了解嵌入系统的引导技术

引导是指在接通电源和装入应用之间,系统完成的一系列步骤,它在理论上简单,但实际上经常很复杂。引导加载器的主要任务是装入操作系统,但软硬件工程师对这个过程的看法并不相同。     

Identifying hazardousness of sewer pipeline gas mixture using classification methods: a comparative study

In this work, we formulated a real-world problem related to sewer pipeline gas detection using the classification-based approaches. The primary goal of this work was to identify the hazardousness of sewer pipeline to offer safe and non-hazardous access to sewer pipeline workers so that the human fatalities, which occurs due to the toxic exposure of sewer gas components, can be avoided. The dataset acquired through laboratory tests, experiments, and various literature sources was organized to design a predictive model that was able to identify/classify hazardous and non-hazardous situation of sewer pipeline. To design such prediction model, several classification algorithms were used and their performances were evaluated and compared, both empirically and statistically, over the collected dataset. In addition, the performances of several ensemble methods were analyzed to understand the extent of improvement offered by these methods. The result of this comprehensive study showed that the instance-based learning algorithm performed better than many other algorithms such as multilayer perceptron, radial basis function network, support vector machine, reduced pruning tree. Similarly, it was observed that multi-scheme ensemble approach enhanced the performance of base predictors.

     

Constructal enhancement of thermal transport in metal foam-PCM composite-assisted latent heat thermal energy storage system

The aim of this study is to augment thermal transport in latent heat thermal energy storage (LHTES) system by the optimum allocation of metal foam-phase change material (PCM) composite. This study emphasizes on the optimal volume and distribution of metal foam-PCM composite (MFPC) to enhance melting performance without delay in the total melting time. Therefore, a MFPC is designed according to constructal theory. The fundamental principle of the theory is to configure high thermal conductivity agents at optimal thermal energy flow path for effective heat exchange. A numerical code based on local thermal nonequilibrium approach equipped enthalpy porosity method is formulated, and evaluated. The results of the proposed configuration show that the provision of MFPC only at high local temperature gradient enhances the conductive transport with improvement in the overall thermal transport. It is derived that the elimination of metal foam volume at low temperature gradient incorporates the advantageous effect of natural convective transport, which is seen to be suppressed. Additionally, the proposed configuration may increase the volume of PCM, thus, the TES capacity. It also reduces the total weight and economy of energy storage system. The overall melting rate is improved by 11.11% in comparison with the LHTES with full volume of this high thermal conductivity agent.     

Organizational readiness for digital innovation: Development and empirical calibration of a construct

The advent and proliferation of digital technologies purport to increase the innovation potential of most organizations. However, approximately 90% of new ideas never convert to new product or service deliveries because of the lack of organizational readiness. This paper conceptualizes a formative multidimensional construct to gauge organizational readiness for digital innovations. Such a construct would facilitate cumulative research on the role of digital innovation, while benchmarking to track organizational readiness. The proposed construct includes 21 measures, categorized under seven subconstructs: resource readiness, IT readiness, cognitive readiness, partnership readiness, innovation valance, cultural readiness, and strategic readiness.     

Predictive modeling of die filling of the pharmaceutical granules using the flexible neural tree

In this work, a computational intelligence (CI) technique named flexible neural tree (FNT) was developed to predict die filling performance of pharmaceutical granules and to identify significant die filling process variables. FNT resembles feedforward neural network, which creates a tree-like structure by using genetic programming. To improve accuracy, FNT parameters were optimized by using differential evolution algorithm. The performance of the FNT-based CI model was evaluated and compared with other CI techniques: multilayer perceptron, Gaussian process regression, and reduced error pruning tree. The accuracy of the CI model was evaluated experimentally using die filling as a case study. The die filling experiments were performed using a model shoe system and three different grades of microcrystalline cellulose (MCC) powders (MCC PH 101, MCC PH 102, and MCC DG). The feed powders were roll-compacted and milled into granules. The granules were then sieved into samples of various size classes. The mass of granules deposited into the die at different shoe speeds was measured. From these experiments, a dataset consisting true density, mean diameter (d50), granule size, and shoe speed as the inputs and the deposited mass as the output was generated. Cross-validation (CV) methods such as 10FCV and 5x2FCV were applied to develop and to validate the predictive models. It was found that the FNT-based CI model (for both CV methods) performed much better than other CI models. Additionally, it was observed that process variables such as the granule size and the shoe speed had a higher impact on the predictability than that of the powder property such as d50. Furthermore, validation of model prediction with experimental data showed that the die filling behavior of coarse granules could be better predicted than that of fine granules.

     

Multi-objective optimisation of hybrid power generation system for a commercial market in Moradabad District of Uttar Pradesh,India

In this paper, a simulation model is developed to optimise the configuration of a hybrid photovoltaic-battery-diesel system with the objectives to minimise its Life Cycle Cost and CO₂ emissions from the system. The decision variables included in the optimisation model are the total area of photo voltaic arrays, number of PV modules of 600 Wp, diesel generator power and number of batteries of 24 V and 150 Ah. The model has been applied to the analysis of a hybrid power generation system for a typical commercial market consisting of 318 shops in Moradabad district of Uttar Pradesh, India. The optimum sizing process is verified by carrying out an appropriate sensitivity analysis. The results attained are fairly encouraging defending the applicability of the simulation model. The model developed can be utilised to determine the optimum dimensions of the hybrid PV–battery–diesel system for the locations having similar climatic conditions.     

Heat transfer and friction characteristics of an equilateral triangular solar air heater duct using inclined continuous ribs as roughness element on the absorber plate

An experimental study has been carried out to determine the effect on the heat transfer and friction characteristics of an equilateral triangular solar air heater duct using inclined continuous ribs as roughness element on the absorber plate. The experimental study encompasses the range of Reynolds numbers from 5600 to 28,000, relative roughness height (e/D_h) 0.021–0.043, relative roughness pitch (p/e) 8–16 and angle of attack (α ) 30–60°. The duct has an aspect ratio (W/H) of 1.15. The effect of flow parameters and roughness parameters on heat transfer and friction factor is discussed. The thermohydraulic performance parameter has been determined for the given range of flow parameters and roughness parameters.     

A decision framework for maximising lean manufacturing performance

Since the development of the original value stream mapping (VSM) by Taichi Ohno at Toyota, a number of authors have suggested several additional VSM tools to understand and improve the value stream through waste reduction. A single best VSM tool, though effective in dealing with a certain waste type, becomes redundant as other wastes take centre stage and/or organisational priorities change. To overcome this, a decision framework based on a novel formulation of the integrated analytical hierarchy process (AHP) – pre-emptive goal programming (PGP) has been proposed. This framework not only guarantees accurate selection of an ideal VSM tool, based on the current organisation's priorities, but also aids the decision maker to arrive at the optimum implementation sequence of a chosen set of VSM tools to identify and reduce all wastes present in the system, thereby maximising organisational performance in the shortest timeframe.     

Thermophoretic particle deposition and heat generation analysis of Newtonian nanofluid flow through magnetized Riga plate

The Riga surface is composed of an electromagnetic actuator that comprises a span-wise associated array of discontinuous electrodes and an everlasting magnet mounted over a planer surface. The electro-magneto-hydrodynamic has an attractive role in thermal reactors, fluidics network flow, liquid chromatography, and micro coolers. Inspired by these applications, a laminar, two-dimensional nanofluid flow with uniform heat sink-source, thermophoretic depositions of the particles, and the Newtonian heating effect are investigated. The equations that describe the fluid motion are reduced into a system of ordinary differential equations with the help of spatial similarity variables. Numeric solutions of ordinary differential equations are executed through the Runge–Kutta–Felhberg 45 order technique via a shooting scheme. The role of various nondimensional factors on physically interesting quantities is elaborated graphically. The velocity profile rises for modified Hartmann number and decreases for porosity parameter. Thermal enhancement is high in the common wall temperature condition comparative to the case of the Newtonian heating conditions. The concentration profile is enhanced with Schmidt number, but the reverse trend is observed for the thermophoretic parameter. The rate of mass transfer is increased with Schmidt number.