DESIGN AND DEVELOPMENT OF REGENERATIVE DAMPERS

Each and every automobile in service or being developed in the industry is benchmarked on the basis of its efficiency in running real conditions. So in our project here we have tried to develop a complete new damper and spring setup which can be used in all sorts of suspension systems and in turn provides a feedback loop of voltage which can then be used charge the batteries and upscale the efficiency of bikes by (5-6)% & and for HUV or Sedans by (2-4)% (can even go higher) depending on the terrain. In this setup we harness the mechanical energy into electrical where earlier it was left as heat and vibrational losses. This setup is as cost effective as the earlier dampers where as providing an efficient output in minimal cost increase due to its novelty. The other Features include Electronic height adjustment & on demand suspension softness or stiffness. Keywords: Dampers, Automobile, Electromagnet, EV (Electric vehicle), Voltage, Magnetic flux, Suspension

DAB Signal Preprocessing for Passive Coherent Location

Digital Audio Broadcast (DAB) transmitters can be successfully used as illumination sources in Passive Coherent Location (PCL). However, extending the integration time in such a configuration leads to the occurrence of periodical artifacts in the bistatic range/Doppler plots, resulting from the time structure of the DAB signal. In this paper, we propose some methods of signal preprocessing (based on symbol removal, substitution by noise, and duplication) that operate on the DAB transmission frame level and improve the received signal’s correlation properties. We also demonstrate that two of these methods allow us to avoid the mentioned artifacts and thus to improve the quality of the range/Doppler plots with detection results. We evaluate the performance of the proposed methods using real DAB signals acquired in an experimental PCL platform. We also provide the analysis of the Signal to Noise Ratio (SNR) during the detection of a moving target which shows that the proposed solution, based on symbol duplication, can offer around 3 dB of gain in SNR. Finally, we carry out the computational complexity analysis showing that the proposed method can be implemented with a minimal cost after some optimizations.

Review of Custom Grids for Updated Vehicles on VANET Simulators

VANET deployment and testing is time-consuming and costly. Simulation is a handy and less expensive alternative to real implementation as a workaround. It is required to develop accurate models in order to receive excellent results from a VANET simulation, which difficult operation owes to the complexity of the VANET infrastructure (for example, simulators have to model the navigation models and communication protocols). The network and navigation components, which are the building blocks of contemporary VANET simulators, are described in this section. Simulators are a useful tool for testing VANETs at a minimal cost and without endangering users. However, in order to be helpful and convey trustworthy findings, simulators must be able to simulate new technologies that enter the VANET and enable safety and security procedures. To put it another way, if simulation is a good tool for VANET development it should be enhanced. VANET simulators have been the subject of research since early 2010 [1-4]. They analyze the correctness of VANET's numerous tools like a navigation simulator and network simulator, as well as how these building blocks are connected. The introduction of new network technologies such as 5G, SDN, edge computing, and VANET research as a result of investments in autonomous cars is forcing VANET simulators to re-evaluate their support for these new capabilities. We present an updated evaluation of VANET simulators in this post, highlighting their key features and current support for emerging technologies.

Data Mining algorithms in search of effective conditions for conducting chemical reactions

В настоящее время накоплено значительное количество экспериментальных данных, фиксирующих процесс протекания химических реакций. Анализ этих данных комплексом алгоритмов Data Mining дает важную практическую информацию для поиска эффективных условий проведения реакций, при которых получается максимальное количество целевого продукта при минимальных затратах. В данной работе на примере работы с базой, содержащей данные о протекании реакции карбонилирования различных олефинов, показано, как разработанный нами программный комплекс позволяет извлечь полезные знания, способствующие повышению эффективности химических реакций. At present, a significant amount of experimental data has been accumulated, recording the process of the occurrence of chemical reactions. Analysis of these data by a set of Data Mining algorithms provides important practical information for finding effective conditions for carrying out reactions, at which the maximum amount of the target product is obtained at minimal cost. In this paper, using the example of working with a database containing data on the course of the carbonylation reaction of various olefins, it is shown how the software package developed by us allows us to extract useful knowledge that contributes to an increase in the efficiency of chemical reactions.

Optimized LQR-PID Controller Using Squirrel Search Algorithm for Trajectory Tracking of a 6-DoF Parallel Manipulator

In 6 Degree of Freedom (DOF) parallel manipulator, trajectory tracking is one of the main challenges. To obtain the desired trajectory, the DC motor needs to generate optimal torque. So to obtain optimal torque, an optimized Linear Quadratic Regulator-Proportional–Integral–Derivative (LQR-PID) controller is presented in this paper. For optimizing the Q, R and gain parameters of LQR-PID controller, Squirrel Search Algorithm (SSA) is presented. In this algorithm, minimal cost function of LQR-PID controller is considered as objective function. The SSA based LQR-PID controller leads the motor to generate optimal torque that helps to attain the desired trajectory of 6-DOF parallel manipulator. Results of the work depicts that the SSA based LQR-PID controller achieves the best mean velocity, sum square error (SSE), integral square error (ISE) and integral absolute error (IAE).

Approximation of value function of differential game with minimal cost

The paper is concerned with the approximation of the value function of the zero-sum differential game with the minimal cost, i.e., the differential game with the payoff functional determined by the minimization of some quantity along the trajectory by the solutions of continuous-time stochastic games with the stopping governed by one player. Notice that the value function of the auxiliary continuous-time stochastic game is described by the Isaacs–Bellman equation with additional inequality constraints. The Isaacs–Bellman equation is a parabolic PDE for the case of stochastic differential game and it takes a form of system of ODEs for the case of continuous-time Markov game. The approximation developed in the paper is based on the concept of the stochastic guide first proposed by Krasovskii and Kotelnikova.

An Astrocyte-Flow Mapping on a Mesh-Based Communication Infrastructure to Defective Neurons Phagocytosis

In deploying the Internet of Things (IoT) and Internet of Medical Things (IoMT)-based applications and infrastructures, the researchers faced many sensors and their output’s values, which have transferred between service requesters and servers. Some case studies addressed the different methods and technologies, including machine learning algorithms, deep learning accelerators, Processing-In-Memory (PIM), and neuromorphic computing (NC) approaches to support the data processing complexity and communication between IoMT nodes. With inspiring human brain structure, some researchers tackled the challenges of rising IoT- and IoMT-based applications and neural structures’ simulation. A defective device has destructive effects on the performance and cost of the applications, and their detection is challenging for a communication infrastructure with many devices. We inspired astrocyte cells to map the flow (AFM) of the Internet of Medical Things onto mesh network processing elements (PEs), and detect the defective devices based on a phagocytosis model. This study focuses on an astrocyte’s cholesterol distribution into neurons and presents an algorithm that utilizes its pattern to distribute IoMT’s dataflow and detect the defective devices. We researched Alzheimer’s symptoms to understand astrocyte and phagocytosis functions against the disease and employ the vaccination COVID-19 dataset to define a set of task graphs. The study improves total runtime and energy by approximately 60.85% and 52.38% after implementing AFM, compared with before astrocyte-flow mapping, which helps IoMT’s infrastructure developers to provide healthcare services to the requesters with minimal cost and high accuracy.

Influence Maximization with Latency Requirements on Social Networks

Targeted marketing strategies are of significant interest in the smartapp economy. Typically, one seeks to identify individuals to strategically target in a social network so that the network is influenced at a minimal cost. In many practical settings, the effects of direct influence predominate, leading to the positive influence dominating set with partial payments (PIDS-PP) problem that we discuss in this paper. The PIDS-PP problem is NP-complete because it generalizes the dominating set problem. We discuss several mixed integer programming formulations for the PIDS-PP problem. First, we describe two compact formulations on the payment space. We then develop a stronger compact extended formulation. We show that when the underlying graph is a tree, this compact extended formulation provides integral solutions for the node selection variables. In conjunction, we describe a polynomial-time dynamic programming algorithm for the PIDS-PP problem on trees. We project the compact extended formulation onto the payment space, providing an equivalently strong formulation that has exponentially many constraints. We present a polynomial time algorithm to solve the associated separation problem. Our computational experience on a test bed of 100 real-world graph instances (with up to approximately 465,000 nodes and 835,000 edges) demonstrates the efficacy of our strongest payment space formulation. It finds solutions that are on average 0.4% from optimality and solves 80 of the 100 instances to optimality. Summary of Contribution: The study of influence propagation is important in a number of applications including marketing, epidemiology, and healthcare. Typically, in these problems, one seeks to identify individuals to strategically target in a social network so that the entire network is influenced at a minimal cost. With the ease of tracking consumers in the smartapp economy, the scope and nature of these problems have become larger. Consequently, there is considerable interest across multiple research communities in computationally solving large-scale influence maximization problems, which thus represent significant opportunities for the development of operations research–based methods and analysis in this interface. This paper introduces the positive influence dominating set with partial payments (PIDS-PP) problem, an influence maximization problem where the effects of direct influence predominate, and it is possible to make partial payments to nodes that are not targeted. The paper focuses on model development to solve large-scale PIDS-PP problems. To this end, starting from an initial base optimization model, it uses several operations research model strengthening techniques to develop two equivalent models that have strong computational performance (and can be theoretically shown to be the best model for trees). Computational experiments on a test bed of 100 real-world graph instances (with up to approximately 465,000 nodes and 835,000 edges) attest to the efficacy of the best model, which finds solutions that are on average 0.4% from optimality and solves 80 of the 100 instances to optimality.

Frequency-amplitude of Vibration of Modern Aesthetic Footbridges for Walking and Cycling

<p>New urban developments are changing the traditional footbridges by contemplating (i) the new cyclic functionality of these structures, (ii) the wood and other light structural materials and, in many cases, (iii) the introduction of aesthetics. Previous studies were made on pedestrian footbridges composed by a simple supported beam with uniform distributed characteristics. The main objective of these past projects was to pass pedestrians across, safe and comfortably, with minimal cost of construction, without much aesthetics.</p><p>Nowadays, footbridges appeal to the best architects and engineering consortiums and each new one is viewed as entering in an aesthetic contest. The objective now is similar as referred before but, besides adding the cycling vehicles, they should look into aesthetics and to the environmental context. They span larger distances making use of more adequate materials. However, the dynamic characteristics might be a problem due to proximity of frequencies of the structure with the rhythm of the stepping of crossing. This is the objective of this paper to understand if more complex geometries and different materials pose problems. After looking into several cases in Portugal and Spain and, describing their main geometric and mechanical characteristics, the most important frequencies of vibration and amplitude of oscillation for various loadings were analyzed. Caution should be exercised to not excite resonance conditions. A case study of one of these structures is analysed in detail for deterministic conditions. Cycling is not a problem.</p>

An An Integrated Automatic-Grading and Quality Measure for Assessing Programming Assignment

Programming teachers very often assess their students' submissions solely from their correctness, sometimes with the help of an automated-grading platform. This approach is arguably effective and efficient at the same time. Unfortunately, this single-dimension assessment approach narrows the students' perspective on a high-quality solution to just a working solution. In the real world setting, a solution should be maintainable with minimal cost. Maintainability is closely related to code quality. In this paper, we present a web-based tool that would help the teachers to assess the students' submissions from both correctness and quality in one place. In this tool, we integrate GitHub Classroom and SonarQube.