean. El objetivo de este artículo es el de medir el impacto del uso de herramientas de Lean Manufacturing en el consumo de energía, partiendo del supuesto de que su aplicación debería reducirlo. La metodología evalúa y documenta la utilización de la energía como parte de la elaboración de Mapas de la Cadena de Valor. Finalmente se presenta una aplicación piloto en una empresa industrial

Low Power and Efficient Re-Configurable Multiplier for Accelerator

Deep learning is a rising topic at the edge of technology, with applications in many areas of our lives, including object detection, speech recognition, natural language processing, and more. Deep learning's advantages of high accuracy, speed, and flexibility are now being used in practically all major sciences and technologies. As a result, any efforts to improve the performance of related techniques are worthwhile. We always have a tendency to generate data faster than we can analyse, comprehend, transfer, and reconstruct it. Demanding data-intensive applications such as Big Data. Deep Learning, Machine Learning (ML), the Internet of Things (IoT), and high- speed computing are driving the demand for "accelerators" to offload work from general-purpose CPUs. An accelerator (a hardware device) works in tandem with the CPU server to improve data processing speed and performance. There are a variety of off-the-shelf accelerator architectures available, including GPU, ASIC, and FPGA architectures. So, this work focus on designing a multiplier unit for the accelerators. This increases the performance of DNN, reduced the area and increasing the training speed of the system

Modernized Wildlife Surveillance and Behaviour Detection using a Novel Machine Learning Algorithm

In a natural ecosystem, understanding the difficulties of the wildlife surveillance is helpful to protect and manage animals also gain knowledge around animals count, behaviour and location. Moreover, camera trap images allow the picture of wildlife as unobtrusively, inexpensively and high volume it can identify animals, and behaviour but  it has the issues of high expensive, time consuming, error, and low accuracy. So, in this research work, designed a novel wildlife surveillance framework using DCNN for accurate prediction of animals and enhance the performance of detection accuracy. The executed research work is implemented in the python tool and 2700 sample input frame datasets are tested and trained to the system. Furthermore, analyze whether animals are present or not using background subtraction and features extracted is performed to extract the significant features. Finally, classification is executed to predict the animal using the fitness of seagull. Additionally, attained results of the developed framework are compared with other state-of-the-art techniques in terms of detection accuracy, sensitivity, F-measure and error

Manufacturing and Evaluation of Mechanical Properties for Rice Husk ParticleBoard Using IoT

In recent times, different types of particleboards are being preferred in the construction of houses, partitions, furnitureetc. The production of such materials can be manufactured using rice husk, which has been obtained as waste produced inrice millers. Adhesive such as formaldehyde, when exposed to fire, causes toxic flames which are fatal in nature. The basiccondition for production of particleboards is to check the temperature and humidity content in the rice husk which has beendone by using DHT 11 sensors i.e., application of Internet of Thing (IoT) erected method. This identification helps infinding the suitable temperature through which bio-based adhesives have been prepared. In present study, two differenttypes of bio-adhesives namely tamarind with formalin and tamarind with boric acid has been used in manufacturing process.The application of IoT erected method follows a complex preparation method but will partially fulfil the job and reduceshuman involvement. Finally, when the proper temperature and moisture level has been measured, the preparation becomeseasy. After manufacturing the particleboard, the strength has been tested by a three-point bend test and have been comparedwith commercially available boards with formaldehyde base adhesive

Role of Multidetector Computed Tomography in the Assessment of Olfactory Fossa Depth among the South Indian Population: A Cross-sectional Study

Introduction: Functional Endoscopic Sinus Surgery (FESS) is one of the most commonly performed surgeries for sinusitis. The olfactory fossa is prone to injury during FESS and the risk of injury depends on the depth of the olfactory fossa. Aim: To assess the depth of the olfactory fossa by multidetector Computed Tomography (CT) and to study the incidence and distribution of asymmetry of olfactory fossa depth. Materials and Methods: A cross-sectional, observational study was conducted at Department of Radiology, Dr Pinnamaneni Siddhartha Institute of Medical Sciences and Research Foundation, Gannavaram, Andhra Pradesh, India from November 2019 to October 2019. The sample size was 500 patients. All patients above the age of 18 years who were referred to the department of radiology for CT paranasal sinuses were included. Olfactory fossa depth was calculated from the CT scan and statistical analysis was done comparing it with the variables such as age, gender and side of fossa. Results: Out of total 500 participants, 311 (74.2%) patients in the study were males. The mean age of patients was 40.3±16.05 years. There was no significant difference in the olfactory fossa depth on the right side (p-value=0.6) and left side (p-value=0.9) in both genders. A total of 400 (80%) patients of the cases had asymmetry of the olfactory fossa. In males, the most common (n=294, 799.2%) was type 2 Keros on the right and 280 (75.5%) patients on the left side. In females on the right side, type 1 Keros was more common (52 patients, 40.3%) and on the left side type 2 Keros was more common (60 patients, 46.5%) and there was a significant difference in the proportion of different types of Keros in both genders (p-value<0.001). There was no significant difference in the proportion of Keros types among the different age groups (p-value=0.56 on the right side and p-value=0.66 on left side). Conclusion: There was a significant difference in the proportion of Keros types among males and females and the majority of the patients had asymmetry. Prospective studies with intraoperative information from the surgeon can add further information on the utility of the Keros grade