Investigation of dual varying area flapping actuator of a robotic fish with energy recovery

Autonomous under-water vehicles (AUV) performing a commanded task require to utilize on-board energy sources. At the time when on-board power source runs low during operation, the vehicle (AUV) is forced to abort the mission and to return to a charging station. The present work proposes the technique of an energy recovery from surrounding medium. This effect is studied for dual action actuator movement that obtains energy from fluid. It is realized that a flapping or vibrating actuator can be used for energy extraction phenomenon apart from the non-traditional propulsive technique. In the present work a simple dual flapping actuator that can switch between simple flat plate and perforated plate at extreme end positions (angles) by using an efficient mechatronic mechanism that would help in overcoming viscous forces of the operating medium is extensively studied. The main objective of the present article is to develop a new approach for energy gain and recharge power pack of on-board sources from the surrounding medium and to create a robotic fish that would work autonomously by using unconventional drive along with the possibility of energy restoration by using dual varying area type vibrating actuator. At the time of recharge, the robotic fish would project its tail (actuator) out of water and use surrounding medium (air) to scavenge the energy. All the equations describing the process are formed according to classical laws of mechanics. The mechatronic system is explained and the results obtained are discussed in detail for air as the operating fluid to scavenge energy

Network Intrusion Detection Method Using Stacked BILSTM Elastic Regression Classifier with Aquila Optimizer Algorithm for Internet of Things (IoT)

Globally, over the past ten years, computer networks and Internet of Things (IoT) networks have grown significantly due to the increasing amount of data that has been collected, ranging from zettabytes to petabytes. As a result, as the network has expanded, security problems have also emerged. The large data sets involved in these types of attacks can make detection difficult. The developing networks are being used for a multitude of sophisticated purposes, such as smart homes, cities, grids, gadgets, and objects, as well as e-commerce, e-banking, and e-government. As a result of the development of numerous intrusion detection systems (IDS), computer networks are now protected from security and privacy threats. Data confidentiality, integrity, and availability will suffer if IDS prevention efforts fail. Complex attacks can't be handled by traditional methods.  There has been a growing interest in advanced deep learning techniques for detecting intrusions and identifying abnormal behavior in networks. This research aims to propose a novel network namely stacked BiLSTM elastic regression classifier (Stack_BiLSTM-ERC) with Aquila optimizer algorithm for feature selection. This optimization method computes use of a cutting-edge transition function that enables it to be transformed into a binary form of the Aquila optimizer. A better solution could be secured once number of possible solutions are found from diverse regions of the search space utilizing the Aquila optimizer method. NSL-KDD and UNSW-NB15 are two datasets that enable learning characteristics from the raw data in order to detect harmful prerequisites characteristics and effective framework patterns. The proposed Stack_BiLSTM-ERC achieves 98.l3% of accuracy, 95.1% of precision, 94.3% of recall and 95.4 of F1-score for NSL-KDD dataset. Moreover, 98.6% of accuracy, 97.2% of precision, 98.5 of recall and 97.5% of F1-score

Analysis of non-stationary flow interaction with simple form objects

ArticleThe paper is devoted to the analysis of a non-stationary rigid body interaction in a fluid flow. Initially, an approximate method for determining the forces due to fluid interaction with the rigid body is offered. For this purpose, the plane movement of a mechanical system with an infinite DOF (degrees of freedom) is reduced to 5 DOF motion: 3 DOF for the body and 2 DOF for the areas of compression and vacuum in fluid flow. Differential equations of non-stationary motion are formed by the laws of classical mechanics. The use of an approximate method has been quantified by computer modelling. The average difference in results was found to be small (< 5%). The analysis of the fluid (air) interaction is carried out for a rigid body of two simple geometries - flat plate and diamond. The results obtained are used to refine the parameters of the proposed approximate method that is addressed in the present study for fluid interaction with the non-stationary rigid body. Theoretical results obtained in the final section are used in the analysis of the movement of prismatic bodies in order to obtain energy from the fluid flow

Analysis of non-stationary flow interaction with simple form objects

ArticleThe paper is devoted to the analysis of a non-stationary rigid body interaction in a fluid flow. Initially, an approximate method for determining the forces due to fluid interaction with the rigid body is offered. For this purpose, the plane movement of a mechanical system with an infinite DOF (degrees of freedom) is reduced to 5 DOF motion: 3 DOF for the body and 2 DOF for the areas of compression and vacuum in fluid flow. Differential equations of non-stationary motion are formed by the laws of classical mechanics. The use of an approximate method has been quantified by computer modelling. The average difference in results was found to be small (< 5%). The analysis of the fluid (air) interaction is carried out for a rigid body of two simple geometries - flat plate and diamond. The results obtained are used to refine the parameters of the proposed approximate method that is addressed in the present study for fluid interaction with the non-stationary rigid body. Theoretical results obtained in the final section are used in the analysis of the movement of prismatic bodies in order to obtain energy from the fluid flow

DDoS defense by offense

This article presents the design, implementation, analysis, and experimental evaluation of speak-up, a defense against application-level distributed denial-of-service (DDoS), in which attackers cripple a server by sending legitimate-looking requests that consume computational resources (e.g., CPU cycles, disk). With speak-up, a victimized server encourages all clients, resources permitting, to automatically send higher volumes of traffic. We suppose that attackers are already using most of their upload bandwidth so cannot react to the encouragement. Good clients, however, have spare upload bandwidth so can react to the encouragement with drastically higher volumes of traffic. The intended outcome of this traffic inflation is that the good clients crowd out the bad ones, thereby capturing a much larger fraction of the server's resources than before. We experiment under various conditions and find that speak-up causes the server to spend resources on a group of clients in rough proportion to their aggregate upload bandwidths, which is the intended result.National Science Foundation (U.S.) (NSF grant CNS-0225660)National Science Foundation (U.S.) (NSF grant CNS-0520241)United States. Dept. of Defense (National Security Science and Engineering Faculty Fellowship

TCP Download Performance in Dense WiFi Scenarios: Analysis and Solution

How does a dense WiFi network perform, specifically for the common case of TCP download? While the empirical answer to this question is 'poor', analysis and experimentation in prior work has indicated that TCP clocks itself quite well, avoiding contention-driven WiFi overload in dense settings. This paper focuses on measurements from a real-life use of WiFi in a dense scenario: a classroom where several students use the network to download quizzes and instruction material. We find that the TCP download performance is poor, contrary to that suggested by prior work. Through careful analysis, we explain the complex interaction of various phenomena which leads to this poor performance. Specifically, we observe that a small amount of upload traffic generated when downloading data upsets the TCP clocking, and increases contention on the channel. Further, contention losses lead to a vicious cycle of poor interaction with autorate adaptation and TCP's timeout mechanism. To reduce channel contention and improve performance, we propose a modification to the AP scheduling policy to improve the performance of large TCP downloads. Our solution, WiFiRR, picks only a subset of clients to be served by the AP during any instant, and varies this set of "active" clients periodically in a round- robin fashion over all clients to ensure that no client starves. We have done extensive evaluation of WiFiRR in simulation and in real settings. By reducing the number of contending nodes at any point of time, WiFiRR improves the download time of large TCP flows upto 3.5x of our classroom scenario. We also compare WiFiRR with state-of-the-art prior work WiFox, WiFiRR improves download time by 2.25x over WiFox

Biofortification—Present Scenario, Possibilities and Challenges: A Scientometric Approach

Biofortification refers to the process by which food crops are improved by the application of biotechnology, conventional plant breeding, and agronomic practices to increase the bioavailability of their nutritious components to human consumers. The biofortification of staple crops is a long-term, sustainable solution to address nutritional inadequacies. Thus, it is a practical and cost-effective way to provide micronutrients to communities that have limited access to various meals and other micronutrient therapies. Existing therapies, such as supplementation and industrial food fortification, which are insufficient to eliminate micronutrient deficiencies on their own, are complemented by biofortification. However, biofortification offers two substantial competitive advantages: the capacity to reach underserved rural communities and long-term cost-effectiveness. Biofortified crops can also be used to target rural populations with limited access to various dietary options or other micronutrient therapies. Hence, an attempt is made herein to provide an overview of the biofortification literature by employing scientometric and network analysis tools to examine records extracted from the Scopus database that were published between 2010 and 2021. This study investigates the most influential authors and journals, top-contributing institutions and countries, variations across publication years, co-occurrence analysis of keywords, and bibliographic coupling of sources. The results obtained through this study describe the real impact of the research published to date and its usage

Central power generation versus distributed generation - An air quality assessment in the South Coast Air Basin of California

This study assesses the air quality impacts of central power generation and compares them with the impacts of distributed generation (DG). The central power plant emissions factors used are from a newly installed combined cycle gas turbine system. Because location of power plants is a key parameter affecting air quality impacts, this study considers three potential locations for the installation of central power plants. Air quality impacts are evaluated for the South Coast Air Basin of California, in the year 2010, using a three-dimensional air quality model. Results are compared to air quality impacts from two potential DG scenarios to meet the same power demand as that of the central power plant case.Even though emissions from central generation are lower than emissions from the DG technology mix considered herein, central generation concentrates emissions in a small area, whereas DG spreads emissions throughout a larger cross-section of the air basin. As a result, air quality impacts from central generation are more significant than those from DG. The study also shows that assessment of air quality impacts from distributed and central generation should not only consider emissions levels, but also the spatial and temporal distribution of emissions and the air quality that results from atmospheric chemistry and transport - highly non-linear processes.Finally, analysis of population exposure to ozone and PM shows that central generation located in coastal areas upwind from populated areas would cause the highest population exposure and even though emissions from central generation are considerably lower than DG emissions spread throughout the basin, results show that central generation causes a higher pollutant exposure than DG. © 2010 Elsevier Ltd. 2.

Witals: AP-Centric Health Diagnosis of WiFi Networks

In recent years, WiFi has grown in capacity as well as deployment demand. WiFi system administrators (sysads) want a simple answer to the question "Is my WiFi network healthy?", and a possible follow-up "What is wrong with it?", if it is reported as "unhealthy". But we are far from having such an interface today. It is this gap that this work attempts to fill. We present Witals, a system for WiFi performance diagnosis. We first design a causal diagnosis graph, that extensively identifies the underlying cause(s) of WiFi performance problems. Next, we identify a set of metrics corresponding to nodes in this causal graph. These metrics are measured in real-time by an operational AP, and help in quantifying the effect of each cause. We design a diagnosis algorithm based on the causal graph and the metrics, which ultimately presents a sanitized view of WiFi network health to the sysad. We have implemented a prototype of Witals on an enterprise grade 802.11n AP platform. Using a variety of controlled as well as real-life measurements, we show that our diagnosis framework follows ground truth accurately. Witals has also helped the sysads uncover some unexpected diagnoses