Set Of Input Values Research Articles

Analysis and optimisation of emissions and fuel economy of biodiesel fuelled CI engine using Taguchi technique

The objectives of the present work are to examine the combined effect of engine operating and injection parameters and to optimise these parameters for better fuel economy, performance, and reduced emissions. The fuels used were diesel and biodiesel blends of Jatropha and Karanja biodiesel. The results indicate that diesel gives higher thermal efficiency at low loads, however, the 20% jatropha blend was slightly more efficient, at high loads. It was observed that the BSFC increases when the EGR is varied from 0% to 20%. Even though the smoke opacity increases with increased EGR, advanced injection at 28o BTDC decreases smoke. Increased EGR also reduced NOx emissions by up to 11%. Blending also has a significant impact on the output parameters. Taguchi analysis was applied to optimise the performance and emission characteristics of the diesel engine and set of input values were obtained for the optimum performance under different conditions.

Performance evolution in machining parameter of Al-Si (LM6) alloy using neural network

The global manufacturing age has increased competition in the manufacturing sector as markets become more agile and customer-focused. Because of the fierce rivalry, manufacturers are paying more attention to automation. In the last several decades, computer numerically controlled (CNC) machine tools have been utilized to achieve complete automation in machining. The artificial neural network theories are used in this research to train a solution for the problem of selecting machine setup settings for a turning operation. A collection of input and output values can be mapped out by an artificial neural network. A network may be used to anticipate output values for a certain set of input values once it has been trained. Process inputs like cutting speed, feed, depth of cut, and coolant flow rate can be generated by a trained program, as can their related process outputs like surface finish. Forward mapping of process inputs and outputs is accomplished using back propagation neural networks in this approach. The optimum machine setup parameter may then be selected interactively using these networks. To solve the model, a MATLAB program has been created. The experiment's findings are verified using a neural network.

WITHDRAWN: Essentials of blockchain technology for modern world applications

Abstract Blockchain is a buzzword these days which has found its significance in areas ranging from the financial sector, banking sector, and various other ones to attain societal benefits. Blockchain adopts a decentralized or distributed property to provide services to its customers. A blockchain is viewed as a collection of blocks just as a linked list, where each node is said to have a data field and a pointer field that points to the next node in the list. Hashing is a preferable technique followed by blockchain where a set of input values are hashed to generate an output. There are enormous components in blockchain architecture, each displays a primary role to make it efficient for communication among multiple parties. It also favours to automate essential activities pertaining to various industries that otherwise is carried out manually and huge costs are paid to the intermediate group of people who does the work. This work presents an overview of blockchain and its associated technologies to make it convenient for the researchers to utilize the benefits. Based on the inputs shared in this work, people can identify the need to switch towards the blockchain technology, which is trending technology in the modern days. Also, the current works prominently focus on throughput and response time metrics which can greatly have an impact on the overall performance of the network with huge number of blocks and transaction inflow, outflow rate. These metrics are upgraded to key based retrieval to ensure secure access by multiple users and robustness to withstand failure of a single block turned to be an intruder. The achievable outcome can be brought down to seconds when using a decentralized cloud-based access.

Characterization of Inter-Cell Interference in 3D NAND Flash Memory

We characterize inter-cell interference in commercial three-dimensional NAND flash memory. By writing random data into 3D NAND and collecting sample means and sample variances of cell values corresponding to a particular set of input values in fixed relative neighboring cell locations, it is shown that the interference coming from any target cell locations can be measured. We observe that four neighboring cells, two along the same pipe and two along the same bit line, are responsible for most of the interference exerted on a given victim cell. Contrary to the general belief, the total amount of interference is found to be fairly significant even in 3D NAND; if compensated properly, the number of errors can be reduced significantly.

Influence of Corporate Taxation on the Financial Leverage of Czech, Polish and Russian Companies

This article aims to compare and contrast the available empirical evidence concerning the capital structure of Polish,Czech and Russian companies. This is an intriguing research area due to the fact that the Czech and Polish economiesbegan their transition to the market economy contemporaneously with Russia, and so along with other cultural andhistorical parallels, the data is comparable.We compare data from a selection of large companies from the selected territories and investigate whether effective taxrate is significant determinant of capital structure. The selected sample is comprised of 69 companies (50 from Russia, 9from Poland, and 10 from Czech Republic), using data over a period of fourteen years. We perform a regression analysisand interpret the results using theoretical knowledge as articulated in the academic literature. The dependent variablein all tested regressions is financial leverage, calculated as the ratio of the sum of short-term and long-term debts to thesum of short-term and long-term assets. Other variables evaluated include interest coverage ratio, the level of companytangibility, and the cost of debt. This set of input values was uploaded from the Bloomberg database.Our results indicate that taxation does have determining effect on the choice of a certain level of leverage. Moreover,the effective tax rate represents the most important factor in determining the model of capital structure utilised by largecompanies in each country studied. We establish the dependence of capital structure models on the level of corporate taxapplied in each country and identify a set of additional determinants which play a significant role.This paper’s novelty may be summarised as representing an advanced understanding of specific aspects of influence ofthe corporate taxation on the capital structure of companies in Russia and other economies of the former Eastern Bloc.This paper shines a new light on the subject area by extending the duration of the studied data beyond previous research,to fourteen years. As such, in this paper we present a comparitive dynamic which may be mapped on to other similarcomparitive studies. Our results will be of interest in professionals and academics who are involved in the fields oftaxation, debt and equity in Eastern Europe and Russia. The schema utilised here may be applied in a similar manner toexamine the development of similar economies in Eastern Europe and further afield.

Analysing Cloud QoS Prediction Approaches and Its Control Parameters: Considering Overall Accuracy and Freshness of a Dataset

service level agreement (SLA) management is one of the key issues in cloud computing. The primary goal of a service provider is to minimize the risk of service violations, as these results in penalties in terms of both money and a decrease in trustworthiness. To avoid SLA violations, the service provider needs to predict the likelihood of violation for each SLO and its measurable characteristics (QoS parameters) and take immediate action to avoid violations occurring. There are several approaches discussed in the literature to predict service violation; however, none of these explores how a change in control parameters and the freshness of data impact prediction accuracy and result in the effective management of an SLA of the cloud service provider. The contribution of this paper is two-fold. First, we analyzed the accuracy of six widely used prediction algorithms—simple exponential smoothing, simple moving average, weighted moving average, Holt–Winter double exponential smoothing, extrapolation, and the autoregressive integrated moving average—by varying their individual control parameters. Each of the approaches is compared to 10 different datasets at different time intervals between 5 min and 4 weeks. Second, we analyzed the prediction accuracy of the simple exponential smoothing method by considering the freshness of a data; i.e., how the accuracy varies in the initial time period of prediction compared to later ones. To achieve this, we divided the cloud QoS dataset into sets of input values that range from 100 to 500 intervals in sets of 1–100, 1–200, 1–300, 1–400, and 1–500. From the analysis, we observed that different prediction methods behave differently based on the control parameter and the nature of the dataset. The analysis helps service providers choose a suitable prediction method with optimal control parameters so that they can obtain accurate prediction results to manage SLA intelligently and avoid violation penalties.

Effort Allocation in Rural Road Safety Analysis under Data-Limited Conditions

Traffic safety policy defines plans that are expressed using numerical values for the planned level of improvement. The directing or apportioning of efforts represents the initial step of planned improvements. If a road is observed as a system of sections, the sections should be prioritized, selected, and investigated according to precise enhancement requests. A temporal approach to road safety analysis enables the application of reliability reallocation theory. The individual application of certain reliability reallocation methods may yield results that are unusable for a road authority in some situations. This paper describes a method that is based on a judicious combination of acceptable features of two reliability reallocation methods [the aeronautical radio incorporated (ARINC) and the minimum effort algorithm] in different iterations. This method enables the possibility of setting a precisely expressed goal with a minimal set of input values to obtain quality and applicable results for a decision maker. The presented approach represents an improvement in the field of road safety decision-making support and is transferable to other areas of transportation engineering and effort allocation. Language: en

Forward kinematics solutions of a special six-degree-of-freedom parallel manipulator with three limbs

This article presents a special 6-degree-of freedom parallel manipulator, and the mechanical structure of this robot has been introduced; with this structure, the kinematic constrain equations are decoupled. Based on this character, the polynomial solutions of the forward kinematics problem are also presented. In this method, the closed-loop kinematic chain of the manipulator is divided into two parts, the solution forward position kinematics is obtained by a first-degree polynomial equation first, and then an eighth-degree polynomial equation in a single variable for the forward orientation kinematics is obtained. Based on those solutions, the configurations of the robot, including position and orientation of the end-effector, are graphically displayed. A numerical simulation is given to verify the algorithm, and the result implies that for a given set of input values, the manipulator can be assembled in eight different configurations at most. And a set of experiments illustrate the motion ability for forward kinematics of the prototype of this manipulator.

Emulating and Calibrating the Multiple-Fidelity Lyon–Fedder–Mobarry Magnetosphere–Ionosphere Coupled Computer Model

SummaryThe Lyon–Fedder–Mobarry global magnetosphere–ionosphere coupled model LFM-MIX is used to study Sun–Earth interactions by simulating geomagnetic storms. This work focuses on relating the multifidelity output from LFM-MIX to field observations of ionospheric conductance. Given a set of input values and solar wind data, LFM-MIX numerically solves the magnetohydrodynamic equations and outputs a bivariate spatiotemporal field of ionospheric energy and flux. Of particular interest here are LFM-MIX input settings required to match corresponding output with field observations. To estimate these input settings, a multivariate spatiotemporal statistical LFM-MIX emulator is constructed. The statistical emulator leverages the multiple fidelities such that the less computationally demanding yet lower fidelity LFM-MIX is used to provide estimates of the higher fidelity output. The higher fidelity LFM-MIX output is then used for calibration by using additive and non-linear discrepancy functions.

Designing a Software Test Automation Framework

Testing is art and science that should ultimately lead to lower cost businesses through increasing control and reducing risk. Testing specialists should thoroughly understand the system or application from both the technical and the business perspective, and then design, build and implement the minimum-cost, maximum-coverage validation framework. Test Au- tomation is important ingredient for testing large scale applications. In this paper we discuss several automation frameworks, their advantages and disadvantages. We also propose a custom automation framework model that is suited for applications with very complex business requirements and numerous interfaces.Keywords: Software Testing, Test Automation, Test Automation Framework, Data Driven, Keyword Driven, HybridIntroductionS oftware testing has been a rapidly grow- ing industry in the past ten years. Neverthe- less, the domain is new so there is a lot of room for improvement and a lot of room for innovative ideas. very interesting and chal- lenging chapter of software testing is soft- ware testing automation. This falls some- where between software testing and software development, using both programming con- cepts as well as testing ones. Diving further into software automation, one of the biggest challenges is to keep the testing perspective while codding, as the independence of testing versus development is extremely im- portant principle.We see a lot of improvements in Software automation in the past five years. As it happens in any growing industry, there were set a lot of trends. It usually starts with rec- ord and play approach and evolved to a mod- ular approach and moving towards the data- driven and keyword driven. Of course, these trends started a lot of debates on which de- sign is better or more suitable for your team, your business and your needs.Before we start discussing automation design, we will define some of the most common terms related to this topic. Software testing is defined as an investigation con- ducted to provide stakeholders with infor- mation about the quality of the product or service under test [3]. Therefore, the main goals of this activity are to detect and prevent defects as well as to insure the intended be- havior of the tested software [5], [6], [7].Software automation represents the use of software to control the execution of tests, the comparison of actual outcomes to pre- dicted outcomes, the setting up of pre- conditions, and other control and re- porting functions (BS 7925-1) [1].Test Automation Framework represents a framework used for automation. It pro- vides some core functionality (e.g. logging and reporting) and allows its testing capabili- ties to be extended by adding new librar- ies [1]. An automated framework may be loosely defined as a set of abstract con- cepts, processes, procedures and environment in which automated tests will be designed, created and implemented. In addition, it in- cludes the physical structures used for creation and implementation, as well as the logical interactions among those compo- nents [2].A automation framework has the struc- ture of a software application. As applica- tion, a automation framework defines common functions such as handling external files, GUI interaction, provides templates for structure, and therefore developing automated solution is very similar to devel- oping software applications [3], [7], [9], [10], [11], [12], [13].In any type of design of software auto- mation framework, in order to appli- cation, we need the following:· Test case or flow - The definition of a case in automation is the same as the case defined by ISTQB: A set of input values, execution preconditions, expected results and execution post- conditions, developed for a particular objective or condition, such as to ex- ercise a particular program path or to verify compliance with a specific re- quirement [After IEEE 610]. …

Estimating Minimum Toll Rates in Public Private Partnerships

Public private partnership (PPP) is a project delivery method which is used in many countries. The main advantage of this method compared with traditional methods is in the allocation of private funds which are used for providing public services and delivery of projects such as hospitals, schools, roads, and bridges. Under road PPP projects, a commonly used mechanism for the repayment of the private investment is the user charge system, i.e., charging tolls to the facility users. Although the toll rate may be set by the government, there are certain constraints which the minimum toll rate has to meet. These constraints are mainly related to financial parameters such as project's financial internal rate of return (IRR) and debt service coverage ratio (DSCR) which private investors evaluate during the decision making process. In other words, there is a minimum toll rate required to attract private investments. In addition to the financial constraints, other project's parameters such as construction cost, concession life, or level of government subsidies also have an impact on toll rates. The objective of this paper is to investigate the relationship between the level of toll rates and several project technical and financial parameters. A financial model included in the Toolkit for PPP in Roads and Highways, developed by the World Bank and the Public-Private Infrastructure Advisory Facility (PPIAF), is used as a tool to calculate toll rates for various sets of input values. The approach which was chosen to test sensitivity of selected parameters to potential changes in input values (e.g., technical and financial parameters) is by estimation of elasticities.

An Integrated Framework to Predict Bus Travel Time and Its Variability Using Traffic Flow Data

Information about bus travel time and its variability is a key indicator of service performance, and it is valued by passengers and operators. Despite the important effect of traffic flow on bus travel time, previous predictive approaches have not fully considered a traffic measure making their predictions unresponsive to the dynamic changes in traffic congestion. In addition, existing methodologies have primarily concerned predicting average travel time given a certain set of input values. However, predicting travel-time variability has not received sufficient attention in previous research. This article proposes an integrated framework to predict bus average travel time and its variability on the basis of a range of input variables including traffic flow data. The framework is applied using GPS-based travel-time data for a bus route in Melbourne, Australia, in conjunction with dynamic traffic flow data collected by the Sydney Coordinated Adaptive Traffic Systems loop detectors and a measure of schedule adherence. Central to the framework are two artificial neural networks that are used to predict the average and variance of travel times for a certain set of input values. The outcomes are then used to construct a prediction interval corresponding to each input value set. The article demonstrates the ability of the proposed framework to provide robust prediction intervals. The article also explores the value that traffic flow data can provide to the accuracy of travel-time predictions compared with when either temporal variables or scheduled travel times are the base for prediction. While the use of scheduled travel times results in the poorest prediction performance, incorporating traffic flow data yields minor improvements in prediction accuracy compared with when temporal variables are used.

A note on Poisson stability and controllability

The connection between Poisson stability and controllability is revisited. For the controllability criterion based on weakly positive Poisson stability (WPPS) and Lie algebra rank condition (LARC), it is shown that two natural assumptions about the set of input values are necessary for strictness. By using the relationship between conservative property and WPPS, sufficient conditions for controllability of affine nonlinear systems are further discussed. At last, for systems defined on compact Riemannian manifold, the WPPS is proved to be equivalent to Poisson stability.

Simulation analysis of risk management for a diversified commercial farm

Managing a profitable commercial agricultural business requires more than effective budgeting and financial bookkeeping. Due to dramatic changes in the agricultural decision-making environment over the past 15 years, farmers have to realise that farming requires effective risk management. A successful farmer is one who can identify these risks, match them up with expected returns and make the best decision on future actions. The farmer must be able to look strategically into the future and position the business in a way that ensures long-term sustainability and survivability. To forecast effectively, it is vital for the agribusiness to predict the effects of various risks on the financial position of the business. This research attempts to develop a simulated dairy management model that can be used as a farm management tool. Normal distributions were used to simulate the movement of maize prices under different scenarios. This model was applied to a 2007 case study, and it was found to be a suitable tool for financial analysis and scenario planning. By utilising different sets of input values, the model gives an indication of the possibility of risks involved in different scenarios. However, the model is in a rather crude form, and further development should be undertaken to account for the interaction between variable inputs. The model highlights the importance of a change in strategic direction, while it is useful in analysing the scenario outcomes of new strategies.

A Graph Model for Imperative Computation

Scott's graph model is a lambda-algebra based on the observation that continuous endofunctions on the lattice of sets of natural numbers can be represented via their graphs. A graph is a relation mapping finite sets of input values to output values. We consider a similar model based on relations whose input values are finite sequences rather than sets. This alteration means that we are taking into account the order in which observations are made. This new notion of graph gives rise to a model of affine lambda-calculus that admits an interpretation of imperative constructs including variable assignment, dereferencing and allocation. Extending this untyped model, we construct a category that provides a model of typed higher-order imperative computation with an affine type system. An appropriate language of this kind is Reynolds's Syntactic Control of Interference. Our model turns out to be fully abstract for this language. At a concrete level, it is the same as Reddy's object spaces model, which was the first "state-free" model of a higher-order imperative programming language and an important precursor of games models. The graph model can therefore be seen as a universal domain for Reddy's model.

Optimal Asphalt Pavement Design Considering Cost and Reliability

A typical asphalt pavement design based on the mechanistic-empirical approach offers multiple design alternatives for a given set of input values. The present paper emphasizes the fact that the cost as well as the reliability levels of these design alternatives are different. A simple methodology has been suggested in this paper to assist a pavement designer in selecting an optimal pavement design thickness which is cost effective yet does not compromise the reliability of the pavement design. Pavement design charts have been developed as an illustrative example to explain how the proposed methodology can be considered as an improvement over the deterministic design.

Configurations of steady states for Hopfield-type neural networks

The dependence of the steady states on the external input vector I for the continuous-time and discrete-time Hopfield-type neural networks of n neurons is discussed. Conditions for the existence of one or several paths of steady states are derived. It is shown that, in some conditions, for an external input I there may exist at least 2 n exponentially stable steady states (called configuration of steady states), and their regions of attraction are estimated. This means that there exist 2 n paths of exponentially stable steady states defined on a certain set of input values. Conditions assuring the transfer of a configuration of exponentially stable steady states to another configuration of exponentially stable steady states by successive changes of the external input are obtained. These results may be important for the design and maneuvering of Hopfield-type neural networks used to analyze associative memories.

Switch-Level Test-Vector Generation for CMOS Combinational Logic

A method is proposed of test-vector generation for stuck-open and other faults in CMOS combinational circuits represented at the switch level. It consists in solving three problems: (1) Identify a stimulus that should be applied to the element under test. (2) Trace a path through which the response could reach an output node. (3) Find a set of input values that could drive internal nodes to logic levels determined in solving problems (1) and (2). The method is illustrated with an example.

Objective assessment of MPEG-2 video quality

The increasing use of video compression standards in broadcasting television systems has required, in recent years, the development of video quality measurements that take into account artifacts specifically caused by digital compression techniques. In this paper we present a methodology for the objective quality as- sessment of MPEG video streams by using circular back- propagation feedforward neural networks. Mapping neural networks can render nonlinear relationships between objective features and subjective judgments, thus avoiding any simplifying assumption on the complexity of the model. The neural network processes an in- stantaneous set of input values, and yields an associated estimate of perceived quality. Therefore, the neural-network approach turns objective quality assessment into adaptive modeling of subjective perception. The objective features used for the estimate are chosen according to the assessed relevance to perceived quality and are continuously extracted in real time from compressed video streams. The overall system mimics perception but does not require any ana- lytical model of the underlying physical phenomenon. The capability to process compressed video streams represents an important ad- vantage over existing approaches, like avoiding the stream- decoding process greatly enhances real-time performance. Experi- mental results confirm that the system provides satisfactory, continuous-time approximations for actual scoring curves concern- ing real test videos. © 2002 SPIE and IS&T.

SELF-STABILIZING DISTRIBUTED SORTING IN TREE NETWORKS

This paper presents a self-stabilizing distributed sorting algorithm for tree networks. The distributed sorting problem can be informally described as follows: Nodes cooperate to reach a global configuration where every node, depending on its identifier, is assigned a specific final value taken from a set of input values distributed across all nodes. The input values may change in time. In our solution, the system reaches its final configuration in a finite time after the input values are stable and the faults cease. The fault-tolerance and the adaptivity to changing input is achieved using Dijkstra's paradigm of self-stabilization. A self-stabilizing algorithm, regardless of the initial system state, will converge in finite time to a set of legitimate states without the need for explicit exception handlers or backward recovery. Our solution is based on a continuous broadcast with acknowledgment along the tree edges to achieve the synchronization among processes in the system. It has 0(n ×h) time complexity and only 0(log(n) × ) memory requirement where h is the degree of the tree and h is the height of the tree.