An Investment-Benefit Assessing Approach for Intelligent Buildings

2014 ◽  
Vol 507 ◽  
pp. 157-162
Author(s):  
Zhe Liang Chen ◽  
Fu Lin Wang
Keyword(s):  
Intelligent Systems ◽  
Capital Investment ◽  
High Performance ◽  
Net Present Value ◽  
Intelligent System ◽  
Cash Flows ◽  
Intelligent Buildings ◽  
Intangible Benefits ◽  
Building Life Cycle ◽  
Hierarchy Process

For the purpose of achieving high performance of intelligent buildings, it needs to pay expanses for maintaining the intelligent systems. So it is in great need to analyze the costs and benefits of building intelligent system to help building owners to make decision on installing intelligent systems or not. This paper proposes an investment-benefit assessing approach for building intelligent systems. Net Present Value (NPV) is used as an index to evaluate the performance of building intelligent system. The NPV is calculated by analyzing the initial capital investment, maintenance costs, and the tangible and intangible benefits in building life cycle. The intangible benefits are quantified using a series of indexes which represent the cash flows brought by the intangible benefits. Different weights of these indexes are used to express the different contributions of these intangible benefits. Analytical Hierarchy Process (AHP) method [ is used to quantify the weights of the indexes.

Usec Inc.

2017 ◽  
pp. 1-11
Author(s):  
Kenneth M. Eades ◽  
Ben Mackovjak ◽  
Lucas Doe
Keyword(s):  
Stock Price ◽  
Capital Investment ◽  
Net Present Value ◽  
Cost Of Capital ◽  
Investment Decision ◽  
Weighted Average ◽  
Cash Flows ◽  
Primary Objective ◽  
Discounted Cash Flow ◽  
Important Input

This case is designed to present students with the challenges of formulating a discounted-cash-flow (DCF) analysis for a strategically important capital-investment decision. Analytically, the problem is representative of most corporate investment decisions, but it is particularly interesting because of the massive size of the American Centrifuge Project and the potential of the project to significantly affect the stock price. Students must determine the relevant cash flows, paying close attention to the treatment of input costs, selling prices, timing of investment outlays, depreciation, and inflation. An important input is the appropriate cost of uranium, which some students argue should be included at book value, while others argue that market value should be used. Although the primary objective of the case is to focus on the estimation of cash flows, students are provided with a straightforward set of inputs to estimate USEC's weighted average cost of capital. The case is designed for students who are learning, or need a refresher on, DCF analysis. Because of the basic issues covered, the case works well with undergraduate, MBA, and executive-education audiences. The case also affords the opportunity to explore a variety of issues related to capital-investment analysis, including relevant costs, incremental analysis, cost of capital, and sensitivity analysis. The case is an excellent example of the value of a firm as the value of assets in place plus the net present value of future growth opportunities.

scholarly journals What Makes Employees Productive and Have High Performance? Human Capital Investment in Universities

2020 ◽  
pp. 21-36
Author(s):  
Fitri Nurmahmudah ◽  
Eka Cahya Sari Putra
Keyword(s):  
Human Capital ◽  
Capital Investment ◽  
High Performance ◽  
Evaluation Method ◽  
Net Present Value ◽  
Pearson Correlation ◽  
Human Capital Investment ◽  
Correlation Technique ◽  
And Performance ◽  
High Level

The study describes the evaluation results concerning the improvement of the education levels among the employees of a university in Indonesia by making an investment in education. The study is aimed at investigating the employees’ productivity and performance after making an investment in education. This study with evaluation method using discrepancy model. The sample of the study consisted of 255  non-academic university employees. Data were collected by way of a questionnaire on Guttmann scale. The questionnaire was validated by using logical and empirical validation by a Pearson correlation technique and reliability by KR-20 technique. The data analysis with descriptive. To calculate the capital human investment, the human capital investment formula was used for finding payback period, benefit/cost ration, return-on-investment, net-present-value, and internal-rate-of-return. The results of the study showed that the employees who made human capital investment in education were able to increase their productivity and performance as their insights, knowledge, and skills improved. The research findings were able to give insights to leaders in high-level institutions or government institutions that investing in education is truly essential, needs more attention, and needs to be done by employees.

Purchasing power return, a new paradigm of capital investment appraisal

2018 ◽  
Vol 44 (2) ◽  
pp. 241-256 ◽  
Author(s):  
David DeBoeuf ◽  
Hongbok Lee ◽  
Don Johnson ◽  
Maksim Masharuev
Keyword(s):  
Capital Investment ◽  
Net Present Value ◽  
Capital Budgeting ◽  
Cash Flows ◽  
Purchasing Power ◽  
New Paradigm ◽  
Content Type ◽  
Investment Projects ◽  
Investment Appraisal ◽  
The Many

Purpose The purpose of this paper is to contribute to financial managers’ capital budgeting decision-making processes by proposing a new paradigm of capital investment appraisal. The expected return, required return structure of the proposed purchasing power return (PPR) methodology eliminates the many flaws associated with the competing internal rate of return (IRR) and modified IRR (MIRR) techniques. Design/methodology/approach The authors provide a new framework for examining long-term investment projects through a percentage return prism. Unlike that of IRR and MIRR, mathematical consistency with net present value (NPV) is a design requirement. Findings PPR eliminates the many flaws found in the IRR and MIRR methodologies, is mathematically consistent with NPV, and identifies positive-NPV investments forecasted to reduce the company’s purchasing power. These projects are acceptable under NPV, but flagged for additional review and potential rejection. Created to examine projects on a percentage return basis, PPR employs market-based inflation rates to convert all cash flows into constant purchasing power units of measure. From these units, an expected real return is estimated and compared to the project’s inflation-adjusted required return, resulting in an accept/reject decision consistent with that of NPV. Originality/value The proposed PPR is a new paradigm of capital investment appraisal that eliminates the many problems found in the IRR and MIRR techniques, is mathematically consistent with the NPV method, and helps financial decision makers examine investment projects on an expected percentage return basis. PPR also flags for further review projects expected to actually reduce the company’s purchasing power.

scholarly journals SEQUENTIAL CAPITAL INVESTMENT DECISION MAKING UNDER EXTREME CASH FL OW SITUATIONS: EVIDENCE USING MONTE CARLO SIMULATION

2015 ◽  
Vol 16 (5) ◽  
pp. 877-900 ◽  
Author(s):  
Wenqing Zhang ◽  
Prasad Padmanabhan ◽  
Chia-Hsing Huang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Capital Investment ◽  
Net Present Value ◽  
Capital Budgeting ◽  
Cash Flows ◽  
Present Value ◽  
Short Term ◽  
Value Analysis

Uncertainty influences a decision maker's choices when making sequential capital investment decisions. With the possibility of extremely negative cash inflows, firms may need to curtail operations significantly. Traditional Net Present Value analysis does not allow for efficient management of these problems. In addition, firm managers may behave irrationally by accepting negative Net Present Value projects in the short term. This paper presents a Monte Carlo simulation based model to provide policy insights on how to incorporate extreme cash flows and manager irrationality scenarios into the capital budgeting process. This paper presents evidence that firms with irrational managers and experiencing extremely negative cash flows may, under certain conditions, reap long term rewards associated with the acceptance of negative Net Present Value projects in the short term. These benefits are largest if cost ratios (discount rates) are small, or investment horizons are high. We argue that acceptance of short term negative Net Present Value projects implies the purchase of a long term real option which can generate positive long term cash flows under certain conditions.

A novel model for optimization of Intelligent Multi-User Visual Comfort System based on soft-computing algorithms

2021 ◽  
pp. 1-22
Author(s):  
Wendoly J. Gpe. Romero-Rodriguez ◽  
R. Baltazar ◽  
Juan Martin Carpio Valadez ◽  
Hector Puga ◽  
Victor Zamudio ◽  
...  
Keyword(s):  
Soft Computing ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Visual Comfort ◽  
Artificial Lighting ◽  
Intelligent Control Systems ◽  
Multiple Users ◽  
Intelligent Buildings ◽  
Single User ◽  
Novel Model

Intelligent buildings are at the forefront due to its main objective of providing comfort to users and saving energy through intelligent control systems. Intelligent systems have been reported to offer comfort to a single user or averaging the comfort of multiple users without considering that their needs may be different from those of other users. This work defines a versatile model for a multi-user intelligent system that negotiates with the resources of the environment to offer visual comfort to multiple users with different profiles, activities and priorities using soft-computing algorithms. In addition, this model makes use of external lighting to provide the recommended amount of illumination for each user without having to totally depend on artificial lighting, inducing there will be an energy efficiency but without measuring it.

Design and Implementation of an Intelligent Robotic Manipulator using LabVIEW for Industrial Applications

2016 ◽  
Vol 7 ◽  
pp. 7
Author(s):  
Rajinder Tiwari
Keyword(s):  
Intelligent Systems ◽  
High Performance ◽  
Intelligent System ◽  
Dominant Role ◽  
Robotic Manipulator ◽  
Industrial Applications ◽  
High Rate ◽  
Process Industries ◽  
Software Modules ◽  
End Effectors

The robotic manipulator plays a dominant role in the domain of process industries based applications such as pick and drop, quality based sorting, etc. With the advent of these intelligent systems, the overall performance has been grown at a quite fast rate. This system has been mostly developed with the help of various hardware and software modules with the help of graphical coding language i.e. LabVIEW by National Instruments or MatLAB by Mathworks. This virtual intelligent system basically consists of a robotic manipulator, vision based systems, AI based processors i.e. a microcontroller, conveyor belts, etc. In this system, the degree of freedom (DOF) i.e. the movement of the manipulator is quite important which depends upon the nature of the application. For this intelligent system, various algorithms based approaches are implemented so as to execute the task i.e. image processing, coordinate determination, movement of the end effectors using various servo as well as DC motors, etc. In this present work, author has put forward a high performance automated intelligent system that provides a precise output with desired level of accuracy. With such characteristics, this virtual intelligent system can be utilized in various industrial applications where the quality is expected at a high rate with other dominant parameters. The simulation work of the system has been carried out with LabVIEW 2015 edition along with other hardware modules with desired results.

Artificial intelligence as a moving force of improvement and innovative development in education and pedagogic

2019 ◽  
pp. 21-30
Author(s):  
M. G. Koliada ◽  
T. I. Bugayova
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Interaction Analysis ◽  
Educational Data Mining ◽  
Main Task ◽  
Intellectual System ◽  
Will Force ◽  
To Come ◽  
Artificial Intelligence Systems

The article discusses the history of the development of the problem of using artificial intelligence systems in education and pedagogic. Two directions of its development are shown: “Computational Pedagogic” and “Educational Data Mining”, in which poorly studied aspects of the internal mechanisms of functioning of artificial intelligence systems in this field of activity are revealed. The main task is a problem of interface of a kernel of the system with blocks of pedagogical and thematic databases, as well as with the blocks of pedagogical diagnostics of a student and a teacher. The role of the pedagogical diagnosis as evident reflection of the complex influence of factors and reasons is shown. It provides the intelligent system with operative and reliable information on how various reasons intertwine in the interaction, which of them are dangerous at present, where recession of characteristics of efficiency is planned. All components of the teaching and educational system are subject to diagnosis; without it, it is impossible to own any pedagogical situation optimum. The means in obtaining information about students, as well as the “mechanisms” of work of intelligent systems based on innovative ideas of advanced pedagogical experience in diagnostics of the professionalism of a teacher, are considered. Ways of realization of skill of the teacher on the basis of the ideas developed by the American scientists are shown. Among them, the approaches of researchers D. Rajonz and U. Bronfenbrenner who put at the forefront the teacher’s attitude towards students, their views, intellectual and emotional characteristics are allocated. An assessment of the teacher’s work according to N. Flanders’s system, in the form of the so-called “The Interaction Analysis”, through the mechanism of fixing such elements as: the verbal behavior of the teacher, events at the lesson and their sequence is also proposed. A system for assessing the professionalism of a teacher according to B. O. Smith and M. O. Meux is examined — through the study of the logic of teaching, using logical operations at the lesson. Samples of forms of external communication of the intellectual system with the learning environment are given. It is indicated that the conclusion of the found productive solutions can have the most acceptable and comfortable form both for students and for the teacher in the form of three approaches. The first shows that artificial intelligence in this area can be represented in the form of robotized being in the shape of a person; the second indicates that it is enough to confine oneself only to specially organized input-output systems for targeted transmission of effective methodological recommendations and instructions to both students and teachers; the third demonstrates that life will force one to come up with completely new hybrid forms of interaction between both sides in the form of interactive educational environments, to some extent resembling the educational spaces of virtual reality.

The Central Role of Cognitive Computations in Human-Information Interaction

2018 ◽  
Author(s):  
Wai-Tat Fu ◽  
Jessie Chin ◽  
Q. Vera Liao
Keyword(s):  
Information Systems ◽  
Cognitive Science ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Levels Of Abstraction ◽  
Intelligent Information Systems ◽  
Emergent Behaviour ◽  
Information Interaction ◽  
Intelligent Information

Cognitive science is a science of intelligent systems. This chapter proposes that cognitive science can provide useful perspectives for research on technology-mediated human-information interaction (HII) when HII is cast as emergent behaviour of a coupled intelligent system. It starts with a review of a few foundational concepts related to cognitive computations and how they can be applied to understand the nature of HII. It discusses several important properties of a coupled cognitive system and their implication to designs of information systems. Finally, it covers how levels of abstraction have been useful for cognitive science, and how these levels can inform design of intelligent information systems that are more compatible with human cognitive computations.

scholarly journals Theoretical, Measured, and Subjective Responsibility in Aided Decision Making

2021 ◽  
Vol 11 (1) ◽  
pp. 1-37
Author(s):  
Nir Douer ◽  
Joachim Meyer
Keyword(s):  
Intelligent Systems ◽  
Intelligent System ◽  
Classification Systems ◽  
Strongly Correlated ◽  
Human Capabilities ◽  
Legal Decisions ◽  
Subjective Perceptions ◽  
Causal Responsibility ◽  
Quantification Model ◽  
Human Responsibility

When humans interact with intelligent systems, their causal responsibility for outcomes becomes equivocal. We analyze the descriptive abilities of a newly developed responsibility quantification model (ResQu) to predict actual human responsibility and perceptions of responsibility in the interaction with intelligent systems. In two laboratory experiments, participants performed a classification task. They were aided by classification systems with different capabilities. We compared the predicted theoretical responsibility values to the actual measured responsibility participants took on and to their subjective rankings of responsibility. The model predictions were strongly correlated with both measured and subjective responsibility. Participants’ behavior with each system was influenced by the system and human capabilities, but also by the subjective perceptions of these capabilities and the perception of the participant's own contribution. A bias existed only when participants with poor classification capabilities relied less than optimally on a system that had superior classification capabilities and assumed higher-than-optimal responsibility. The study implies that when humans interact with advanced intelligent systems, with capabilities that greatly exceed their own, their comparative causal responsibility will be small, even if formally the human is assigned major roles. Simply putting a human into the loop does not ensure that the human will meaningfully contribute to the outcomes. The results demonstrate the descriptive value of the ResQu model to predict behavior and perceptions of responsibility by considering the characteristics of the human, the intelligent system, the environment, and some systematic behavioral biases. The ResQu model is a new quantitative method that can be used in system design and can guide policy and legal decisions regarding human responsibility in events involving intelligent systems.

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