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Object detection and tracking are the integral elements for the perception of the spatio-temporal environment. The availability and affordability of camera and lidar as the leading sensor modalities have used for object detection and tracking in research. The usage of deep learning algorithms for the object detection and tracking using camera and lidar have illustrated the promising results, but these sensor modalities are prone to weather conditions, have sparse data and spatial resolution problems. In this work, we explore the problem of detecting distant objects and tracking using radar. For the efficacy of our proposed work, extensive experimentation in different traffic scenario are performed by using our self-driving car test-bed.

Raja Rao 1908 2006 is one of the best Indian novelists writing in English. He occupies a central position in any discussion of Indian English literature. He is the foremost of those writers whose work has placed Indo English literature on the map of world literatures. His first and best known novel, Kanthapura 1938 earned him an international acclaim and acceptance as one of the major novelists in Indian English literature. Kanthapura is a novel dealing with the impact of the Gandhian freedom struggle on a remote South Indian village of that name. In this novel Raja Rao uses myths and legends to enrich the texture of the novel and impart to it a rare expansiveness, elevation and dignity. The paper attempts to show parallelism between Ramayana and Kanthapura by examining Raja Rao's artistic use of myth in the novel. Ishfaq Hussain Bhat "Use of Myth in Kanthapura: Parallelism Between Ramayana and Kanthapura" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: https://www.ijtsrd.com/papers/ijtsrd5940.pdf

Today’s arena of global village organizations, social applications, and commercial websites provides huge information about products, individuals, and activities. This is leading to a plethora of content that requires effective handling to obtain the desired information. A recommendation system (RS) suggests relevant items to the user according to his/her desired preference. It processes various information related to users and items. However, RSs suffer from data sparsity. Generally, deep learning techniques are used in RSs for deep analysis of item contents to create precise recommendations. However, the effective handling of user reviews in parallel with item reviews is still an open research domain that can be further explored. In this paper, a hybrid model that handles both user and item metadata concurrently is proposed with the aim of solving the sparsity problem. To demonstrate the viability of the proposed methodology, a series of experiments was performed on three real-world datasets. The results show that the proposed model outperforms other state-of-the-art approaches to the best of our knowledge.

Product redesign is not a straightforward task, specifically for complex commodities. Engineering change requirements can be evoked in any phase of the product development process, thus making engineering change management a challenging task. The motive of this study is to explore the best possible way of managing engineering change requirements taking execution sequence of change requirements into consideration. In this article, a new approach supporting engineering change requirements implementation sequence, by considering the risk associated with engineering changes, is presented. The risk of the redesign is hard to foresee since the engineering change effects are being dispersed from the instigating component to other associated components. In this article, the term of rework-risk is used for the amount of rework needed to be done to redesign the products’ components. The practicality of suggested method is analyzed using the redesign of an optical mouse as a case study. Managing engineering change requirements in a group with proper sequence can ensue with a 15% decrease in the redesign duration as compared with the prompt implementation of engineering change requirements. Conversely, it can also cause 36.23% increase in the redesign duration, if not handled in an appropriate sequence. The results from a single, simple case, indicates that running engineering change requirement batches can be beneficial.

Multicore architectures are mainstream due to ever increasing demand of throughput by modern applications. However, the suboptimal utilization of available resources in these architectures may impl...

Design projects have been surrounded by tight schedule and cost overruns. Therefore, it is indispensable to resolve the design changes in an economical way. This work introduces an advanced technique to assess and optimize change propagation paths for multiple change requirements occurring simultaneously during the product development process. A novel multiple change requirement algorithm and a mathematical model considering the overall propagated risk are developed, to explore cost-effective change propagation paths in terms of lead time. The risk is quantified with regard to propagation likelihood and change impact, which results in re-work. Design structure matrix framework is used to capture the dependencies between components. It is revealed that the change requirements execution sequence has a significant effect on the total number of change propagation paths, change steps, distinct change components, and completion time. This approach is illustrated by a case study, which indicates that the proposed methodology can assist the designer in exploring and selecting optimal change propagation paths.

The adverse environmental conditions build a bottleneck for the autonomous driving. This challenge is resolved by data fusion of sensor modalities. Here, thermal and Lidar data are fused together for the precise perception of environment.

Signal-to-noise ratio (SNR) is the foremost parameter which provides insight into the design and performance of any receiver. The pulse parameters accuracy and probability of detection of a receiver are directly estimated by calculating the SNR. Measurement of SNR Rf (SNR at RF level) and SNR video (SNR at video level) in analog receivers has brought much disagreement among different authors. This paper presents a straightforward methodology for estimating the SNR Rf and SNR video in microwave receivers in both theoretical and practical sense. The calculations and practical experiments are performed by employing successive detector log video amplifier (SDLVA) receiver which is the basic component used in electronic warfare (EW) systems for transforming radio frequency (RF) signals into a baseband (video) signals. The relation between SNR Rf and SNR video is explained and a new formulation is proposed for the noise limited case of SDLVA. The proposed methodology is validated by using a broadband SDLVA receiver having an operational frequency as 2 - 18 GHz, video logging slope as 50 mV/dB, and dynamic range as 75 dB. In general, the proposed method can be employed to estimate SNR of any microwave receiver.

This paper demonstrates that interval type-2 Fuzzy Logic Systems (FLS’s) are suited to Multiprocessor System-on-a-Chip (MPSoC) design modeling because of their ability to handle the uncertainty associated with input parameters. This makes for a scalable modeling process, whereas prior usage of type-1 FLS’s for modeling inhibited scalability. Specifically, the paper proposes a type-2 Takagi Sugeno Kang (TSK) FLS for modeling MPSoCs built around a multicore processor with shared memory. The paper also presents a TSK FLS reconfiguration methodology in order to dynamically reduce the energy consumption of such a multiprocessor. Modeling of MPSoC’s by means of the type-2 TSK FLS was found to be effective in terms of a reduction in the Energy Delay Product when applied to five large-scale numerical processing applications on an MPSoC. In fact, experimental results show a significant reduction (by 87–93% across the applications) in the energy consumption of an MPSoC.

The well-known model of Vestal aims to avoid excessive pessimism in the quantification of the processing requirements of mixed-criticality systems, while still guaranteeing the timeliness of higher-criticality functions. This can bring important savings in system costs, and indirectly help meet size, weight and power constraints. This efficiency is promoted via the use of multiple worst-case execution time (WCET) estimates for the same task, with each such estimate characterised by a confidence associated with a different criticality level. However, even this approach can be very pessimistic when the WCET of successive instances of the same task can vary greatly according to a known pattern, as in MP3 and MPEG codecs or the processing of ADVB video streams. In this paper, we present a schedulability analysis for the multiframe mixed-criticality model, which allows tasks to have multiple, periodically repeating, WCETs in the same mode of operation. Our work extends both the analysis techniques for Static Mixed-Cricality scheduling (SMC) and Adaptive Mixed-Criticality scheduling (AMC), on one hand, and the schedulability analysis for multiframe task systems on the other. Our proposed worst-case response time (WCRT) analysis for multiframe mixed-criticality systems is considerably less pessimistic than applying the SMC, AMC-rtb and AMC-max tests obliviously to the WCET variation patterns. Experimental evaluation with synthetic task sets demonstrates up to 63.8% higher scheduling success ratio (in absolute terms) compared to the best of the frame-oblivious tests.

The well-known model of Vestal aims to avoid excessive pessimism in the quantification of the processing requirements of mixed-criticality systems, while still guaranteeing the timeliness of higher-criticality functions. This can bring important savings in system costs, and indirectly help meet size, weight and power constraints. This efficiency is promoted via the use of multiple worst-case execution time (WCET) estimates for the same task, with each such estimate characterized by a confidence associated with a different criticality level. However, even this approach can be very pessimistic when the WCET of successive instances of the same task can vary greatly according to a known pattern, as in MP3 and MPEG codecs or the processing of ADVB video streams. In this paper, we present a schedulability analysis for the new multiframe mixed-criticality model, which allows tasks to have multiple, periodically repeating, WCETs in the same mode of operation. Our work extends both the analysis techniques for Static Mixed-Criticality scheduling (SMC) and Adaptive Mixed-Criticality scheduling (AMC), on one hand, and the schedulability analysis for multiframe task systems on the other. A constrained-deadline model is initially targeted, and then extended to the more general, but also more complex, arbitrary-deadline scenario. The corresponding optimal priority assignment for our schedulability analysis is also identified. Our proposed worst-case response time (WCRT) analysis for multiframe mixed-criticality systems is considerably less pessimistic than applying the static and adaptive mixed-criticality scheduling tests oblivious to the WCET variation patterns. Experimental evaluation with synthetic task sets demonstrates up to 20% and 31.4% higher scheduling success ratio (in absolute terms) for constrained-deadline analyses and arbitrary-deadline analyses, respectively, when compared to the best of their corresponding frame-oblivious tests.

Recently, the Internet has been utilized by many applications to convey time-sensitive messages. The persistently expanding Internet coverage and its easy accessibility have offered to ascend to a problem which was once regarded as not essential to contemplate. Nowadays, the Internet has been utilized by many applications to convey time-sensitive messages. Wireless access points have widely been used but these access points have limitations regarding area coverage. So for covering a wider space, various access points need to be introduced. Therefore, when the user moves to some other place, the devices expected to switch between access points. Packet loss amid the handovers is a trivial issue. MediaSense is an Internet of Things distributed architecture enabling the development of the IoT application faster. It deals with this trivial handover issue by utilizing a protocol called Distributed Context eXchange Protocol. However, this protocol is centralized in nature and also suffers in a scenario when both sender and receiver address change simultaneously. This paper presents a mechanism to deal with this scenario and presents a distributed solution to deal with this issue within the MediaSense platform. The proposed protocol improves dissemination using retransmission mechanism to diminish packet loss. The proposed protocol has been delineated with a proof of concept chat application and the outcomes have indicated a significant improvement in terms of packet loss.

Generation of a mesh is the first step in the development of electromagnetic (EM) field solver and mesh quality plays vital role in defining the consumption of computational resources like execution time and memory usage. The modeling of regular structures (structures whose interfaces coincide with the mesh cells) using simple mesh grids is easy to achieve but for irregular structures (structures whose interfaces do not coincide with mesh cells) is hard to achieve. Different methods have already been proposed to deal with domain decomposition for the irregular structures, e.g., thin-layer problems. The methods include subgridding and fine-mesh generation in the locality of the thin layers. This high resolution in the domain decomposition leads to the redundancy of number of cells in the computational domain hence demanding for extra computational resources. This paper presents two adaptive mesh generation techniques in 1-D which have successfully integrated the complicated multilayer structure composed of irregular thicknesses. Adaptation in the mesh for the discontinuous Galerkin time domain (DGTD) based EM solver is achieved by using i) nodes displacement, and ii) node insertion methods. The two methods use an optimum number of nonoverlapping elements (K) for the domain decomposition and adapt the locations of the nodes to incorporate the complex structures. Algorithms and associated methodologies for the two techniques are presented and their validation is achieved by comparing the numerical results with the analytical results for an irregular structure composed of multilayer with different values of thickness. High accuracy is achieved by the both methods but tradeoff exists between the complexity of the algorithms and the execution time. The node displacement method has a complex algorithm and consumes lesser execution time while the node insertion method has the simplest algorithm but requires more execution time for solving the same problem.

The performance of amplitude- and phase-based passive direction finding (DF) systems is evaluated in a multi-path environment. For performance analysis and fair comparison, a parametric circular DF array is modelled and analyzed in a two-wave (direct and reflected) environment. The parameterized model varies the aperture size and number of antenna elements of DF array, frequency, strength and angle-of-incidence of direct and reflected waves. The root-mean-square (RMS) bearing error is estimated for all the possible combinations of the said parameters. The MATLAB simulation results based on the analytical model show the better reflection immunity of the phase-based direction finding system in a multi-path environment, subject to the selection of appropriate antenna-pattern and field-of-view.

The introduction of the space object conjunction method in electromagnetic compatibility modeling and simulation is quite a novel concept. It is useful for the stochastic analysis of an electromagnetic (EM) environment which is based on the probability of conjunction assessment. The space conjunction methodology is anticipated as the frontline defense for the protection of active satellites in space. EM congestion occurs in an environment with the increase in the number of operational EM devices. In a theoretical sense, this congestion is analogous to the space conjunction. Therefore, the space conjunction model can be applied in the EM scenarios. In this paper, we have investigated the application of the defined conjunction model by using the analytical expression of the probability of electromagnetic conjunction, which is based on the orbital parameters of the system under test. Additionally, we have elaborated the influence of these orbital parameters on the probability of conjunction. The simulations have been performed by considering different EM scenarios and the results are validated by using Monte Carlo simulations. The results show that errors in the analytical and Monte Carlo simulations are within a 1% range, which makes the analytical model effective. Computationally, the proposed analytical model is cost effective as compared to the numerical method, i.e., Monte Carlo. Moreover, from the results, it has been validated that the probability of conjunction increases with the increase in transmitted power and decreases with the compatible threshold limit of the receiving system, thus, making this method useful for analyzing the electromagnetic environment and as a frontline safety tool for electromagnetic systems.

Modern multicore architectures comprise a large set of components and parameters that require being matched to achieve the best balance between power consumption and throughput performance for a particular application domain. The exploration of design space for finding the best power–throughput trade-off is a combinatorial optimization problem with a large number of combinations, and. in general, its solution is prohibitively difficult to be explored exhaustively. However, fortunately, evolutionary algorithms EAs have the potential to efficiently solve this problem with reasonable computational complexity. In this paper, we consider a multiobjective design space exploration DSE problem with two conflicting objectives. The first objective corresponds to power consumption minimization while the second objective relates to throughput maximization. We approach this problem by employing the estimation of distribution algorithm EDA , which belongs to the family of EAs. The proposed EDA-based DSE EDA-DSE scheme efficiently selects the design parameters i.e. cache size, number of cores, and operating frequency with an efficient power–throughput ratio. The proposed scheme is verified using cycle-accurate simulations over a set of benchmarks and the simulation results show a significant reduction in energy-delay product for all benchmark applications when compared to the default baseline configuration and genetic algorithm.