Generic Methodology Research Articles

Generic development methodology for flexible robotic pick-and-place workcells based on Digital Twin

Together with the trends of mass personalization, flexible robotic applications become more and more popular. Although conventional robotic automation of workpiece manipulation seems to be solved, advanced tasks still need great amount of effort to be reached. In most cases, on-site robot programming methods, which are intuitive and easy to use, are not applicable in flexible scenarios. On the other hand, the application of offline programming methods requires careful modeling and planning. Consequently, this paper proposes a generalized development methodology for flexible robotic pick-and-place workcells, in order to provide guidance and thus facilitate the development process. The methodology is based on the Digital Twin (DT) concept, which allows the iterative refinement of the workcell both in the digital and in the physical space. The goal is to speed up the overall commissioning (or reconfiguration) process and reduce the amount of work in the physical workcell. This can be achieved by digitizing and automating the development, and maintaining sufficient twin closeness. With that, the operation of the digital model can be accurately realized in the physical workcell. The methodology is presented through a semi-structured pick-and-place task, realized in an experimental robotic workcell together with a reconfiguration scenario.

Occurrence of micropollutants in the Yesilirmak River Basin, Turkey.

The European Water Framework Directive (WFD) (2000/60/EC) is the most visionary piece of European environmental legislation that aims to achieve good water status of both surface water and groundwater bodies. The Directive provides a fundamental basis for surface water monitoring activities in the European Member States. The objective of this study is to investigate the occurrence of micropollutants in the Yesilirmak River and to develop a cost-effective monitoring strategy based on spatiotemporal data. A 2-year seasonal monitoring program was conducted between 2016 and 2018, and the water samples were analyzed for 45 priority substances as defined by the WFD and 250 national river basin-specific pollutants. In the basin, 166 pollutants were quantified in at least one of the samples with individual concentrations ranging from 6 × 10-6μg/L to 100 mg/L. Fifty-four pollutants with a frequency of occurrence greater than 5% were selected for further evaluation. Based on statistical evaluation of the data, 20 pollutants were identified as the pollutants of primary concern. These 20 pollutants were grouped under three categories (metals, biocides, and industrial organic compounds) and their spatiotemporal distributions in the basin were assessed to establish a monitoring strategy specific to each pollutant category. The results of the study revealed that the common season for the monitoring of all pollutant categories was the spring. This study provides a generic methodology for the development of a cost-effective water quality monitoring strategy, which can be applicable for use in different basins and pollutant datasets.

RASSLE: Return Address Stack based Side-channel LEakage

Microarchitectural attacks on computing systems often stem from simple artefacts in the underlying architecture. In this paper, we focus on the Return Address Stack (RAS), a small hardware stack present in modern processors to reduce the branch miss penalty by storing the return addresses of each function call. The RAS is useful to handle specifically the branch predictions for the RET instructions which are not accurately predicted by the typical branch prediction units. In particular, we envisage a spy process who crafts an overflow condition in the RAS by filling it with arbitrary return addresses, and wrestles with a concurrent process to establish a timing side channel between them. We call this attack principle, RASSLE 1 (Return Address Stack based Side-channel Leakage), which an adversary can launch on modern processors by first reverse engineering the RAS using a generic methodology exploiting the established timing channel. Subsequently, we show three concrete attack scenarios: i) How a spy can establish a covert channel with another co-residing process? ii) How RASSLE can be utilized to determine the secret key of the P-384 curves in OpenSSL (v1.1.1 library)? iii) How an Elliptic Curve Digital Signature Algorithm (ECDSA) secret key on P-256 curve of OpenSSL can be revealed using Lattice Attack on partially leaked nonces with the aid of RASSLE? In this attack, we show that the OpenSSL implementation of scalar multiplication on this curve has varying number of add-and-sub function calls, which depends on the secret scalar bits. We demonstrate through several experiments that the number of add-and-sub function calls can be used to template the secret bit, which can be picked up by the spy using the principles of RASSLE. Finally, we demonstrate a full end-to-end attack on OpenSSL ECDSA using curve parameters of curve P-256. In this part of our experiments with RASSLE, we abuse the deadline scheduler policy to attain perfect synchronization between the spy and victim, without any aid of induced synchronization from the victim code. This synchronization and timing leakage through RASSLE is sufficient to retrieve the Most Significant Bits (MSB) of the ephemeral nonces used while signature generation, from which we subsequently retrieve the secret signing key of the sender applying the Hidden Number Problem.
 1RASSLE is a non-standard spelling for wrestle.

A Targeted and Tuneable DNA Damage Tool Using CRISPR/Cas9.

Mammalian cells are constantly subjected to a variety of DNA damaging events that lead to the activation of DNA repair pathways. Understanding the molecular mechanisms of the DNA damage response allows the development of therapeutics which target elements of these pathways. Double-strand breaks (DSB) are particularly deleterious to cell viability and genome stability. Typically, DSB repair is studied using DNA damaging agents such as ionising irradiation or genotoxic drugs. These induce random lesions at non-predictive genome sites, where damage dosage is difficult to control. Such interventions are unsuitable for studying how different DNA damage recognition and repair pathways are invoked at specific DSB sites in relation to the local chromatin state. The RNA-guided Cas9 (CRISPR-associated protein 9) endonuclease enzyme is a powerful tool to mediate targeted genome alterations. Cas9-based genomic intervention is attained through DSB formation in the genomic area of interest. Here, we have harnessed the power to induce DSBs at defined quantities and locations across the human genome, using custom-designed promiscuous guide RNAs, based on in silico predictions. This was achieved using electroporation of recombinant Cas9-guide complex, which provides a generic, low-cost and rapid methodology for inducing controlled DNA damage in cell culture models.

Large-area integration of two-dimensional materials and their heterostructures by wafer bonding

Integrating two-dimensional (2D) materials into semiconductor manufacturing lines is essential to exploit their material properties in a wide range of application areas. However, current approaches are not compatible with high-volume manufacturing on wafer level. Here, we report a generic methodology for large-area integration of 2D materials by adhesive wafer bonding. Our approach avoids manual handling and uses equipment, processes, and materials that are readily available in large-scale semiconductor manufacturing lines. We demonstrate the transfer of CVD graphene from copper foils (100-mm diameter) and molybdenum disulfide (MoS2) from SiO2/Si chips (centimeter-sized) to silicon wafers (100-mm diameter). Furthermore, we stack graphene with CVD hexagonal boron nitride and MoS2 layers to heterostructures, and fabricate encapsulated field-effect graphene devices, with high carrier mobilities of up to 4520;{mathrm{cm}}^2{mathrm{V}}^{ - 1}{mathrm{s}}^{ - 1}. Thus, our approach is suited for backend of the line integration of 2D materials on top of integrated circuits, with potential to accelerate progress in electronics, photonics, and sensing.

Accurate Power-Efficient Format-Scalable Multi-Parallel Optical Digital-to-Analogue Conversion

In optical transmitters generating multi-level constellations, optical modulators are preceded by Electronic Digital-to-Analog-Converters (eDAC). It is advantageous to use eDAC-free Optical Analog to Digital Converters (oDAC) to directly convert digital bitstreams into multilevel PAM/QAM optical signals. State-of-the-art oDACs are based on Segmented Mach-Zehnder-Modulators (SEMZM) using multiple modulation segments strung along the MZM waveguides to serially accumulate binary-modulated optical phases. Here we aim to assess performance limits of the Serial oDACs (SEMZM) and introduce an alternative improved Multi-Parallel oDAC (MPoDAC) architecture, in particular based on arraying multiple binary-driven MZMs in parallel: Multi-parallel MZM (MPMZM) oDAC. We develop generic methodologies of oDAC specification and optimization encompassing both SEMZM and MPMZM options in Direct-Detection (DD) and Coherent-Detection (COH) implementations. We quantify and compare intrinsic performance limits of the various serial/parallel DD/COH subclasses for general constellation orders, comparing with the scant prior-work on the multi-parallel option. A key finding: COH-MPMZM is the only class synthesizing ‘perfect’ (equi-spaced max-full-scale) constellations while maximizing energy-efficiency-SEMZM/MPMZM for DD are less accurate when maximal energy-efficiency is required. In particular, we introduce multiple variants of PAM4|8 DD and QAM16|64 COH MPMZMs, working out their accuracy vs. energy-efficiency-and-complexity tradeoffs, establishing their format-reconfigurability (format-flexible switching of constellation order and/or DD/COH).

On transferability and calibration of pedestrian and car motion models in shared spaces

ABSTRACT Modelling and simulation of mixed-traffic zones is an essential tool for transportation planners to assess safety, efficiency, and human-friendliness of future urban areas. This paper addresses the calibration and transferability of existing shared space models for pedestrians and cars. Specifically, our first contribution is enhancing the Game-Theoretic Social Force Model (GSFM) by a generic methodology for largely automated model calibration. The second contribution is an investigation into the transferability of shared space models. We define criteria for model transferability and present a case study, in which we evaluate transferability of the model we constructed based on the ``German data set'' to a different shared space environment from China. Our results indicate that although the model faces difficulties replicating road users’ motion from a new environment, by adding social norms (derived through analysis) of that environment to our model, satisfactory improvement of model accuracy can be obtained with little effort.

Modeling and multi-objective optimization of commercial ethylene oxide reactor to strike a delicate balance between profit and negative environmental impact

The present work emphasizes the development of a generic methodology that addresses the core issue of any running chemical plant, i.e., how to maintain a delicate balance between profit and environmental impact. Here, ethylene oxide (EO) production plant has been taken as a case study. The production of EO takes place in a multiphase catalytic reactor, the reliable first principle-based model of which is still not available in the literature. Artificial neural network (ANN) was therefore applied to develop a data-driven model of the complex reactor with the help of actual industrial data. The model successfully built up a correlation between the catalyst selectivity and other operational parameters. This model was used to establish two objective functions, profit and environmental impact. In this paper, the negative environmental impact has been designated by Eco-indicator 99, which considers all the negative health and environmental impacts of a certain product. A recently developed metaheuristic optimization technique, namely multi-objective firefly (MOF) algorithm, was used to develop Pareto diagram of profit vs. Eco-99. The Pareto diagram will help the plant engineers to make strategy on what operating conditions to be maintained to make a delicate balance between profit and environmental impact. It was also found that by applying this modeling and optimization technique, for a 130 kTA EO plant, approximately 7048 t/year of carbon dioxide can be saved from emission into the atmosphere.

Near-Infrared Chiral Plasmonic Microwires through Precision Assembly of Gold Nanorods on Soft Biotemplates

Directing the assembly of plasmonic nanoparticles into chiral superstructures has diverse applications including, chiroptical sensing, nonlinear optics, and biomedicine. Though soft template-mediated assemblies of both spherical and nonspherical gold nanoparticles have made significant progress, most approaches require sophisticated chemical synthesis or advanced methodologies. Besides, reports of structurally precise chiral plasmonic assemblies beyond nanoscale are limited. Here, we propose an efficient yet simple strategy to grow such precision assemblies up to mesoscale, which is beneficial for a broader community. Briefly, cationic gold nanorods (AuNRs) are allowed to systematically assemble along atomically precise, chiral, rodlike tobacco mosaic virus (TMV) particles via electrostatic attraction under ambient condition. This leads to spontaneous formation of helical hybrid microwires with high structural precision, as evidenced by cryogenic transmission electron microscopy and tomography. Resulting composite superstructures show a strong circular dichroism response at the plasmon wavelength of the AuNRs, which is supported by simulations using discrete dipole approximation. Further, chirality of the system is investigated at a single-microwire level using polarized dark-field scattering microscopy. An alternative chiral template, negatively charged colloidal cellulose nanocrystals, also arrange AuNRs into similar chiral microstructures. Thus, our report proposes a generic methodology to obtain chiral plasmonic response at the NIR region using inexpensive templates that will encourage the exploration of a wider range of nanoscale templates for creating hybrid mesostructures with emerging optoelectronic properties.

A methodology to devise consistent probability density function models for particle dynamics in turbulent dispersed two-phase flows

The purpose of this article is to propose a generic methodology to build consistent Lagrangian models for polydisperse turbulent two-phase flows where the main issue is to devise a stochastic model for the velocity of the fluid seen by discrete particles. By consistent, it is meant that such models should meet the requirements set forth by Minier et al. (Phys. Fluids, 26, 113303, 2014) and, in the limit of vanishing particle inertia, retrieve the state-of-the-art stochastic models referred to as generalized Langevin models (GLMs) used for the simulation of turbulent single-phase flows. The methodology is generic in the sense that the resulting stochastic models for polydisperse two-phase flows are not limited to one particular fluid model but allows extending any GLM formulation to the two-phase flow situation. This is obtained by introducing a specific operator, which represents how statistical characteristics of fluid particles are transformed, or mapped, to the ones pertaining to the velocity of the fluid seen. In practice, this operator can be worked out separately from first principles or by resorting to some physical inputs. Once it is expressed, the present methodology shows how to extend a GLM for fluid particles to obtain a two-phase GLM formulation in a consistent manner. This is helpful to decouple physics-based developments used to obtain such an operator from the construction of practical stochastic models while ensuring that they remain consistent with fluid descriptions.

Aliased informed model selection strategies for six‐factor no‐confounding designs

AbstractNonregular designs are a preferable alternative to regular resolution IV designs because they avoid confounding two‐factor interactions. As a result nonregular designs can estimate and identify a few active two‐factor interactions. However, due to the sometimes complex alias structure of nonregular designs, standard screening strategies can fail to identify all active effects. In this paper, we explore a specific no‐confounding six‐factor 16‐run nonregular design with orthogonal main effects. By utilizing our knowledge of the alias structure, we can inform the model selection process. Our aliased informed model selection (AIMS) strategy is a design‐specific approach that we compare to three generic model selection methods; stepwise regression, Lasso, and the Dantzig selector. The AIMS approach substantially increases the power to detect active main effects and two‐factor interactions versus the aforementioned generic methodologies.

The potential impact of experiencing social inclusion in recreation for children with and without disabilities

Purpose Inclusive recreation programs can have individual and community impacts for children with and without disabilities. However, studies that explore the impact of such programs on children’s attitudes are mixed. The purpose of this study was to explore the perspectives of children with and without disabilities on the individual impact of an inclusive recreation program. Material and Method This study adopted a generic qualitative methodology. Interviews were conducted with participants between the ages of eight and 18 enrolled in the same program and each participant was interviewed twice. Inductive thematic analysis was used to analyze results. Results 17 participants were recruited for this study, which included nine children without disabilities (CWODs) and eight children with disabilities (CWDs). This study revealed five themes: a) CWODs have limited exposure to people with disabilities; b) CWODs and CWDs’ hopes of change; c) CWODs learned how to interact with people with disabilities; d) CWODs reported greater perceived similarity in functional ability and hobbies/interests between themselves and CWDs, and; e) CWODs become more comfortable being around people with disabilities. Conclusions This study helps broaden understandings of how inclusive experiences in recreation settings impact children with and without disability. IMPLICATIONS FOR REHABILITATION Children without disabilities can develop more positive attitudes toward children with disabilities in affective and cognitive domains after participating in an inclusive recreation program. Incorporating inclusive language into program design and implementation may promote positive attitudes toward diversity in recreation settings. Children without disabilities would benefit from more opportunities to interact with children with disabilities in unstructured, inclusive or integrated recreation settings.

QUALIFICATION OF ANC9 GENERIC INSERT METHODOLOGY (GIM)

Discrete burnable poisons like the Wet Annular Burnable Absorber and Pyrex have been used in PWR core to improve core power distribution and provide more negative moderator temperature coefficient. The burnable absorber in the burnable poison rods burns fast and is completely gone after one cycle exposure in the core. Traditionally, the burnable poison rods are designed to be part of the fuel assembly. They are burned together with the fuel in the first loading cycle and discharged after one cycle. In recent years, different insertion scenarios of the burnable poison rods have been introduced in the PWR plants operation to improve the fuel performance, for instance, fresh burnable poison rods are inserted into a burned assembly; burned burnable poison rods stay in the original assembly or are replaced in a different assembly. A Generic Insert Methodology [1] was developed in Westinghouse and implemented in NEXUS/ANC9 code system. With this new methodology, ANC9 is able to follow the assembly history and model all types of absorber insert components for all kinds of insertion scenarios. An extensive methods validation and qualification effort has been completed by modeling different insertion cases. This paper provides details of the qualification cases along with the analysis of the results.

Modelo de evaluación sistémica en la gestión integral de pequeñas y medianas empresas porcinas

This research article aproaches in a systematic way the intrinsic problems typical of the daily management of small and medium-sized pig companies in the semi-arid region of the province of La Pampa, Argentina. Through the methodological use of a case study, from the point of view of the Balanced Scorecard, a set of indicators was constructed, grouped into four perspectives, which allowed to develop an adequate diagnosis of the current situation and to establish parameters for continuous improvement in the medium and long term. deadline to achieve the proposed strategic objectives. The document aims to present a generic evaluation methodology, which can be successfully replicated in other companies related to the pig agrifood chain, taking into account the particularities of any organization that develops productive activities.

Towards a systematic method for assessing the impact of chemical pollution on ecosystem services of water systems

Chemical pollution impinges on the quality of water systems and the ecosystem services (ESs) they provide. Expression of ESs in monetary units has become an essential tool for sustainable ecosystem management. However, the impact of chemical pollution on ESs is rarely quantified, and ES valuation often focuses on individual services without considering the total services provided by the ecosystem. The purpose of the study was to develop a stepwise approach to quantify the impact of sediment pollution on the total ES value provided by water systems. Thereby, we calculated the total ES value loss as a function of the multi-substance potentially affected fraction of species at the HC50 level (msPAF(HC50)). The function is a combination of relationships between, subsequently: the msPAF(HC50), diversity, productivity and total ES value. Regardless of the inherent differences between terrestrial and aquatic ecosystems, an increase of diversity generally corresponded to an increase in productivity with curvilinear or linear effects. A positive correlation between productivity and total values of ESs of biomes was observed. The combined relationships showed that 1% msPAF(HC50) corresponded to on average 0.5% (0.05–1.40%) of total ES value loss. The ES loss due to polluted sediments in the Waal-Meuse river estuary (the Netherlands) and Flemish waterways (Belgium) was estimated to be 0.3–5 and 0.6–10 thousand 2007$/ha/yr, respectively. Our study presents a novel methodology to assess the impact of chemical exposure on diversity, productivity, and total value that ecosystems provide. With sufficient monitoring data, our generic methodology can be applied for any chemical and region of interest and help water managers make informed decisions on cost-effective measures to remedy pollution. Acknowledging that the ES loss estimates as a function of PAF(HC50) are crude, we explicitly discuss the uncertainties in each step for further development and application of the methodology.

Comparative evaluation of intelligent regression algorithms for performance and emissions prediction of a hydrogen-enriched Wankel engine

In order to satisfy the heightened emissions regulation and further enhance the performance of the engine, efforts on amelioration of the engine management system are of great significance besides using intelligent regression algorithms. Based on a hydrogen-enriched Wankel rotary engine, multiple engine operations with variable excess air ratios, variable ignition timing, and variable hydrogen enrichment have been carried out a series of engine calibration tests in detail. After recording the required experimental data, three different methods, including quadratic polynomial, artificial neural networks (ANN), and support vector machine (SVM) are applied to construct a multi-objective regression model which gives a unique insight into the mathematical relationship between the engine performance and the operation and control parameters. For the ANN, the effect of the number of nodes in the hidden layer on the regression performance was discussed, and the weight values of the ANN was optimized using a genetic algorithm. For the SVM, the effects of the kernel function and three optimization methods on regression performance were discussed. The results indicated that the SVM exhibited the best fitting results among the three methods. The optimal R2 for brake thermal efficiency, fuel energy flow rate, nitrogen oxide, carbon monoxide, and unburned hydrocarbon is 0.9877, 0.9840, 0.9949, 0.9937, and 0.9992, respectively. It is highly recommended that the SVM method as a generic methodology may be a new direction for nonlinear control system modeling of the Wankel engine.

A Lie-Theory-Based Dynamic Parameter Identification Methodology for Serial Manipulators

Accurate estimation of the dynamic parameters comprising a robot's dynamics model is of paramount importance for simulation and real-time model-based control. The conventional approaches for obtaining the identification model are extremely cumbersome, and incapable of offering universal applicability, as well as physical feasibility of dynamic parameter identification. To this end, the work presented herein proposes a novel and generic identification methodology, for retrieving the dynamic parameters of serial manipulators with arbitrary degrees of freedom (DOFs), based on the Lie theory. In this approach, the robot dynamics model that includes frictional terms is analytically represented as a closed-form matrix equation, by rearranging the classical recursive Newton–Euler formulation. The link inertia matrix that comprises inertia tensors, masses, and Center of Mass (CoM) positions, together with the joint friction coefficients, are extracted from the regrouped linear dynamics model by means of the Kronecker product. Meanwhile, the introduced Kronecker–Sylvester identification equation is formulated as an optimization problem involving dynamic parameters with physical feasibility constraints, and is ultimately estimated via linear matrix inequality techniques and semidefinite programming using joint position, velocity, acceleration, and torque data. Identification results of dynamic parameters are accurately procured through a series of practical tests that entail providing a seven-DOF Rokae xMate robot, with optimized Fourier-series-based excitation trajectories. Experimental validation serves the purpose of demonstrating the proposed method's efficacy, in terms of accurately retrieving a serial manipulator's dynamic parameters.

Impact of HMI on driver’s distraction on a freeway under heavy foggy condition based on visual characteristics

Connected vehicle technology relying on Human Machine Interface (HMI) achieve a dominant position in the overall safety improvement. However, the impact of HMI on the driver’s visual attention cannot be ignored, especially on the accident-prone foggy freeway. The objective of this paper is to evaluate the level of distraction caused by HMI in data analysis of drivers’ visual characteristics and to establish a generic evaluation methodology. A connected vehicle test platform has been established based on the driving simulator, in which visibility was set to the level of heavy fog and the technical condition was set in two conditions (with or without HMI). Measurement of driving behavior parameters include frequency of fixations and saccades and the proportion of fixation. The researchers compared and analyzed the driver’s visual characteristics and the degree of distraction in a combination of indices based on the AttenD algorithm, setting two technical conditions in a heavy fog. Drivers suffering more visual distraction and interference with HMI may have an impact on the driver’s driving safety. The results provide a generic approach to evaluate the HMI of a connected vehicle system and a safety assessment methodology for the connected vehicle system.

A Trail to Milieu Research Methodology for Application of Implementation Frameworks in Manufacturing Sector

The profusely used tools of operational management research in lean manufacturing context include roadmap, conceptual model, implementation frameworks, descriptive planning and assessment checklist. Out of these, an implementation framework development in lean manufacturing sector is common, but faces quandary regarding its development, consolidation and validation – thereby confirming the requirement of availability of succinct platform that aids in research methodology development. The aim of this research is to attain a clear research context, achieved accordingly by detailed literature review study that would subsequently aid in developing a generic research methodology design framework. Concomitant to it, the four layers, the layers of research onion were discussed; followed by selection of appropriate methods for development of research methodology in order to arrive at implementation frameworks. It was observed that for the methodology development, the philosophy of pragmatism is highly suitable, followed by abductive logic, in case of technique, mixed mode research is best, whereas in strategy selection, case study strategy is the most suitable due to its multi-functional ability of in-depth operational study. In addition to that, the mixed-mode approach carries the ability of comparative qualitative and quantitative research through longitudinal and cross-sectional case study respectively. Furthermore, the data collection processes were discussed in relevance to the research objective, which culminated in the formation of a detailed research methodology which has been divided into three major stages of research context and approach, framework development and validation, resulting in attaining implementation framework through literature review, longitudinal case study and cross-sectional case study respectively. The major strength and contribution of this research study is the development of one concise research methodology that is considered as the paradigm shift and a clear innovation towards this field.

Power- and Area-Optimized High-Level Synthesis Implementation of a Digital Down Converter for Software-Defined Radio Applications

In digital signal processing, digital down converters (DDCs) convert digitized, band-limited signals to lower frequency signals at a smaller sampling rate to simplify subsequent filtering stages. Software-defined radio (SDR) is a radio communication system in which components that are traditionally implemented in hardware are implemented in software on an embedded system. DDCs are widely used in modern communication systems, such as SDRs. Herein, we propose a low-power- and area-optimized implementation of a DDC for SDR applications. The DDC was designed using an innovative and novel high-level synthesis (HLS) design method based on application-specific bit widths for data nodes. The results achieved after a field programmable gate array (FPGA) implementation are superior to those obtained from hand-coded register transfer level (RTL) implementations in terms of area and power efficiency, with almost the same speed of operation. Our results were obtained using the MATLAB hardware description language (HDL) coder for HLS and Xilinx Vivado (a software for the synthesis and analysis of HDL designs) for synthesis. The DDC down-converts an input of 200 MHz signal to an output of 2 MHz signal. This implementation was conducted on a real FPGA hardware (Xilinx Kintex-7) and verified against the design specifications using an FPGA in the loop feature of HDL Verifier and MATLAB. In addition, we propose a generic methodology for improving the area, speed, and power for different application designs and HLS tools. The proposed methodology is also applicable to hand-coded RTL designs for any application.